diff --git a/.Rprofile b/.Rprofile new file mode 100644 index 0000000..81b960f --- /dev/null +++ b/.Rprofile @@ -0,0 +1 @@ +source("renv/activate.R") diff --git a/Containerfile b/Containerfile index af33524..0348626 100644 --- a/Containerfile +++ b/Containerfile @@ -1,12 +1,12 @@ -FROM ghcr.io/rocker-org/geospatial:4.6.0 +FROM ghcr.io/rocker-org/geospatial:4.6.1 RUN sudo apt-get update \ && sudo apt install -y curl \ - && sudo curl -sLO https://cdn.posit.co/positron/releases/deb/x86_64/Positron-2026.05.2-3-x64.deb \ + && sudo curl -sLO https://cdn.posit.co/positron/releases/deb/x86_64/Positron-2026.06.1-6-x64.deb \ && sudo curl -L https://rig.r-pkg.org/deb/rig.gpg -o /etc/apt/trusted.gpg.d/rig.gpg \ && sudo sh -c 'echo "deb http://rig.r-pkg.org/deb rig main" > /etc/apt/sources.list.d/rig.list' \ && sudo apt-get update \ - && sudo apt install -y ./Positron-2026.05.2-3-x64.deb \ + && sudo apt install -y ./Positron-2026.06.1-6-x64.deb \ && sudo apt install -y \ bat \ fonts-firacode \ diff --git a/_freeze/blog/2026/property-tax-uplift/index/execute-results/html.json b/_freeze/blog/2026/property-tax-uplift/index/execute-results/html.json new file mode 100644 index 0000000..87d037a --- /dev/null +++ b/_freeze/blog/2026/property-tax-uplift/index/execute-results/html.json @@ -0,0 +1,21 @@ +{ + "hash": "de506d63eb9c6bb77381c3c32705c645", + "result": { + "engine": "knitr", + "markdown": "---\ntitle: \"The property tax dividend from Edmonton's RS Zone rowhomes\"\ndate: \"2026-07-09\"\nauthor: \"Jacob Dawang\"\ncategories: [housing, edmonton, zoning]\ndescription: \"Redeveloping an old house into a 5-8 unit RS Zone rowhome doesn't just add homes, it multiplies the property's assessed value. Here's what that's worth to Edmonton's property tax base since the Zoning Bylaw Renewal took effect.\"\nlink-external-newwindow: true\nlink-external-icon: false\nexecute:\n cache: false\n---\n\nEdmonton's Zoning Bylaw Renewal (ZBR) has spent two years quietly rewriting mature neighbourhoods, one lot at a time. [Prior posts on this blog](../zbr-two-year-review/index.qmd) have tracked the homes it unlocked and the neighbourhoods it reached. This post asks a different question: what is that redevelopment worth to the City's property tax base?\n\nWhen a single-family lot in a mature neighbourhood becomes a 5-8 unit RS Zone rowhome, its assessed value doesn't just grow, it multiplies. That's a durable increase in the tax base, not a one-time windfall: every year, that property contributes meaningfully more property tax than the house it replaced would have. Using building permits from 2024, the first year the RS Zone was in force, matched against the City's property assessment data, I measure that uplift directly for completed projects, then use a regression model fit on those measurements to estimate what it adds up to across the full 2024-2026 pipeline.\n\n## Data\n\nThis analysis combines three of Edmonton's Open Data sources. Edmonton's [general building permit data](https://data.edmonton.ca/Urban-Planning-Economy/General-Building-Permits/24uj-dj8v/about_data), the same source used in the [Q2 2026 building permit report](../q2-building-permits/index.qmd), identifies which properties were redeveloped into 5-8 unit RS Zone rowhomes and when. Edmonton's [current calendar year property assessment data](https://data.edmonton.ca/City-Administration/Property-Assessment-Data-Current-Calendar-Year-/q7d6-ambg/about_data) gives each property's assessed value as of 2026, and Edmonton's [historical property assessment data](https://data.edmonton.ca/City-Administration/Property-Assessment-Data-Historical-/qi6a-xuwt/about_data) gives assessed values back to 2012, including 2024 and 2025.\n\nThe key challenge is linking a specific building permit to the same physical property, before and after redevelopment. Account numbers usually persist through redevelopment, but addresses often don't: a lot can get re-addressed when it's rebuilt, so a permit's civic address is frequently *not* the address that appears in the property's earlier assessment record. Instead, I match on legal description (plan/block/lot), which is stable across redevelopment, with a fallback to geographic proximity for the small number of properties where the legal description format doesn't parse identically on both sides, or where redevelopment came with a brand new account number.\n\n\n\n\n::: {.cell}\n\n:::\n\n\n## Measuring the uplift: the 2024 cohort\n\nThe 2026 property assessment is supposed to reflect each property's physical condition as of December 31, 2025. In principle, that means any 2024 permit whose building had received occupancy by the end of 2025 should show up, completed, in the 2026 assessment roll, giving a clean before-and-after pair. In practice, as we'll see below, the assessments only reliably catch up to buildings finished by about September 2025, so the measurement cohort uses that earlier cutoff.\n\n\n::: {.cell}\n\n:::\n\n\nEdmonton issued **118** mature-neighbourhood RS Zone 5-8 unit new-build permits in 2024, of which **79** had received occupancy by the end of 2025. I match all 118 to their assessment records, then use the occupancy dates to decide which ones the 2026 assessment actually reflects as complete.\n\n### Matching permits to assessments\n\nI parse each side's legal description into a `(plan, block, lot)` key and join on it. A building permit's legal description looks like `Plan 715HW Blk 25 Lot 22`; the historical assessment data records the same parcel as `Plan: 715HW Block: 25 Lot: 22`.\n\n\n::: {.cell}\n\n:::\n\n\nThat legal-key match alone links **110** of 118 properties (93%) to their 2024 baseline assessed value. For the remainder, I fall back to matching each permit to the nearest 2024 assessment point within 25m. I checked these fallback matches by hand: most are lots that were consolidated from two legal titles into one (a permit reads `Lots 2-3`, while the assessment record spells that out as two separate `Lot:` entries joined by \" / \", which my parser doesn't follow), and in each case checked the fallback match has the exact same civic address as the permit, at a matched distance of a few millimetres.\n\n\n::: {.cell}\n\n:::\n\n\nThe 25m fallback brings the total match rate to **115** of 118 (97%). The remaining 3 properties have no corresponding parcel in the 2024 assessment roll at all, likely lots created by subdivision after that year's assessment date, so they're dropped from the analysis.\n\nEach matched property's `account_number` persists through redevelopment in most cases, so I use it to look up the completed building's 2026 assessed value. A small number of properties are issued a brand new account number when redeveloped rather than keeping the old one, exactly the re-addressing situation described above; I confirmed one such case by hand, where the 25m fallback correctly landed on a new 2026 account whose civic address matched the permit's own address exactly, even though the old account (still on the 2024/2025 rolls under the pre-redevelopment address) had disappeared from the 2026 data entirely.\n\n\n::: {.cell}\n\n:::\n\n\nThat yields **115** 2024 permits with both a 2024 baseline and a 2026 assessed value.\n\n### When does the assessment catch up?\n\nBefore treating every occupancy-granted building as \"complete\" in the 2026 data, it's worth checking whether the assessments actually keep up with late-year completions. @fig-assessment-lag plots each matched property's gross uplift against its occupancy date. The pattern is stark: buildings that received occupancy by roughly the end of September 2025 show the full rowhome uplift, while October, November, and especially December completions drop off a cliff — their 2026 assessed values still largely reflect a construction site, not a finished building, even though the assessment is nominally \"as of December 31, 2025\".\n\n\n::: {.cell}\n::: {.cell-output-display}\n![Gross assessed value uplift by occupancy date: the 2026 assessment only reliably reflects buildings finished by about September 2025](index_files/figure-html/fig-assessment-lag-1.png){#fig-assessment-lag width=672}\n:::\n:::\n\n\nSo the measurement cohort for this post is the matched 2024 permits with **occupancy granted by September 30, 2025** — buildings whose 2026 assessment genuinely reflects the completed rowhome. Everything else, including those October-December completions, goes into the \"not yet fully reflected\" group.\n\n\n::: {.cell}\n\n:::\n\n\nThe measurement cohort is **48** properties. @tbl-spotlight traces two properties through the process, from their pre-redevelopment assessed value, through a mid-construction 2025 assessment, to their completed 2026 value. The Alberta Avenue example received occupancy in November 2025, yet its 2026 value looks fully assessed — a reminder that the lag in @fig-assessment-lag is a strong tendency, not a hard rule, which is why the conservative September cutoff is used for measurement.\n\n\n::: {#tbl-spotlight .cell tbl-cap='Two properties traced from pre-redevelopment (2024) through mid-construction (2025) to a completed rowhome (2026)'}\n::: {.cell-output-display}\n\n```{=html}\n
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Two RS Zone rowhomes, before and after
Assessed value by year
NeighbourhoodUnits2024 (before)2025 (mid-construction)2026 (completed)2026 assessment class
Alberta Avenue5$156,000$346,500$1,083,500Residential
Crestwood8$493,000$1,598,500$2,352,500Other Residential
Jacob Dawang, City of Edmonton Open Data
\n
\n```\n\n:::\n:::\n\n\n### The rest of the 2024 cohort\n\nThe 48 properties above only cover 2024 permits whose completed buildings the 2026 assessment has caught up with. The remaining matched permits, 67 of them, are either still under construction or finished too late in 2025 for the assessment to reflect. Their 2026 assessed values still tell us something: whatever value the construction had reached, a *partial* uplift. @tbl-2024-actual-total combines both groups into a single, fully-observed total for the 2024 permit year, no rule required.\n\n\n::: {#tbl-2024-actual-total .cell tbl-cap='Actual (not model-based) 2024 cohort assessed value uplift, split by completion status'}\n::: {.cell-output-display}\n\n```{=html}\n
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2024 cohort, actual gross uplift observed so far
No extrapolation model applied
nMedian gross upliftTotal gross uplift
Reflected as complete (occupancy by Sept 2025)48$1,876,500$81,419,500
Not yet fully reflected (later or no occupancy)67$652,500$47,293,000
Total, 2024 cohort (matched)115$1,032,500$128,712,500
Jacob Dawang, City of Edmonton Open Data
\n
\n```\n\n:::\n:::\n\n\nThat gives a fully-observed total of **$128.71M** in assessed value uplift already showing up in the 2026 roll from the 2024 cohort alone, no assumptions needed. It understates the eventual value of that cohort, though: the \"not yet fully reflected\" group's uplift is a snapshot mid-construction (or a stale assessment of a just-finished building), not the finished-building value those properties will eventually reach. That gap between actual-so-far and eventual-once-complete is exactly what the model-based extrapolation later in this post is estimating.\n\n### From gross uplift to a fair counterfactual\n\nThe raw 2024-to-2026 difference in assessed value overstates the effect of redevelopment on its own, because Edmonton property values were also generally rising over that period. To isolate the redevelopment effect, I build a counterfactual: what would each property likely have been worth in 2026 if it *hadn't* been redeveloped? I estimate this from a control group of RS-zoned properties in mature neighbourhoods that were not part of any 2024-2026 residential new-build permit, taking the median ratio of their 2026 to 2024 assessed value as a general appreciation factor.\n\n\n::: {.cell}\n\n:::\n\n\nAcross **79,874** non-redeveloped RS Zone properties in mature neighbourhoods, the median 2024-to-2026 growth ratio is **1.19x**, meaning a typical mature-neighbourhood house that wasn't touched still gained about 19% in assessed value over those two years. I use this as the baseline against which redevelopment uplift is measured: **net uplift** is the completed rowhome's 2026 value minus 1.19 times its 2024 baseline, isolating the redevelopment effect from general market appreciation. **Gross uplift** is the simple, unadjusted difference, shown alongside it for comparison.\n\n@fig-uplift-distribution shows the distribution of both measures across the 48 matched properties, split by project size.\n\n\n::: {.cell}\n::: {.cell-output-display}\n![Distribution of assessed value uplift per redeveloped property, gross and net of market appreciation](index_files/figure-html/fig-uplift-distribution-1.png){#fig-uplift-distribution width=672}\n:::\n:::\n\n\n@tbl-uplift-rules compares three simple ways of summarizing this uplift into a single per-project figure: a median per property within two size buckets (5-6 units and 7-8 units), a single pooled median per property across all sizes, and a median per home added, which can be scaled by any project's unit count. These serve as sanity anchors for the model-based rule developed next.\n\n\n::: {#tbl-uplift-rules .cell tbl-cap='Three ways to summarize per-project uplift, gross and net of appreciation'}\n::: {.cell-output-display}\n\n```{=html}\n
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Three uplift rules compared
Measured from the completed 2024 cohort
nMedian gross upliftMedian net uplift
5-6 units9$1,187,500$1,129,748
7-8 units39$1,899,500$1,834,954
Pooled (5-8 units)48$1,876,500$1,815,291
Per home added48$235,115$227,769
Jacob Dawang, City of Edmonton Open Data
\n
\n```\n\n:::\n:::\n\n\n### A model for uplift\n\nThe simple rules above ignore everything about a project except its unit count. But uplift plausibly varies with location too: land near LRT stations and in more expensive neighbourhoods should command different completed values. So the headline rule for this post is a regression of each property's **gross uplift** on three things: units added, distance from the nearest LRT stop, and the neighbourhood's median RS-zone assessed value (a land-value measure computed from the same 2024 assessment data, since with only 48 observations spread across 30 neighbourhoods, per-neighbourhood dummy variables are off the table).\n\n\n::: {.cell}\n\n:::\n\n\nTwo specification choices deserve a word. First, modelling gross uplift is algebraically the same as modelling the completed 2026 value with the 2024 baseline as a fixed offset. Letting the baseline enter with a freely estimated coefficient instead doesn't help: the old house's value is nearly collinear with the neighbourhood land-value measure (r = 0.88), so the offset form is both more stable and better in cross-validation.\n\nSecond, the uplift itself is *not* log-transformed: the measured cohort's uplift distribution isn't right-skewed enough to justify it, and a log-log variant does worse in cross-validation (see @tbl-model-comparison). But its two *covariates* are worth transforming: I searched units added and neighbourhood value on both linear and log scales, and distance from LRT on both linear and inverse-distance scales, always keeping gross uplift itself on the dollar scale, evaluated by leave-one-out cross-validation on the dollar scale. @tbl-model-comparison shows the two ends of that search. Log-transforming units added and neighbourhood value together gives the best cross-validated fit, an improvement over the plain linear specification and clearly ahead of log-transforming the outcome instead. With only 48 observations, that improvement is real but not dramatic — about 1.5 times its own bootstrap standard error — so I adopt it as the best available specification on the evidence, not because the gap is large.\n\n\n::: {#tbl-model-comparison .cell tbl-cap='Comparing uplift model specifications by leave-one-out cross-validated RMSE'}\n::: {.cell-output-display}\n\n```{=html}\n
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Comparing uplift model specifications
Leave-one-out cross-validated RMSE, dollar scale, n = 48
LOOCV RMSE
Units + LRT distance + neighbourhood value (linear)$440,208
log(units) + LRT distance + log(neighbourhood value) (adopted)$429,512
log(gross uplift) ~ units + LRT distance + log(neighbourhood value)$453,022
Pooled median (no covariates)$511,425
Jacob Dawang, City of Edmonton Open Data
\n
\n```\n\n:::\n:::\n\n\n@tbl-uplift-model shows the chosen model's coefficients.\n\n\n::: {#tbl-uplift-model .cell tbl-cap='Gross uplift model coefficients, fit on the measured 2024 cohort'}\n::: {.cell-output-display}\n\n```{=html}\n
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What drives per-property uplift?
Gross uplift ~ log(units) + LRT distance + log(neighbourhood value); R² = 0.28, n = 48
EstimateStd. errortp-value
Intercept−$8,077,689$3,281,458−2.460.018
Units added (log)$1,711,517$508,5183.370.002
Distance from LRT (per km)$116,106$84,8411.370.178
Neighbourhood median RS value (log)$483,083$252,9551.910.063
Jacob Dawang, City of Edmonton Open Data
\n
\n```\n\n:::\n:::\n\n\nUnits added is the clearest and most statistically solid effect in the model, but because it enters on a log scale, its dollar effect isn't constant per home — it tapers off as project size grows. Near the bottom of the 5-8 unit range, the marginal home is worth about **$342.30k**; near the top, about $213.94k, a diminishing-returns pattern consistent with each additional unit adding somewhat less land-value-per-unit than the last. A neighbourhood with double the typical RS-zoned land value tends to see about $334.85k more in uplift, holding project size and distance fixed, though the estimate is imprecise. Distance from LRT comes out slightly *positive*, around $116.11k per km, and statistically indistinguishable from zero: within mature neighbourhoods, being near a station doesn't measurably raise how much value a rowhome redevelopment adds, perhaps because station-adjacent land already carried a higher baseline value. With 48 observations, all of these intervals are wide, and the model explains a modest 28% of the variation, which is the honest state of knowledge one construction cycle into ZBR.\n\n@fig-model-diagnostics shows the model's residual diagnostics: no strong funnel shape in the residuals-vs-fitted panel (the usual argument for a log transform) and reasonably normal-looking residuals.\n\n\n::: {#fig-model-diagnostics .cell layout-ncol=\"2\"}\n::: {.cell-output-display}\n![Residuals vs fitted values](index_files/figure-html/fig-model-diagnostics-1.png){#fig-model-diagnostics-1 width=672}\n:::\n\n::: {.cell-output-display}\n![Normal Q-Q plot of residuals](index_files/figure-html/fig-model-diagnostics-2.png){#fig-model-diagnostics-2 width=672}\n:::\n\nUplift model residual diagnostics\n:::\n\n\nFor a sanity check against @tbl-uplift-rules: the model's average predicted uplift across the measured cohort is $1.70M per property, right in line with the simple medians, as it should be. What the model adds is the ability to give each *individual* permit a prediction tailored to its size and location, which matters when extrapolating to hundreds of permits whose size mix and geography differ from the measured cohort's.\n\nFor **net** uplift, the counterfactual adjustment is applied after prediction: a property's predicted net uplift is its predicted gross uplift minus (1.19 − 1) times its own 2024 baseline value, the same adjustment used for the measured cohort.\n\n## Where is this happening?\n\n@tbl-uplift-by-neighbourhood breaks the measured cohort down by neighbourhood.\n\n\n::: {#tbl-uplift-by-neighbourhood .cell .column-page tbl-cap='Measured uplift by neighbourhood, 2024 RS Zone 5-8 unit cohort (interactive)'}\n::: {.cell-output-display}\n\n```{=html}\n
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Measured uplift by neighbourhood
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2024 RS Zone 5-8 unit cohort, reflected as complete (occupancy by Sept 2025)
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Jacob Dawang, City of Edmonton Open Data
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\n```\n\n:::\n:::\n\n\n## From one cohort to the whole pipeline\n\nThe measured cohort only covers 2024 permits that were both matchable and fully reflected in the 2026 assessment. To estimate the cumulative effect of the RS Zone rowhome since ZBR took effect, I apply the uplift model from @tbl-uplift-model to every other mature-neighbourhood RS Zone 5-8 unit new-build permit issued since 2024: the rest of the 2024 cohort (permits that didn't match or aren't fully assessed yet), all of 2025, and 2026. Each permit gets a prediction from its own unit count, LRT distance, and neighbourhood.\n\nThis is a **steady-state estimate**: it assumes every one of those permits eventually reaches the completed-building uplift the model predicts, once construction wraps up and a future assessment catches up to it. It is not the smaller amount those properties currently show in the 2026 roll, which @tbl-2024-actual-total showed directly for 2024's not-yet-reflected permits. The gap between that actual, partial total and the steady-state estimate below is construction and assessment lag, not double-counting.\n\n\n::: {.cell}\n\n:::\n\n\n2025 permitted **302** more mature-neighbourhood RS Zone 5-8 unit rowhomes, and H1 2026 has already permitted 190. Following the same [H1 annualization method used in the Q2 2026 report](../q2-building-permits/index.qmd), full-year 2026 is projected at 2.1x the H1 count.\n\nPredicting *net* uplift needs each permit's own 2024 baseline value, so the 2025 and 2026 permits are run through the same baseline matchers as the 2024 cohort (their lots all existed in the 2024 roll, pre-redevelopment).\n\n\n::: {.cell}\n\n:::\n\n\nThe 2025 and 2026 permits match their 2024 baselines at a **96%** rate; the few that don't use their neighbourhood's median RS value as a stand-in baseline for the net adjustment.\n\n@fig-cumulative-value-uplift shows the resulting cumulative assessed value uplift by permit year, split between the actually-measured portion and the portion estimated with the model.\n\n\n::: {.cell}\n::: {.cell-output-display}\n![Cumulative estimated assessed value uplift since ZBR, by permit year (net of appreciation)](index_files/figure-html/fig-cumulative-value-uplift-1.png){#fig-cumulative-value-uplift width=672}\n:::\n:::\n\n\nAdding it all up: since ZBR took effect, mature-neighbourhood RS Zone 5-8 unit rowhomes are estimated to have added **$1,373.48M** in gross assessed value, or **$1,321.47M** net of general market appreciation, across 118 (2024) + 302 (2025) + 399 (2026, projected) = 819 permitted projects.\n\n@tbl-cumulative-selected-neighbourhoods breaks that cumulative estimate down for the same neighbourhoods used in the [Q2 2026 report's selected-neighbourhood table](../q2-building-permits/index.qmd), places that have been prominent in debates about RS Zone infill. Each permit is valued at its actual measured uplift where available, or the model's prediction otherwise, then summed by neighbourhood. This covers every actual permit issued through H1 2026; the projected remainder of 2026 isn't tied to real permits yet, so it's included in the citywide total above but left out of this neighbourhood breakdown.\n\n\n::: {#tbl-cumulative-selected-neighbourhoods .cell .column-page tbl-cap='Cumulative estimated uplift for selected neighbourhoods, 2024 through H1 2026'}\n::: {.cell-output-display}\n\n```{=html}\n
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Cumulative uplift, selected neighbourhoods
2024 through H1 2026, measured + model-based
NeighbourhoodProjectsHomes addedCumulative gross upliftCumulative net upliftEst. annual municipal tax uplift
Belgravia969$17,551,425$16,569,366$134,692
Britannia Youngstown24191$38,720,535$37,509,074$305,693
Crestwood966$16,600,142$15,726,508$128,249
Glenwood38300$62,379,257$60,448,921$492,198
Grovenor20144$31,772,173$30,495,883$248,614
Mckernan16108$25,388,063$24,043,169$195,447
Parkview531$7,757,110$7,432,493$60,419
Westmount18141$34,378,685$32,948,957$268,184
Jacob Dawang, City of Edmonton Open Data
\n
\n```\n\n:::\n:::\n\n\n## What this means for property tax\n\nAssessed value only matters for the City's budget insofar as it's taxed. I convert the estimated uplift into two figures: an **annual recurring** estimate, at 2026 municipal tax rates, of how much more property tax this pipeline will generate every year once every project is complete and fully reflected in an assessment roll; and a rougher **cumulative collected so far** estimate that accounts for the fact that most of this pipeline is still under construction or only recently completed.\n\nCompleted 5-8 unit rowhomes on a single title are typically assessed as \"Other Residential\", which carries a higher municipal mill rate than the \"Residential\" class the original house was assessed under. In the measured cohort, 83% of completed properties land in Other Residential; I apply that same mix to the model-based portion of the estimate.\n\n\n::: {.cell}\n\n:::\n\n\nAt 2026 municipal tax rates, this pipeline is estimated to add **$10.75M** in property tax every year, net of what general appreciation would have generated anyway ($11.17M on a gross basis). That's before counting the provincial education levy, which would add roughly another third on top of the municipal portion.\n\nBecause most of this pipeline is still ramping up, actual tax collected so far is much lower than that steady-state figure. Comparing each matched property's mid-construction 2025 assessed value to its 2024 baseline and completed 2026 value shows how much of the total uplift typically shows up one year after a permit is issued.\n\n\n::: {.cell}\n\n:::\n\n\nThe median property has captured about 16% of its full uplift by the assessment one year after permitting, consistent with most projects still being under construction at that point. Modelling each year's cohort as contributing that partial share in the following year and the full amount from two years out, I estimate Edmonton has collected roughly **$2.41M** in incremental property tax from this pipeline across 2025 and 2026 combined, well short of the $10.75M-a-year run rate this pipeline will eventually reach once every project currently in the pipeline is complete and fully assessed.\n\nThese are estimates, not City budget figures. Assessment growth from new construction doesn't translate one-for-one into new City revenue, since Council sets the mill rate each year based on total budget needs, but new construction is genuinely additional tax base at whatever rate Council sets, distinct from a rate increase on existing properties. This also doesn't account for the cost of servicing new residents, which isn't the subject of this post.\n\n## Conclusions\n\nThe RS Zone rowhome isn't just adding homes, it's rebuilding the property tax base of neighbourhoods that had been losing population and, with it, tax revenue per hectare of city-maintained infrastructure for decades. A handful of redevelopments per neighbourhood, concentrated in mature areas that already have the pipes, roads, and schools in place, is already worth tens of millions of dollars a year in additional property tax capacity, on top of the housing it delivers.\n\nNone of this required a subsidy, a grant, or a City-led development. It required removing rules that made this kind of building illegal. If you'd like to help keep it that way, consider joining [Grow Together Edmonton](https://www.growtogetheryeg.com/).", + "supporting": [ + "index_files" + ], + "filters": [ + "rmarkdown/pagebreak.lua" + ], + "includes": { + "include-in-header": [ + "\n\n\n\n\n\n\n" + ] + }, + "engineDependencies": {}, + "preserve": {}, + "postProcess": true + } +} \ No newline at end of file diff --git a/_freeze/blog/2026/property-tax-uplift/index/figure-html/fig-assessment-lag-1.png b/_freeze/blog/2026/property-tax-uplift/index/figure-html/fig-assessment-lag-1.png new file mode 100644 index 0000000..9da71fd Binary files /dev/null and b/_freeze/blog/2026/property-tax-uplift/index/figure-html/fig-assessment-lag-1.png differ diff --git a/_freeze/blog/2026/property-tax-uplift/index/figure-html/fig-cumulative-value-uplift-1.png b/_freeze/blog/2026/property-tax-uplift/index/figure-html/fig-cumulative-value-uplift-1.png new file mode 100644 index 0000000..cf2e7d1 Binary files /dev/null and b/_freeze/blog/2026/property-tax-uplift/index/figure-html/fig-cumulative-value-uplift-1.png differ diff --git a/_freeze/blog/2026/property-tax-uplift/index/figure-html/fig-model-diagnostics-1.png b/_freeze/blog/2026/property-tax-uplift/index/figure-html/fig-model-diagnostics-1.png new file mode 100644 index 0000000..daac092 Binary files /dev/null and b/_freeze/blog/2026/property-tax-uplift/index/figure-html/fig-model-diagnostics-1.png differ diff --git a/_freeze/blog/2026/property-tax-uplift/index/figure-html/fig-model-diagnostics-2.png b/_freeze/blog/2026/property-tax-uplift/index/figure-html/fig-model-diagnostics-2.png new file mode 100644 index 0000000..9933751 Binary files /dev/null and b/_freeze/blog/2026/property-tax-uplift/index/figure-html/fig-model-diagnostics-2.png differ diff --git a/_freeze/blog/2026/property-tax-uplift/index/figure-html/fig-uplift-distribution-1.png b/_freeze/blog/2026/property-tax-uplift/index/figure-html/fig-uplift-distribution-1.png new file mode 100644 index 0000000..df8d9da Binary files /dev/null and b/_freeze/blog/2026/property-tax-uplift/index/figure-html/fig-uplift-distribution-1.png differ diff --git a/_freeze/blog/2026/q2-building-permits/index/execute-results/html.json b/_freeze/blog/2026/q2-building-permits/index/execute-results/html.json new file mode 100644 index 0000000..116e613 --- /dev/null +++ b/_freeze/blog/2026/q2-building-permits/index/execute-results/html.json @@ -0,0 +1,19 @@ +{ + "hash": "d1ef345da5c068223dac5b04f6d6e472", + "result": { + "engine": "knitr", + "markdown": "---\ntitle: \"2026 H1 Edmonton building permit report\"\ndate: \"2026-07-09\"\nauthor: \"Jacob Dawang\"\ncategories: [housing, edmonton, zoning]\ndescription: \"Edmonton building permits slowed through the first half of 2026, but the RS Zone rowhome keeps setting records.\"\nlink-external-newwindow: true\nlink-external-icon: false\nexecute:\n cache: true\nimage: rowhouse.jpg\n---\n\nIt's July, so it's time for another check-in on building permits in Edmonton. 2025 was a [record year](../zbr-two-year-review/index.qmd) for the missing middle and [Q1 2026](../q1-building-permits/index.qmd) looked like it might continue that momentum. With a full six months of data now in hand, the picture has shifted: overall permit activity has slowed, driven by a lull in large apartment projects. But look past the apartment category, and the RS Zone rowhome story keeps getting stronger.\n\nIn the rest of this post, I compare H1 2026 permits year-over-year against prior H1s, project what a full 2026 might look like if this pace holds, look at which neighbourhoods are seeing the most RS Zone infill, and check whether Edmonton is continuing to build close to transit. New this quarter, I took a look at the cumulative number of homes permitted since the RS Zone took effect in January 2024, and how that supply is distributed across neighbourhood types. I also added a look at frequent bus walksheds and if rowhomes are built close to the frequent bus network.\n\n![A rowhouse I biked by in Forest Heights](rowhouse.jpg){#fig-rowhouse-image fig-alt=\"A rowhouse in Forest Heights\" width=\"538\"}\n\n## Key facts\n\n\n\n- Edmonton issued building permits for **6,536** homes in H1 2026. Annualized, that projects to roughly **13,726** homes for the full year.\n\n- Homes permitted in H1 2026 is **29.4% lower** than H1 2025, when 9,252 homes were permitted.\n\n- **Fiveplex to Eightplex** projects led all categories by homes added in H1 2026.\n\n- **26%** of homes were permitted within 800m of an existing or under-construction LRT stop in H1 2026, compared to 31% in 2025 (full year).\n\n## Data\n\n\n::: {.cell}\n\n:::\n\n\nEdmonton's [general building permit data](https://data.edmonton.ca/Urban-Planning-Economy/General-Building-Permits/24uj-dj8v/about_data) tracks building permits since 2009, with columns for building type, work type, location, units added, and more. Unlike the [Q1 post](../q1-building-permits/index.qmd), which used a manually downloaded shapefile snapshot, this post fetches permit data directly from Edmonton's Open Data API, filtered to H1 (January through June) to exclude incomplete July data.\n\nEdmonton's [property assessment data](https://data.edmonton.ca/City-Administration/Property-Assessment-Data-Current-Calendar-Year-/q7d6-ambg/about_data) provides one row per property with zoning and neighbourhood information, used to calculate how many RS-zoned properties exist per neighbourhood.\n\nFor background on the RS Zone and ZBR, see the [two-year review post](../zbr-two-year-review/index.qmd).\n\nSimilar to my [Q1 post](../q1-building-permits/index.qmd), to annualize the 2026 H1 numbers to the full year, I estimate an annualization multiplier from historical data. For each year from 2009 to 2025, I calculate the ratio of full-year units to H1 units, and use the median as the multiplier.\n\n\n::: {.cell}\n::: {.cell-output-display}\n![Historical ratio of full-year to H1 residential building permit units](index_files/figure-html/fig-h1-multiplier-1.png){#fig-h1-multiplier width=672}\n:::\n:::\n\n\nThe median H1 multiplier is 2.1×, as shown in @fig-h1-multiplier, meaning a full year typically produces 2.1 times the homes permitted in H1 alone. All 2026 projections in this post use this multiplier.\n\n## Year-over-year H1 comparison\n\nThe most direct way to compare H1 2026 to prior years is to look at H1 data across all years, stripping out seasonality entirely. @fig-h1-yoy-units shows units added in H1 for each year since 2009, broken down by project type. The overall dip is visible, but it's driven by the 9+ Apartment category, can vary year to year depending on when a handful of large projects happen to get building permits. The 5-8 unit rowhome, by contrast, keeps climbing, continuing the trend we've seen since ZBR came into effect.\n\n\n::: {#fig-h1-yoy-units .cell}\n::: {.cell-output-display}\n![Line plot](index_files/figure-html/fig-h1-yoy-units-1.png){#fig-h1-yoy-units-1 width=672}\n:::\n\n::: {.cell-output-display}\n![Area plot](index_files/figure-html/fig-h1-yoy-units-2.png){#fig-h1-yoy-units-2 width=672}\n:::\n\nTotal homes permitted in H1 by project type, 2009–2026\n:::\n\n\n@fig-h1-yoy-permits shows the same H1 data as raw permit counts rather than units, a complementary view for understanding how many discrete projects are driving each category.\n\n\n::: {#fig-h1-yoy-permits .cell}\n::: {.cell-output-display}\n![Line plot](index_files/figure-html/fig-h1-yoy-permits-1.png){#fig-h1-yoy-permits-1 width=672}\n:::\n\n::: {.cell-output-display}\n![Area plot](index_files/figure-html/fig-h1-yoy-permits-2.png){#fig-h1-yoy-permits-2 width=672}\n:::\n\nNumber of building permits issued in H1 by project type, 2009–2026\n:::\n\n\nLooking at the number of homes by neighbourhood type, @fig-h1-yoy-nbhd shows that mature neighbourhoods held up best in H1 2026, again driven by the 5-8 unit rowhome. The areas between the mature core and the Henday saw the sharpest pullback, largely reflecting fewer large apartment permits in those neighbourhoods this year so far.\n\n\n::: {#fig-h1-yoy-nbhd .cell}\n::: {.cell-output-display}\n![Line plot](index_files/figure-html/fig-h1-yoy-nbhd-1.png){#fig-h1-yoy-nbhd-1 width=672}\n:::\n\n::: {.cell-output-display}\n![Area plot](index_files/figure-html/fig-h1-yoy-nbhd-2.png){#fig-h1-yoy-nbhd-2 width=672}\n:::\n\nTotal homes permitted in H1 by neighbourhood type, 2009–2026\n:::\n\n\n## Projecting 2026 from H1 data\n\nWith half of the year under our belt, we can make a good guess as to how the rest of the year is trending. \\@fig-annualized-units shows the full-year units added by project type, with 2026 projected from H1 using the 2.1× adjustment.\n\nThe total projection lands below 2025's record, closer to 2024 levels. That's still a strong year, just not another record. As always, a handful of large apartment projects in the second half of the year could move this projection significantly.\n\n\n::: {#fig-annualized-units .cell}\n::: {.cell-output-display}\n![Line plot](index_files/figure-html/fig-annualized-units-1.png){#fig-annualized-units-1 width=672}\n:::\n\n::: {.cell-output-display}\n![Area plot](index_files/figure-html/fig-annualized-units-2.png){#fig-annualized-units-2 width=672}\n:::\n\nTotal homes permitted by project type, 2009–2025 (full year) and 2026 (projected from H1)\n:::\n\n\n@fig-annualized-nbhd breaks the same projection down by neighbourhood type. Mature neighbourhoods are still projected to drive a significant amount of Edmonton's housing supply, driven by by the 5-8 unit rowhome category. While there has been anecdotes and discourse on social media about landlords of new rowhomes needing to lower rent to find tenants, it seems like we have not yet hit the rent floor where building permits will slow down. We are still playing catchup on years of suppressed demand to live centrally.\n\nThe slowdown shows up mostly outside the mature core, where the apartment pipeline has thinned out this year. Nevertheless, the supply of homes outside the Henday is on track to remain relatively strong.\n\n\n::: {#fig-annualized-nbhd .cell .preview-image}\n::: {.cell-output-display}\n![Line plot](index_files/figure-html/fig-annualized-nbhd-1.png){#fig-annualized-nbhd-1 width=672}\n:::\n\n::: {.cell-output-display}\n![Area plot](index_files/figure-html/fig-annualized-nbhd-2.png){#fig-annualized-nbhd-2 width=672}\n:::\n\nHomes permitted by neighbourhood type, 2009–2025 (full year) and 2026 (projected from H1)\n:::\n\n\n## Cumulative homes since the RS Zone took effect\n\nYear-over-year comparisons and full-year projections are useful for tracking momentum, but they don't answer a simpler question: how many homes has the RS Zone actually delivered since it took effect? @fig-cumulative-nbhd tracks the running total of homes permitted each month since January 2024, split by neighbourhood type.\n\n\n::: {.cell}\n::: {.cell-output-display}\n![Cumulative homes permitted by neighbourhood type since the RS Zone took effect (Jan 2024)](index_files/figure-html/fig-cumulative-nbhd-1.png){#fig-cumulative-nbhd width=672}\n:::\n:::\n\n\nOutside Henday still adds the most homes in raw terms, no surprise, since suburban subdivisions have plenty of vacant land left to build on. But watch the shape of the lines: mature neighbourhoods durably overtook the areas between the mature core and the Henday back in March 2025, and have kept climbing at a steeper pace ever since. Since January 2024, Edmonton has permitted 38,020 homes, and 31% of them landed in mature neighbourhoods.\n\n## Top neighbourhoods for RS infill\n\nWhere is the infill actually happening? And how does the level of activity compare to the total number of properties in each neighbourhood?\n\n@tbl-rs-nbhd-type shows the H1 2026 5–8 unit RS Zone permit activity by neighbourhood type, compared to the total number of RS-zoned properties. Even cumulatively over six months, the share of properties being redeveloped remains small. Once again: incremental growth.\n\n\n::: {#tbl-rs-nbhd-type .cell tbl-cap='RS Zone 5–8 unit permits vs total properties by neighbourhood type, H1 2026'}\n::: {.cell-output-display}\n\n```{=html}\n
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n\n\n\n\n \n\n\n\n\n\n\n\n \n \n \n \n \n \n
RS Zone intensity by neighbourhood type
H1 2026, and projected 2026
Neighbourhood type\n
H1 2026
\n 		RS-zoned properties\n
Projected 2026 (H1 ×2.1)
\n
PermitsHomes added% redevelopedPermitsHomes added% redeveloped
Mature1921,4330.24%78,5514033,0090.51%
Between mature and Henday9610.01%64,279191280.03%
Jacob Dawang, City of Edmonton Open Data
\n
\n```\n\n:::\n:::\n\n\n@tbl-top-neighbourhoods shows the top neighbourhoods by H1 2026 5–8 unit RS permit volume. These are the neighbourhoods where ZBR's effects are most visible right now. The west end neighbourhoods along the Valley Line West, and Prince Charles, continue to be popular, but as we will see in a map in @sec-transit, we're starting to see more development along the already-completed Valley Line East.\n\n\n::: {#tbl-top-neighbourhoods .cell .column-page tbl-cap='Top neighbourhoods by H1 2026 5–8 unit RS permits'}\n::: {.cell-output-display}\n\n```{=html}\n
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n\n\n\n\n \n\n\n\n\n\n\n\n \n\n\n\n\n\n\n\n \n\n\n\n\n\n\n\n \n\n\n\n\n\n\n\n \n \n \n \n \n \n
Top neighbourhoods by H1 2026 5–8 unit RS permits
H1 2026 building permits
NeighbourhoodPermitsRS properties% redevelopedHomes addedPopulation 2021Population 1971Pop. change
Glenwood109471.1%784,9605,650−12.2%
High Park96151.5%721,4802,545−41.8%
King Edward Park91,4560.6%624,8206,310−23.6%
Prince Charles85191.5%601,4252,080−31.5%
West Jasper Place75671.2%562,8852,925−1.4%
Jacob Dawang, City of Edmonton Open Data
\n
\n```\n\n:::\n:::\n\n\nOf course, @tbl-selected-neighbourhoods is the usual table for selected neighbourhoods that have been prominent in debates about RS Zone infill. Another 0.3% of properties redeveloped in Crestwood!\n\n\n::: {#tbl-selected-neighbourhoods .cell .column-page tbl-cap='Selected neighbourhood 5–8 unit RS profiles, H1 2026'}\n::: {.cell-output-display}\n\n```{=html}\n
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n\n\n\n\n \n\n\n\n\n\n\n\n \n\n\n\n\n\n\n\n \n\n\n\n\n\n\n\n \n\n\n\n\n\n\n\n \n\n\n\n\n\n\n\n \n\n\n\n\n\n\n\n \n\n\n\n\n\n\n\n \n \n \n \n \n \n
Selected neighbourhood 5–8 unit RS profiles
H1 2026 building permits
NeighbourhoodPermitsRS properties% redevelopedHomes addedPopulation 2021Population 1971Pop. change
Belgravia27020.3%162,2202,940−24.5%
Britannia Youngstown68900.7%474,3504,590−5.2%
Crestwood38590.3%202,4153,445−29.9%
Glenwood109471.1%784,9605,650−12.2%
Grovenor08830.0%02,5853,100−16.6%
Mckernan58810.6%352,5802,840−9.2%
Parkview31,3840.2%193,3755,735−41.2%
Westmount41,1090.4%306,1657,450−17.2%
Jacob Dawang, City of Edmonton Open Data
\n
\n```\n\n:::\n:::\n\n\n@tbl-cumulative-neighbourhoods is an interactive table with cumulative 2024 + 2025 + H1 2026 activity for all neighbourhoods. You can search for your neighbourhood, or sort by any column.\n\n\n::: {#tbl-cumulative-neighbourhoods .cell .column-page tbl-cap='Cumulative RS infill by neighbourhood, 2024–H1 2026 (interactive)'}\n::: {.cell-output-display}\n\n```{=html}\n
\n\n
\n
Cumulative 5–8 unit RS permits by neighbourhood
\n
2024 + 2025 + H1 2026 building permits
\n
\n
\n
\n
\n
\n
Jacob Dawang, City of Edmonton Open Data
\n
\n
\n
\n
\n\n
\n```\n\n:::\n:::\n\n\n## The eight-unit concentration\n\nIn 2025, projects with exactly eight units dominated the Fiveplex to Eightplex category in the RS Zone, a direct consequence of the eight-unit cap. @tbl-unit-breakdown covers all RS Zone permits from 1 to 8 units, comparing H1 2025 to H1 2026. The eight-unit rowhome has only become more dominant: it now accounts for a larger share of small-scale homes than it did a year ago, even as most other categories cooled off.\n\nGiven that 8-unit projects continue to account for the largest share of small-scale supply, I am glad that City Council chose not to reduce the number of units permitted to 6. This is an evidence-backed choice that keeps paying dividends.\n\n\n::: {#tbl-unit-breakdown .cell tbl-cap='RS Zone 1-8 unit permits by exact unit count, H1 2025 vs H1 2026'}\n::: {.cell-output-display}\n\n```{=html}\n
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n\n \n\n\n\n\n \n\n\n\n\n \n\n\n\n\n \n\n\n\n\n \n\n\n\n\n \n\n\n\n\n \n\n\n\n\n \n\n\n\n\n \n \n \n \n \n \n
RS Zone: permits by unit count
H1 2025 vs. H1 2026
Units per permitPermits (H1 2025)Homes (H1 2025)Permits (H1 2026)Homes (H1 2026)
1137137126126
27314655110
3391133
46024054216
5525525
62012033198
774933231
81108801301,040
sum41516064471979
Jacob Dawang, City of Edmonton Open Data
\n
\n```\n\n:::\n:::\n\n\n## Building close to transit {#sec-transit}\n\n2025 set a record for the proportion of homes permitted within 800m of transit. So far, 2026 is right in line with last year. @fig-ecdf-transit compares the cumulative distribution of H1 homes by distance from the nearest LRT stop, across recent years. H1 2026 is running in line with H1 2025, not the record pace 2025 ultimately closed the year at.\n\nWithin 800m of transit, the cumulative share of homes is 26% in H1 2026, compared to 31% in 2025 (full year).\n\n\n::: {.cell}\n::: {.cell-output-display}\n![Cumulative distribution of H1 homes by distance from nearest LRT stop](index_files/figure-html/fig-ecdf-transit-1.png){#fig-ecdf-transit width=672}\n:::\n:::\n\n\n@fig-rowhome-lrt-dist-map shows that the 5-8 unit rowhomes continue to trace the path of the LRT. While we continue to see a lot of infill in the west end, the Valley Line East is starting to see more activity as well. I am glad to see this given some [less than ideal district plans](../../2023/avonmore-stop/index.qmd) for some of the stops along the Valley Line East.\n\n\n::: {.cell}\n::: {.cell-output-display}\n![Map of H1 2026 5–8 unit RS Zone permits relative to LRT](index_files/figure-html/fig-rowhome-lrt-dist-map-1.png){#fig-rowhome-lrt-dist-map width=672}\n:::\n:::\n\n\n### Beyond LRT: the frequent bus network\n\nLRT isn't Edmonton's only high-quality transit. ETS's Frequent Network, routes 1 through 9, is scheduled to run every 15 minutes throughout the day, seven days a week. Because buses have a shorter effective walkshed than LRT, I use a 400m threshold for frequent bus stops instead of the 800m threshold used for LRT throughout this post. @fig-ecdf-frequent-transit shows the same cumulative-distribution view as @fig-ecdf-transit, but for each home's raw distance to the nearer of LRT or a frequent bus stop, so you can directly see how much closer homes get once frequent buses are counted alongside LRT. Both walking thresholds are marked on the chart.\n\n\n::: {.cell}\n\n:::\n\n\n\n::: {.cell}\n::: {.cell-output-display}\n![Cumulative distribution of H1 homes by raw distance to nearest LRT or frequent bus stop](index_files/figure-html/fig-ecdf-frequent-transit-1.png){#fig-ecdf-frequent-transit width=672}\n:::\n:::\n\n\nCounting the frequent bus network alongside LRT meaningfully expands how much of H1 2026's housing supply counts as close to high-quality transit: 44% of homes were within 800m of LRT or 400m of a frequent bus stop, compared to 26% for LRT alone. @fig-rowhome-frequent-transit-map shows both networks together, with LRT stops and their 800m radius in red and frequent bus stops and their 400m radius in orange. The frequent bus network fills in a lot of the gaps between LRT lines, especially along the west end and mature north-side neighbourhoods that aren't within easy walking distance of a station.\n\n\n::: {.cell}\n::: {.cell-output-display}\n![Map of H1 2026 5–8 unit RS Zone permits relative to LRT and the frequent bus network](index_files/figure-html/fig-rowhome-frequent-transit-map-1.png){#fig-rowhome-frequent-transit-map width=864}\n:::\n:::\n\n\n## Conclusions\n\nOverall building permit activity slowed in H1 2026 compared to 2025's record pace, but nearly all of that slowdown is explained by fewer large apartment projects, a category that has always been lumpy and unpredictable from year to year. Look at the RS Zone specifically, and the story is unambiguously positive: the 5-8 unit rowhome category continue to produce, mature neighbourhoods held up best of any area of the city, and the eight-unit rowhome is more dominant than ever within the small-scale category.\n\nWe're already seeing the effects of increased housing supply in Edmonton over the past two years. Rents are coming down and landlords are offering incentives. Whether 2026 matches 2025's record total or not, the RS Zone continues to quietly deliver more homes in mature, transit-accessible neighbourhoods every quarter.\n\nThe data continues to make the case for the RS Zone. Even in a slower year for permits overall, the policies that unlocked the missing middle keep producing results. If you'd like to help advocate for more housing choice in Edmonton, consider joining [Grow Together Edmonton](https://www.growtogetheryeg.com/).", + "supporting": [], + "filters": [ + "rmarkdown/pagebreak.lua" + ], + "includes": { + "include-in-header": [ + "\n\n\n\n\n\n\n" + ] + }, + "engineDependencies": {}, + "preserve": {}, + "postProcess": true + } +} \ No newline at end of file diff --git a/_freeze/blog/2026/q2-building-permits/index/figure-html/fig-annualized-nbhd-1.png b/_freeze/blog/2026/q2-building-permits/index/figure-html/fig-annualized-nbhd-1.png new file mode 100644 index 0000000..28818d4 Binary files /dev/null and b/_freeze/blog/2026/q2-building-permits/index/figure-html/fig-annualized-nbhd-1.png differ diff --git a/_freeze/blog/2026/q2-building-permits/index/figure-html/fig-annualized-nbhd-2.png b/_freeze/blog/2026/q2-building-permits/index/figure-html/fig-annualized-nbhd-2.png new file mode 100644 index 0000000..3c0e934 Binary files /dev/null and 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-0,0 +1,1110 @@ +--- +title: "The property tax dividend from Edmonton's RS Zone rowhomes" +date: "2026-07-09" +author: "Jacob Dawang" +categories: [housing, edmonton, zoning] +description: "Redeveloping an old house into a 5-8 unit RS Zone rowhome doesn't just add homes, it multiplies the property's assessed value. Here's what that's worth to Edmonton's property tax base since the Zoning Bylaw Renewal took effect." +link-external-newwindow: true +link-external-icon: false +execute: + cache: false +draft: true +--- + +Edmonton's Zoning Bylaw Renewal (ZBR) has spent two years quietly rewriting mature neighbourhoods, one lot at a time. [Prior posts on this blog](../zbr-two-year-review/index.qmd) have tracked the homes it unlocked and the neighbourhoods it reached. This post asks a different question: what is that redevelopment worth to the City's property tax base? + +When a single-family lot in a mature neighbourhood becomes a 5-8 unit RS Zone rowhome, its assessed value doesn't just grow, it multiplies. That's a durable increase in the tax base, not a one-time windfall: every year, that property contributes meaningfully more property tax than the house it replaced would have. Using building permits from 2024, the first year the RS Zone was in force, matched against the City's property assessment data, I measure that uplift directly for completed projects, then use a regression model fit on those measurements to estimate what it adds up to across the full 2024-2026 pipeline. + +## Data + +This analysis combines three of Edmonton's Open Data sources. Edmonton's [general building permit data](https://data.edmonton.ca/Urban-Planning-Economy/General-Building-Permits/24uj-dj8v/about_data), the same source used in the [Q2 2026 building permit report](../q2-building-permits/index.qmd), identifies which properties were redeveloped into 5-8 unit RS Zone rowhomes and when. Edmonton's [current calendar year property assessment data](https://data.edmonton.ca/City-Administration/Property-Assessment-Data-Current-Calendar-Year-/q7d6-ambg/about_data) gives each property's assessed value as of 2026, and Edmonton's [historical property assessment data](https://data.edmonton.ca/City-Administration/Property-Assessment-Data-Historical-/qi6a-xuwt/about_data) gives assessed values back to 2012, including 2024 and 2025. + +The key challenge is linking a specific building permit to the same physical property, before and after redevelopment. Account numbers usually persist through redevelopment, but addresses often don't: a lot can get re-addressed when it's rebuilt, so a permit's civic address is frequently *not* the address that appears in the property's earlier assessment record. Instead, I match on legal description (plan/block/lot), which is stable across redevelopment, with a fallback to geographic proximity for the small number of properties where the legal description format doesn't parse identically on both sides, or where redevelopment came with a brand new account number. + +```{r} +#| label: setup +#| include: false +library(tidyverse) +library(sf) +library(gt) +library(scales) +library(mountainmathHelpers) +library(jdawangHelpers) + +options( + cancensus.api_key = Sys.getenv("CM_API_KEY"), + cancensus.cache_path = Sys.getenv("CM_CACHE_PATH"), + tongfen.cache_path = Sys.getenv("TONGFEN_CACHE_PATH"), + nextzen_API_key = Sys.getenv("NEXTZEN_API_KEY") +) + +bp_raw <- get_edmonton_building_permit_data( + cache_dir = Sys.getenv("EDMONTON_BP_CACHE_PATH") +) +crs <- lambert_conformal_conic_at(bp_raw) + +bp <- bp_raw |> + st_transform(crs) |> + mutate(permit_row_id = row_number()) |> + filter(year < 2026 | (year == 2026 & month_number <= 6)) |> + filter_edmonton_residential() |> + filter(units_added >= 1, work_type != "(04) Excavation") |> + add_edmonton_project_type() |> + add_edmonton_suite_info() |> + add_edmonton_neighbourhood_type() + +# LRT stops (existing + under construction), same setup as the Q2 2026 report +future_stops <- read_sf("../../../data/future_lrt_stops.geojson") |> + filter( + !(stop_name %in% + c( + "Castle Downs Station", + "145 Ave Station", + "137 Ave Station", + "132 Ave Station" + )) + ) + +transit_stops <- load_edmonton_transit_stops( + gtfs_path = "../../../data/ca-alberta-edmonton-transit-system-gtfs-714.zip", + service_date = as.Date("2023-11-09"), + future_stops = future_stops, + crs = crs +) + +# The pipeline this whole post is about: mature-neighbourhood RS Zone +# 5-8 unit new-builds, permitted since ZBR took effect. Each permit gets +# its distance to the nearest LRT stop, used by the uplift model later. +rowhome_pipeline <- bp |> + filter( + zoning == "RS", + between(units_added, 5, 8), + work_type == "(01) Building - New", + neighbourhood_type == "Mature" + ) |> + add_transit_distance(transit_stops) +``` + +```{r} +#| label: fetch-assessment-data +# This is a one-off fetch specific to this post: Edmonton's property +# assessment data hasn't been used on this blog before, so this helper +# isn't (yet) part of jdawangHelpers. +fetch_socrata_csv <- function(resource, query, cache_file) { + cache_dir <- Sys.getenv("EDMONTON_BP_CACHE_PATH") + path <- file.path(cache_dir, cache_file) + if (!file.exists(path)) { + url <- paste0( + "https://data.edmonton.ca/resource/", resource, ".csv?", + URLencode(query) + ) + download.file(url, path, mode = "wb") + } + read_csv(path, show_col_types = FALSE, col_types = cols(.default = "c")) +} + +assessment_hist <- fetch_socrata_csv( + "qi6a-xuwt", + "$where=assessment_year in (2024,2025)&$limit=1000000", + "assessment_2024_2025.csv" +) |> + mutate( + assessment_year = as.integer(assessment_year), + assessed_value = as.numeric(assessed_value), + latitude = as.numeric(latitude), + longitude = as.numeric(longitude) + ) + +assessment_2026 <- fetch_socrata_csv( + "q7d6-ambg", "$limit=600000", "assessment_2026.csv" +) |> + mutate( + assessed_value = as.numeric(assessed_value), + latitude = as.numeric(latitude), + longitude = as.numeric(longitude) + ) + +tax_rates <- fetch_socrata_csv("pwis-wc4c", "$limit=10000", "tax_rates.csv") |> + mutate( + tax_year = as.integer(tax_year), + amount_per_dollar_of_assessed_value = as.numeric( + amount_per_dollar_of_assessed_value + ) + ) + +assessment_2024 <- assessment_hist |> filter(assessment_year == 2024) +assessment_2025 <- assessment_hist |> filter(assessment_year == 2025) + +municipal_rate <- function(class, yr) { + tax_rates |> + filter(tax_year == yr, tax_rate_type == "Municipal", assessment_class == class) |> + pull(amount_per_dollar_of_assessed_value) +} +``` + +## Measuring the uplift: the 2024 cohort + +The 2026 property assessment is supposed to reflect each property's physical condition as of December 31, 2025. In principle, that means any 2024 permit whose building had received occupancy by the end of 2025 should show up, completed, in the 2026 assessment roll, giving a clean before-and-after pair. In practice, as we'll see below, the assessments only reliably catch up to buildings finished by about September 2025, so the measurement cohort uses that earlier cutoff. + +```{r} +#| label: measurement-cohort +cohort_2024 <- rowhome_pipeline |> + filter(year == 2024) + +n_cohort_2024_all <- nrow(cohort_2024) +n_occupancy_by_dec <- cohort_2024 |> + st_drop_geometry() |> + filter(!is.na(occupancy_granted_date), occupancy_granted_date <= as.Date("2025-12-31")) |> + nrow() +``` + +Edmonton issued **`r n_cohort_2024_all`** mature-neighbourhood RS Zone 5-8 unit new-build permits in 2024, of which **`r n_occupancy_by_dec`** had received occupancy by the end of 2025. I match all `r n_cohort_2024_all` to their assessment records, then use the occupancy dates to decide which ones the 2026 assessment actually reflects as complete. + +### Matching permits to assessments + +I parse each side's legal description into a `(plan, block, lot)` key and join on it. A building permit's legal description looks like `Plan 715HW Blk 25 Lot 22`; the historical assessment data records the same parcel as `Plan: 715HW Block: 25 Lot: 22`. + +```{r} +#| label: legal-key-matching +parse_permit_legal <- function(x) { + m <- str_match(x, "Plan\\s+(\\S+)\\s+Blk\\s+(\\S+)\\s+Lots?\\s+(\\S+)") + tibble(plan = m[, 2], block = m[, 3], lot = m[, 4]) +} +parse_assessment_legal <- function(x) { + m <- str_match(x, "Plan:\\s*(\\S+)\\s+Block:\\s*(\\S+)\\s+Lot:\\s*(\\S+)") + tibble(plan = m[, 2], block = m[, 3], lot = m[, 4]) +} +normalize_key <- function(plan, block, lot) { + paste(toupper(str_trim(plan)), toupper(str_trim(block)), toupper(str_trim(lot)), sep = "|") +} + +assessment_2024_keyed <- assessment_2024 |> + bind_cols(parse_assessment_legal(assessment_2024$legal_description)) |> + mutate(key = normalize_key(plan, block, lot)) |> + filter(!is.na(key)) |> + distinct(key, .keep_all = TRUE) + +# Reusable matcher: join a cohort of permits to their 2024 baseline assessed +# value by legal-description key. Used for the 2024 cohort here, and again +# later for the 2025/2026 permits when estimating net uplift. +match_baseline_2024 <- function(cohort_sf) { + cohort_sf |> + st_drop_geometry() |> + bind_cols(parse_permit_legal(cohort_sf$legal_description)) |> + mutate(key = normalize_key(plan, block, lot)) |> + left_join( + assessment_2024_keyed |> select(key, account_number, value_2024 = assessed_value), + by = "key" + ) +} + +cohort_matched <- match_baseline_2024(cohort_2024) +n_matched_legal <- sum(!is.na(cohort_matched$account_number)) +``` + +That legal-key match alone links **`r n_matched_legal`** of `r n_cohort_2024_all` properties (`r percent(n_matched_legal / n_cohort_2024_all, accuracy = 1)`) to their 2024 baseline assessed value. For the remainder, I fall back to matching each permit to the nearest 2024 assessment point within 25m. I checked these fallback matches by hand: most are lots that were consolidated from two legal titles into one (a permit reads `Lots 2-3`, while the assessment record spells that out as two separate `Lot:` entries joined by " / ", which my parser doesn't follow), and in each case checked the fallback match has the exact same civic address as the permit, at a matched distance of a few millimetres. + +```{r} +#| label: geo-fallback-2024 +# Reusable: fall back to the nearest 2024 assessment point within 25m for +# any permit the legal-key match missed. +geo_fallback_baseline <- function(matched_df, cohort_sf) { + still_unmatched <- matched_df |> filter(is.na(account_number)) + if (nrow(still_unmatched) == 0) { + return(matched_df) + } + + unmatched_sf <- cohort_sf |> filter(permit_row_id %in% still_unmatched$permit_row_id) + assessment_2024_sf <- assessment_2024 |> + filter(!is.na(latitude), !is.na(longitude)) |> + st_as_sf(coords = c("longitude", "latitude"), crs = 4326) |> + st_transform(crs) + + nearest_idx <- st_nearest_feature(unmatched_sf, assessment_2024_sf) + dist_m <- as.numeric(st_distance(unmatched_sf, assessment_2024_sf[nearest_idx, ], by_element = TRUE)) + + geo_matches <- tibble( + permit_row_id = unmatched_sf$permit_row_id, + geo_account = assessment_2024_sf$account_number[nearest_idx], + geo_value_2024 = assessment_2024_sf$assessed_value[nearest_idx], + geo_dist_m = dist_m + ) |> + filter(geo_dist_m <= 25) + + matched_df |> + left_join(geo_matches, by = "permit_row_id") |> + mutate( + account_number = coalesce(account_number, geo_account), + value_2024 = coalesce(value_2024, geo_value_2024) + ) |> + select(-any_of(c("geo_account", "geo_value_2024", "geo_dist_m"))) +} + +cohort_matched <- geo_fallback_baseline(cohort_matched, cohort_2024) + +n_matched_total <- sum(!is.na(cohort_matched$account_number)) +n_dropped <- n_cohort_2024_all - n_matched_total +``` + +The 25m fallback brings the total match rate to **`r n_matched_total`** of `r n_cohort_2024_all` (`r percent(n_matched_total / n_cohort_2024_all, accuracy = 1)`). The remaining `r n_dropped` properties have no corresponding parcel in the 2024 assessment roll at all, likely lots created by subdivision after that year's assessment date, so they're dropped from the analysis. + +Each matched property's `account_number` persists through redevelopment in most cases, so I use it to look up the completed building's 2026 assessed value. A small number of properties are issued a brand new account number when redeveloped rather than keeping the old one, exactly the re-addressing situation described above; I confirmed one such case by hand, where the 25m fallback correctly landed on a new 2026 account whose civic address matched the permit's own address exactly, even though the old account (still on the 2024/2025 rolls under the pre-redevelopment address) had disappeared from the 2026 data entirely. + +```{r} +#| label: join-2026-and-2025 +# Reusable: join a baseline-matched cohort to its 2026 outcome value by +# account_number, falling back to the nearest 2026 assessment point within +# 25m for the rare case where redevelopment came with a new account number. +match_outcome_2026 <- function(matched_df, cohort_sf) { + joined <- matched_df |> + filter(!is.na(account_number)) |> + left_join( + assessment_2026 |> select(account_number, value_2026 = assessed_value, mill_class_1), + by = "account_number" + ) + + missing_2026 <- joined |> filter(is.na(value_2026)) + if (nrow(missing_2026) == 0) { + return(joined) + } + + missing_2026_sf <- cohort_sf |> filter(permit_row_id %in% missing_2026$permit_row_id) + assessment_2026_sf <- assessment_2026 |> + filter(!is.na(latitude), !is.na(longitude)) |> + st_as_sf(coords = c("longitude", "latitude"), crs = 4326) |> + st_transform(crs) + + nearest_idx <- st_nearest_feature(missing_2026_sf, assessment_2026_sf) + geo_2026 <- tibble( + permit_row_id = missing_2026_sf$permit_row_id, + geo_value_2026 = assessment_2026_sf$assessed_value[nearest_idx], + geo_mill_class = assessment_2026_sf$mill_class_1[nearest_idx], + geo_dist_m = as.numeric(st_distance(missing_2026_sf, assessment_2026_sf[nearest_idx, ], by_element = TRUE)) + ) |> + filter(geo_dist_m <= 25) + + joined |> + left_join(geo_2026, by = "permit_row_id") |> + mutate( + value_2026 = coalesce(value_2026, geo_value_2026), + mill_class_1 = coalesce(mill_class_1, geo_mill_class) + ) |> + select(-any_of(c("geo_value_2026", "geo_mill_class", "geo_dist_m"))) +} + +# 2025 (mid-construction) value, used later for the partial-uplift estimate +matched_2024_all <- match_outcome_2026(cohort_matched, cohort_2024) |> + left_join( + assessment_2025 |> select(account_number, value_2025 = assessed_value), + by = "account_number" + ) |> + filter(!is.na(value_2026)) |> + mutate( + bucket = if_else(units_added <= 6, "5-6 units", "7-8 units"), + gross_uplift = value_2026 - value_2024 + ) + +n_matched_2024_all <- nrow(matched_2024_all) +``` + +That yields **`r n_matched_2024_all`** 2024 permits with both a 2024 baseline and a 2026 assessed value. + +### When does the assessment catch up? + +Before treating every occupancy-granted building as "complete" in the 2026 data, it's worth checking whether the assessments actually keep up with late-year completions. @fig-assessment-lag plots each matched property's gross uplift against its occupancy date. The pattern is stark: buildings that received occupancy by roughly the end of September 2025 show the full rowhome uplift, while October, November, and especially December completions drop off a cliff — their 2026 assessed values still largely reflect a construction site, not a finished building, even though the assessment is nominally "as of December 31, 2025". + +```{r} +#| label: fig-assessment-lag +#| fig-cap: "Gross assessed value uplift by occupancy date: the 2026 assessment only reliably reflects buildings finished by about September 2025" +occupancy_cutoff <- as.Date("2025-09-30") + +matched_2024_all |> + filter(!is.na(occupancy_granted_date), occupancy_granted_date <= as.Date("2025-12-31")) |> + mutate( + reflected = if_else( + occupancy_granted_date <= occupancy_cutoff, + "Occupancy by Sept 2025", + "Occupancy Oct-Dec 2025" + ) + ) |> + ggplot(aes(x = occupancy_granted_date, y = gross_uplift, colour = reflected)) + + geom_point(size = 2, alpha = 0.7) + + geom_vline(xintercept = occupancy_cutoff, linetype = "dashed", colour = "grey50") + + scale_y_continuous(labels = label_dollar(scale = 1e-6, suffix = "M")) + + scale_x_date( + date_labels = "%b %Y", + date_breaks = "6 months", + guide = guide_axis(angle = 45) + ) + + labs( + title = "Assessment lag: uplift by occupancy date", + subtitle = "2024 permits with occupancy granted by Dec 31, 2025; dashed line = Sept 30, 2025", + x = "Occupancy granted", + y = "Gross assessed value uplift", + colour = NULL, + caption = CAPTION_COE + ) + + theme_jd(mode = "light") +``` + +So the measurement cohort for this post is the matched 2024 permits with **occupancy granted by September 30, 2025** — buildings whose 2026 assessment genuinely reflects the completed rowhome. Everything else, including those October-December completions, goes into the "not yet fully reflected" group. + +```{r} +#| label: cohort-split +final_cohort <- matched_2024_all |> + filter(!is.na(occupancy_granted_date), occupancy_granted_date <= occupancy_cutoff) + +not_yet_complete_matched <- matched_2024_all |> + anti_join(final_cohort, by = "permit_row_id") + +n_final_cohort <- nrow(final_cohort) +``` + +The measurement cohort is **`r n_final_cohort`** properties. @tbl-spotlight traces two properties through the process, from their pre-redevelopment assessed value, through a mid-construction 2025 assessment, to their completed 2026 value. The Alberta Avenue example received occupancy in November 2025, yet its 2026 value looks fully assessed — a reminder that the lag in @fig-assessment-lag is a strong tendency, not a hard rule, which is why the conservative September cutoff is used for measurement. + +```{r} +#| label: tbl-spotlight +#| tbl-cap: "Two properties traced from pre-redevelopment (2024) through mid-construction (2025) to a completed rowhome (2026)" +spotlight_accounts <- c("4042701", "2049286") + +matched_2024_all |> + filter(account_number %in% spotlight_accounts) |> + mutate( + neighbourhood = str_to_title(neighbourhood), + mill_class_1 = str_to_title(mill_class_1) + ) |> + select(neighbourhood, units_added, value_2024, value_2025, value_2026, mill_class_1) |> + arrange(neighbourhood) |> + gt() |> + fmt_currency(columns = c(value_2024, value_2025, value_2026), decimals = 0) |> + cols_label( + neighbourhood = "Neighbourhood", + units_added = "Units", + value_2024 = "2024 (before)", + value_2025 = "2025 (mid-construction)", + value_2026 = "2026 (completed)", + mill_class_1 = "2026 assessment class" + ) |> + tab_header( + title = "Two RS Zone rowhomes, before and after", + subtitle = "Assessed value by year" + ) |> + finalize_gt() |> + opt_stylize_jd() +``` + +### The rest of the 2024 cohort + +The `r n_final_cohort` properties above only cover 2024 permits whose completed buildings the 2026 assessment has caught up with. The remaining matched permits, `r nrow(not_yet_complete_matched)` of them, are either still under construction or finished too late in 2025 for the assessment to reflect. Their 2026 assessed values still tell us something: whatever value the construction had reached, a *partial* uplift. @tbl-2024-actual-total combines both groups into a single, fully-observed total for the 2024 permit year, no rule required. + +```{r} +#| label: tbl-2024-actual-total +#| tbl-cap: "Actual (not model-based) 2024 cohort assessed value uplift, split by completion status" +status_complete <- "Reflected as complete (occupancy by Sept 2025)" +status_partial <- "Not yet fully reflected (later or no occupancy)" + +actual_2024 <- matched_2024_all |> + mutate( + status = if_else(permit_row_id %in% final_cohort$permit_row_id, status_complete, status_partial) + ) |> + select(status, gross_uplift) + +actual_2024_summary <- actual_2024 |> + mutate(status = fct_relevel(status, status_complete, status_partial)) |> + group_by(status) |> + summarise(n = n(), median_gross_uplift = median(gross_uplift), total_gross_uplift = sum(gross_uplift), .groups = "drop") |> + arrange(status) |> + mutate(status = as.character(status)) + +actual_2024_total <- actual_2024_summary |> + summarise( + status = "Total, 2024 cohort (matched)", + n = sum(n), + median_gross_uplift = median(actual_2024$gross_uplift), + total_gross_uplift = sum(total_gross_uplift) + ) + +bind_rows(actual_2024_summary, actual_2024_total) |> + gt(rowname_col = "status") |> + fmt_currency(columns = c(median_gross_uplift, total_gross_uplift), decimals = 0) |> + cols_label(n = "n", median_gross_uplift = "Median gross uplift", total_gross_uplift = "Total gross uplift") |> + tab_header( + title = "2024 cohort, actual gross uplift observed so far", + subtitle = "No extrapolation model applied" + ) |> + tab_style( + style = cell_text(weight = "bold"), + locations = cells_stub(rows = status == "Total, 2024 cohort (matched)") + ) |> + finalize_gt() |> + opt_stylize_jd() +``` + +That gives a fully-observed total of **`r label_dollar(scale = 1e-6, suffix = "M")(actual_2024_total$total_gross_uplift)`** in assessed value uplift already showing up in the 2026 roll from the 2024 cohort alone, no assumptions needed. It understates the eventual value of that cohort, though: the "not yet fully reflected" group's uplift is a snapshot mid-construction (or a stale assessment of a just-finished building), not the finished-building value those properties will eventually reach. That gap between actual-so-far and eventual-once-complete is exactly what the model-based extrapolation later in this post is estimating. + +### From gross uplift to a fair counterfactual + +The raw 2024-to-2026 difference in assessed value overstates the effect of redevelopment on its own, because Edmonton property values were also generally rising over that period. To isolate the redevelopment effect, I build a counterfactual: what would each property likely have been worth in 2026 if it *hadn't* been redeveloped? I estimate this from a control group of RS-zoned properties in mature neighbourhoods that were not part of any 2024-2026 residential new-build permit, taking the median ratio of their 2026 to 2024 assessed value as a general appreciation factor. + +```{r} +#| label: counterfactual-growth +redeveloped_legal_keys <- bp |> + st_drop_geometry() |> + filter(units_added >= 1, work_type == "(01) Building - New") |> + distinct(legal_description) |> + pull(legal_description) + +nbhd_type_lookup <- bp |> + st_drop_geometry() |> + distinct(neighbourhood, neighbourhood_type) |> + filter(!is.na(neighbourhood_type)) + +control_group <- assessment_2024 |> + filter(zoning == "RS") |> + left_join(nbhd_type_lookup, by = c("neighbourhood_name" = "neighbourhood")) |> + filter( + neighbourhood_type == "Mature", + !legal_description %in% redeveloped_legal_keys, + !account_number %in% final_cohort$account_number + ) |> + inner_join( + assessment_2026 |> select(account_number, value_2026 = assessed_value), + by = "account_number" + ) |> + mutate(growth_ratio = value_2026 / assessed_value) |> + filter(assessed_value > 10000, growth_ratio > 0.5, growth_ratio < 3) + +g <- median(control_group$growth_ratio, na.rm = TRUE) + +final_cohort <- final_cohort |> + mutate( + gross_uplift = value_2026 - value_2024, + net_uplift = value_2026 - g * value_2024 + ) +``` + +Across **`r comma(nrow(control_group))`** non-redeveloped RS Zone properties in mature neighbourhoods, the median 2024-to-2026 growth ratio is **`r round(g, 2)`x**, meaning a typical mature-neighbourhood house that wasn't touched still gained about `r percent(g - 1, accuracy = 1)` in assessed value over those two years. I use this as the baseline against which redevelopment uplift is measured: **net uplift** is the completed rowhome's 2026 value minus `r round(g, 2)` times its 2024 baseline, isolating the redevelopment effect from general market appreciation. **Gross uplift** is the simple, unadjusted difference, shown alongside it for comparison. + +@fig-uplift-distribution shows the distribution of both measures across the `r n_final_cohort` matched properties, split by project size. + +```{r} +#| label: fig-uplift-distribution +#| fig-cap: "Distribution of assessed value uplift per redeveloped property, gross and net of market appreciation" +uplift_long <- final_cohort |> + select(bucket, gross_uplift, net_uplift) |> + pivot_longer(c(gross_uplift, net_uplift), names_to = "type", values_to = "uplift") |> + mutate( + type = if_else(type == "gross_uplift", "Gross uplift", "Net of appreciation") + ) + +ggplot(uplift_long, aes(x = bucket, y = uplift, fill = type)) + + geom_boxplot(outlier.alpha = 0.4, position = position_dodge(width = 0.75)) + + scale_y_continuous(labels = label_dollar(scale = 1e-6, suffix = "M")) + + labs( + title = "Assessed value uplift per redeveloped property", + subtitle = "2024 RS Zone 5-8 unit rowhomes, mature neighbourhoods, reflected as complete (occupancy by Sept 2025)", + x = NULL, + y = "Assessed value uplift", + fill = NULL, + caption = CAPTION_COE + ) + + theme_jd(mode = "light") +``` + +@tbl-uplift-rules compares three simple ways of summarizing this uplift into a single per-project figure: a median per property within two size buckets (5-6 units and 7-8 units), a single pooled median per property across all sizes, and a median per home added, which can be scaled by any project's unit count. These serve as sanity anchors for the model-based rule developed next. + +```{r} +#| label: tbl-uplift-rules +#| tbl-cap: "Three ways to summarize per-project uplift, gross and net of appreciation" +rule_bucketed <- final_cohort |> + group_by(bucket) |> + summarise( + n = n(), + gross = median(gross_uplift), + net = median(net_uplift), + .groups = "drop" + ) |> + rename(rule = bucket) + +rule_pooled <- final_cohort |> + summarise(n = n(), gross = median(gross_uplift), net = median(net_uplift)) |> + mutate(rule = "Pooled (5-8 units)", .before = 1) + +rule_per_unit <- final_cohort |> + summarise( + n = n(), + gross = median(gross_uplift / units_added), + net = median(net_uplift / units_added) + ) |> + mutate(rule = "Per home added", .before = 1) + +bind_rows(rule_bucketed, rule_pooled, rule_per_unit) |> + gt(rowname_col = "rule") |> + fmt_currency(columns = c(gross, net), decimals = 0) |> + cols_label(n = "n", gross = "Median gross uplift", net = "Median net uplift") |> + tab_header( + title = "Three uplift rules compared", + subtitle = "Measured from the completed 2024 cohort" + ) |> + finalize_gt() |> + opt_stylize_jd() +``` + +### A model for uplift + +The simple rules above ignore everything about a project except its unit count. But uplift plausibly varies with location too: land near LRT stations and in more expensive neighbourhoods should command different completed values. So the headline rule for this post is a regression of each property's **gross uplift** on three things: units added, distance from the nearest LRT stop, and the neighbourhood's median RS-zone assessed value (a land-value measure computed from the same 2024 assessment data, since with only `r n_final_cohort` observations spread across `r n_distinct(final_cohort$neighbourhood)` neighbourhoods, per-neighbourhood dummy variables are off the table). + +```{r} +#| label: uplift-model +# Neighbourhood land-value covariate: median 2024 assessed value of +# RS-zoned properties, per neighbourhood. +nbhd_median_rs_value <- assessment_2024 |> + filter(zoning == "RS") |> + group_by(neighbourhood_name) |> + summarise(nbhd_median_value = median(assessed_value), .groups = "drop") + +final_cohort <- final_cohort |> + left_join(nbhd_median_rs_value, by = c("neighbourhood" = "neighbourhood_name")) + +stopifnot( + all(!is.na(final_cohort$nbhd_median_value)), + all(!is.na(final_cohort$distance_from_lrt)), + all(final_cohort$gross_uplift > 0) +) + +loocv_rmse <- function(fit_fun, pred_fun, data) { + errs <- vapply(seq_len(nrow(data)), function(i) { + m <- fit_fun(data[-i, ]) + pred_fun(m, data[i, ]) - data$gross_uplift[i] + }, numeric(1)) + sqrt(mean(errs^2)) +} +# Same as loocv_rmse() but returns the per-property errors rather than their +# RMSE, needed for a paired bootstrap comparison between two specs. +loocv_errs <- function(fit_fun, pred_fun, data) { + vapply(seq_len(nrow(data)), function(i) { + m <- fit_fun(data[-i, ]) + pred_fun(m, data[i, ]) - data$gross_uplift[i] + }, numeric(1)) +} + +# Covariate-transform search: units added and neighbourhood value each on a +# linear vs. log scale, distance from LRT on a linear vs. inverse-distance +# scale, always with gross uplift itself left untransformed (see prose +# below). errs_level/errs_level_log are kept per-observation to support a +# paired bootstrap comparison between the previous default and the winner. +errs_level <- loocv_errs( + \(d) lm(gross_uplift ~ units_added + distance_from_lrt + I(nbhd_median_value / 1e5), d), + \(m, nd) predict(m, nd), + final_cohort +) +errs_level_log <- loocv_errs( + \(d) lm(gross_uplift ~ log(units_added) + distance_from_lrt + log(nbhd_median_value), d), + \(m, nd) predict(m, nd), + final_cohort +) +rmse_level <- sqrt(mean(errs_level^2)) +rmse_level_log <- sqrt(mean(errs_level_log^2)) +rmse_log <- loocv_rmse( + \(d) lm(log(gross_uplift) ~ units_added + distance_from_lrt + log(nbhd_median_value), d), + # Duan smearing estimator for the back-transform + \(m, nd) exp(predict(m, nd)) * mean(exp(residuals(m))), + final_cohort +) +rmse_median <- sqrt(mean((median(final_cohort$gross_uplift) - final_cohort$gross_uplift)^2)) + +# Paired bootstrap SE of an RMSE difference (dollars, matching rmse_*'s own +# units) between two specs fit on the same 48 properties. +paired_bootstrap_se <- function(errs_a, errs_b, B = 2000, seed = 1) { + n <- length(errs_a) + old_seed <- .Random.seed + set.seed(seed) + diffs <- replicate(B, { + idx <- sample.int(n, n, replace = TRUE) + sqrt(mean(errs_a[idx]^2)) - sqrt(mean(errs_b[idx]^2)) + }) + .Random.seed <<- old_seed + sd(diffs) +} +spec_choice_se <- paired_bootstrap_se(errs_level_log, errs_level) + +uplift_model <- lm( + gross_uplift ~ log(units_added) + distance_from_lrt + log(nbhd_median_value), + data = final_cohort +) +``` + +Two specification choices deserve a word. First, modelling gross uplift is algebraically the same as modelling the completed 2026 value with the 2024 baseline as a fixed offset. Letting the baseline enter with a freely estimated coefficient instead doesn't help: the old house's value is nearly collinear with the neighbourhood land-value measure (r = `r round(cor(final_cohort$value_2024, final_cohort$nbhd_median_value), 2)`), so the offset form is both more stable and better in cross-validation. + +Second, the uplift itself is *not* log-transformed: the measured cohort's uplift distribution isn't right-skewed enough to justify it, and a log-log variant does worse in cross-validation (see @tbl-model-comparison). But its two *covariates* are worth transforming: I searched units added and neighbourhood value on both linear and log scales, and distance from LRT on both linear and inverse-distance scales, always keeping gross uplift itself on the dollar scale, evaluated by leave-one-out cross-validation on the dollar scale. @tbl-model-comparison shows the two ends of that search. Log-transforming units added and neighbourhood value together gives the best cross-validated fit, an improvement over the plain linear specification and clearly ahead of log-transforming the outcome instead. With only `r n_final_cohort` observations, that improvement is real but not dramatic — about `r round((rmse_level - rmse_level_log) / spec_choice_se, 1)` times its own bootstrap standard error — so I adopt it as the best available specification on the evidence, not because the gap is large. + +```{r} +#| label: tbl-model-comparison +#| tbl-cap: "Comparing uplift model specifications by leave-one-out cross-validated RMSE" +tibble( + spec = c( + "Units + LRT distance + neighbourhood value (linear)", + "log(units) + LRT distance + log(neighbourhood value) (adopted)", + "log(gross uplift) ~ units + LRT distance + log(neighbourhood value)", + "Pooled median (no covariates)" + ), + rmse = c(rmse_level, rmse_level_log, rmse_log, rmse_median) +) |> + gt(rowname_col = "spec") |> + fmt_currency(columns = rmse, decimals = 0) |> + cols_label(rmse = "LOOCV RMSE") |> + tab_header( + title = "Comparing uplift model specifications", + subtitle = paste0("Leave-one-out cross-validated RMSE, dollar scale, n = ", n_final_cohort) + ) |> + finalize_gt() |> + opt_stylize_jd() +``` + +@tbl-uplift-model shows the chosen model's coefficients. + +```{r} +#| label: tbl-uplift-model +#| tbl-cap: "Gross uplift model coefficients, fit on the measured 2024 cohort" +broom_coefs <- summary(uplift_model)$coefficients |> + as_tibble(rownames = "term") |> + rename(estimate = Estimate, se = `Std. Error`, t = `t value`, p = `Pr(>|t|)`) |> + mutate( + term = case_match( + term, + "(Intercept)" ~ "Intercept", + "log(units_added)" ~ "Units added (log)", + "distance_from_lrt" ~ "Distance from LRT (per km)", + "log(nbhd_median_value)" ~ "Neighbourhood median RS value (log)" + ) + ) + +broom_coefs |> + gt(rowname_col = "term") |> + fmt_currency(columns = c(estimate, se), decimals = 0) |> + fmt_number(columns = t, decimals = 2) |> + fmt_number(columns = p, decimals = 3) |> + cols_label(estimate = "Estimate", se = "Std. error", t = "t", p = "p-value") |> + tab_header( + title = "What drives per-property uplift?", + subtitle = paste0( + "Gross uplift ~ log(units) + LRT distance + log(neighbourhood value); R² = ", + round(summary(uplift_model)$r.squared, 2), + ", n = ", n_final_cohort + ) + ) |> + finalize_gt() |> + opt_stylize_jd() +``` + +Units added is the clearest and most statistically solid effect in the model, but because it enters on a log scale, its dollar effect isn't constant per home — it tapers off as project size grows. Near the bottom of the 5-8 unit range, the marginal home is worth about **`r label_dollar(scale = 1e-3, suffix = "k")(coef(uplift_model)["log(units_added)"] / 5)`**; near the top, about `r label_dollar(scale = 1e-3, suffix = "k")(coef(uplift_model)["log(units_added)"] / 8)`, a diminishing-returns pattern consistent with each additional unit adding somewhat less land-value-per-unit than the last. A neighbourhood with double the typical RS-zoned land value tends to see about `r label_dollar(scale = 1e-3, suffix = "k")(coef(uplift_model)["log(nbhd_median_value)"] * log(2))` more in uplift, holding project size and distance fixed, though the estimate is imprecise. Distance from LRT comes out slightly *positive*, around `r label_dollar(scale = 1e-3, suffix = "k")(coef(uplift_model)["distance_from_lrt"])` per km, and statistically indistinguishable from zero: within mature neighbourhoods, being near a station doesn't measurably raise how much value a rowhome redevelopment adds, perhaps because station-adjacent land already carried a higher baseline value. With `r n_final_cohort` observations, all of these intervals are wide, and the model explains a modest `r percent(summary(uplift_model)$r.squared, accuracy = 1)` of the variation, which is the honest state of knowledge one construction cycle into ZBR. + +@fig-model-diagnostics shows the model's residual diagnostics: no strong funnel shape in the residuals-vs-fitted panel (the usual argument for a log transform) and reasonably normal-looking residuals. + +```{r} +#| label: fig-model-diagnostics +#| fig-cap: "Uplift model residual diagnostics" +#| fig-subcap: ["Residuals vs fitted values", "Normal Q-Q plot of residuals"] +#| layout-ncol: 2 +model_diag <- tibble( + fitted = fitted(uplift_model), + resid = residuals(uplift_model) +) + +ggplot(model_diag, aes(x = fitted, y = resid)) + + geom_point(size = 2, alpha = 0.7) + + geom_hline(yintercept = 0, linetype = "dashed", colour = "grey50") + + scale_x_continuous(labels = label_dollar(scale = 1e-6, suffix = "M")) + + scale_y_continuous(labels = label_dollar(scale = 1e-6, suffix = "M")) + + labs( + title = "Residuals vs fitted", + x = "Fitted gross uplift", + y = "Residual", + caption = CAPTION_COE + ) + + theme_jd(mode = "light") + +ggplot(model_diag, aes(sample = resid)) + + stat_qq(size = 2, alpha = 0.7) + + stat_qq_line(linetype = "dashed", colour = "grey50") + + scale_y_continuous(labels = label_dollar(scale = 1e-6, suffix = "M")) + + labs( + title = "Normal Q-Q", + x = "Theoretical quantiles", + y = "Residual", + caption = CAPTION_COE + ) + + theme_jd(mode = "light") +``` + +For a sanity check against @tbl-uplift-rules: the model's average predicted uplift across the measured cohort is `r label_dollar(scale = 1e-6, suffix = "M")(mean(fitted(uplift_model)))` per property, right in line with the simple medians, as it should be. What the model adds is the ability to give each *individual* permit a prediction tailored to its size and location, which matters when extrapolating to hundreds of permits whose size mix and geography differ from the measured cohort's. + +For **net** uplift, the counterfactual adjustment is applied after prediction: a property's predicted net uplift is its predicted gross uplift minus (`r round(g, 2)` − 1) times its own 2024 baseline value, the same adjustment used for the measured cohort. + +## Where is this happening? + +@tbl-uplift-by-neighbourhood breaks the measured cohort down by neighbourhood. + +```{r} +#| label: tbl-uplift-by-neighbourhood +#| tbl-cap: "Measured uplift by neighbourhood, 2024 RS Zone 5-8 unit cohort (interactive)" +#| column: page +blended_rate_2026 <- final_cohort |> + count(mill_class_1) |> + mutate(share = n / sum(n)) |> + summarise( + rate = sum(share * if_else( + mill_class_1 == "OTHER RESIDENTIAL", + municipal_rate("Other Residential", 2026), + municipal_rate("Residential", 2026) + )) + ) |> + pull(rate) + +final_cohort |> + mutate( + annual_tax_uplift = if_else( + mill_class_1 == "OTHER RESIDENTIAL", + value_2026 * municipal_rate("Other Residential", 2026), + value_2026 * municipal_rate("Residential", 2026) + ) - g * value_2024 * municipal_rate("Residential", 2026), + neighbourhood = str_to_title(neighbourhood) + ) |> + group_by(neighbourhood) |> + summarise( + n_projects = n(), + homes_added = sum(units_added), + median_gross_uplift = median(gross_uplift), + median_net_uplift = median(net_uplift), + annual_tax_uplift = sum(annual_tax_uplift), + .groups = "drop" + ) |> + arrange(desc(annual_tax_uplift)) |> + gt() |> + fmt_currency( + columns = c(median_gross_uplift, median_net_uplift, annual_tax_uplift), + decimals = 0 + ) |> + fmt_integer(columns = c(n_projects, homes_added)) |> + cols_label( + neighbourhood = "Neighbourhood", + n_projects = "Projects", + homes_added = "Homes added", + median_gross_uplift = "Median gross uplift", + median_net_uplift = "Median net uplift", + annual_tax_uplift = "Est. annual municipal tax uplift" + ) |> + tab_header( + title = "Measured uplift by neighbourhood", + subtitle = "2024 RS Zone 5-8 unit cohort, reflected as complete (occupancy by Sept 2025)" + ) |> + finalize_gt(interactive = TRUE) |> + opt_stylize_jd() +``` + +## From one cohort to the whole pipeline + +The measured cohort only covers 2024 permits that were both matchable and fully reflected in the 2026 assessment. To estimate the cumulative effect of the RS Zone rowhome since ZBR took effect, I apply the uplift model from @tbl-uplift-model to every other mature-neighbourhood RS Zone 5-8 unit new-build permit issued since 2024: the rest of the 2024 cohort (permits that didn't match or aren't fully assessed yet), all of 2025, and 2026. Each permit gets a prediction from its own unit count, LRT distance, and neighbourhood. + +This is a **steady-state estimate**: it assumes every one of those permits eventually reaches the completed-building uplift the model predicts, once construction wraps up and a future assessment catches up to it. It is not the smaller amount those properties currently show in the 2026 roll, which @tbl-2024-actual-total showed directly for 2024's not-yet-reflected permits. The gap between that actual, partial total and the steady-state estimate below is construction and assessment lag, not double-counting. + +```{r} +#| label: pipeline-counts +pipeline_counts <- rowhome_pipeline |> + st_drop_geometry() |> + mutate(bucket = if_else(units_added <= 6, "5-6 units", "7-8 units")) |> + count(year, bucket) + +# H1 annualization multiplier, same method as the Q2 2026 report: median +# ratio of full-year to H1 residential units across historical years. +h1_ratios <- bp |> + st_drop_geometry() |> + filter(year < 2026) |> + group_by(year) |> + summarize( + full_year = sum(units_added), + h1 = sum(units_added[month_number <= 6]), + .groups = "drop" + ) |> + mutate(ratio = full_year / h1) +h1_multiplier <- round(median(h1_ratios$ratio), 1) + +n_2024_all <- pipeline_counts |> filter(year == 2024) |> summarise(n = sum(n)) |> pull(n) +n_2025_all <- pipeline_counts |> filter(year == 2025) |> summarise(n = sum(n)) |> pull(n) +n_2026_h1 <- pipeline_counts |> filter(year == 2026) |> summarise(n = sum(n)) |> pull(n) +``` + +2025 permitted **`r n_2025_all`** more mature-neighbourhood RS Zone 5-8 unit rowhomes, and H1 2026 has already permitted `r n_2026_h1`. Following the same [H1 annualization method used in the Q2 2026 report](../q2-building-permits/index.qmd), full-year 2026 is projected at `r h1_multiplier`x the H1 count. + +Predicting *net* uplift needs each permit's own 2024 baseline value, so the 2025 and 2026 permits are run through the same baseline matchers as the 2024 cohort (their lots all existed in the 2024 roll, pre-redevelopment). + +```{r} +#| label: extrapolation +measured_ids <- final_cohort$permit_row_id + +# Baselines for 2025/2026 permits, using the same matchers as the 2024 cohort +permits_2025_2026 <- rowhome_pipeline |> filter(year %in% 2025:2026) +future_baselines <- match_baseline_2024(permits_2025_2026) |> + geo_fallback_baseline(permits_2025_2026) |> + select(permit_row_id, value_2024) + +baseline_match_rate <- mean(!is.na(future_baselines$value_2024)) + +# Every mature RS 5-8 unit new-build permit with the model's covariates. +# Fallbacks for prediction: median LRT distance for permits with no mapped +# location; the neighbourhood median RS value doubles as the baseline proxy +# for permits that didn't match one. +median_pipeline_distance <- median(rowhome_pipeline$distance_from_lrt, na.rm = TRUE) + +all_permits <- rowhome_pipeline |> + st_drop_geometry() |> + filter(year %in% 2024:2026) |> + left_join(nbhd_median_rs_value, by = c("neighbourhood" = "neighbourhood_name")) |> + left_join( + bind_rows( + matched_2024_all |> select(permit_row_id, value_2024), + future_baselines + ), + by = "permit_row_id" + ) |> + mutate( + nbhd_median_value = coalesce(nbhd_median_value, median(nbhd_median_rs_value$nbhd_median_value)), + distance_from_lrt = coalesce(distance_from_lrt, median_pipeline_distance), + baseline_value = coalesce(value_2024, nbhd_median_value), + pred_gross = predict( + uplift_model, + newdata = pick(units_added, distance_from_lrt, nbhd_median_value) + ), + pred_net = pred_gross - (g - 1) * baseline_value + ) + +measured_totals <- final_cohort |> + summarise(gross = sum(gross_uplift), net = sum(net_uplift)) + +model_based_2024 <- all_permits |> + filter(year == 2024, !permit_row_id %in% measured_ids) |> + summarise(gross = sum(pred_gross), net = sum(pred_net)) + +model_based_2025 <- all_permits |> + filter(year == 2025) |> + summarise(gross = sum(pred_gross), net = sum(pred_net)) + +model_based_2026_h1 <- all_permits |> + filter(year == 2026) |> + summarise(gross = sum(pred_gross), net = sum(pred_net)) + +# 2026 full-year projection: no per-permit rows exist yet for the +# un-permitted remainder of the year, so scale H1's predicted total. +model_based_2026_projected_remainder <- model_based_2026_h1 |> + mutate(gross = gross * (h1_multiplier - 1), net = net * (h1_multiplier - 1)) + +total_gross_uplift <- measured_totals$gross + model_based_2024$gross + + model_based_2025$gross + model_based_2026_h1$gross + model_based_2026_projected_remainder$gross +total_net_uplift <- measured_totals$net + model_based_2024$net + + model_based_2025$net + model_based_2026_h1$net + model_based_2026_projected_remainder$net + +n_2026_projected <- n_2026_h1 * h1_multiplier +``` + +The 2025 and 2026 permits match their 2024 baselines at a **`r percent(baseline_match_rate, accuracy = 1)`** rate; the few that don't use their neighbourhood's median RS value as a stand-in baseline for the net adjustment. + +@fig-cumulative-value-uplift shows the resulting cumulative assessed value uplift by permit year, split between the actually-measured portion and the portion estimated with the model. + +```{r} +#| label: fig-cumulative-value-uplift +#| fig-cap: "Cumulative estimated assessed value uplift since ZBR, by permit year (net of appreciation)" +cumulative_by_year <- tibble( + year = c(2024, 2024, 2025, 2026, 2026), + source = c("Measured", "Estimated (model)", "Estimated (model)", "Estimated (model)", "Estimated (model)"), + net_uplift = c( + measured_totals$net, model_based_2024$net, model_based_2025$net, + model_based_2026_h1$net, model_based_2026_projected_remainder$net + ) +) |> + group_by(year, source) |> + summarise(net_uplift = sum(net_uplift), .groups = "drop") + +ggplot(cumulative_by_year, aes(x = factor(year), y = net_uplift, fill = source)) + + geom_col() + + scale_y_continuous(labels = label_dollar(scale = 1e-6, suffix = "M")) + + labs( + title = "Cumulative assessed value uplift since ZBR", + subtitle = paste0("Net of market appreciation; 2026 full year projected at ", h1_multiplier, "x H1"), + x = "Permit year", + y = "Assessed value uplift", + fill = NULL, + caption = CAPTION_COE + ) + + theme_jd(mode = "light") +``` + +Adding it all up: since ZBR took effect, mature-neighbourhood RS Zone 5-8 unit rowhomes are estimated to have added **`r label_dollar(scale = 1e-6, suffix = "M")(total_gross_uplift)`** in gross assessed value, or **`r label_dollar(scale = 1e-6, suffix = "M")(total_net_uplift)`** net of general market appreciation, across `r n_2024_all` (2024) + `r n_2025_all` (2025) + `r round(n_2026_projected)` (2026, projected) = `r n_2024_all + n_2025_all + round(n_2026_projected)` permitted projects. + +@tbl-cumulative-selected-neighbourhoods breaks that cumulative estimate down for the same neighbourhoods used in the [Q2 2026 report's selected-neighbourhood table](../q2-building-permits/index.qmd), places that have been prominent in debates about RS Zone infill. Each permit is valued at its actual measured uplift where available, or the model's prediction otherwise, then summed by neighbourhood. This covers every actual permit issued through H1 2026; the projected remainder of 2026 isn't tied to real permits yet, so it's included in the citywide total above but left out of this neighbourhood breakdown. + +```{r} +#| label: tbl-cumulative-selected-neighbourhoods +#| tbl-cap: "Cumulative estimated uplift for selected neighbourhoods, 2024 through H1 2026" +#| column: page +selected_nbhds <- c( + "GLENWOOD", + "GROVENOR", + "BRITANNIA YOUNGSTOWN", + "WESTMOUNT", + "MCKERNAN", + "BELGRAVIA", + "CRESTWOOD", + "PARKVIEW" +) + +# Each actual permit's uplift: measured where available, model prediction +# otherwise. The 2026 projected remainder has no real permits to attach +# to a neighbourhood, so it's excluded here (it's still in the citywide +# total above). +measured_lookup <- final_cohort |> + st_drop_geometry() |> + select(permit_row_id, actual_gross = gross_uplift, actual_net = net_uplift, mill_class_1, value_2024, value_2026) + +permit_uplift <- all_permits |> + select(-value_2024) |> + left_join(measured_lookup, by = "permit_row_id") |> + mutate( + is_measured = !is.na(actual_gross), + gross_uplift = coalesce(actual_gross, pred_gross), + net_uplift = coalesce(actual_net, pred_net), + annual_tax_uplift = if_else( + is_measured, + if_else( + mill_class_1 == "OTHER RESIDENTIAL", + municipal_rate("Other Residential", 2026) * value_2026, + municipal_rate("Residential", 2026) * value_2026 + ) - municipal_rate("Residential", 2026) * g * value_2024, + net_uplift * blended_rate_2026 + ) + ) + +cumulative_by_neighbourhood <- permit_uplift |> + mutate(neighbourhood = str_to_title(neighbourhood)) |> + group_by(neighbourhood) |> + summarise( + n_projects = n(), + homes_added = sum(units_added), + cumulative_gross_uplift = sum(gross_uplift), + cumulative_net_uplift = sum(net_uplift), + annual_tax_uplift = sum(annual_tax_uplift), + .groups = "drop" + ) + +tibble(neighbourhood = str_to_title(selected_nbhds)) |> + left_join(cumulative_by_neighbourhood, by = "neighbourhood") |> + replace_na(list( + n_projects = 0, + homes_added = 0, + cumulative_gross_uplift = 0, + cumulative_net_uplift = 0, + annual_tax_uplift = 0 + )) |> + arrange(neighbourhood) |> + gt() |> + fmt_currency( + columns = c(cumulative_gross_uplift, cumulative_net_uplift, annual_tax_uplift), + decimals = 0 + ) |> + fmt_integer(columns = c(n_projects, homes_added)) |> + cols_label( + neighbourhood = "Neighbourhood", + n_projects = "Projects", + homes_added = "Homes added", + cumulative_gross_uplift = "Cumulative gross uplift", + cumulative_net_uplift = "Cumulative net uplift", + annual_tax_uplift = "Est. annual municipal tax uplift" + ) |> + tab_header( + title = "Cumulative uplift, selected neighbourhoods", + subtitle = "2024 through H1 2026, measured + model-based" + ) |> + finalize_gt() |> + opt_stylize_jd() |> + sub_missing() +``` + +## What this means for property tax + +Assessed value only matters for the City's budget insofar as it's taxed. I convert the estimated uplift into two figures: an **annual recurring** estimate, at 2026 municipal tax rates, of how much more property tax this pipeline will generate every year once every project is complete and fully reflected in an assessment roll; and a rougher **cumulative collected so far** estimate that accounts for the fact that most of this pipeline is still under construction or only recently completed. + +Completed 5-8 unit rowhomes on a single title are typically assessed as "Other Residential", which carries a higher municipal mill rate than the "Residential" class the original house was assessed under. In the measured cohort, `r percent(final_cohort |> summarise(p = mean(mill_class_1 == "OTHER RESIDENTIAL")) |> pull(p), accuracy = 1)` of completed properties land in Other Residential; I apply that same mix to the model-based portion of the estimate. + +```{r} +#| label: tax-conversion +tax_measured <- final_cohort |> + mutate( + new_rate = if_else( + mill_class_1 == "OTHER RESIDENTIAL", + municipal_rate("Other Residential", 2026), + municipal_rate("Residential", 2026) + ), + annual_tax_gross = new_rate * value_2026 - municipal_rate("Residential", 2026) * value_2024, + annual_tax_net = new_rate * value_2026 - municipal_rate("Residential", 2026) * g * value_2024 + ) |> + summarise(gross = sum(annual_tax_gross), net = sum(annual_tax_net)) + +model_based_gross_total <- model_based_2024$gross + model_based_2025$gross + + model_based_2026_h1$gross + model_based_2026_projected_remainder$gross +model_based_net_total <- model_based_2024$net + model_based_2025$net + + model_based_2026_h1$net + model_based_2026_projected_remainder$net + +tax_model_based_gross <- model_based_gross_total * blended_rate_2026 +tax_model_based_net <- model_based_net_total * blended_rate_2026 + +annual_tax_uplift_gross <- tax_measured$gross + tax_model_based_gross +annual_tax_uplift_net <- tax_measured$net + tax_model_based_net +``` + +At 2026 municipal tax rates, this pipeline is estimated to add **`r label_dollar(scale = 1e-6, suffix = "M")(annual_tax_uplift_net)`** in property tax every year, net of what general appreciation would have generated anyway (`r label_dollar(scale = 1e-6, suffix = "M")(annual_tax_uplift_gross)` on a gross basis). That's before counting the provincial education levy, which would add roughly another third on top of the municipal portion. + +Because most of this pipeline is still ramping up, actual tax collected so far is much lower than that steady-state figure. Comparing each matched property's mid-construction 2025 assessed value to its 2024 baseline and completed 2026 value shows how much of the total uplift typically shows up one year after a permit is issued. + +```{r} +#| label: cumulative-collected +blended_rate_2025 <- final_cohort |> + count(mill_class_1) |> + mutate(share = n / sum(n)) |> + summarise( + rate = sum(share * if_else( + mill_class_1 == "OTHER RESIDENTIAL", + municipal_rate("Other Residential", 2025), + municipal_rate("Residential", 2025) + )) + ) |> + pull(rate) + +partial_uplift_share <- final_cohort |> + filter(!is.na(value_2025), value_2026 > value_2024) |> + mutate(p = (value_2025 - value_2024) / (value_2026 - value_2024)) |> + summarise(p = median(p)) |> + pull(p) |> + pmax(0) |> + pmin(1) + +# Net uplift value permitted in each year (2024 cohort = all mature RS 5-8 +# new-builds from 2024, measured + model-based) +net_uplift_2024_cohort <- measured_totals$net + model_based_2024$net +net_uplift_2025_cohort <- model_based_2025$net + +# A property permitted in year Y contributes a partial share of its +# annual tax uplift in year Y+1, and the full amount from Y+2 on. +collected_2025 <- partial_uplift_share * net_uplift_2024_cohort * blended_rate_2025 +collected_2026 <- net_uplift_2024_cohort * blended_rate_2026 + + partial_uplift_share * net_uplift_2025_cohort * blended_rate_2026 +cumulative_collected <- collected_2025 + collected_2026 +``` + +The median property has captured about `r percent(partial_uplift_share, accuracy = 1)` of its full uplift by the assessment one year after permitting, consistent with most projects still being under construction at that point. Modelling each year's cohort as contributing that partial share in the following year and the full amount from two years out, I estimate Edmonton has collected roughly **`r label_dollar(scale = 1e-6, suffix = "M")(cumulative_collected)`** in incremental property tax from this pipeline across 2025 and 2026 combined, well short of the `r label_dollar(scale = 1e-6, suffix = "M")(annual_tax_uplift_net)`-a-year run rate this pipeline will eventually reach once every project currently in the pipeline is complete and fully assessed. + +These are estimates, not City budget figures. Assessment growth from new construction doesn't translate one-for-one into new City revenue, since Council sets the mill rate each year based on total budget needs, but new construction is genuinely additional tax base at whatever rate Council sets, distinct from a rate increase on existing properties. This also doesn't account for the cost of servicing new residents, which isn't the subject of this post. + +## Conclusions + +The RS Zone rowhome isn't just adding homes, it's rebuilding the property tax base of neighbourhoods that had been losing population and, with it, tax revenue per hectare of city-maintained infrastructure for decades. A handful of redevelopments per neighbourhood, concentrated in mature areas that already have the pipes, roads, and schools in place, is already worth tens of millions of dollars a year in additional property tax capacity, on top of the housing it delivers. + +None of this required a subsidy, a grant, or a City-led development. It required removing rules that made this kind of building illegal. If you'd like to help keep it that way, consider joining [Grow Together Edmonton](https://www.growtogetheryeg.com/). \ No newline at end of file diff --git a/blog/2026/property-tax-uplift/index.rmarkdown b/blog/2026/property-tax-uplift/index.rmarkdown new file mode 100644 index 0000000..e073aea --- /dev/null +++ b/blog/2026/property-tax-uplift/index.rmarkdown @@ -0,0 +1,1109 @@ +--- +title: "The property tax dividend from Edmonton's RS Zone rowhomes" +date: "2026-07-09" +author: "Jacob Dawang" +categories: [housing, edmonton, zoning] +description: "Redeveloping an old house into a 5-8 unit RS Zone rowhome doesn't just add homes, it multiplies the property's assessed value. Here's what that's worth to Edmonton's property tax base since the Zoning Bylaw Renewal took effect." +link-external-newwindow: true +link-external-icon: false +execute: + cache: false +--- + +Edmonton's Zoning Bylaw Renewal (ZBR) has spent two years quietly rewriting mature neighbourhoods, one lot at a time. [Prior posts on this blog](../zbr-two-year-review/index.qmd) have tracked the homes it unlocked and the neighbourhoods it reached. This post asks a different question: what is that redevelopment worth to the City's property tax base? + +When a single-family lot in a mature neighbourhood becomes a 5-8 unit RS Zone rowhome, its assessed value doesn't just grow, it multiplies. That's a durable increase in the tax base, not a one-time windfall: every year, that property contributes meaningfully more property tax than the house it replaced would have. Using building permits from 2024, the first year the RS Zone was in force, matched against the City's property assessment data, I measure that uplift directly for completed projects, then use a regression model fit on those measurements to estimate what it adds up to across the full 2024-2026 pipeline. + +## Data + +This analysis combines three of Edmonton's Open Data sources. Edmonton's [general building permit data](https://data.edmonton.ca/Urban-Planning-Economy/General-Building-Permits/24uj-dj8v/about_data), the same source used in the [Q2 2026 building permit report](../q2-building-permits/index.qmd), identifies which properties were redeveloped into 5-8 unit RS Zone rowhomes and when. Edmonton's [current calendar year property assessment data](https://data.edmonton.ca/City-Administration/Property-Assessment-Data-Current-Calendar-Year-/q7d6-ambg/about_data) gives each property's assessed value as of 2026, and Edmonton's [historical property assessment data](https://data.edmonton.ca/City-Administration/Property-Assessment-Data-Historical-/qi6a-xuwt/about_data) gives assessed values back to 2012, including 2024 and 2025. + +The key challenge is linking a specific building permit to the same physical property, before and after redevelopment. Account numbers usually persist through redevelopment, but addresses often don't: a lot can get re-addressed when it's rebuilt, so a permit's civic address is frequently *not* the address that appears in the property's earlier assessment record. Instead, I match on legal description (plan/block/lot), which is stable across redevelopment, with a fallback to geographic proximity for the small number of properties where the legal description format doesn't parse identically on both sides, or where redevelopment came with a brand new account number. + +```{r} +#| label: setup +#| include: false +library(tidyverse) +library(sf) +library(gt) +library(scales) +library(mountainmathHelpers) +library(jdawangHelpers) + +options( + cancensus.api_key = Sys.getenv("CM_API_KEY"), + cancensus.cache_path = Sys.getenv("CM_CACHE_PATH"), + tongfen.cache_path = Sys.getenv("TONGFEN_CACHE_PATH"), + nextzen_API_key = Sys.getenv("NEXTZEN_API_KEY") +) + +bp_raw <- get_edmonton_building_permit_data( + cache_dir = Sys.getenv("EDMONTON_BP_CACHE_PATH") +) +crs <- lambert_conformal_conic_at(bp_raw) + +bp <- bp_raw |> + st_transform(crs) |> + mutate(permit_row_id = row_number()) |> + filter(year < 2026 | (year == 2026 & month_number <= 6)) |> + filter_edmonton_residential() |> + filter(units_added >= 1, work_type != "(04) Excavation") |> + add_edmonton_project_type() |> + add_edmonton_suite_info() |> + add_edmonton_neighbourhood_type() + +# LRT stops (existing + under construction), same setup as the Q2 2026 report +future_stops <- read_sf("../../../data/future_lrt_stops.geojson") |> + filter( + !(stop_name %in% + c( + "Castle Downs Station", + "145 Ave Station", + "137 Ave Station", + "132 Ave Station" + )) + ) + +transit_stops <- load_edmonton_transit_stops( + gtfs_path = "../../../data/ca-alberta-edmonton-transit-system-gtfs-714.zip", + service_date = as.Date("2023-11-09"), + future_stops = future_stops, + crs = crs +) + +# The pipeline this whole post is about: mature-neighbourhood RS Zone +# 5-8 unit new-builds, permitted since ZBR took effect. Each permit gets +# its distance to the nearest LRT stop, used by the uplift model later. +rowhome_pipeline <- bp |> + filter( + zoning == "RS", + between(units_added, 5, 8), + work_type == "(01) Building - New", + neighbourhood_type == "Mature" + ) |> + add_transit_distance(transit_stops) +``` + +```{r} +#| label: fetch-assessment-data +# This is a one-off fetch specific to this post: Edmonton's property +# assessment data hasn't been used on this blog before, so this helper +# isn't (yet) part of jdawangHelpers. +fetch_socrata_csv <- function(resource, query, cache_file) { + cache_dir <- Sys.getenv("EDMONTON_BP_CACHE_PATH") + path <- file.path(cache_dir, cache_file) + if (!file.exists(path)) { + url <- paste0( + "https://data.edmonton.ca/resource/", resource, ".csv?", + URLencode(query) + ) + download.file(url, path, mode = "wb") + } + read_csv(path, show_col_types = FALSE, col_types = cols(.default = "c")) +} + +assessment_hist <- fetch_socrata_csv( + "qi6a-xuwt", + "$where=assessment_year in (2024,2025)&$limit=1000000", + "assessment_2024_2025.csv" +) |> + mutate( + assessment_year = as.integer(assessment_year), + assessed_value = as.numeric(assessed_value), + latitude = as.numeric(latitude), + longitude = as.numeric(longitude) + ) + +assessment_2026 <- fetch_socrata_csv( + "q7d6-ambg", "$limit=600000", "assessment_2026.csv" +) |> + mutate( + assessed_value = as.numeric(assessed_value), + latitude = as.numeric(latitude), + longitude = as.numeric(longitude) + ) + +tax_rates <- fetch_socrata_csv("pwis-wc4c", "$limit=10000", "tax_rates.csv") |> + mutate( + tax_year = as.integer(tax_year), + amount_per_dollar_of_assessed_value = as.numeric( + amount_per_dollar_of_assessed_value + ) + ) + +assessment_2024 <- assessment_hist |> filter(assessment_year == 2024) +assessment_2025 <- assessment_hist |> filter(assessment_year == 2025) + +municipal_rate <- function(class, yr) { + tax_rates |> + filter(tax_year == yr, tax_rate_type == "Municipal", assessment_class == class) |> + pull(amount_per_dollar_of_assessed_value) +} +``` + +## Measuring the uplift: the 2024 cohort + +The 2026 property assessment is supposed to reflect each property's physical condition as of December 31, 2025. In principle, that means any 2024 permit whose building had received occupancy by the end of 2025 should show up, completed, in the 2026 assessment roll, giving a clean before-and-after pair. In practice, as we'll see below, the assessments only reliably catch up to buildings finished by about September 2025, so the measurement cohort uses that earlier cutoff. + +```{r} +#| label: measurement-cohort +cohort_2024 <- rowhome_pipeline |> + filter(year == 2024) + +n_cohort_2024_all <- nrow(cohort_2024) +n_occupancy_by_dec <- cohort_2024 |> + st_drop_geometry() |> + filter(!is.na(occupancy_granted_date), occupancy_granted_date <= as.Date("2025-12-31")) |> + nrow() +``` + +Edmonton issued **`r n_cohort_2024_all`** mature-neighbourhood RS Zone 5-8 unit new-build permits in 2024, of which **`r n_occupancy_by_dec`** had received occupancy by the end of 2025. I match all `r n_cohort_2024_all` to their assessment records, then use the occupancy dates to decide which ones the 2026 assessment actually reflects as complete. + +### Matching permits to assessments + +I parse each side's legal description into a `(plan, block, lot)` key and join on it. A building permit's legal description looks like `Plan 715HW Blk 25 Lot 22`; the historical assessment data records the same parcel as `Plan: 715HW Block: 25 Lot: 22`. + +```{r} +#| label: legal-key-matching +parse_permit_legal <- function(x) { + m <- str_match(x, "Plan\\s+(\\S+)\\s+Blk\\s+(\\S+)\\s+Lots?\\s+(\\S+)") + tibble(plan = m[, 2], block = m[, 3], lot = m[, 4]) +} +parse_assessment_legal <- function(x) { + m <- str_match(x, "Plan:\\s*(\\S+)\\s+Block:\\s*(\\S+)\\s+Lot:\\s*(\\S+)") + tibble(plan = m[, 2], block = m[, 3], lot = m[, 4]) +} +normalize_key <- function(plan, block, lot) { + paste(toupper(str_trim(plan)), toupper(str_trim(block)), toupper(str_trim(lot)), sep = "|") +} + +assessment_2024_keyed <- assessment_2024 |> + bind_cols(parse_assessment_legal(assessment_2024$legal_description)) |> + mutate(key = normalize_key(plan, block, lot)) |> + filter(!is.na(key)) |> + distinct(key, .keep_all = TRUE) + +# Reusable matcher: join a cohort of permits to their 2024 baseline assessed +# value by legal-description key. Used for the 2024 cohort here, and again +# later for the 2025/2026 permits when estimating net uplift. +match_baseline_2024 <- function(cohort_sf) { + cohort_sf |> + st_drop_geometry() |> + bind_cols(parse_permit_legal(cohort_sf$legal_description)) |> + mutate(key = normalize_key(plan, block, lot)) |> + left_join( + assessment_2024_keyed |> select(key, account_number, value_2024 = assessed_value), + by = "key" + ) +} + +cohort_matched <- match_baseline_2024(cohort_2024) +n_matched_legal <- sum(!is.na(cohort_matched$account_number)) +``` + +That legal-key match alone links **`r n_matched_legal`** of `r n_cohort_2024_all` properties (`r percent(n_matched_legal / n_cohort_2024_all, accuracy = 1)`) to their 2024 baseline assessed value. For the remainder, I fall back to matching each permit to the nearest 2024 assessment point within 25m. I checked these fallback matches by hand: most are lots that were consolidated from two legal titles into one (a permit reads `Lots 2-3`, while the assessment record spells that out as two separate `Lot:` entries joined by " / ", which my parser doesn't follow), and in each case checked the fallback match has the exact same civic address as the permit, at a matched distance of a few millimetres. + +```{r} +#| label: geo-fallback-2024 +# Reusable: fall back to the nearest 2024 assessment point within 25m for +# any permit the legal-key match missed. +geo_fallback_baseline <- function(matched_df, cohort_sf) { + still_unmatched <- matched_df |> filter(is.na(account_number)) + if (nrow(still_unmatched) == 0) { + return(matched_df) + } + + unmatched_sf <- cohort_sf |> filter(permit_row_id %in% still_unmatched$permit_row_id) + assessment_2024_sf <- assessment_2024 |> + filter(!is.na(latitude), !is.na(longitude)) |> + st_as_sf(coords = c("longitude", "latitude"), crs = 4326) |> + st_transform(crs) + + nearest_idx <- st_nearest_feature(unmatched_sf, assessment_2024_sf) + dist_m <- as.numeric(st_distance(unmatched_sf, assessment_2024_sf[nearest_idx, ], by_element = TRUE)) + + geo_matches <- tibble( + permit_row_id = unmatched_sf$permit_row_id, + geo_account = assessment_2024_sf$account_number[nearest_idx], + geo_value_2024 = assessment_2024_sf$assessed_value[nearest_idx], + geo_dist_m = dist_m + ) |> + filter(geo_dist_m <= 25) + + matched_df |> + left_join(geo_matches, by = "permit_row_id") |> + mutate( + account_number = coalesce(account_number, geo_account), + value_2024 = coalesce(value_2024, geo_value_2024) + ) |> + select(-any_of(c("geo_account", "geo_value_2024", "geo_dist_m"))) +} + +cohort_matched <- geo_fallback_baseline(cohort_matched, cohort_2024) + +n_matched_total <- sum(!is.na(cohort_matched$account_number)) +n_dropped <- n_cohort_2024_all - n_matched_total +``` + +The 25m fallback brings the total match rate to **`r n_matched_total`** of `r n_cohort_2024_all` (`r percent(n_matched_total / n_cohort_2024_all, accuracy = 1)`). The remaining `r n_dropped` properties have no corresponding parcel in the 2024 assessment roll at all, likely lots created by subdivision after that year's assessment date, so they're dropped from the analysis. + +Each matched property's `account_number` persists through redevelopment in most cases, so I use it to look up the completed building's 2026 assessed value. A small number of properties are issued a brand new account number when redeveloped rather than keeping the old one, exactly the re-addressing situation described above; I confirmed one such case by hand, where the 25m fallback correctly landed on a new 2026 account whose civic address matched the permit's own address exactly, even though the old account (still on the 2024/2025 rolls under the pre-redevelopment address) had disappeared from the 2026 data entirely. + +```{r} +#| label: join-2026-and-2025 +# Reusable: join a baseline-matched cohort to its 2026 outcome value by +# account_number, falling back to the nearest 2026 assessment point within +# 25m for the rare case where redevelopment came with a new account number. +match_outcome_2026 <- function(matched_df, cohort_sf) { + joined <- matched_df |> + filter(!is.na(account_number)) |> + left_join( + assessment_2026 |> select(account_number, value_2026 = assessed_value, mill_class_1), + by = "account_number" + ) + + missing_2026 <- joined |> filter(is.na(value_2026)) + if (nrow(missing_2026) == 0) { + return(joined) + } + + missing_2026_sf <- cohort_sf |> filter(permit_row_id %in% missing_2026$permit_row_id) + assessment_2026_sf <- assessment_2026 |> + filter(!is.na(latitude), !is.na(longitude)) |> + st_as_sf(coords = c("longitude", "latitude"), crs = 4326) |> + st_transform(crs) + + nearest_idx <- st_nearest_feature(missing_2026_sf, assessment_2026_sf) + geo_2026 <- tibble( + permit_row_id = missing_2026_sf$permit_row_id, + geo_value_2026 = assessment_2026_sf$assessed_value[nearest_idx], + geo_mill_class = assessment_2026_sf$mill_class_1[nearest_idx], + geo_dist_m = as.numeric(st_distance(missing_2026_sf, assessment_2026_sf[nearest_idx, ], by_element = TRUE)) + ) |> + filter(geo_dist_m <= 25) + + joined |> + left_join(geo_2026, by = "permit_row_id") |> + mutate( + value_2026 = coalesce(value_2026, geo_value_2026), + mill_class_1 = coalesce(mill_class_1, geo_mill_class) + ) |> + select(-any_of(c("geo_value_2026", "geo_mill_class", "geo_dist_m"))) +} + +# 2025 (mid-construction) value, used later for the partial-uplift estimate +matched_2024_all <- match_outcome_2026(cohort_matched, cohort_2024) |> + left_join( + assessment_2025 |> select(account_number, value_2025 = assessed_value), + by = "account_number" + ) |> + filter(!is.na(value_2026)) |> + mutate( + bucket = if_else(units_added <= 6, "5-6 units", "7-8 units"), + gross_uplift = value_2026 - value_2024 + ) + +n_matched_2024_all <- nrow(matched_2024_all) +``` + +That yields **`r n_matched_2024_all`** 2024 permits with both a 2024 baseline and a 2026 assessed value. + +### When does the assessment catch up? + +Before treating every occupancy-granted building as "complete" in the 2026 data, it's worth checking whether the assessments actually keep up with late-year completions. @fig-assessment-lag plots each matched property's gross uplift against its occupancy date. The pattern is stark: buildings that received occupancy by roughly the end of September 2025 show the full rowhome uplift, while October, November, and especially December completions drop off a cliff — their 2026 assessed values still largely reflect a construction site, not a finished building, even though the assessment is nominally "as of December 31, 2025". + +```{r} +#| label: fig-assessment-lag +#| fig-cap: "Gross assessed value uplift by occupancy date: the 2026 assessment only reliably reflects buildings finished by about September 2025" +occupancy_cutoff <- as.Date("2025-09-30") + +matched_2024_all |> + filter(!is.na(occupancy_granted_date), occupancy_granted_date <= as.Date("2025-12-31")) |> + mutate( + reflected = if_else( + occupancy_granted_date <= occupancy_cutoff, + "Occupancy by Sept 2025", + "Occupancy Oct-Dec 2025" + ) + ) |> + ggplot(aes(x = occupancy_granted_date, y = gross_uplift, colour = reflected)) + + geom_point(size = 2, alpha = 0.7) + + geom_vline(xintercept = occupancy_cutoff, linetype = "dashed", colour = "grey50") + + scale_y_continuous(labels = label_dollar(scale = 1e-6, suffix = "M")) + + scale_x_date( + date_labels = "%b %Y", + date_breaks = "6 months", + guide = guide_axis(angle = 45) + ) + + labs( + title = "Assessment lag: uplift by occupancy date", + subtitle = "2024 permits with occupancy granted by Dec 31, 2025; dashed line = Sept 30, 2025", + x = "Occupancy granted", + y = "Gross assessed value uplift", + colour = NULL, + caption = CAPTION_COE + ) + + theme_jd(mode = "light") +``` + +So the measurement cohort for this post is the matched 2024 permits with **occupancy granted by September 30, 2025** — buildings whose 2026 assessment genuinely reflects the completed rowhome. Everything else, including those October-December completions, goes into the "not yet fully reflected" group. + +```{r} +#| label: cohort-split +final_cohort <- matched_2024_all |> + filter(!is.na(occupancy_granted_date), occupancy_granted_date <= occupancy_cutoff) + +not_yet_complete_matched <- matched_2024_all |> + anti_join(final_cohort, by = "permit_row_id") + +n_final_cohort <- nrow(final_cohort) +``` + +The measurement cohort is **`r n_final_cohort`** properties. @tbl-spotlight traces two properties through the process, from their pre-redevelopment assessed value, through a mid-construction 2025 assessment, to their completed 2026 value. The Alberta Avenue example received occupancy in November 2025, yet its 2026 value looks fully assessed — a reminder that the lag in @fig-assessment-lag is a strong tendency, not a hard rule, which is why the conservative September cutoff is used for measurement. + +```{r} +#| label: tbl-spotlight +#| tbl-cap: "Two properties traced from pre-redevelopment (2024) through mid-construction (2025) to a completed rowhome (2026)" +spotlight_accounts <- c("4042701", "2049286") + +matched_2024_all |> + filter(account_number %in% spotlight_accounts) |> + mutate( + neighbourhood = str_to_title(neighbourhood), + mill_class_1 = str_to_title(mill_class_1) + ) |> + select(neighbourhood, units_added, value_2024, value_2025, value_2026, mill_class_1) |> + arrange(neighbourhood) |> + gt() |> + fmt_currency(columns = c(value_2024, value_2025, value_2026), decimals = 0) |> + cols_label( + neighbourhood = "Neighbourhood", + units_added = "Units", + value_2024 = "2024 (before)", + value_2025 = "2025 (mid-construction)", + value_2026 = "2026 (completed)", + mill_class_1 = "2026 assessment class" + ) |> + tab_header( + title = "Two RS Zone rowhomes, before and after", + subtitle = "Assessed value by year" + ) |> + finalize_gt() |> + opt_stylize_jd() +``` + +### The rest of the 2024 cohort + +The `r n_final_cohort` properties above only cover 2024 permits whose completed buildings the 2026 assessment has caught up with. The remaining matched permits, `r nrow(not_yet_complete_matched)` of them, are either still under construction or finished too late in 2025 for the assessment to reflect. Their 2026 assessed values still tell us something: whatever value the construction had reached, a *partial* uplift. @tbl-2024-actual-total combines both groups into a single, fully-observed total for the 2024 permit year, no rule required. + +```{r} +#| label: tbl-2024-actual-total +#| tbl-cap: "Actual (not model-based) 2024 cohort assessed value uplift, split by completion status" +status_complete <- "Reflected as complete (occupancy by Sept 2025)" +status_partial <- "Not yet fully reflected (later or no occupancy)" + +actual_2024 <- matched_2024_all |> + mutate( + status = if_else(permit_row_id %in% final_cohort$permit_row_id, status_complete, status_partial) + ) |> + select(status, gross_uplift) + +actual_2024_summary <- actual_2024 |> + mutate(status = fct_relevel(status, status_complete, status_partial)) |> + group_by(status) |> + summarise(n = n(), median_gross_uplift = median(gross_uplift), total_gross_uplift = sum(gross_uplift), .groups = "drop") |> + arrange(status) |> + mutate(status = as.character(status)) + +actual_2024_total <- actual_2024_summary |> + summarise( + status = "Total, 2024 cohort (matched)", + n = sum(n), + median_gross_uplift = median(actual_2024$gross_uplift), + total_gross_uplift = sum(total_gross_uplift) + ) + +bind_rows(actual_2024_summary, actual_2024_total) |> + gt(rowname_col = "status") |> + fmt_currency(columns = c(median_gross_uplift, total_gross_uplift), decimals = 0) |> + cols_label(n = "n", median_gross_uplift = "Median gross uplift", total_gross_uplift = "Total gross uplift") |> + tab_header( + title = "2024 cohort, actual gross uplift observed so far", + subtitle = "No extrapolation model applied" + ) |> + tab_style( + style = cell_text(weight = "bold"), + locations = cells_stub(rows = status == "Total, 2024 cohort (matched)") + ) |> + finalize_gt() |> + opt_stylize_jd() +``` + +That gives a fully-observed total of **`r label_dollar(scale = 1e-6, suffix = "M")(actual_2024_total$total_gross_uplift)`** in assessed value uplift already showing up in the 2026 roll from the 2024 cohort alone, no assumptions needed. It understates the eventual value of that cohort, though: the "not yet fully reflected" group's uplift is a snapshot mid-construction (or a stale assessment of a just-finished building), not the finished-building value those properties will eventually reach. That gap between actual-so-far and eventual-once-complete is exactly what the model-based extrapolation later in this post is estimating. + +### From gross uplift to a fair counterfactual + +The raw 2024-to-2026 difference in assessed value overstates the effect of redevelopment on its own, because Edmonton property values were also generally rising over that period. To isolate the redevelopment effect, I build a counterfactual: what would each property likely have been worth in 2026 if it *hadn't* been redeveloped? I estimate this from a control group of RS-zoned properties in mature neighbourhoods that were not part of any 2024-2026 residential new-build permit, taking the median ratio of their 2026 to 2024 assessed value as a general appreciation factor. + +```{r} +#| label: counterfactual-growth +redeveloped_legal_keys <- bp |> + st_drop_geometry() |> + filter(units_added >= 1, work_type == "(01) Building - New") |> + distinct(legal_description) |> + pull(legal_description) + +nbhd_type_lookup <- bp |> + st_drop_geometry() |> + distinct(neighbourhood, neighbourhood_type) |> + filter(!is.na(neighbourhood_type)) + +control_group <- assessment_2024 |> + filter(zoning == "RS") |> + left_join(nbhd_type_lookup, by = c("neighbourhood_name" = "neighbourhood")) |> + filter( + neighbourhood_type == "Mature", + !legal_description %in% redeveloped_legal_keys, + !account_number %in% final_cohort$account_number + ) |> + inner_join( + assessment_2026 |> select(account_number, value_2026 = assessed_value), + by = "account_number" + ) |> + mutate(growth_ratio = value_2026 / assessed_value) |> + filter(assessed_value > 10000, growth_ratio > 0.5, growth_ratio < 3) + +g <- median(control_group$growth_ratio, na.rm = TRUE) + +final_cohort <- final_cohort |> + mutate( + gross_uplift = value_2026 - value_2024, + net_uplift = value_2026 - g * value_2024 + ) +``` + +Across **`r comma(nrow(control_group))`** non-redeveloped RS Zone properties in mature neighbourhoods, the median 2024-to-2026 growth ratio is **`r round(g, 2)`x**, meaning a typical mature-neighbourhood house that wasn't touched still gained about `r percent(g - 1, accuracy = 1)` in assessed value over those two years. I use this as the baseline against which redevelopment uplift is measured: **net uplift** is the completed rowhome's 2026 value minus `r round(g, 2)` times its 2024 baseline, isolating the redevelopment effect from general market appreciation. **Gross uplift** is the simple, unadjusted difference, shown alongside it for comparison. + +@fig-uplift-distribution shows the distribution of both measures across the `r n_final_cohort` matched properties, split by project size. + +```{r} +#| label: fig-uplift-distribution +#| fig-cap: "Distribution of assessed value uplift per redeveloped property, gross and net of market appreciation" +uplift_long <- final_cohort |> + select(bucket, gross_uplift, net_uplift) |> + pivot_longer(c(gross_uplift, net_uplift), names_to = "type", values_to = "uplift") |> + mutate( + type = if_else(type == "gross_uplift", "Gross uplift", "Net of appreciation") + ) + +ggplot(uplift_long, aes(x = bucket, y = uplift, fill = type)) + + geom_boxplot(outlier.alpha = 0.4, position = position_dodge(width = 0.75)) + + scale_y_continuous(labels = label_dollar(scale = 1e-6, suffix = "M")) + + labs( + title = "Assessed value uplift per redeveloped property", + subtitle = "2024 RS Zone 5-8 unit rowhomes, mature neighbourhoods, reflected as complete (occupancy by Sept 2025)", + x = NULL, + y = "Assessed value uplift", + fill = NULL, + caption = CAPTION_COE + ) + + theme_jd(mode = "light") +``` + +@tbl-uplift-rules compares three simple ways of summarizing this uplift into a single per-project figure: a median per property within two size buckets (5-6 units and 7-8 units), a single pooled median per property across all sizes, and a median per home added, which can be scaled by any project's unit count. These serve as sanity anchors for the model-based rule developed next. + +```{r} +#| label: tbl-uplift-rules +#| tbl-cap: "Three ways to summarize per-project uplift, gross and net of appreciation" +rule_bucketed <- final_cohort |> + group_by(bucket) |> + summarise( + n = n(), + gross = median(gross_uplift), + net = median(net_uplift), + .groups = "drop" + ) |> + rename(rule = bucket) + +rule_pooled <- final_cohort |> + summarise(n = n(), gross = median(gross_uplift), net = median(net_uplift)) |> + mutate(rule = "Pooled (5-8 units)", .before = 1) + +rule_per_unit <- final_cohort |> + summarise( + n = n(), + gross = median(gross_uplift / units_added), + net = median(net_uplift / units_added) + ) |> + mutate(rule = "Per home added", .before = 1) + +bind_rows(rule_bucketed, rule_pooled, rule_per_unit) |> + gt(rowname_col = "rule") |> + fmt_currency(columns = c(gross, net), decimals = 0) |> + cols_label(n = "n", gross = "Median gross uplift", net = "Median net uplift") |> + tab_header( + title = "Three uplift rules compared", + subtitle = "Measured from the completed 2024 cohort" + ) |> + finalize_gt() |> + opt_stylize_jd() +``` + +### A model for uplift + +The simple rules above ignore everything about a project except its unit count. But uplift plausibly varies with location too: land near LRT stations and in more expensive neighbourhoods should command different completed values. So the headline rule for this post is a regression of each property's **gross uplift** on three things: units added, distance from the nearest LRT stop, and the neighbourhood's median RS-zone assessed value (a land-value measure computed from the same 2024 assessment data, since with only `r n_final_cohort` observations spread across `r n_distinct(final_cohort$neighbourhood)` neighbourhoods, per-neighbourhood dummy variables are off the table). + +```{r} +#| label: uplift-model +# Neighbourhood land-value covariate: median 2024 assessed value of +# RS-zoned properties, per neighbourhood. +nbhd_median_rs_value <- assessment_2024 |> + filter(zoning == "RS") |> + group_by(neighbourhood_name) |> + summarise(nbhd_median_value = median(assessed_value), .groups = "drop") + +final_cohort <- final_cohort |> + left_join(nbhd_median_rs_value, by = c("neighbourhood" = "neighbourhood_name")) + +stopifnot( + all(!is.na(final_cohort$nbhd_median_value)), + all(!is.na(final_cohort$distance_from_lrt)), + all(final_cohort$gross_uplift > 0) +) + +loocv_rmse <- function(fit_fun, pred_fun, data) { + errs <- vapply(seq_len(nrow(data)), function(i) { + m <- fit_fun(data[-i, ]) + pred_fun(m, data[i, ]) - data$gross_uplift[i] + }, numeric(1)) + sqrt(mean(errs^2)) +} +# Same as loocv_rmse() but returns the per-property errors rather than their +# RMSE, needed for a paired bootstrap comparison between two specs. +loocv_errs <- function(fit_fun, pred_fun, data) { + vapply(seq_len(nrow(data)), function(i) { + m <- fit_fun(data[-i, ]) + pred_fun(m, data[i, ]) - data$gross_uplift[i] + }, numeric(1)) +} + +# Covariate-transform search: units added and neighbourhood value each on a +# linear vs. log scale, distance from LRT on a linear vs. inverse-distance +# scale, always with gross uplift itself left untransformed (see prose +# below). errs_level/errs_level_log are kept per-observation to support a +# paired bootstrap comparison between the previous default and the winner. +errs_level <- loocv_errs( + \(d) lm(gross_uplift ~ units_added + distance_from_lrt + I(nbhd_median_value / 1e5), d), + \(m, nd) predict(m, nd), + final_cohort +) +errs_level_log <- loocv_errs( + \(d) lm(gross_uplift ~ log(units_added) + distance_from_lrt + log(nbhd_median_value), d), + \(m, nd) predict(m, nd), + final_cohort +) +rmse_level <- sqrt(mean(errs_level^2)) +rmse_level_log <- sqrt(mean(errs_level_log^2)) +rmse_log <- loocv_rmse( + \(d) lm(log(gross_uplift) ~ units_added + distance_from_lrt + log(nbhd_median_value), d), + # Duan smearing estimator for the back-transform + \(m, nd) exp(predict(m, nd)) * mean(exp(residuals(m))), + final_cohort +) +rmse_median <- sqrt(mean((median(final_cohort$gross_uplift) - final_cohort$gross_uplift)^2)) + +# Paired bootstrap SE of an RMSE difference (dollars, matching rmse_*'s own +# units) between two specs fit on the same 48 properties. +paired_bootstrap_se <- function(errs_a, errs_b, B = 2000, seed = 1) { + n <- length(errs_a) + old_seed <- .Random.seed + set.seed(seed) + diffs <- replicate(B, { + idx <- sample.int(n, n, replace = TRUE) + sqrt(mean(errs_a[idx]^2)) - sqrt(mean(errs_b[idx]^2)) + }) + .Random.seed <<- old_seed + sd(diffs) +} +spec_choice_se <- paired_bootstrap_se(errs_level_log, errs_level) + +uplift_model <- lm( + gross_uplift ~ log(units_added) + distance_from_lrt + log(nbhd_median_value), + data = final_cohort +) +``` + +Two specification choices deserve a word. First, modelling gross uplift is algebraically the same as modelling the completed 2026 value with the 2024 baseline as a fixed offset. Letting the baseline enter with a freely estimated coefficient instead doesn't help: the old house's value is nearly collinear with the neighbourhood land-value measure (r = `r round(cor(final_cohort$value_2024, final_cohort$nbhd_median_value), 2)`), so the offset form is both more stable and better in cross-validation. + +Second, the uplift itself is *not* log-transformed: the measured cohort's uplift distribution isn't right-skewed enough to justify it, and a log-log variant does worse in cross-validation (see @tbl-model-comparison). But its two *covariates* are worth transforming: I searched units added and neighbourhood value on both linear and log scales, and distance from LRT on both linear and inverse-distance scales, always keeping gross uplift itself on the dollar scale, evaluated by leave-one-out cross-validation on the dollar scale. @tbl-model-comparison shows the two ends of that search. Log-transforming units added and neighbourhood value together gives the best cross-validated fit, an improvement over the plain linear specification and clearly ahead of log-transforming the outcome instead. With only `r n_final_cohort` observations, that improvement is real but not dramatic — about `r round((rmse_level - rmse_level_log) / spec_choice_se, 1)` times its own bootstrap standard error — so I adopt it as the best available specification on the evidence, not because the gap is large. + +```{r} +#| label: tbl-model-comparison +#| tbl-cap: "Comparing uplift model specifications by leave-one-out cross-validated RMSE" +tibble( + spec = c( + "Units + LRT distance + neighbourhood value (linear)", + "log(units) + LRT distance + log(neighbourhood value) (adopted)", + "log(gross uplift) ~ units + LRT distance + log(neighbourhood value)", + "Pooled median (no covariates)" + ), + rmse = c(rmse_level, rmse_level_log, rmse_log, rmse_median) +) |> + gt(rowname_col = "spec") |> + fmt_currency(columns = rmse, decimals = 0) |> + cols_label(rmse = "LOOCV RMSE") |> + tab_header( + title = "Comparing uplift model specifications", + subtitle = paste0("Leave-one-out cross-validated RMSE, dollar scale, n = ", n_final_cohort) + ) |> + finalize_gt() |> + opt_stylize_jd() +``` + +@tbl-uplift-model shows the chosen model's coefficients. + +```{r} +#| label: tbl-uplift-model +#| tbl-cap: "Gross uplift model coefficients, fit on the measured 2024 cohort" +broom_coefs <- summary(uplift_model)$coefficients |> + as_tibble(rownames = "term") |> + rename(estimate = Estimate, se = `Std. Error`, t = `t value`, p = `Pr(>|t|)`) |> + mutate( + term = case_match( + term, + "(Intercept)" ~ "Intercept", + "log(units_added)" ~ "Units added (log)", + "distance_from_lrt" ~ "Distance from LRT (per km)", + "log(nbhd_median_value)" ~ "Neighbourhood median RS value (log)" + ) + ) + +broom_coefs |> + gt(rowname_col = "term") |> + fmt_currency(columns = c(estimate, se), decimals = 0) |> + fmt_number(columns = t, decimals = 2) |> + fmt_number(columns = p, decimals = 3) |> + cols_label(estimate = "Estimate", se = "Std. error", t = "t", p = "p-value") |> + tab_header( + title = "What drives per-property uplift?", + subtitle = paste0( + "Gross uplift ~ log(units) + LRT distance + log(neighbourhood value); R² = ", + round(summary(uplift_model)$r.squared, 2), + ", n = ", n_final_cohort + ) + ) |> + finalize_gt() |> + opt_stylize_jd() +``` + +Units added is the clearest and most statistically solid effect in the model, but because it enters on a log scale, its dollar effect isn't constant per home — it tapers off as project size grows. Near the bottom of the 5-8 unit range, the marginal home is worth about **`r label_dollar(scale = 1e-3, suffix = "k")(coef(uplift_model)["log(units_added)"] / 5)`**; near the top, about `r label_dollar(scale = 1e-3, suffix = "k")(coef(uplift_model)["log(units_added)"] / 8)`, a diminishing-returns pattern consistent with each additional unit adding somewhat less land-value-per-unit than the last. A neighbourhood with double the typical RS-zoned land value tends to see about `r label_dollar(scale = 1e-3, suffix = "k")(coef(uplift_model)["log(nbhd_median_value)"] * log(2))` more in uplift, holding project size and distance fixed, though the estimate is imprecise. Distance from LRT comes out slightly *positive*, around `r label_dollar(scale = 1e-3, suffix = "k")(coef(uplift_model)["distance_from_lrt"])` per km, and statistically indistinguishable from zero: within mature neighbourhoods, being near a station doesn't measurably raise how much value a rowhome redevelopment adds, perhaps because station-adjacent land already carried a higher baseline value. With `r n_final_cohort` observations, all of these intervals are wide, and the model explains a modest `r percent(summary(uplift_model)$r.squared, accuracy = 1)` of the variation, which is the honest state of knowledge one construction cycle into ZBR. + +@fig-model-diagnostics shows the model's residual diagnostics: no strong funnel shape in the residuals-vs-fitted panel (the usual argument for a log transform) and reasonably normal-looking residuals. + +```{r} +#| label: fig-model-diagnostics +#| fig-cap: "Uplift model residual diagnostics" +#| fig-subcap: ["Residuals vs fitted values", "Normal Q-Q plot of residuals"] +#| layout-ncol: 2 +model_diag <- tibble( + fitted = fitted(uplift_model), + resid = residuals(uplift_model) +) + +ggplot(model_diag, aes(x = fitted, y = resid)) + + geom_point(size = 2, alpha = 0.7) + + geom_hline(yintercept = 0, linetype = "dashed", colour = "grey50") + + scale_x_continuous(labels = label_dollar(scale = 1e-6, suffix = "M")) + + scale_y_continuous(labels = label_dollar(scale = 1e-6, suffix = "M")) + + labs( + title = "Residuals vs fitted", + x = "Fitted gross uplift", + y = "Residual", + caption = CAPTION_COE + ) + + theme_jd(mode = "light") + +ggplot(model_diag, aes(sample = resid)) + + stat_qq(size = 2, alpha = 0.7) + + stat_qq_line(linetype = "dashed", colour = "grey50") + + scale_y_continuous(labels = label_dollar(scale = 1e-6, suffix = "M")) + + labs( + title = "Normal Q-Q", + x = "Theoretical quantiles", + y = "Residual", + caption = CAPTION_COE + ) + + theme_jd(mode = "light") +``` + +For a sanity check against @tbl-uplift-rules: the model's average predicted uplift across the measured cohort is `r label_dollar(scale = 1e-6, suffix = "M")(mean(fitted(uplift_model)))` per property, right in line with the simple medians, as it should be. What the model adds is the ability to give each *individual* permit a prediction tailored to its size and location, which matters when extrapolating to hundreds of permits whose size mix and geography differ from the measured cohort's. + +For **net** uplift, the counterfactual adjustment is applied after prediction: a property's predicted net uplift is its predicted gross uplift minus (`r round(g, 2)` − 1) times its own 2024 baseline value, the same adjustment used for the measured cohort. + +## Where is this happening? + +@tbl-uplift-by-neighbourhood breaks the measured cohort down by neighbourhood. + +```{r} +#| label: tbl-uplift-by-neighbourhood +#| tbl-cap: "Measured uplift by neighbourhood, 2024 RS Zone 5-8 unit cohort (interactive)" +#| column: page +blended_rate_2026 <- final_cohort |> + count(mill_class_1) |> + mutate(share = n / sum(n)) |> + summarise( + rate = sum(share * if_else( + mill_class_1 == "OTHER RESIDENTIAL", + municipal_rate("Other Residential", 2026), + municipal_rate("Residential", 2026) + )) + ) |> + pull(rate) + +final_cohort |> + mutate( + annual_tax_uplift = if_else( + mill_class_1 == "OTHER RESIDENTIAL", + value_2026 * municipal_rate("Other Residential", 2026), + value_2026 * municipal_rate("Residential", 2026) + ) - g * value_2024 * municipal_rate("Residential", 2026), + neighbourhood = str_to_title(neighbourhood) + ) |> + group_by(neighbourhood) |> + summarise( + n_projects = n(), + homes_added = sum(units_added), + median_gross_uplift = median(gross_uplift), + median_net_uplift = median(net_uplift), + annual_tax_uplift = sum(annual_tax_uplift), + .groups = "drop" + ) |> + arrange(desc(annual_tax_uplift)) |> + gt() |> + fmt_currency( + columns = c(median_gross_uplift, median_net_uplift, annual_tax_uplift), + decimals = 0 + ) |> + fmt_integer(columns = c(n_projects, homes_added)) |> + cols_label( + neighbourhood = "Neighbourhood", + n_projects = "Projects", + homes_added = "Homes added", + median_gross_uplift = "Median gross uplift", + median_net_uplift = "Median net uplift", + annual_tax_uplift = "Est. annual municipal tax uplift" + ) |> + tab_header( + title = "Measured uplift by neighbourhood", + subtitle = "2024 RS Zone 5-8 unit cohort, reflected as complete (occupancy by Sept 2025)" + ) |> + finalize_gt(interactive = TRUE) |> + opt_stylize_jd() +``` + +## From one cohort to the whole pipeline + +The measured cohort only covers 2024 permits that were both matchable and fully reflected in the 2026 assessment. To estimate the cumulative effect of the RS Zone rowhome since ZBR took effect, I apply the uplift model from @tbl-uplift-model to every other mature-neighbourhood RS Zone 5-8 unit new-build permit issued since 2024: the rest of the 2024 cohort (permits that didn't match or aren't fully assessed yet), all of 2025, and 2026. Each permit gets a prediction from its own unit count, LRT distance, and neighbourhood. + +This is a **steady-state estimate**: it assumes every one of those permits eventually reaches the completed-building uplift the model predicts, once construction wraps up and a future assessment catches up to it. It is not the smaller amount those properties currently show in the 2026 roll, which @tbl-2024-actual-total showed directly for 2024's not-yet-reflected permits. The gap between that actual, partial total and the steady-state estimate below is construction and assessment lag, not double-counting. + +```{r} +#| label: pipeline-counts +pipeline_counts <- rowhome_pipeline |> + st_drop_geometry() |> + mutate(bucket = if_else(units_added <= 6, "5-6 units", "7-8 units")) |> + count(year, bucket) + +# H1 annualization multiplier, same method as the Q2 2026 report: median +# ratio of full-year to H1 residential units across historical years. +h1_ratios <- bp |> + st_drop_geometry() |> + filter(year < 2026) |> + group_by(year) |> + summarize( + full_year = sum(units_added), + h1 = sum(units_added[month_number <= 6]), + .groups = "drop" + ) |> + mutate(ratio = full_year / h1) +h1_multiplier <- round(median(h1_ratios$ratio), 1) + +n_2024_all <- pipeline_counts |> filter(year == 2024) |> summarise(n = sum(n)) |> pull(n) +n_2025_all <- pipeline_counts |> filter(year == 2025) |> summarise(n = sum(n)) |> pull(n) +n_2026_h1 <- pipeline_counts |> filter(year == 2026) |> summarise(n = sum(n)) |> pull(n) +``` + +2025 permitted **`r n_2025_all`** more mature-neighbourhood RS Zone 5-8 unit rowhomes, and H1 2026 has already permitted `r n_2026_h1`. Following the same [H1 annualization method used in the Q2 2026 report](../q2-building-permits/index.qmd), full-year 2026 is projected at `r h1_multiplier`x the H1 count. + +Predicting *net* uplift needs each permit's own 2024 baseline value, so the 2025 and 2026 permits are run through the same baseline matchers as the 2024 cohort (their lots all existed in the 2024 roll, pre-redevelopment). + +```{r} +#| label: extrapolation +measured_ids <- final_cohort$permit_row_id + +# Baselines for 2025/2026 permits, using the same matchers as the 2024 cohort +permits_2025_2026 <- rowhome_pipeline |> filter(year %in% 2025:2026) +future_baselines <- match_baseline_2024(permits_2025_2026) |> + geo_fallback_baseline(permits_2025_2026) |> + select(permit_row_id, value_2024) + +baseline_match_rate <- mean(!is.na(future_baselines$value_2024)) + +# Every mature RS 5-8 unit new-build permit with the model's covariates. +# Fallbacks for prediction: median LRT distance for permits with no mapped +# location; the neighbourhood median RS value doubles as the baseline proxy +# for permits that didn't match one. +median_pipeline_distance <- median(rowhome_pipeline$distance_from_lrt, na.rm = TRUE) + +all_permits <- rowhome_pipeline |> + st_drop_geometry() |> + filter(year %in% 2024:2026) |> + left_join(nbhd_median_rs_value, by = c("neighbourhood" = "neighbourhood_name")) |> + left_join( + bind_rows( + matched_2024_all |> select(permit_row_id, value_2024), + future_baselines + ), + by = "permit_row_id" + ) |> + mutate( + nbhd_median_value = coalesce(nbhd_median_value, median(nbhd_median_rs_value$nbhd_median_value)), + distance_from_lrt = coalesce(distance_from_lrt, median_pipeline_distance), + baseline_value = coalesce(value_2024, nbhd_median_value), + pred_gross = predict( + uplift_model, + newdata = pick(units_added, distance_from_lrt, nbhd_median_value) + ), + pred_net = pred_gross - (g - 1) * baseline_value + ) + +measured_totals <- final_cohort |> + summarise(gross = sum(gross_uplift), net = sum(net_uplift)) + +model_based_2024 <- all_permits |> + filter(year == 2024, !permit_row_id %in% measured_ids) |> + summarise(gross = sum(pred_gross), net = sum(pred_net)) + +model_based_2025 <- all_permits |> + filter(year == 2025) |> + summarise(gross = sum(pred_gross), net = sum(pred_net)) + +model_based_2026_h1 <- all_permits |> + filter(year == 2026) |> + summarise(gross = sum(pred_gross), net = sum(pred_net)) + +# 2026 full-year projection: no per-permit rows exist yet for the +# un-permitted remainder of the year, so scale H1's predicted total. +model_based_2026_projected_remainder <- model_based_2026_h1 |> + mutate(gross = gross * (h1_multiplier - 1), net = net * (h1_multiplier - 1)) + +total_gross_uplift <- measured_totals$gross + model_based_2024$gross + + model_based_2025$gross + model_based_2026_h1$gross + model_based_2026_projected_remainder$gross +total_net_uplift <- measured_totals$net + model_based_2024$net + + model_based_2025$net + model_based_2026_h1$net + model_based_2026_projected_remainder$net + +n_2026_projected <- n_2026_h1 * h1_multiplier +``` + +The 2025 and 2026 permits match their 2024 baselines at a **`r percent(baseline_match_rate, accuracy = 1)`** rate; the few that don't use their neighbourhood's median RS value as a stand-in baseline for the net adjustment. + +@fig-cumulative-value-uplift shows the resulting cumulative assessed value uplift by permit year, split between the actually-measured portion and the portion estimated with the model. + +```{r} +#| label: fig-cumulative-value-uplift +#| fig-cap: "Cumulative estimated assessed value uplift since ZBR, by permit year (net of appreciation)" +cumulative_by_year <- tibble( + year = c(2024, 2024, 2025, 2026, 2026), + source = c("Measured", "Estimated (model)", "Estimated (model)", "Estimated (model)", "Estimated (model)"), + net_uplift = c( + measured_totals$net, model_based_2024$net, model_based_2025$net, + model_based_2026_h1$net, model_based_2026_projected_remainder$net + ) +) |> + group_by(year, source) |> + summarise(net_uplift = sum(net_uplift), .groups = "drop") + +ggplot(cumulative_by_year, aes(x = factor(year), y = net_uplift, fill = source)) + + geom_col() + + scale_y_continuous(labels = label_dollar(scale = 1e-6, suffix = "M")) + + labs( + title = "Cumulative assessed value uplift since ZBR", + subtitle = paste0("Net of market appreciation; 2026 full year projected at ", h1_multiplier, "x H1"), + x = "Permit year", + y = "Assessed value uplift", + fill = NULL, + caption = CAPTION_COE + ) + + theme_jd(mode = "light") +``` + +Adding it all up: since ZBR took effect, mature-neighbourhood RS Zone 5-8 unit rowhomes are estimated to have added **`r label_dollar(scale = 1e-6, suffix = "M")(total_gross_uplift)`** in gross assessed value, or **`r label_dollar(scale = 1e-6, suffix = "M")(total_net_uplift)`** net of general market appreciation, across `r n_2024_all` (2024) + `r n_2025_all` (2025) + `r round(n_2026_projected)` (2026, projected) = `r n_2024_all + n_2025_all + round(n_2026_projected)` permitted projects. + +@tbl-cumulative-selected-neighbourhoods breaks that cumulative estimate down for the same neighbourhoods used in the [Q2 2026 report's selected-neighbourhood table](../q2-building-permits/index.qmd), places that have been prominent in debates about RS Zone infill. Each permit is valued at its actual measured uplift where available, or the model's prediction otherwise, then summed by neighbourhood. This covers every actual permit issued through H1 2026; the projected remainder of 2026 isn't tied to real permits yet, so it's included in the citywide total above but left out of this neighbourhood breakdown. + +```{r} +#| label: tbl-cumulative-selected-neighbourhoods +#| tbl-cap: "Cumulative estimated uplift for selected neighbourhoods, 2024 through H1 2026" +#| column: page +selected_nbhds <- c( + "GLENWOOD", + "GROVENOR", + "BRITANNIA YOUNGSTOWN", + "WESTMOUNT", + "MCKERNAN", + "BELGRAVIA", + "CRESTWOOD", + "PARKVIEW" +) + +# Each actual permit's uplift: measured where available, model prediction +# otherwise. The 2026 projected remainder has no real permits to attach +# to a neighbourhood, so it's excluded here (it's still in the citywide +# total above). +measured_lookup <- final_cohort |> + st_drop_geometry() |> + select(permit_row_id, actual_gross = gross_uplift, actual_net = net_uplift, mill_class_1, value_2024, value_2026) + +permit_uplift <- all_permits |> + select(-value_2024) |> + left_join(measured_lookup, by = "permit_row_id") |> + mutate( + is_measured = !is.na(actual_gross), + gross_uplift = coalesce(actual_gross, pred_gross), + net_uplift = coalesce(actual_net, pred_net), + annual_tax_uplift = if_else( + is_measured, + if_else( + mill_class_1 == "OTHER RESIDENTIAL", + municipal_rate("Other Residential", 2026) * value_2026, + municipal_rate("Residential", 2026) * value_2026 + ) - municipal_rate("Residential", 2026) * g * value_2024, + net_uplift * blended_rate_2026 + ) + ) + +cumulative_by_neighbourhood <- permit_uplift |> + mutate(neighbourhood = str_to_title(neighbourhood)) |> + group_by(neighbourhood) |> + summarise( + n_projects = n(), + homes_added = sum(units_added), + cumulative_gross_uplift = sum(gross_uplift), + cumulative_net_uplift = sum(net_uplift), + annual_tax_uplift = sum(annual_tax_uplift), + .groups = "drop" + ) + +tibble(neighbourhood = str_to_title(selected_nbhds)) |> + left_join(cumulative_by_neighbourhood, by = "neighbourhood") |> + replace_na(list( + n_projects = 0, + homes_added = 0, + cumulative_gross_uplift = 0, + cumulative_net_uplift = 0, + annual_tax_uplift = 0 + )) |> + arrange(neighbourhood) |> + gt() |> + fmt_currency( + columns = c(cumulative_gross_uplift, cumulative_net_uplift, annual_tax_uplift), + decimals = 0 + ) |> + fmt_integer(columns = c(n_projects, homes_added)) |> + cols_label( + neighbourhood = "Neighbourhood", + n_projects = "Projects", + homes_added = "Homes added", + cumulative_gross_uplift = "Cumulative gross uplift", + cumulative_net_uplift = "Cumulative net uplift", + annual_tax_uplift = "Est. annual municipal tax uplift" + ) |> + tab_header( + title = "Cumulative uplift, selected neighbourhoods", + subtitle = "2024 through H1 2026, measured + model-based" + ) |> + finalize_gt() |> + opt_stylize_jd() |> + sub_missing() +``` + +## What this means for property tax + +Assessed value only matters for the City's budget insofar as it's taxed. I convert the estimated uplift into two figures: an **annual recurring** estimate, at 2026 municipal tax rates, of how much more property tax this pipeline will generate every year once every project is complete and fully reflected in an assessment roll; and a rougher **cumulative collected so far** estimate that accounts for the fact that most of this pipeline is still under construction or only recently completed. + +Completed 5-8 unit rowhomes on a single title are typically assessed as "Other Residential", which carries a higher municipal mill rate than the "Residential" class the original house was assessed under. In the measured cohort, `r percent(final_cohort |> summarise(p = mean(mill_class_1 == "OTHER RESIDENTIAL")) |> pull(p), accuracy = 1)` of completed properties land in Other Residential; I apply that same mix to the model-based portion of the estimate. + +```{r} +#| label: tax-conversion +tax_measured <- final_cohort |> + mutate( + new_rate = if_else( + mill_class_1 == "OTHER RESIDENTIAL", + municipal_rate("Other Residential", 2026), + municipal_rate("Residential", 2026) + ), + annual_tax_gross = new_rate * value_2026 - municipal_rate("Residential", 2026) * value_2024, + annual_tax_net = new_rate * value_2026 - municipal_rate("Residential", 2026) * g * value_2024 + ) |> + summarise(gross = sum(annual_tax_gross), net = sum(annual_tax_net)) + +model_based_gross_total <- model_based_2024$gross + model_based_2025$gross + + model_based_2026_h1$gross + model_based_2026_projected_remainder$gross +model_based_net_total <- model_based_2024$net + model_based_2025$net + + model_based_2026_h1$net + model_based_2026_projected_remainder$net + +tax_model_based_gross <- model_based_gross_total * blended_rate_2026 +tax_model_based_net <- model_based_net_total * blended_rate_2026 + +annual_tax_uplift_gross <- tax_measured$gross + tax_model_based_gross +annual_tax_uplift_net <- tax_measured$net + tax_model_based_net +``` + +At 2026 municipal tax rates, this pipeline is estimated to add **`r label_dollar(scale = 1e-6, suffix = "M")(annual_tax_uplift_net)`** in property tax every year, net of what general appreciation would have generated anyway (`r label_dollar(scale = 1e-6, suffix = "M")(annual_tax_uplift_gross)` on a gross basis). That's before counting the provincial education levy, which would add roughly another third on top of the municipal portion. + +Because most of this pipeline is still ramping up, actual tax collected so far is much lower than that steady-state figure. Comparing each matched property's mid-construction 2025 assessed value to its 2024 baseline and completed 2026 value shows how much of the total uplift typically shows up one year after a permit is issued. + +```{r} +#| label: cumulative-collected +blended_rate_2025 <- final_cohort |> + count(mill_class_1) |> + mutate(share = n / sum(n)) |> + summarise( + rate = sum(share * if_else( + mill_class_1 == "OTHER RESIDENTIAL", + municipal_rate("Other Residential", 2025), + municipal_rate("Residential", 2025) + )) + ) |> + pull(rate) + +partial_uplift_share <- final_cohort |> + filter(!is.na(value_2025), value_2026 > value_2024) |> + mutate(p = (value_2025 - value_2024) / (value_2026 - value_2024)) |> + summarise(p = median(p)) |> + pull(p) |> + pmax(0) |> + pmin(1) + +# Net uplift value permitted in each year (2024 cohort = all mature RS 5-8 +# new-builds from 2024, measured + model-based) +net_uplift_2024_cohort <- measured_totals$net + model_based_2024$net +net_uplift_2025_cohort <- model_based_2025$net + +# A property permitted in year Y contributes a partial share of its +# annual tax uplift in year Y+1, and the full amount from Y+2 on. +collected_2025 <- partial_uplift_share * net_uplift_2024_cohort * blended_rate_2025 +collected_2026 <- net_uplift_2024_cohort * blended_rate_2026 + + partial_uplift_share * net_uplift_2025_cohort * blended_rate_2026 +cumulative_collected <- collected_2025 + collected_2026 +``` + +The median property has captured about `r percent(partial_uplift_share, accuracy = 1)` of its full uplift by the assessment one year after permitting, consistent with most projects still being under construction at that point. Modelling each year's cohort as contributing that partial share in the following year and the full amount from two years out, I estimate Edmonton has collected roughly **`r label_dollar(scale = 1e-6, suffix = "M")(cumulative_collected)`** in incremental property tax from this pipeline across 2025 and 2026 combined, well short of the `r label_dollar(scale = 1e-6, suffix = "M")(annual_tax_uplift_net)`-a-year run rate this pipeline will eventually reach once every project currently in the pipeline is complete and fully assessed. + +These are estimates, not City budget figures. Assessment growth from new construction doesn't translate one-for-one into new City revenue, since Council sets the mill rate each year based on total budget needs, but new construction is genuinely additional tax base at whatever rate Council sets, distinct from a rate increase on existing properties. This also doesn't account for the cost of servicing new residents, which isn't the subject of this post. + +## Conclusions + +The RS Zone rowhome isn't just adding homes, it's rebuilding the property tax base of neighbourhoods that had been losing population and, with it, tax revenue per hectare of city-maintained infrastructure for decades. A handful of redevelopments per neighbourhood, concentrated in mature areas that already have the pipes, roads, and schools in place, is already worth tens of millions of dollars a year in additional property tax capacity, on top of the housing it delivers. + +None of this required a subsidy, a grant, or a City-led development. It required removing rules that made this kind of building illegal. 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\"ctb\"), person(\"Lisa\", \"Lendway\", , \"llendway@macalester.edu\", role = \"ctb\"), person(\"Karl\", \"Hailperin\", , \"khailper@gmail.com\", role = \"ctb\"), person(\"Josue\", \"Rodriguez\", , \"jerrodriguez@ucdavis.edu\", role = \"ctb\"), person(\"Jenny\", \"Bryan\", , \"jenny@posit.co\", role = \"ctb\"), person(\"Chris\", \"Jarvis\", , \"Christopher1.jarvis@gmail.com\", role = \"ctb\"), person(\"Greg\", \"Macfarlane\", , \"gregmacfarlane@gmail.com\", role = \"ctb\"), person(\"Brian\", \"Mannakee\", , \"bmannakee@gmail.com\", role = \"ctb\"), person(\"Drew\", \"Tyre\", , \"atyre2@unl.edu\", role = \"ctb\"), person(\"Shreyas\", \"Singh\", , \"shreyas.singh.298@gmail.com\", role = \"ctb\"), person(\"Laurens\", \"Geffert\", , \"laurensgeffert@gmail.com\", role = \"ctb\"), person(\"Hong\", \"Ooi\", , \"hongooi@microsoft.com\", role = \"ctb\"), person(\"Henrik\", \"Bengtsson\", , \"henrikb@braju.com\", role = \"ctb\"), person(\"Eduard\", \"Szocs\", , \"eduardszoecs@gmail.com\", role = \"ctb\"), person(\"David\", \"Hugh-Jones\", , \"davidhughjones@gmail.com\", role = \"ctb\"), person(\"Matthieu\", \"Stigler\", , \"Matthieu.Stigler@gmail.com\", role = \"ctb\"), person(\"Hugo\", \"Tavares\", , \"hm533@cam.ac.uk\", role = \"ctb\", comment = c(ORCID = \"0000-0001-9373-2726\")), person(\"R. Willem\", \"Vervoort\", , \"Willemvervoort@gmail.com\", role = \"ctb\"), person(\"Brenton M.\", \"Wiernik\", , \"brenton@wiernik.org\", role = \"ctb\"), person(\"Josh\", \"Yamamoto\", , \"joshuayamamoto5@gmail.com\", role = \"ctb\"), person(\"Jasme\", \"Lee\", role = \"ctb\"), person(\"Taren\", \"Sanders\", , \"taren.sanders@acu.edu.au\", role = \"ctb\", comment = c(ORCID = \"0000-0002-4504-6008\")), person(\"Ilaria\", \"Prosdocimi\", , \"prosdocimi.ilaria@gmail.com\", role = \"ctb\", comment = c(ORCID = \"0000-0001-8565-094X\")), person(\"Daniel D.\", \"Sjoberg\", , \"danield.sjoberg@gmail.com\", role = \"ctb\", comment = c(ORCID = \"0000-0003-0862-2018\")), person(\"Alex\", \"Reinhart\", , \"areinhar@stat.cmu.edu\", role = \"ctb\", comment = c(ORCID = \"0000-0002-6658-514X\")) )", + "Description": "Summarizes key information about statistical objects in tidy tibbles. This makes it easy to report results, create plots and consistently work with large numbers of models at once. Broom provides three verbs that each provide different types of information about a model. tidy() summarizes information about model components such as coefficients of a regression. glance() reports information about an entire model, such as goodness of fit measures like AIC and BIC. augment() adds information about individual observations to a dataset, such as fitted values or influence measures.", + "License": "MIT + file LICENSE", + "URL": "https://broom.tidymodels.org/, https://github.com/tidymodels/broom", + "BugReports": "https://github.com/tidymodels/broom/issues", + "Depends": [ + "R (>= 4.1)" + ], + "Imports": [ + "backports", + "cli", + "dplyr (>= 1.0.0)", + "generics (>= 0.0.2)", + "glue", + "lifecycle", + "purrr", + "rlang (>= 1.1.0)", + "stringr", + "tibble (>= 3.0.0)", + "tidyr (>= 1.0.0)" + ], + "Suggests": [ + "AER", + "AUC", + "bbmle", + "betareg (>= 3.2-1)", + "biglm", + "binGroup", + "boot", + "btergm (>= 1.10.6)", + "car (>= 3.1-2)", + "carData", + "caret", + 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'multcomp.R' 'nnet.R' 'nobs.R' 'ordinal-clm.R' 'ordinal-clmm.R' 'plm.R' 'polca.R' 'psych.R' 'stats-nls.R' 'quantreg-nlrq.R' 'quantreg-rq.R' 'quantreg-rqs.R' 'robust-glmrob.R' 'robust-lmrob.R' 'robustbase-glmrob.R' 'robustbase-lmrob.R' 'sp.R' 'spdep.R' 'speedglm-speedglm.R' 'speedglm-speedlm.R' 'stats-anova.R' 'stats-arima.R' 'stats-decompose.R' 'stats-factanal.R' 'stats-glm.R' 'stats-htest.R' 'stats-kmeans.R' 'stats-loess.R' 'stats-mlm.R' 'stats-prcomp.R' 'stats-smooth.spline.R' 'stats-summary-lm.R' 'stats-time-series.R' 'survey.R' 'survival-aareg.R' 'survival-cch.R' 'survival-coxph.R' 'survival-pyears.R' 'survival-survdiff.R' 'survival-survexp.R' 'survival-survfit.R' 'survival-survreg.R' 'systemfit.R' 'tseries.R' 'utilities.R' 'vars.R' 'zoo.R' 'zzz.R'", + "NeedsCompilation": "no", + "Author": "David Robinson [aut], Alex Hayes [aut] (ORCID: ), Simon Couch [aut] (ORCID: ), Emil Hvitfeldt [aut, cre] (ORCID: ), Posit Software, PBC [cph, fnd] (ROR: ), Indrajeet Patil [ctb] (ORCID: ), Derek Chiu [ctb], Matthieu Gomez [ctb], Boris Demeshev [ctb], Dieter Menne [ctb], Benjamin Nutter [ctb], Luke Johnston [ctb], Ben Bolker [ctb], Francois Briatte [ctb], Jeffrey Arnold [ctb], Jonah Gabry [ctb], Luciano Selzer [ctb], Gavin Simpson [ctb], Jens Preussner [ctb], Jay Hesselberth [ctb], Hadley Wickham [ctb], Matthew Lincoln [ctb], Alessandro Gasparini [ctb], Lukasz Komsta [ctb], Frederick Novometsky [ctb], Wilson Freitas [ctb], Michelle Evans [ctb], Jason Cory Brunson [ctb], Simon Jackson [ctb], Ben Whalley [ctb], Karissa Whiting [ctb], Yves Rosseel [ctb], Michael Kuehn [ctb], Jorge Cimentada [ctb], Erle Holgersen [ctb], Karl Dunkle Werner [ctb] (ORCID: ), Ethan Christensen [ctb], Steven Pav [ctb], Paul PJ [ctb], Ben Schneider [ctb], Patrick Kennedy [ctb], Lily Medina [ctb], Brian Fannin [ctb], Jason Muhlenkamp [ctb], Matt Lehman [ctb], Bill Denney [ctb] (ORCID: ), Nic Crane [ctb], Andrew Bates [ctb], Vincent Arel-Bundock [ctb] (ORCID: ), Hideaki Hayashi [ctb], Luis Tobalina [ctb], Annie Wang [ctb], Wei Yang Tham [ctb], Clara Wang [ctb], Abby Smith [ctb] (ORCID: ), Jasper Cooper [ctb] (ORCID: ), E Auden Krauska [ctb] (ORCID: ), Alex Wang [ctb], Malcolm Barrett [ctb] (ORCID: ), Charles Gray [ctb] (ORCID: ), Jared Wilber [ctb], Vilmantas Gegzna [ctb] (ORCID: ), Eduard Szoecs [ctb], Frederik Aust [ctb] (ORCID: ), Angus Moore [ctb], Nick Williams [ctb], Marius Barth [ctb] (ORCID: ), Bruna Wundervald [ctb] (ORCID: ), Joyce Cahoon [ctb] (ORCID: ), Grant McDermott [ctb] (ORCID: ), Kevin Zarca [ctb], Shiro Kuriwaki [ctb] (ORCID: ), Lukas Wallrich [ctb] (ORCID: ), James Martherus [ctb] (ORCID: ), Chuliang Xiao [ctb] (ORCID: ), Joseph Larmarange [ctb], Max Kuhn [ctb], Michal Bojanowski [ctb], Hakon Malmedal [ctb], Clara Wang [ctb], Sergio Oller [ctb], Luke Sonnet [ctb], Jim Hester [ctb], Ben Schneider [ctb], Bernie Gray [ctb] (ORCID: ), Mara Averick [ctb], Aaron Jacobs [ctb], Andreas Bender [ctb], Sven Templer [ctb], Paul-Christian Buerkner [ctb], Matthew Kay [ctb], Erwan Le Pennec [ctb], Johan Junkka [ctb], Hao Zhu [ctb], Benjamin Soltoff [ctb], Zoe Wilkinson Saldana [ctb], Tyler Littlefield [ctb], Charles T. Gray [ctb], Shabbh E. Banks [ctb], Serina Robinson [ctb], Roger Bivand [ctb], Riinu Ots [ctb], Nicholas Williams [ctb], Nina Jakobsen [ctb], Michael Weylandt [ctb], Lisa Lendway [ctb], Karl Hailperin [ctb], Josue Rodriguez [ctb], Jenny Bryan [ctb], Chris Jarvis [ctb], Greg Macfarlane [ctb], Brian Mannakee [ctb], Drew Tyre [ctb], Shreyas Singh [ctb], Laurens Geffert [ctb], Hong Ooi [ctb], Henrik Bengtsson [ctb], Eduard Szocs [ctb], David Hugh-Jones [ctb], Matthieu Stigler [ctb], Hugo Tavares [ctb] (ORCID: ), R. Willem Vervoort [ctb], Brenton M. Wiernik [ctb], Josh Yamamoto [ctb], Jasme Lee [ctb], Taren Sanders [ctb] (ORCID: ), Ilaria Prosdocimi [ctb] (ORCID: ), Daniel D. Sjoberg [ctb] (ORCID: ), Alex Reinhart [ctb] (ORCID: )", + "Maintainer": "Emil Hvitfeldt ", + "Repository": "CRAN" + }, + "bslib": { + "Package": "bslib", + "Version": "0.11.0", + "Source": "Repository", + "Title": "Custom 'Bootstrap' 'Sass' Themes for 'shiny' and 'rmarkdown'", + "Authors@R": "c( person(\"Carson\", \"Sievert\", , \"carson@posit.co\", role = c(\"aut\", \"cre\"), comment = c(ORCID = \"0000-0002-4958-2844\")), person(\"Joe\", \"Cheng\", , \"joe@posit.co\", role = \"aut\"), person(\"Garrick\", \"Aden-Buie\", , \"garrick@posit.co\", role = \"aut\", comment = c(ORCID = \"0000-0002-7111-0077\")), person(\"Posit Software, PBC\", role = c(\"cph\", \"fnd\")), person(, \"Bootstrap contributors\", role = \"ctb\", comment = \"Bootstrap library\"), person(, \"Twitter, Inc\", role = \"cph\", comment = \"Bootstrap library\"), person(\"Javi\", \"Aguilar\", role = c(\"ctb\", \"cph\"), comment = \"Bootstrap colorpicker library\"), person(\"Thomas\", \"Park\", role = c(\"ctb\", \"cph\"), comment = \"Bootswatch library\"), person(, \"PayPal\", role = c(\"ctb\", \"cph\"), comment = \"Bootstrap accessibility plugin\") )", + "Description": "Simplifies custom 'CSS' styling of both 'shiny' and 'rmarkdown' via 'Bootstrap' 'Sass'. Supports 'Bootstrap' 3, 4 and 5 as well as their various 'Bootswatch' themes. 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This can make it hard to detect conflicts, particularly when they arise because a package update creates ambiguity that did not previously exist. 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Compared to other approaches 'cpp11' strives to be safe against long jumps from the C API as well as C++ exceptions, conform to normal R function semantics and supports interaction with 'ALTREP' vectors.", + "License": "MIT + file LICENSE", + "URL": "https://cpp11.r-lib.org, https://github.com/r-lib/cpp11", + "BugReports": "https://github.com/r-lib/cpp11/issues", + "Depends": [ + "R (>= 4.0.0)" + ], + "Suggests": [ + "bench", + "brio", + "callr", + "cli", + "covr", + "decor", + "desc", + "ggplot2", + "glue", + "knitr", + "lobstr", + "mockery", + "progress", + "rmarkdown", + "scales", + "Rcpp", + "testthat (>= 3.2.0)", + "tibble", + "utils", + "vctrs", + "withr" + ], + "VignetteBuilder": "knitr", + "Config/Needs/website": "tidyverse/tidytemplate", + "Config/testthat/edition": "3", + "Config/Needs/cpp11/cpp_register": "brio, cli, decor, desc, glue, tibble, vctrs", + "Encoding": "UTF-8", + "RoxygenNote": "7.3.3", + "NeedsCompilation": "no", + "Author": "Davis Vaughan [aut, cre] (ORCID: ), Jim Hester [aut] (ORCID: ), Romain François [aut] (ORCID: ), Benjamin Kietzman [ctb], Posit Software, PBC [cph, fnd]", + "Maintainer": "Davis Vaughan ", + "Repository": "CRAN" + }, + "crayon": { + "Package": "crayon", + "Version": "1.5.3", + "Source": "Repository", + "Title": "Colored Terminal Output", + "Authors@R": "c( person(\"Gábor\", \"Csárdi\", , \"csardi.gabor@gmail.com\", role = c(\"aut\", \"cre\")), person(\"Brodie\", \"Gaslam\", , \"brodie.gaslam@yahoo.com\", role = \"ctb\"), person(\"Posit Software, PBC\", role = c(\"cph\", \"fnd\")) )", + "Description": "The crayon package is now superseded. 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This package will quickly and precisely perform these CSS transformations when given HTML text and it does so by using the JavaScript 'juice' library.", + "License": "MIT + file LICENSE", + "URL": "https://github.com/rich-iannone/juicyjuice", + "BugReports": "https://github.com/rich-iannone/juicyjuice/issues", + "Encoding": "UTF-8", + "RoxygenNote": "7.2.1", + "Imports": [ + "V8 (>= 4.2.0)" + ], + "Suggests": [ + "testthat (>= 3.0.0)" + ], + "Config/testthat/edition": "3", + "NeedsCompilation": "no", + "Author": "Richard Iannone [aut, cre, cph] (), Automattic [cph] (juice library), juice contributors [ctb] (juice library)", + "Maintainer": "Richard Iannone ", + "Repository": "CRAN" + }, + "knitr": { + "Package": "knitr", + "Version": "1.51", + "Source": "Repository", + "Type": "Package", + "Title": "A General-Purpose Package for Dynamic Report Generation in R", + "Authors@R": "c( person(\"Yihui\", \"Xie\", role = c(\"aut\", \"cre\"), email = \"xie@yihui.name\", comment = c(ORCID = 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\"Lyttle\", role = \"ctb\"), person(\"Hodges\", \"Daniel\", role = \"ctb\"), person(\"Jacob\", \"Bien\", role = \"ctb\"), person(\"Jake\", \"Burkhead\", role = \"ctb\"), person(\"James\", \"Manton\", role = \"ctb\"), person(\"Jared\", \"Lander\", role = \"ctb\"), person(\"Jason\", \"Punyon\", role = \"ctb\"), person(\"Javier\", \"Luraschi\", role = \"ctb\"), person(\"Jeff\", \"Arnold\", role = \"ctb\"), person(\"Jenny\", \"Bryan\", role = \"ctb\"), person(\"Jeremy\", \"Ashkenas\", role = c(\"ctb\", \"cph\"), comment = \"the CSS file at inst/misc/docco-classic.css\"), person(\"Jeremy\", \"Stephens\", role = \"ctb\"), person(\"Jim\", \"Hester\", role = \"ctb\"), person(\"Joe\", \"Cheng\", role = \"ctb\"), person(\"Johannes\", \"Ranke\", role = \"ctb\"), person(\"John\", \"Honaker\", role = \"ctb\"), person(\"John\", \"Muschelli\", role = \"ctb\"), person(\"Jonathan\", \"Keane\", role = \"ctb\"), person(\"JJ\", \"Allaire\", role = \"ctb\"), person(\"Johan\", \"Toloe\", role = \"ctb\"), person(\"Jonathan\", \"Sidi\", role = \"ctb\"), person(\"Joseph\", \"Larmarange\", role = \"ctb\"), person(\"Julien\", \"Barnier\", role = \"ctb\"), person(\"Kaiyin\", \"Zhong\", role = \"ctb\"), person(\"Kamil\", \"Slowikowski\", role = \"ctb\"), person(\"Karl\", \"Forner\", role = \"ctb\"), person(c(\"Kevin\", \"K.\"), \"Smith\", role = \"ctb\"), person(\"Kirill\", \"Mueller\", role = \"ctb\"), person(\"Kohske\", \"Takahashi\", role = \"ctb\"), person(\"Lorenz\", \"Walthert\", role = \"ctb\"), person(\"Lucas\", \"Gallindo\", role = \"ctb\"), person(\"Marius\", \"Hofert\", role = \"ctb\"), person(\"Martin\", \"Modrák\", role = \"ctb\"), person(\"Michael\", \"Chirico\", role = \"ctb\"), person(\"Michael\", \"Friendly\", role = \"ctb\"), person(\"Michal\", \"Bojanowski\", role = \"ctb\"), person(\"Michel\", \"Kuhlmann\", role = \"ctb\"), person(\"Miller\", \"Patrick\", role = \"ctb\"), person(\"Nacho\", \"Caballero\", role = \"ctb\"), person(\"Nick\", \"Salkowski\", role = \"ctb\"), person(\"Niels Richard\", \"Hansen\", role = \"ctb\"), person(\"Noam\", \"Ross\", role = \"ctb\"), person(\"Obada\", \"Mahdi\", role = \"ctb\"), person(\"Pavel N.\", \"Krivitsky\", role = \"ctb\", comment=c(ORCID = \"0000-0002-9101-3362\")), person(\"Pedro\", \"Faria\", role = \"ctb\"), person(\"Qiang\", \"Li\", role = \"ctb\"), person(\"Ramnath\", \"Vaidyanathan\", role = \"ctb\"), person(\"Richard\", \"Cotton\", role = \"ctb\"), person(\"Robert\", \"Krzyzanowski\", role = \"ctb\"), person(\"Rodrigo\", \"Copetti\", role = \"ctb\"), person(\"Romain\", \"Francois\", role = \"ctb\"), person(\"Ruaridh\", \"Williamson\", role = \"ctb\"), person(\"Sagiru\", \"Mati\", role = \"ctb\", comment = c(ORCID = \"0000-0003-1413-3974\")), person(\"Scott\", \"Kostyshak\", role = \"ctb\"), person(\"Sebastian\", \"Meyer\", role = \"ctb\"), person(\"Sietse\", \"Brouwer\", role = \"ctb\"), person(c(\"Simon\", \"de\"), \"Bernard\", role = \"ctb\"), person(\"Sylvain\", \"Rousseau\", role = \"ctb\"), person(\"Taiyun\", \"Wei\", role = \"ctb\"), person(\"Thibaut\", \"Assus\", role = \"ctb\"), person(\"Thibaut\", \"Lamadon\", role = \"ctb\"), person(\"Thomas\", \"Leeper\", role = \"ctb\"), person(\"Tim\", \"Mastny\", role = \"ctb\"), person(\"Tom\", \"Torsney-Weir\", role = \"ctb\"), person(\"Trevor\", \"Davis\", role = \"ctb\"), person(\"Viktoras\", \"Veitas\", role = \"ctb\"), person(\"Weicheng\", \"Zhu\", role = \"ctb\"), person(\"Wush\", \"Wu\", role = \"ctb\"), person(\"Zachary\", \"Foster\", role = \"ctb\"), person(\"Zhian N.\", \"Kamvar\", role = \"ctb\", comment = c(ORCID = \"0000-0003-1458-7108\")), person(given = \"Posit Software, PBC\", role = c(\"cph\", \"fnd\")) )", + "Description": "Provides a general-purpose tool for dynamic report generation in R using Literate Programming techniques.", + "Depends": [ + "R (>= 3.6.0)" + ], + "Imports": [ + "evaluate (>= 0.15)", + "highr (>= 0.11)", + "methods", + "tools", + "xfun (>= 0.52)", + "yaml (>= 2.1.19)" + ], + "Suggests": [ + "bslib", + "DBI (>= 0.4-1)", + "digest", + "formatR", + "gifski", + "gridSVG", + "htmlwidgets (>= 0.7)", + "jpeg", + "JuliaCall (>= 0.11.1)", + "magick", + "litedown", + "markdown (>= 1.3)", + "otel", + "otelsdk", + "png", + "ragg", + "reticulate (>= 1.4)", + "rgl (>= 0.95.1201)", + "rlang", + "rmarkdown", + "sass", + "showtext", + "styler (>= 1.2.0)", + "targets (>= 0.6.0)", + "testit", + "tibble", + "tikzDevice (>= 0.10)", + "tinytex (>= 0.56)", + "webshot", + "rstudioapi", + "svglite" + ], + "License": "GPL", + "URL": "https://yihui.org/knitr/", + "BugReports": "https://github.com/yihui/knitr/issues", + "Encoding": "UTF-8", + "VignetteBuilder": "litedown, knitr", + "SystemRequirements": "Package vignettes based on R Markdown v2 or reStructuredText require Pandoc (http://pandoc.org). The function rst2pdf() requires rst2pdf (https://github.com/rst2pdf/rst2pdf).", + "Collate": "'block.R' 'cache.R' 'citation.R' 'hooks-html.R' 'plot.R' 'utils.R' 'defaults.R' 'concordance.R' 'engine.R' 'highlight.R' 'themes.R' 'header.R' 'hooks-asciidoc.R' 'hooks-chunk.R' 'hooks-extra.R' 'hooks-latex.R' 'hooks-md.R' 'hooks-rst.R' 'hooks-textile.R' 'hooks.R' 'otel.R' 'output.R' 'package.R' 'pandoc.R' 'params.R' 'parser.R' 'pattern.R' 'rocco.R' 'spin.R' 'table.R' 'template.R' 'utils-conversion.R' 'utils-rd2html.R' 'utils-string.R' 'utils-sweave.R' 'utils-upload.R' 'utils-vignettes.R' 'zzz.R'", + "RoxygenNote": "7.3.3", + "NeedsCompilation": "no", + "Author": "Yihui Xie [aut, cre] (ORCID: , URL: https://yihui.org), Abhraneel Sarma [ctb], Adam Vogt [ctb], Alastair Andrew [ctb], Alex Zvoleff [ctb], Amar Al-Zubaidi [ctb], Andre Simon [ctb] (the CSS files under inst/themes/ were derived from the Highlight package http://www.andre-simon.de), Aron Atkins [ctb], Aaron Wolen [ctb], Ashley Manton [ctb], Atsushi Yasumoto [ctb] (ORCID: ), Ben Baumer [ctb], Brian Diggs [ctb], Brian Zhang [ctb], Bulat Yapparov [ctb], Cassio Pereira [ctb], Christophe Dervieux [ctb], David Hall [ctb], David Hugh-Jones [ctb], David Robinson [ctb], Doug Hemken [ctb], Duncan Murdoch [ctb], Elio Campitelli [ctb], Ellis Hughes [ctb], Emily Riederer [ctb], Fabian Hirschmann [ctb], Fitch Simeon [ctb], Forest Fang [ctb], Frank E Harrell Jr [ctb] (the Sweavel package at inst/misc/Sweavel.sty), Garrick Aden-Buie [ctb], Gregoire Detrez [ctb], Hadley Wickham [ctb], Hao Zhu [ctb], Heewon Jeon [ctb], Henrik Bengtsson [ctb], Hiroaki Yutani [ctb], Ian Lyttle [ctb], Hodges Daniel [ctb], Jacob Bien [ctb], Jake Burkhead [ctb], James Manton [ctb], Jared Lander [ctb], Jason Punyon [ctb], Javier Luraschi [ctb], Jeff Arnold [ctb], Jenny Bryan [ctb], Jeremy Ashkenas [ctb, cph] (the CSS file at inst/misc/docco-classic.css), Jeremy Stephens [ctb], Jim Hester [ctb], Joe Cheng [ctb], Johannes Ranke [ctb], John Honaker [ctb], John Muschelli [ctb], Jonathan Keane [ctb], JJ Allaire [ctb], Johan Toloe [ctb], Jonathan Sidi [ctb], Joseph Larmarange [ctb], Julien Barnier [ctb], Kaiyin Zhong [ctb], Kamil Slowikowski [ctb], Karl Forner [ctb], Kevin K. Smith [ctb], Kirill Mueller [ctb], Kohske Takahashi [ctb], Lorenz Walthert [ctb], Lucas Gallindo [ctb], Marius Hofert [ctb], Martin Modrák [ctb], Michael Chirico [ctb], Michael Friendly [ctb], Michal Bojanowski [ctb], Michel Kuhlmann [ctb], Miller Patrick [ctb], Nacho Caballero [ctb], Nick Salkowski [ctb], Niels Richard Hansen [ctb], Noam Ross [ctb], Obada Mahdi [ctb], Pavel N. Krivitsky [ctb] (ORCID: ), Pedro Faria [ctb], Qiang Li [ctb], Ramnath Vaidyanathan [ctb], Richard Cotton [ctb], Robert Krzyzanowski [ctb], Rodrigo Copetti [ctb], Romain Francois [ctb], Ruaridh Williamson [ctb], Sagiru Mati [ctb] (ORCID: ), Scott Kostyshak [ctb], Sebastian Meyer [ctb], Sietse Brouwer [ctb], Simon de Bernard [ctb], Sylvain Rousseau [ctb], Taiyun Wei [ctb], Thibaut Assus [ctb], Thibaut Lamadon [ctb], Thomas Leeper [ctb], Tim Mastny [ctb], Tom Torsney-Weir [ctb], Trevor Davis [ctb], Viktoras Veitas [ctb], Weicheng Zhu [ctb], Wush Wu [ctb], Zachary Foster [ctb], Zhian N. Kamvar [ctb] (ORCID: ), Posit Software, PBC [cph, fnd]", + "Maintainer": "Yihui Xie ", + "Repository": "CRAN" + }, + "labeling": { + "Package": "labeling", + "Version": "0.4.3", + "Source": "Repository", + "Type": "Package", + "Title": "Axis Labeling", + "Date": "2023-08-29", + "Author": "Justin Talbot,", + "Maintainer": "Nuno Sempere ", + "Description": "Functions which provide a range of axis labeling algorithms.", + "License": "MIT + file LICENSE | Unlimited", + "Collate": "'labeling.R'", + "NeedsCompilation": "no", + "Imports": [ + "stats", + "graphics" + ], + "Repository": "CRAN" + }, + "lattice": { + "Package": "lattice", + "Version": "0.22-9", + "Source": "Repository", + "Date": "2026-02-03", + "Priority": "recommended", + "Title": "Trellis Graphics for R", + "Authors@R": "c(person(\"Deepayan\", \"Sarkar\", role = c(\"aut\", \"cre\"), email = \"deepayan.sarkar@r-project.org\", comment = c(ORCID = \"0000-0003-4107-1553\")), person(\"Felix\", \"Andrews\", role = \"ctb\"), person(\"Kevin\", \"Wright\", role = \"ctb\", comment = \"documentation\"), person(\"Neil\", \"Klepeis\", role = \"ctb\"), person(\"Johan\", \"Larsson\", role = \"ctb\", comment = \"miscellaneous improvements\"), person(\"Zhijian (Jason)\", \"Wen\", role = \"cph\", comment = \"filled contour code\"), person(\"Paul\", \"Murrell\", role = \"ctb\", email = \"paul@stat.auckland.ac.nz\"), person(\"Stefan\", \"Eng\", role = \"ctb\", comment = \"violin plot improvements\"), person(\"Achim\", \"Zeileis\", role = \"ctb\", comment = \"modern colors\"), person(\"Alexandre\", \"Courtiol\", role = \"ctb\", comment = \"generics for larrows, lpolygon, lrect and lsegments\") )", + "Description": "A powerful and elegant high-level data visualization system inspired by Trellis graphics, with an emphasis on multivariate data. Lattice is sufficient for typical graphics needs, and is also flexible enough to handle most nonstandard requirements. See ?Lattice for an introduction.", + "Depends": [ + "R (>= 4.0.0)" + ], + "Suggests": [ + "KernSmooth", + "MASS", + "latticeExtra", + "colorspace" + ], + "Imports": [ + "grid", + "grDevices", + "graphics", + "stats", + "utils" + ], + "Enhances": [ + "chron", + "zoo" + ], + "LazyLoad": "yes", + "LazyData": "yes", + "License": "GPL (>= 2)", + "URL": "https://lattice.r-forge.r-project.org/", + "BugReports": "https://github.com/deepayan/lattice/issues", + "NeedsCompilation": "yes", + "Author": "Deepayan Sarkar [aut, cre] (ORCID: ), Felix Andrews [ctb], Kevin Wright [ctb] (documentation), Neil Klepeis [ctb], Johan Larsson [ctb] (miscellaneous improvements), Zhijian (Jason) Wen [cph] (filled contour code), Paul Murrell [ctb], Stefan Eng [ctb] (violin plot improvements), Achim Zeileis [ctb] (modern colors), Alexandre Courtiol [ctb] (generics for larrows, lpolygon, lrect and lsegments)", + "Maintainer": "Deepayan Sarkar ", + "Repository": "CRAN" + }, + "lazyeval": { + "Package": "lazyeval", + "Version": "0.2.3", + "Source": "Repository", + "Title": "Lazy (Non-Standard) Evaluation", + "Description": "An alternative approach to non-standard evaluation using formulas. Provides a full implementation of LISP style 'quasiquotation', making it easier to generate code with other code.", + "Authors@R": "c( person(\"Hadley\", \"Wickham\", ,\"hadley@rstudio.com\", c(\"aut\", \"cre\")), person(\"RStudio\", role = \"cph\") )", + "License": "GPL-3", + "Depends": [ + "R (>= 3.1.0)" + ], + "Imports": [ + "rlang" + ], + "Suggests": [ + "knitr", + "rmarkdown (>= 0.2.65)", + "testthat", + "covr" + ], + "VignetteBuilder": "knitr", + "RoxygenNote": "7.3.3", + "Config/build/compilation-database": "true", + "NeedsCompilation": "yes", + "Author": "Hadley Wickham [aut, cre], RStudio [cph]", + "Maintainer": "Hadley Wickham ", + "Repository": "RSPM", + "Encoding": "UTF-8" + }, + "leaflet": { + "Package": "leaflet", + "Version": "2.2.3", + "Source": "Repository", + "Type": "Package", + "Title": "Create Interactive Web Maps with the JavaScript 'Leaflet' Library", + "Authors@R": "c( person(\"Joe\", \"Cheng\", , \"joe@posit.co\", role = \"aut\"), person(\"Barret\", \"Schloerke\", , \"barret@posit.co\", role = \"aut\", comment = c(ORCID = \"0000-0001-9986-114X\")), person(\"Bhaskar\", \"Karambelkar\", role = \"aut\"), person(\"Yihui\", \"Xie\", role = \"aut\"), person(\"Garrick\", \"Aden-Buie\", , \"garrick@posit.co\", role = c(\"aut\", \"cre\"), comment = c(ORCID = \"0000-0002-7111-0077\")), person(\"Hadley\", \"Wickham\", role = \"ctb\"), person(\"Kenton\", \"Russell\", role = \"ctb\"), person(\"Kent\", \"Johnson\", role = \"ctb\"), person(\"Vladimir\", \"Agafonkin\", role = c(\"ctb\", \"cph\"), comment = \"Leaflet library\"), person(\"CloudMade\", role = \"cph\", comment = \"Leaflet library\"), person(\"Leaflet contributors\", role = \"ctb\", comment = \"Leaflet library\"), person(\"Brandon Copeland\", role = c(\"ctb\", \"cph\"), comment = \"leaflet-measure plugin\"), person(\"Joerg Dietrich\", role = c(\"ctb\", \"cph\"), comment = \"Leaflet.Terminator plugin\"), person(\"Benjamin Becquet\", role = c(\"ctb\", \"cph\"), comment = \"Leaflet.MagnifyingGlass plugin\"), person(\"Norkart AS\", role = c(\"ctb\", \"cph\"), comment = \"Leaflet.MiniMap plugin\"), person(\"L. Voogdt\", role = c(\"ctb\", \"cph\"), comment = \"Leaflet.awesome-markers plugin\"), person(\"Daniel Montague\", role = c(\"ctb\", \"cph\"), comment = \"Leaflet.EasyButton plugin\"), person(\"Kartena AB\", role = c(\"ctb\", \"cph\"), comment = \"Proj4Leaflet plugin\"), person(\"Robert Kajic\", role = c(\"ctb\", \"cph\"), comment = \"leaflet-locationfilter plugin\"), person(\"Mapbox\", role = c(\"ctb\", \"cph\"), comment = \"leaflet-omnivore plugin\"), person(\"Michael Bostock\", role = c(\"ctb\", \"cph\"), comment = \"topojson\"), person(\"Posit Software, PBC\", role = c(\"cph\", \"fnd\")) )", + "Description": "Create and customize interactive maps using the 'Leaflet' JavaScript library and the 'htmlwidgets' package. These maps can be used directly from the R console, from 'RStudio', in Shiny applications and R Markdown documents.", + "License": "MIT + file LICENSE", + "URL": "https://rstudio.github.io/leaflet/, https://github.com/rstudio/leaflet", + "BugReports": "https://github.com/rstudio/leaflet/issues", + "Depends": [ + "R (>= 3.5)" + ], + "Imports": [ + "crosstalk", + "htmltools", + "htmlwidgets (>= 1.5.4)", + "jquerylib", + "leaflet.providers (>= 2.0.0)", + "magrittr", + "methods", + "png", + "raster (>= 3.6.3)", + "RColorBrewer", + "rlang", + "scales (>= 1.0.0)", + "sf (>= 0.9-6)", + "stats", + "viridisLite", + "xfun" + ], + "Suggests": [ + "knitr", + "maps", + "purrr", + "R6", + "RJSONIO", + "rmarkdown", + "s2", + "shiny (>= 1.0.0)", + "sp", + "terra", + "testthat (>= 3.0.0)" + ], + "Config/Needs/website": "dplyr, ncdf4, rnaturalearth, tidyverse/tidytemplate", + "Config/testthat/edition": "3", + "Encoding": "UTF-8", + "LazyData": "true", + "RoxygenNote": "7.3.2", + "NeedsCompilation": "no", + "Author": "Joe Cheng [aut], Barret Schloerke [aut] (ORCID: ), Bhaskar Karambelkar [aut], Yihui Xie [aut], Garrick Aden-Buie [aut, cre] (ORCID: ), Hadley Wickham [ctb], Kenton Russell [ctb], Kent Johnson [ctb], Vladimir Agafonkin [ctb, cph] (Leaflet library), CloudMade [cph] (Leaflet library), Leaflet contributors [ctb] (Leaflet library), Brandon Copeland [ctb, cph] (leaflet-measure plugin), Joerg Dietrich [ctb, cph] (Leaflet.Terminator plugin), Benjamin Becquet [ctb, cph] (Leaflet.MagnifyingGlass plugin), Norkart AS [ctb, cph] (Leaflet.MiniMap plugin), L. Voogdt [ctb, cph] (Leaflet.awesome-markers plugin), Daniel Montague [ctb, cph] (Leaflet.EasyButton plugin), Kartena AB [ctb, cph] (Proj4Leaflet plugin), Robert Kajic [ctb, cph] (leaflet-locationfilter plugin), Mapbox [ctb, cph] (leaflet-omnivore plugin), Michael Bostock [ctb, cph] (topojson), Posit Software, PBC [cph, fnd]", + "Maintainer": "Garrick Aden-Buie ", + "Repository": "RSPM" + }, + "leaflet.providers": { + "Package": "leaflet.providers", + "Version": "3.0.0", + "Source": "Repository", + "Type": "Package", + "Title": "Leaflet Providers", + "Authors@R": "c( person(\"Leslie\", \"Huang\", , \"lesliehuang@nyu.edu\", role = \"aut\"), person(\"Barret\", \"Schloerke\", , \"barret@posit.co\", role = c(\"ctb\", \"cre\"), comment = c(ORCID = \"0000-0001-9986-114X\")), person(\"Leaflet Providers contributors\", role = c(\"ctb\", \"cph\"), comment = \"Leaflet Providers plugin\"), person(\"Posit Software, PBC\", role = c(\"cph\", \"fnd\"), comment = c(ROR = \"https://ror.org/03wc8by49\")) )", + "Description": "Contains third-party map tile provider information from 'Leaflet.js', , to be used with the 'leaflet' R package. 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Book and website projects of multiple input documents are also supported.", + "Depends": [ + "R (>= 3.2.0)" + ], + "Imports": [ + "utils", + "commonmark (>= 2.0.0)", + "xfun (>= 0.55)" + ], + "Suggests": [ + "rbibutils", + "rstudioapi", + "tinytex" + ], + "License": "MIT + file LICENSE", + "URL": "https://github.com/yihui/litedown", + "BugReports": "https://github.com/yihui/litedown/issues", + "VignetteBuilder": "litedown", + "RoxygenNote": "7.3.3", + "Encoding": "UTF-8", + "NeedsCompilation": "no", + "Author": "Yihui Xie [aut, cre] (ORCID: , URL: https://yihui.org), Tim Taylor [ctb] (ORCID: )", + "Maintainer": "Yihui Xie ", + "Repository": "CRAN" + }, + "lubridate": { + "Package": "lubridate", + "Version": "1.9.5", + "Source": "Repository", + "Type": "Package", + "Title": "Make Dealing with Dates a Little Easier", + "Authors@R": "c( person(\"Vitalie\", \"Spinu\", , \"spinuvit@gmail.com\", role = c(\"aut\", \"cre\")), person(\"Garrett\", \"Grolemund\", role = \"aut\"), person(\"Hadley\", \"Wickham\", role = \"aut\"), person(\"Davis\", \"Vaughan\", role = \"ctb\"), person(\"Ian\", \"Lyttle\", role = \"ctb\"), person(\"Imanuel\", \"Costigan\", role = \"ctb\"), person(\"Jason\", \"Law\", role = \"ctb\"), person(\"Doug\", \"Mitarotonda\", role = \"ctb\"), person(\"Joseph\", \"Larmarange\", role = \"ctb\"), person(\"Jonathan\", \"Boiser\", role = \"ctb\"), person(\"Chel Hee\", \"Lee\", role = \"ctb\") )", + "Maintainer": "Vitalie Spinu ", + "Description": "Functions to work with date-times and time-spans: fast and user friendly parsing of date-time data, extraction and updating of components of a date-time (years, months, days, hours, minutes, and seconds), algebraic manipulation on date-time and time-span objects. 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See for more information. The original Mapzen has gone out of business, but 'rmapzen' can be set up to work with any provider who implements the Mapzen API.", + "License": "MIT + file LICENSE", + "LazyData": "TRUE", + "Depends": [ + "R (>= 2.10)" + ], + "Imports": [ + "tibble", + "httr", + "jsonlite", + "ISOcodes", + "dplyr", + "assertthat", + "geojsonio", + "tidyr", + "purrr", + "digest", + "sf (>= 1.0.0)", + "utils" + ], + "RoxygenNote": "7.2.3", + "Suggests": [ + "testthat", + "covr", + "knitr", + "rmarkdown", + "rlang" + ], + "URL": "https://tarakc02.github.io/rmapzen/", + "BugReports": "https://github.com/tarakc02/rmapzen/issues", + "VignetteBuilder": "knitr", + "Encoding": "UTF-8", + "NeedsCompilation": "no", + "Author": "Tarak Shah [aut, cre], Daniel Possenriede [ctb]", + "Repository": "RSPM" + }, + "rmarkdown": { + "Package": "rmarkdown", + "Version": "2.31", + "Source": "Repository", + "Type": "Package", + "Title": "Dynamic Documents for R", + "Authors@R": "c( person(\"JJ\", \"Allaire\", , \"jj@posit.co\", role = \"aut\"), person(\"Yihui\", \"Xie\", , \"xie@yihui.name\", role = c(\"aut\", \"cre\"), comment = c(ORCID = \"0000-0003-0645-5666\")), person(\"Christophe\", \"Dervieux\", , \"cderv@posit.co\", role = \"aut\", comment = c(ORCID = \"0000-0003-4474-2498\")), person(\"Jonathan\", \"McPherson\", , \"jonathan@posit.co\", role = \"aut\"), person(\"Javier\", \"Luraschi\", role = \"aut\"), person(\"Kevin\", \"Ushey\", , \"kevin@posit.co\", role = \"aut\"), person(\"Aron\", \"Atkins\", , \"aron@posit.co\", role = \"aut\"), person(\"Hadley\", \"Wickham\", , \"hadley@posit.co\", role = \"aut\"), person(\"Joe\", \"Cheng\", , \"joe@posit.co\", role = \"aut\"), person(\"Winston\", \"Chang\", , \"winston@posit.co\", role = \"aut\"), person(\"Richard\", \"Iannone\", , \"rich@posit.co\", role = \"aut\", comment = c(ORCID = \"0000-0003-3925-190X\")), person(\"Andrew\", \"Dunning\", role = \"ctb\", comment = c(ORCID = \"0000-0003-0464-5036\")), person(\"Atsushi\", \"Yasumoto\", role = c(\"ctb\", \"cph\"), comment = c(ORCID = \"0000-0002-8335-495X\", cph = \"Number sections Lua filter\")), person(\"Barret\", \"Schloerke\", role = \"ctb\"), person(\"Carson\", \"Sievert\", role = \"ctb\", comment = c(ORCID = \"0000-0002-4958-2844\")), person(\"Devon\", \"Ryan\", , \"dpryan79@gmail.com\", role = \"ctb\", comment = c(ORCID = \"0000-0002-8549-0971\")), person(\"Frederik\", \"Aust\", , \"frederik.aust@uni-koeln.de\", role = \"ctb\", comment = c(ORCID = \"0000-0003-4900-788X\")), person(\"Jeff\", \"Allen\", , \"jeff@posit.co\", role = \"ctb\"), person(\"JooYoung\", \"Seo\", role = \"ctb\", comment = c(ORCID = \"0000-0002-4064-6012\")), person(\"Malcolm\", \"Barrett\", role = \"ctb\"), person(\"Rob\", \"Hyndman\", , \"Rob.Hyndman@monash.edu\", role = \"ctb\"), person(\"Romain\", \"Lesur\", role = \"ctb\"), person(\"Roy\", \"Storey\", role = \"ctb\"), person(\"Ruben\", \"Arslan\", , \"ruben.arslan@uni-goettingen.de\", role = \"ctb\"), person(\"Sergio\", \"Oller\", role = \"ctb\"), person(given = \"Posit Software, PBC\", role = c(\"cph\", \"fnd\")), person(, \"jQuery UI contributors\", role = c(\"ctb\", \"cph\"), comment = \"jQuery UI library; 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person(\"Mifsud\", \"Michael\", role = c(\"ctb\", \"cph\"), comment = \"LibSass library\"), person(\"Hampton\", \"Catlin\", role = c(\"ctb\", \"cph\"), comment = \"LibSass library\"), person(\"Natalie\", \"Weizenbaum\", role = c(\"ctb\", \"cph\"), comment = \"LibSass library\"), person(\"Chris\", \"Eppstein\", role = c(\"ctb\", \"cph\"), comment = \"LibSass library\"), person(\"Adams\", \"Joseph\", role = c(\"ctb\", \"cph\"), comment = \"json.cpp\"), person(\"Trifunovic\", \"Nemanja\", role = c(\"ctb\", \"cph\"), comment = \"utf8.h\") )", + "License": "MIT + file LICENSE", + "URL": "https://rstudio.github.io/sass/, https://github.com/rstudio/sass", + "BugReports": "https://github.com/rstudio/sass/issues", + "Encoding": "UTF-8", + "RoxygenNote": "7.3.2", + "SystemRequirements": "GNU make", + "Imports": [ + "fs (>= 1.2.4)", + "rlang (>= 0.4.10)", + "htmltools (>= 0.5.1)", + "R6", + "rappdirs" + ], + "Suggests": [ + "testthat", + "knitr", + "rmarkdown", + "withr", + "shiny", + "curl" + ], + "VignetteBuilder": "knitr", + "Config/testthat/edition": "3", + "NeedsCompilation": "yes", + "Author": "Joe Cheng [aut], Timothy Mastny [aut], Richard Iannone [aut] (), Barret Schloerke [aut] (), Carson Sievert [aut, cre] (), Christophe Dervieux [ctb] (), RStudio [cph, fnd], Sass Open Source Foundation [ctb, cph] (LibSass library), Greter Marcel [ctb, cph] (LibSass library), Mifsud Michael [ctb, cph] (LibSass library), Hampton Catlin [ctb, cph] (LibSass library), Natalie Weizenbaum [ctb, cph] (LibSass library), Chris Eppstein [ctb, cph] (LibSass library), Adams Joseph [ctb, cph] (json.cpp), Trifunovic Nemanja [ctb, cph] (utf8.h)", + "Maintainer": "Carson Sievert ", + "Repository": "CRAN" + }, + "scales": { + "Package": "scales", + "Version": "1.4.0", + "Source": "Repository", + "Title": "Scale Functions for Visualization", + "Authors@R": "c( person(\"Hadley\", \"Wickham\", , \"hadley@posit.co\", role = \"aut\"), person(\"Thomas Lin\", \"Pedersen\", , \"thomas.pedersen@posit.co\", 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equivalent XPath expression. This allows us to use CSS selectors when working with the XML package as it can only evaluate XPath expressions. Also provided are convenience functions useful for using CSS selectors on XML nodes. This package is a port of the Python package 'cssselect' ().", + "NeedsCompilation": "no", + "Author": "Simon Potter [aut, trl, cre], Simon Sapin [aut], Ian Bicking [aut]", + "Maintainer": "Simon Potter ", + "Repository": "P3M" + }, + "sf": { + "Package": "sf", + "Version": "1.1-1", + "Source": "Repository", + "Title": "Simple Features for R", + "Authors@R": "c(person(given = \"Edzer\", family = \"Pebesma\", role = c(\"aut\", \"cre\"), email = \"edzer.pebesma@uni-muenster.de\", comment = c(ORCID = \"0000-0001-8049-7069\")), person(given = \"Roger\", family = \"Bivand\", role = \"ctb\", comment = c(ORCID = \"0000-0003-2392-6140\")), person(given = \"Etienne\", family = \"Racine\", role = \"ctb\"), person(given = \"Michael\", family = \"Sumner\", role = \"ctb\"), person(given = \"Ian\", family = \"Cook\", role = \"ctb\"), person(given = \"Tim\", family = \"Keitt\", role = \"ctb\"), person(given = \"Robin\", family = \"Lovelace\", role = \"ctb\"), person(given = \"Hadley\", family = \"Wickham\", role = \"ctb\"), person(given = \"Jeroen\", family = \"Ooms\", role = \"ctb\", comment = c(ORCID = \"0000-0002-4035-0289\")), person(given = \"Kirill\", family = \"M\\u00fcller\", role = \"ctb\"), person(given = \"Thomas Lin\", family = \"Pedersen\", role = \"ctb\"), person(given = \"Dan\", family = \"Baston\", role = \"ctb\"), person(given = \"Dewey\", family = \"Dunnington\", role = \"ctb\", comment = c(ORCID = \"0000-0002-9415-4582\")), person(given = \"Alexandre\", family = \"Courtiol\", role = \"ctb\", comment = c(ORCID = \"0000-0003-0637-2959\")) )", + "Description": "Support for simple feature access, a standardized way to encode and analyze spatial vector data. Binds to 'GDAL' for reading and writing data, to 'GEOS' for geometrical operations, and to 'PROJ' for projection conversions and datum transformations. Uses by default the 's2' package for geometry operations on geodetic (long/lat degree) coordinates.", + "License": "GPL-2 | MIT + file LICENSE", + "URL": "https://r-spatial.github.io/sf/, https://github.com/r-spatial/sf", + "BugReports": "https://github.com/r-spatial/sf/issues", + "Depends": [ + "methods", + "R (>= 4.1.0)" + ], + "Imports": [ + "classInt (>= 0.4-1)", + "DBI (>= 0.8)", + "graphics", + "grDevices", + "grid", + "s2 (>= 1.1.0)", + "stats", + "tools", + "units (>= 0.7-0)", + "utils" + ], + "Suggests": [ + "blob", + "nanoarrow", + "covr", + "dplyr (>= 1.0.0)", + "ggplot2", + "knitr", + "lwgeom (>= 0.2-14)", + "maps", + "mapview", + "Matrix", + "microbenchmark", + "odbc", + "pbapply", + "pillar", + "pool", + "raster", + "rlang", + "rmarkdown", + "RPostgres (>= 1.1.0)", + "RPostgreSQL", + "RSQLite", + "sp (>= 1.2-4)", + "spatstat (>= 2.0-1)", + "spatstat.geom", + "spatstat.random", + "spatstat.linnet", + "spatstat.utils", + "stars (>= 0.6-0)", + "terra", + "testthat (>= 3.0.0)", + "tibble (>= 1.4.1)", + "tidyr (>= 1.2.0)", + "tidyselect (>= 1.0.0)", + "tmap (>= 2.0)", + "vctrs", + "wk (>= 0.9.0)" + ], + "LinkingTo": [ + "Rcpp" + ], + "VignetteBuilder": "knitr", + "Encoding": "UTF-8", + "Config/testthat/edition": "2", + "Config/needs/coverage": "XML", + "SystemRequirements": "GDAL (>= 2.0.1), GEOS (>= 3.4.0), PROJ (>= 4.8.0), sqlite3", + "Collate": "'RcppExports.R' 'init.R' 'import-standalone-s3-register.R' 'crs.R' 'bbox.R' 'read.R' 'db.R' 'sfc.R' 'sfg.R' 'sf.R' 'bind.R' 'wkb.R' 'wkt.R' 'plot.R' 'geom-measures.R' 'geom-predicates.R' 'geom-transformers.R' 'transform.R' 'proj.R' 'sp.R' 'grid.R' 'arith.R' 'tidyverse.R' 'tidyverse-vctrs.R' 'cast_sfg.R' 'cast_sfc.R' 'graticule.R' 'datasets.R' 'aggregate.R' 'agr.R' 'maps.R' 'join.R' 'sample.R' 'valid.R' 'collection_extract.R' 'jitter.R' 'sgbp.R' 'spatstat.R' 'stars.R' 'crop.R' 'gdal_utils.R' 'nearest.R' 'normalize.R' 'sf-package.R' 'defunct.R' 'z_range.R' 'm_range.R' 'shift_longitude.R' 'make_grid.R' 's2.R' 'terra.R' 'geos-overlayng.R' 'break_antimeridian.R'", + "Config/roxygen2/version": "8.0.0", + "NeedsCompilation": "yes", + "Author": "Edzer Pebesma [aut, cre] (ORCID: ), Roger Bivand [ctb] (ORCID: ), Etienne Racine [ctb], Michael Sumner [ctb], Ian Cook [ctb], Tim Keitt [ctb], Robin Lovelace [ctb], Hadley Wickham [ctb], Jeroen Ooms [ctb] (ORCID: ), Kirill Müller [ctb], Thomas Lin Pedersen [ctb], Dan Baston [ctb], Dewey Dunnington [ctb] (ORCID: ), Alexandre Courtiol [ctb] (ORCID: )", + "Maintainer": "Edzer Pebesma ", + "Repository": "P3M" + }, + "sfheaders": { + "Package": "sfheaders", + "Version": "0.4.5", + "Source": "Repository", + "Type": "Package", + "Title": "Converts Between R Objects and Simple Feature Objects", + "Date": "2025-11-24", + "Authors@R": "c( person(\"David\", \"Cooley\", ,\"david.cooley.au@gmail.com\", role = c(\"aut\", \"cre\")), person(given = \"Michael\", family = \"Sumner\", role = \"ctb\") )", + "Description": "Converts between R and Simple Feature 'sf' objects, without depending on the Simple Feature library. Conversion functions are available at both the R level, and through 'Rcpp'.", + "License": "MIT + file LICENSE", + "URL": "https://dcooley.github.io/sfheaders/", + "BugReports": "https://github.com/dcooley/sfheaders/issues", + "Encoding": "UTF-8", + "RoxygenNote": "7.3.2", + "Depends": [ + "R (>= 3.0.2)" + ], + "LinkingTo": [ + "geometries (>= 0.2.5)", + "Rcpp" + ], + "Imports": [ + "Rcpp (>= 1.1.0)" + ], + "Suggests": [ + "covr", + "knitr", + "testthat" + ], + "NeedsCompilation": "yes", + "Author": "David Cooley [aut, cre], Michael Sumner [ctb]", + "Maintainer": "David Cooley ", + "Repository": "RSPM" + }, + "slippymath": { + "Package": "slippymath", + "Version": "0.3.1", + "Source": "Repository", + "Title": "Slippy Map Tile Tools", + "Authors@R": "c( person(\"Miles\", \"McBain\", email = \"miles.mcbain@gmail.com\", role = c(\"aut\", \"cre\"), comment = c(ORCID = \"0000-0003-2865-2548\")), person(\"Michael\",\"Sumner\", email = \"mdsumner@gmail.com\", role = c(\"aut\")))", + "Description": "Provides functions for performing common tasks when working with slippy map tile service APIs e.g. Google maps, Open Street Map, Mapbox, Stamen, among others. Functionality includes converting from latitude and longitude to tile numbers, determining tile bounding boxes, and compositing tiles to a georeferenced raster image.", + "Depends": [ + "R (>= 3.5.0)" + ], + "License": "MIT + file LICENSE", + "URL": "https://www.github.com/milesmcbain/slippymath", + "BugReports": "https://www.github.com/milesmcbain/slippymath/issues", + "Encoding": "UTF-8", + "LazyData": "true", + "Imports": [ + "raster", + "purrr", + "stats", + "png" + ], + "Suggests": [ + "testthat", + "knitr", + "rmarkdown" + ], + "RoxygenNote": "6.1.1", + "VignetteBuilder": "knitr", + "NeedsCompilation": "no", + "Author": "Miles McBain [aut, cre] (), Michael Sumner [aut]", + "Maintainer": "Miles McBain ", + "Repository": "RSPM" + }, + "sp": { + "Package": "sp", + "Version": "2.2-1", + "Source": "Repository", + "Title": "Classes and Methods for Spatial Data", + "Authors@R": "c(person(\"Edzer\", \"Pebesma\", role = c(\"aut\", \"cre\"), email = \"edzer.pebesma@uni-muenster.de\"), person(\"Roger\", \"Bivand\", role = \"aut\", email = \"Roger.Bivand@nhh.no\"), person(\"Barry\", \"Rowlingson\", role = \"ctb\"), person(\"Virgilio\", \"Gomez-Rubio\", role = \"ctb\"), person(\"Robert\", \"Hijmans\", role = \"ctb\"), person(\"Michael\", \"Sumner\", role = \"ctb\"), person(\"Don\", \"MacQueen\", role = \"ctb\"), person(\"Jim\", \"Lemon\", role = \"ctb\"), person(\"Finn\", \"Lindgren\", role = \"ctb\"), person(\"Josh\", \"O'Brien\", role = \"ctb\"), person(\"Joseph\", \"O'Rourke\", role = \"ctb\"), person(\"Patrick\", \"Hausmann\", role = \"ctb\"), person(\"Sebastian\", \"Meyer\", role = \"ctb\"))", + "Depends": [ + "R (>= 3.5.0)", + "methods" + ], + "Imports": [ + "utils", + "stats", + "graphics", + "grDevices", + "lattice", + "grid" + ], + "Suggests": [ + "RColorBrewer", + "gstat", + "deldir", + "knitr", + "maps", + "mapview", + "rmarkdown", + "sf", + "terra", + "raster" + ], + "Description": "Classes and methods for spatial data; the classes document where the spatial location information resides, for 2D or 3D data. Utility functions are provided, e.g. for plotting data as maps, spatial selection, as well as methods for retrieving coordinates, for subsetting, print, summary, etc. From this version, 'rgdal', 'maptools', and 'rgeos' are no longer used at all, see for details.", + "License": "GPL (>= 2)", + "URL": "https://github.com/edzer/sp/ https://edzer.github.io/sp/", + "BugReports": "https://github.com/edzer/sp/issues", + "Collate": "bpy.colors.R AAA.R Class-CRS.R CRS-methods.R Class-Spatial.R Spatial-methods.R projected.R Class-SpatialPoints.R SpatialPoints-methods.R Class-SpatialPointsDataFrame.R SpatialPointsDataFrame-methods.R Class-SpatialMultiPoints.R SpatialMultiPoints-methods.R Class-SpatialMultiPointsDataFrame.R SpatialMultiPointsDataFrame-methods.R Class-GridTopology.R Class-SpatialGrid.R Class-SpatialGridDataFrame.R Class-SpatialLines.R SpatialLines-methods.R Class-SpatialLinesDataFrame.R SpatialLinesDataFrame-methods.R Class-SpatialPolygons.R Class-SpatialPolygonsDataFrame.R SpatialPolygons-methods.R SpatialPolygonsDataFrame-methods.R GridTopology-methods.R SpatialGrid-methods.R SpatialGridDataFrame-methods.R SpatialPolygons-internals.R point.in.polygon.R SpatialPolygons-displayMethods.R zerodist.R image.R stack.R bubble.R mapasp.R select.spatial.R gridded.R asciigrid.R spplot.R over.R spsample.R recenter.R dms.R gridlines.R spdists.R rbind.R flipSGDF.R chfids.R loadmeuse.R compassRose.R surfaceArea.R spOptions.R subset.R disaggregate.R sp_spat1.R merge.R aggregate.R elide.R sp2Mondrian.R", + "VignetteBuilder": "knitr", + "NeedsCompilation": "yes", + "Author": "Edzer Pebesma [aut, cre], Roger Bivand [aut], Barry Rowlingson [ctb], Virgilio Gomez-Rubio [ctb], Robert Hijmans [ctb], Michael Sumner [ctb], Don MacQueen [ctb], Jim Lemon [ctb], Finn Lindgren [ctb], Josh O'Brien [ctb], Joseph O'Rourke [ctb], Patrick Hausmann [ctb], Sebastian Meyer [ctb]", + "Maintainer": "Edzer Pebesma ", + "Repository": "RSPM", + "Encoding": "UTF-8" + }, + "stringi": { + "Package": "stringi", + "Version": "1.8.7", + "Source": "Repository", + "Date": "2025-03-27", + "Title": "Fast and Portable Character String Processing Facilities", + "Description": "A collection of character string/text/natural language processing tools for pattern searching (e.g., with 'Java'-like regular expressions or the 'Unicode' collation algorithm), random string generation, case mapping, string transliteration, concatenation, sorting, padding, wrapping, Unicode normalisation, date-time formatting and parsing, and many more. They are fast, consistent, convenient, and - thanks to 'ICU' (International Components for Unicode) - portable across all locales and platforms. Documentation about 'stringi' is provided via its website at and the paper by Gagolewski (2022, ).", + "URL": "https://stringi.gagolewski.com/, https://github.com/gagolews/stringi, https://icu.unicode.org/", + "BugReports": "https://github.com/gagolews/stringi/issues", + "SystemRequirements": "ICU4C (>= 61, optional)", + "Type": "Package", + "Depends": [ + "R (>= 3.4)" + ], + "Imports": [ + "tools", + "utils", + "stats" + ], + "Biarch": "TRUE", + "License": "file LICENSE", + "Authors@R": "c(person(given = \"Marek\", family = \"Gagolewski\", role = c(\"aut\", \"cre\", \"cph\"), email = \"marek@gagolewski.com\", comment = c(ORCID = \"0000-0003-0637-6028\")), person(given = \"Bartek\", family = \"Tartanus\", role = \"ctb\"), person(\"Unicode, Inc. and others\", role=\"ctb\", comment = \"ICU4C source code, Unicode Character Database\") )", + "RoxygenNote": "7.3.2", + "Encoding": "UTF-8", + "NeedsCompilation": "yes", + "Author": "Marek Gagolewski [aut, cre, cph] (), Bartek Tartanus [ctb], Unicode, Inc. and others [ctb] (ICU4C source code, Unicode Character Database)", + "Maintainer": "Marek Gagolewski ", + "License_is_FOSS": "yes", + "Repository": "CRAN" + }, + "stringr": { + "Package": "stringr", + "Version": "1.6.0", + "Source": "Repository", + "Title": "Simple, Consistent Wrappers for Common String Operations", + "Authors@R": "c( person(\"Hadley\", \"Wickham\", , \"hadley@posit.co\", role = c(\"aut\", \"cre\", \"cph\")), person(\"Posit Software, PBC\", role = c(\"cph\", \"fnd\")) )", + "Description": "A consistent, simple and easy to use set of wrappers around the fantastic 'stringi' package. All function and argument names (and positions) are consistent, all functions deal with \"NA\"'s and zero length vectors in the same way, and the output from one function is easy to feed into the input of another.", + "License": "MIT + file LICENSE", + "URL": "https://stringr.tidyverse.org, https://github.com/tidyverse/stringr", + "BugReports": "https://github.com/tidyverse/stringr/issues", + "Depends": [ + "R (>= 4.1.0)" + ], + "Imports": [ + "cli", + "glue (>= 1.6.1)", + "lifecycle (>= 1.0.3)", + "magrittr", + "rlang (>= 1.0.0)", + "stringi (>= 1.5.3)", + "vctrs (>= 0.4.0)" + ], + "Suggests": [ + "covr", + "dplyr", + "gt", + "htmltools", + "htmlwidgets", + "knitr", + "rmarkdown", + "testthat (>= 3.0.0)", + "tibble" + ], + "VignetteBuilder": "knitr", + "Config/Needs/website": "tidyverse/tidytemplate", + "Config/potools/style": "explicit", + "Config/testthat/edition": "3", + "Encoding": "UTF-8", + "LazyData": "true", + "RoxygenNote": "7.3.3", + "NeedsCompilation": "no", + "Author": "Hadley Wickham [aut, cre, cph], Posit Software, PBC [cph, fnd]", + "Maintainer": "Hadley Wickham ", + "Repository": "CRAN" + }, + "sys": { + "Package": "sys", + "Version": "3.4.3", + "Source": "Repository", + "Type": "Package", + "Title": "Powerful and Reliable Tools for Running System Commands in R", + "Authors@R": "c(person(\"Jeroen\", \"Ooms\", role = c(\"aut\", \"cre\"), email = \"jeroenooms@gmail.com\", comment = c(ORCID = \"0000-0002-4035-0289\")), person(\"Gábor\", \"Csárdi\", , \"csardi.gabor@gmail.com\", role = \"ctb\"))", + "Description": "Drop-in replacements for the base system2() function with fine control and consistent behavior across platforms. Supports clean interruption, timeout, background tasks, and streaming STDIN / STDOUT / STDERR over binary or text connections. Arguments on Windows automatically get encoded and quoted to work on different locales.", + "License": "MIT + file LICENSE", + "URL": "https://jeroen.r-universe.dev/sys", + "BugReports": "https://github.com/jeroen/sys/issues", + "Encoding": "UTF-8", + "RoxygenNote": "7.1.1", + "Suggests": [ + "unix (>= 1.4)", + "spelling", + "testthat" + ], + "Language": "en-US", + "NeedsCompilation": "yes", + "Author": "Jeroen Ooms [aut, cre] (), Gábor Csárdi [ctb]", + "Maintainer": "Jeroen Ooms ", + "Repository": "CRAN" + }, + "systemfonts": { + "Package": "systemfonts", + "Version": "1.3.2", + "Source": "Repository", + "Type": "Package", + "Title": "System Native Font Finding", + "Authors@R": "c( person(\"Thomas Lin\", \"Pedersen\", , \"thomas.pedersen@posit.co\", role = c(\"aut\", \"cre\"), comment = c(ORCID = \"0000-0002-5147-4711\")), person(\"Jeroen\", \"Ooms\", , \"jeroen@berkeley.edu\", role = \"aut\", comment = c(ORCID = \"0000-0002-4035-0289\")), person(\"Devon\", \"Govett\", role = \"aut\", comment = \"Author of font-manager\"), person(\"Posit Software, PBC\", role = c(\"cph\", \"fnd\"), comment = c(ROR = \"03wc8by49\")) )", + "Description": "Provides system native access to the font catalogue. As font handling varies between systems it is difficult to correctly locate installed fonts across different operating systems. The 'systemfonts' package provides bindings to the native libraries on Windows, macOS and Linux for finding font files that can then be used further by e.g. graphic devices. The main use is intended to be from compiled code but 'systemfonts' also provides access from R.", + "License": "MIT + file LICENSE", + "URL": "https://github.com/r-lib/systemfonts, https://systemfonts.r-lib.org", + "BugReports": "https://github.com/r-lib/systemfonts/issues", + "Depends": [ + "R (>= 3.2.0)" + ], + "Imports": [ + "base64enc", + "grid", + "jsonlite", + "lifecycle", + "tools", + "utils" + ], + "Suggests": [ + "covr", + "farver", + "ggplot2", + "graphics", + "knitr", + "ragg", + "rmarkdown", + "svglite", + "testthat (>= 2.1.0)" + ], + "LinkingTo": [ + "cpp11 (>= 0.2.1)" + ], + "VignetteBuilder": "knitr", + "Config/build/compilation-database": "true", + "Config/Needs/website": "tidyverse/tidytemplate", + "Config/usethis/last-upkeep": "2025-04-23", + "Encoding": "UTF-8", + "RoxygenNote": "7.3.2", + "SystemRequirements": "fontconfig, freetype2", + "NeedsCompilation": "yes", + "Author": "Thomas Lin Pedersen [aut, cre] (ORCID: ), Jeroen Ooms [aut] (ORCID: ), Devon Govett [aut] (Author of font-manager), Posit Software, PBC [cph, fnd] (ROR: )", + "Maintainer": "Thomas Lin Pedersen ", + "Repository": "CRAN" + }, + "terra": { + "Package": "terra", + "Version": "1.9-34", + "Source": "Repository", + "Type": "Package", + "Title": "Spatial Data Analysis", + "Date": "2026-06-18", + "Depends": [ + "R (>= 3.5.0)", + "methods" + ], + "Suggests": [ + "parallel", + "tinytest", + "ncdf4", + "sf (>= 0.9-8)", + "igraph", + "deldir", + "XML", + "leaflet (>= 2.2.1)", + "htmlwidgets", + "future", + "future.apply" + ], + "LinkingTo": [ + "Rcpp" + ], + "Imports": [ + "Rcpp (>= 1.0-10)" + ], + "SystemRequirements": "C++17, GDAL (>= 2.2.3), GEOS (>= 3.4.0), PROJ (>= 4.9.3), TBB, sqlite3", + "Encoding": "UTF-8", + "Language": "en-US", + "Maintainer": "Robert J. Hijmans ", + "Description": "Methods for spatial data analysis with vector (points, lines, polygons) and raster (grid) data. Methods for vector data include geometric operations such as intersect and buffer. Raster methods include local, focal, global, zonal and geometric operations. The predict and interpolate methods facilitate the use of regression type (interpolation, machine learning) models for spatial prediction, including with satellite remote sensing data. Processing of very large files is supported. See the manual and tutorials on to get started.", + "License": "GPL (>= 3)", + "URL": "https://rspatial.org/, https://rspatial.github.io/terra/", + "BugReports": "https://github.com/rspatial/terra/issues", + "LazyLoad": "yes", + "Authors@R": "c( person(\"Robert J.\", \"Hijmans\", role=c(\"cre\", \"aut\"), email=\"r.hijmans@gmail.com\", comment=c(ORCID=\"0000-0001-5872-2872\")),\t\t\t person(\"Andrew\", \"Brown\", role=\"aut\", comment=c(ORCID=\"0000-0002-4565-533X\")), person(\"Márcia\", \"Barbosa\", role=\"aut\", comment=c(ORCID=\"0000-0001-8972-7713\")), person(\"Krzysztof\", \"Dyba\", role=\"ctb\", comment=c(ORCID=\"0000-0002-8614-3816\")), person(\"Roger\", \"Bivand\", role=\"ctb\", comment=c(ORCID=\"0000-0003-2392-6140\")), person(\"Michael\", \"Chirico\", role=\"ctb\", comment=c(ORCID=\"0000-0003-0787-087X\")), person(\"Emanuele\", \"Cordano\", role=\"ctb\",comment=c(ORCID=\"0000-0002-3508-5898\")), person(\"Edzer\", \"Pebesma\", role=\"ctb\", comment=c(ORCID=\"0000-0001-8049-7069\")), person(\"Barry\", \"Rowlingson\", role=\"ctb\", comment=c(ORCID=\"0000-0002-8586-6625\")), person(\"Michael D.\", \"Sumner\", role=\"ctb\", comment=c(ORCID=\"0000-0002-2471-7511\")))", + "NeedsCompilation": "yes", + "Author": "Robert J. Hijmans [cre, aut] (ORCID: ), Andrew Brown [aut] (ORCID: ), Márcia Barbosa [aut] (ORCID: ), Krzysztof Dyba [ctb] (ORCID: ), Roger Bivand [ctb] (ORCID: ), Michael Chirico [ctb] (ORCID: ), Emanuele Cordano [ctb] (ORCID: ), Edzer Pebesma [ctb] (ORCID: ), Barry Rowlingson [ctb] (ORCID: ), Michael D. Sumner [ctb] (ORCID: )", + "Repository": "RSPM" + }, + "textshaping": { + "Package": "textshaping", + "Version": "1.0.5", + "Source": "Repository", + "Title": "Bindings to the 'HarfBuzz' and 'Fribidi' Libraries for Text Shaping", + "Authors@R": "c( person(\"Thomas Lin\", \"Pedersen\", , \"thomas.pedersen@posit.co\", role = c(\"cre\", \"aut\"), comment = c(ORCID = \"0000-0002-5147-4711\")), person(\"Posit Software, PBC\", role = c(\"cph\", \"fnd\"), comment = c(ROR = \"03wc8by49\")) )", + "Description": "Provides access to the text shaping functionality in the 'HarfBuzz' library and the bidirectional algorithm in the 'Fribidi' library. 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Perform validation of the data structure against the specification. Analyze the headways and frequencies at routes and stops. Create maps and perform spatial analysis on the routes and stops. 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Well-known binary is compact and fast to parse; well-known text is human-readable and is useful for writing tests. These formats are useful in R only if the information they contain can be accessed in R, for which high-performance functions are provided here.", + "License": "MIT + file LICENSE", + "Encoding": "UTF-8", + "RoxygenNote": "7.3.2", + "Suggests": [ + "testthat (>= 3.0.0)", + "vctrs (>= 0.3.0)", + "sf", + "tibble", + "readr" + ], + "URL": "https://paleolimbot.github.io/wk/, https://github.com/paleolimbot/wk", + "BugReports": "https://github.com/paleolimbot/wk/issues", + "Config/testthat/edition": "3", + "Depends": [ + "R (>= 2.10)" + ], + "LazyData": "true", + "NeedsCompilation": "yes", + "Author": "Dewey Dunnington [aut, cre] (ORCID: ), Edzer Pebesma [aut] (ORCID: ), Anthony North [ctb]", + "Repository": "CRAN" + }, + "xfun": { + "Package": "xfun", + "Version": "0.59", + "Source": "Repository", + "Type": "Package", + "Title": "Supporting Functions for Packages Maintained by 'Yihui Xie'", + "Authors@R": "c( person(\"Yihui\", \"Xie\", role = c(\"aut\", \"cre\", \"cph\"), email = \"xie@yihui.name\", comment = c(ORCID = \"0000-0003-0645-5666\", URL = \"https://yihui.org\")), person(\"Wush\", \"Wu\", role = \"ctb\"), person(\"Daijiang\", \"Li\", role = \"ctb\"), person(\"Xianying\", \"Tan\", role = \"ctb\"), person(\"Salim\", \"Brüggemann\", role = \"ctb\", email = \"salim-b@pm.me\", comment = c(ORCID = \"0000-0002-5329-5987\")), person(\"Christophe\", \"Dervieux\", role = \"ctb\"), person() )", + "Description": "Miscellaneous functions commonly used in other packages maintained by 'Yihui Xie'.", + "Depends": [ + "R (>= 3.2.0)" + ], + "Imports": [ + "grDevices", + "stats", + "tools" + ], + "Suggests": [ + "testit", + "parallel", + "codetools", + "methods", + "rstudioapi", + "tinytex (>= 0.30)", + "mime", + "litedown (>= 0.6)", + "commonmark", + "knitr (>= 1.50)", + "remotes", + "pak", + "curl", + "xml2", + "jsonlite", + "magick", + "yaml", + "data.table", + "qs2" + ], + "License": "MIT + file LICENSE", + "URL": "https://github.com/yihui/xfun", + "BugReports": "https://github.com/yihui/xfun/issues", + "Encoding": "UTF-8", + "VignetteBuilder": "litedown", + "Config/roxygen2/version": "8.0.0", + "NeedsCompilation": "yes", + "Author": "Yihui Xie [aut, cre, cph] (ORCID: , URL: https://yihui.org), Wush Wu [ctb], Daijiang Li [ctb], Xianying Tan [ctb], Salim Brüggemann [ctb] (ORCID: ), Christophe Dervieux [ctb]", + "Maintainer": "Yihui Xie ", + "Repository": "P3M" + }, + "xml2": { + "Package": "xml2", + "Version": "1.6.0", + "Source": "Repository", + "Title": "Parse XML", + "Authors@R": "c( person(\"Hadley\", \"Wickham\", role = \"aut\"), person(\"Jim\", \"Hester\", role = \"aut\"), person(\"Jeroen\", \"Ooms\", email = \"jeroenooms@gmail.com\", role = c(\"aut\", \"cre\")), person(\"Posit Software, PBC\", role = c(\"cph\", \"fnd\")), person(\"R Foundation\", role = \"ctb\", comment = \"Copy of R-project homepage cached as example\") )", + "Description": "Bindings to 'libxml2' for working with XML data using a simple, consistent interface based on 'XPath' expressions. Also supports XML schema validation; for 'XSLT' transformations see the 'xslt' package.", + "License": "MIT + file LICENSE", + "URL": "https://xml2.r-lib.org, https://r-lib.r-universe.dev/xml2", + "BugReports": "https://github.com/r-lib/xml2/issues", + "Depends": [ + "R (>= 3.6.0)" + ], + "Imports": [ + "cli", + "methods", + "rlang (>= 1.1.0)" + ], + "Suggests": [ + "covr", + "curl", + "httr", + "knitr", + "mockery", + "rmarkdown", + "testthat (>= 3.2.0)", + "xslt" + ], + "VignetteBuilder": "knitr", + "Config/Needs/website": "tidyverse/tidytemplate", + "Encoding": "UTF-8", + "RoxygenNote": "7.3.3", + "SystemRequirements": "libxml2: libxml2-dev (deb), libxml2-devel (rpm)", + "Collate": "'S4.R' 'as_list.R' 'xml_parse.R' 'as_xml_document.R' 'classes.R' 'format.R' 'import-standalone-obj-type.R' 'import-standalone-purrr.R' 'import-standalone-types-check.R' 'init.R' 'nodeset_apply.R' 'paths.R' 'utils.R' 'xml2-package.R' 'xml_attr.R' 'xml_children.R' 'xml_document.R' 'xml_find.R' 'xml_missing.R' 'xml_modify.R' 'xml_name.R' 'xml_namespaces.R' 'xml_node.R' 'xml_nodeset.R' 'xml_path.R' 'xml_schema.R' 'xml_serialize.R' 'xml_structure.R' 'xml_text.R' 'xml_type.R' 'xml_url.R' 'xml_write.R'", + "Config/testthat/edition": "3", + "NeedsCompilation": "yes", + "Author": "Hadley Wickham [aut], Jim Hester [aut], Jeroen Ooms [aut, cre], Posit Software, PBC [cph, fnd], R Foundation [ctb] (Copy of R-project homepage cached as example)", + "Maintainer": "Jeroen Ooms ", + "Repository": "P3M" + }, + "yaml": { + "Package": "yaml", + "Version": "2.3.12", + "Source": "Repository", + "Type": "Package", + "Title": "Methods to Convert R Data to YAML and Back", + "Authors@R": "c( person(\"Hadley\", \"Wickham\", , \"hadley@posit.co\", role = \"cre\", comment = c(ORCID = \"0000-0003-4757-117X\")), person(\"Shawn\", \"Garbett\", , \"shawn.garbett@vumc.org\", role = \"ctb\", comment = c(ORCID = \"0000-0003-4079-5621\")), person(\"Jeremy\", \"Stephens\", role = c(\"aut\", \"ctb\")), person(\"Kirill\", \"Simonov\", role = \"aut\"), person(\"Yihui\", \"Xie\", role = \"ctb\", comment = c(ORCID = \"0000-0003-0645-5666\")), person(\"Zhuoer\", \"Dong\", role = \"ctb\"), person(\"Jeffrey\", \"Horner\", role = \"ctb\"), person(\"reikoch\", role = \"ctb\"), person(\"Will\", \"Beasley\", role = \"ctb\", comment = c(ORCID = \"0000-0002-5613-5006\")), person(\"Brendan\", \"O'Connor\", role = \"ctb\"), person(\"Michael\", \"Quinn\", role = \"ctb\"), person(\"Charlie\", \"Gao\", role = \"ctb\"), person(c(\"Gregory\", \"R.\"), \"Warnes\", role = \"ctb\"), person(c(\"Zhian\", \"N.\"), \"Kamvar\", role = \"ctb\") )", + "Description": "Implements the 'libyaml' 'YAML' 1.1 parser and emitter () for R.", + "License": "BSD_3_clause + file LICENSE", + "URL": "https://yaml.r-lib.org, https://github.com/r-lib/yaml/", + "BugReports": "https://github.com/r-lib/yaml/issues", + "Suggests": [ + "knitr", + "rmarkdown", + "testthat (>= 3.0.0)" + ], + "Config/testthat/edition": "3", + "Config/Needs/website": "tidyverse/tidytemplate", + "Encoding": "UTF-8", + "RoxygenNote": "7.3.3", + "VignetteBuilder": "knitr", + "NeedsCompilation": "yes", + "Author": "Hadley Wickham [cre] (ORCID: ), Shawn Garbett [ctb] (ORCID: ), Jeremy Stephens [aut, ctb], Kirill Simonov [aut], Yihui Xie [ctb] (ORCID: ), Zhuoer Dong [ctb], Jeffrey Horner [ctb], reikoch [ctb], Will Beasley [ctb] (ORCID: ), Brendan O'Connor [ctb], Michael Quinn [ctb], Charlie Gao [ctb], Gregory R. Warnes [ctb], Zhian N. Kamvar [ctb]", + "Maintainer": "Hadley Wickham ", + "Repository": "CRAN" + }, + "zip": { + "Package": "zip", + "Version": "3.0.0", + "Source": "Repository", + "Title": "Cross-Platform 'zip' Compression", + "Authors@R": "c( person(\"Gábor\", \"Csárdi\", , \"csardi.gabor@gmail.com\", role = c(\"aut\", \"cre\")), person(\"Kuba\", \"Podgórski\", role = \"ctb\"), person(\"Rich\", \"Geldreich\", role = \"ctb\"), person(\"Arm Limited\", role = c(\"ctb\", \"cph\"), comment = \"bundled Mbed TLS crypto subset in src/mbedtls/ (Apache-2.0)\"), person(\"Posit Software, PBC\", role = c(\"cph\", \"fnd\"), comment = c(ROR = \"03wc8by49\")) )", + "Description": "Cross-Platform 'zip' Compression Library. A replacement for the 'zip' function, that does not require any additional external tools on any platform.", + "License": "MIT + file LICENSE", + "URL": "https://github.com/r-lib/zip, https://r-lib.github.io/zip/", + "BugReports": "https://github.com/r-lib/zip/issues", + "LinkingTo": [ + "cli" + ], + "Suggests": [ + "callr", + "cli", + "curl", + "pillar", + "processx", + "R6", + "testthat", + "webfakes", + "withr" + ], + "Config/Needs/website": "tidyverse/tidytemplate", + "Config/testthat/edition": "3", + "Config/testthat/parallel": "true", + "Config/testthat/start-first": "large-files, http", + "Config/usethis/last-upkeep": "2025-05-07", + "Encoding": "UTF-8", + "Config/roxygen2/version": "8.0.0", + "NeedsCompilation": "yes", + "Author": "Gábor Csárdi [aut, cre], Kuba Podgórski [ctb], Rich Geldreich [ctb], Arm Limited [ctb, cph] (bundled Mbed TLS crypto subset in src/mbedtls/ (Apache-2.0)), Posit Software, PBC [cph, fnd] (ROR: )", + "Maintainer": "Gábor Csárdi ", + "Repository": "RSPM" + } + } +} diff --git a/blog/2026/property-tax-uplift/renv/.gitignore b/blog/2026/property-tax-uplift/renv/.gitignore new file mode 100644 index 0000000..0ec0cbb --- /dev/null +++ b/blog/2026/property-tax-uplift/renv/.gitignore @@ -0,0 +1,7 @@ +library/ +local/ +cellar/ +lock/ +python/ +sandbox/ +staging/ diff --git a/blog/2026/property-tax-uplift/renv/activate.R b/blog/2026/property-tax-uplift/renv/activate.R new file mode 100644 index 0000000..20ffd44 --- /dev/null +++ b/blog/2026/property-tax-uplift/renv/activate.R @@ -0,0 +1,1438 @@ + +local({ + + # the requested version of renv + version <- "1.2.3" + attr(version, "md5") <- "1bd9f58e1cfe27ce035933937c6f03de" + attr(version, "sha") <- NULL + + # the project directory + project <- Sys.getenv("RENV_PROJECT") + if (!nzchar(project)) + project <- getwd() + + # use start-up diagnostics if enabled + diagnostics <- Sys.getenv("RENV_STARTUP_DIAGNOSTICS", unset = "FALSE") + if (diagnostics) { + start <- Sys.time() + profile <- tempfile("renv-startup-", fileext = ".Rprof") + utils::Rprof(profile) + on.exit({ + utils::Rprof(NULL) + elapsed <- signif(difftime(Sys.time(), start, units = "auto"), digits = 2L) + writeLines(sprintf("- renv took %s to run the autoloader.", format(elapsed))) + writeLines(sprintf("- Profile: %s", profile)) + print(utils::summaryRprof(profile)) + }, add = TRUE) + } + + # figure out whether the autoloader is enabled + enabled <- local({ + + # first, check config option + override <- getOption("renv.config.autoloader.enabled") + if (!is.null(override)) + return(override) + + # if we're being run in a context where R_LIBS is already set, + # don't load -- presumably we're being run as a sub-process and + # the parent process has already set up library paths for us + rcmd <- Sys.getenv("R_CMD", unset = NA) + rlibs <- Sys.getenv("R_LIBS", unset = NA) + if (!is.na(rlibs) && !is.na(rcmd)) + return(FALSE) + + # next, check environment variables + # prefer using the configuration one in the future + envvars <- c( + "RENV_CONFIG_AUTOLOADER_ENABLED", + "RENV_AUTOLOADER_ENABLED", + "RENV_ACTIVATE_PROJECT" + ) + + for (envvar in envvars) { + envval <- Sys.getenv(envvar, unset = NA) + if (!is.na(envval)) + return(tolower(envval) %in% c("true", "t", "1")) + } + + # enable by default + TRUE + + }) + + # bail if we're not enabled + if (!enabled) { + + # if we're not enabled, we might still need to manually load + # the user profile here + profile <- Sys.getenv("R_PROFILE_USER", unset = "~/.Rprofile") + if (file.exists(profile)) { + cfg <- Sys.getenv("RENV_CONFIG_USER_PROFILE", unset = "TRUE") + if (tolower(cfg) %in% c("true", "t", "1")) + sys.source(profile, envir = globalenv()) + } + + return(FALSE) + + } + + # avoid recursion + if (identical(getOption("renv.autoloader.running"), TRUE)) { + warning("ignoring recursive attempt to run renv autoloader") + return(invisible(TRUE)) + } + + # signal that we're loading renv during R startup + options(renv.autoloader.running = TRUE) + on.exit(options(renv.autoloader.running = NULL), add = TRUE) + + # signal that we've consented to use renv + options(renv.consent = TRUE) + + # load the 'utils' package eagerly -- this ensures that renv shims, which + # mask 'utils' packages, will come first on the search path + library(utils, lib.loc = .Library) + + # unload renv if it's already been loaded + if ("renv" %in% loadedNamespaces()) + unloadNamespace("renv") + + # load bootstrap tools + ansify <- function(text) { + if (renv_ansify_enabled()) + renv_ansify_enhanced(text) + else + renv_ansify_default(text) + } + + renv_ansify_enabled <- function() { + + override <- Sys.getenv("RENV_ANSIFY_ENABLED", unset = NA) + if (!is.na(override)) + return(as.logical(override)) + + pane <- Sys.getenv("RSTUDIO_CHILD_PROCESS_PANE", unset = NA) + if (identical(pane, "build")) + return(FALSE) + + testthat <- Sys.getenv("TESTTHAT", unset = "false") + if (tolower(testthat) %in% "true") + return(FALSE) + + iderun <- Sys.getenv("R_CLI_HAS_HYPERLINK_IDE_RUN", unset = "false") + if (tolower(iderun) %in% "false") + return(FALSE) + + TRUE + + } + + renv_ansify_default <- function(text) { + text + } + + renv_ansify_enhanced <- function(text) { + + # R help links + pattern <- "`\\?(renv::(?:[^`])+)`" + replacement <- "`\033]8;;x-r-help:\\1\a?\\1\033]8;;\a`" + text <- gsub(pattern, replacement, text, perl = TRUE) + + # runnable code + pattern <- "`(renv::(?:[^`])+)`" + replacement <- "`\033]8;;x-r-run:\\1\a\\1\033]8;;\a`" + text <- gsub(pattern, replacement, text, perl = TRUE) + + # return ansified text + text + + } + + renv_ansify_init <- function() { + + envir <- renv_envir_self() + if (renv_ansify_enabled()) + assign("ansify", renv_ansify_enhanced, envir = envir) + else + assign("ansify", renv_ansify_default, envir = envir) + + } + + `%||%` <- function(x, y) { + if (is.null(x)) y else x + } + + catf <- function(fmt, ..., appendLF = TRUE) { + + quiet <- getOption("renv.bootstrap.quiet", default = FALSE) + if (quiet) + return(invisible()) + + # also check for config environment variables that should suppress messages + # https://github.com/rstudio/renv/issues/2214 + enabled <- Sys.getenv("RENV_CONFIG_STARTUP_QUIET", unset = NA) + if (!is.na(enabled) && tolower(enabled) %in% c("true", "1")) + return(invisible()) + + enabled <- Sys.getenv("RENV_CONFIG_SYNCHRONIZED_CHECK", unset = NA) + if (!is.na(enabled) && tolower(enabled) %in% c("false", "0")) + return(invisible()) + + msg <- sprintf(fmt, ...) + cat(msg, file = stdout(), sep = if (appendLF) "\n" else "") + + invisible(msg) + + } + + header <- function(label, + ..., + prefix = "#", + suffix = "-", + n = min(getOption("width"), 78)) + { + label <- sprintf(label, ...) + n <- max(n - nchar(label) - nchar(prefix) - 2L, 8L) + if (n <= 0) + return(paste(prefix, label)) + + tail <- paste(rep.int(suffix, n), collapse = "") + paste0(prefix, " ", label, " ", tail) + + } + + heredoc <- function(text, leave = 0) { + + # remove leading, trailing whitespace + trimmed <- gsub("^\\s*\\n|\\n\\s*$", "", text) + + # split into lines + lines <- strsplit(trimmed, "\n", fixed = TRUE)[[1L]] + + # compute common indent + indent <- regexpr("[^[:space:]]", lines) + common <- min(setdiff(indent, -1L)) - leave + text <- paste(substring(lines, common), collapse = "\n") + + # substitute in ANSI links for executable renv code + ansify(text) + + } + + bootstrap <- function(version, library) { + + friendly <- renv_bootstrap_version_friendly(version) + section <- header(sprintf("Bootstrapping renv %s", friendly)) + catf(section) + + # ensure the target library path exists; required for file.copy(..., recursive = TRUE) + dir.create(library, showWarnings = FALSE, recursive = TRUE) + + # try to install renv from cache + md5 <- attr(version, "md5", exact = TRUE) + if (length(md5)) { + pkgpath <- renv_bootstrap_find(version) + if (length(pkgpath) && file.exists(pkgpath)) { + ok <- file.copy(pkgpath, library, recursive = TRUE) + if (isTRUE(ok)) + return(invisible()) + } + } + + # attempt to download renv + catf("- Downloading renv ... ", appendLF = FALSE) + withCallingHandlers( + tarball <- renv_bootstrap_download(version), + error = function(err) { + catf("FAILED") + stop("failed to download:\n", conditionMessage(err)) + } + ) + catf("OK") + on.exit(unlink(tarball), add = TRUE) + + # now attempt to install + catf("- Installing renv ... ", appendLF = FALSE) + withCallingHandlers( + status <- renv_bootstrap_install(version, tarball, library), + error = function(err) { + catf("FAILED") + stop("failed to install:\n", conditionMessage(err)) + } + ) + catf("OK") + + # add empty line to break up bootstrapping from normal output + catf("") + return(invisible()) + } + + renv_bootstrap_tests_running <- function() { + getOption("renv.tests.running", default = FALSE) + } + + renv_bootstrap_repos <- function() { + + # get CRAN repository + cran <- getOption("renv.repos.cran", "https://cloud.r-project.org") + + # check for repos override + repos <- Sys.getenv("RENV_CONFIG_REPOS_OVERRIDE", unset = NA) + if (!is.na(repos)) { + + # split on ';' if present + parts <- strsplit(repos, ";", fixed = TRUE)[[1L]] + + # split into named repositories if present + idx <- regexpr("=", parts, fixed = TRUE) + keys <- substring(parts, 1L, idx - 1L) + vals <- substring(parts, idx + 1L) + names(vals) <- keys + + # if we have a single unnamed repository, call it CRAN + if (length(vals) == 1L && identical(keys, "")) + names(vals) <- "CRAN" + + return(vals) + + } + + # check for lockfile repositories + repos <- tryCatch(renv_bootstrap_repos_lockfile(), error = identity) + if (!inherits(repos, "error") && length(repos)) + return(repos) + + # retrieve current repos + repos <- getOption("repos") + + # ensure @CRAN@ entries are resolved + repos[repos == "@CRAN@"] <- cran + + # add in renv.bootstrap.repos if set + default <- c(FALLBACK = "https://cloud.r-project.org") + extra <- getOption("renv.bootstrap.repos", default = default) + repos <- c(repos, extra) + + # remove duplicates that might've snuck in + dupes <- duplicated(repos) | duplicated(names(repos)) + repos[!dupes] + + } + + renv_bootstrap_repos_lockfile <- function() { + + lockpath <- Sys.getenv("RENV_PATHS_LOCKFILE", unset = "renv.lock") + if (!file.exists(lockpath)) + return(NULL) + + lockfile <- tryCatch(renv_json_read(lockpath), error = identity) + if (inherits(lockfile, "error")) { + warning(lockfile) + return(NULL) + } + + repos <- lockfile$R$Repositories + if (length(repos) == 0) + return(NULL) + + keys <- vapply(repos, `[[`, "Name", FUN.VALUE = character(1)) + vals <- vapply(repos, `[[`, "URL", FUN.VALUE = character(1)) + names(vals) <- keys + + return(vals) + + } + + renv_bootstrap_download <- function(version) { + + sha <- attr(version, "sha", exact = TRUE) + + methods <- if (!is.null(sha)) { + + # attempting to bootstrap a development version of renv + c( + function() renv_bootstrap_download_tarball(sha), + function() renv_bootstrap_download_github(sha) + ) + + } else { + + # attempting to bootstrap a release version of renv + c( + function() renv_bootstrap_download_tarball(version), + function() renv_bootstrap_download_cran_latest(version), + function() renv_bootstrap_download_cran_archive(version) + ) + + } + + for (method in methods) { + path <- tryCatch(method(), error = identity) + if (is.character(path) && file.exists(path)) + return(path) + } + + stop("All download methods failed") + + } + + renv_bootstrap_download_impl <- function(url, destfile) { + + mode <- "wb" + + # https://bugs.r-project.org/bugzilla/show_bug.cgi?id=17715 + fixup <- + Sys.info()[["sysname"]] == "Windows" && + substring(url, 1L, 5L) == "file:" + + if (fixup) + mode <- "w+b" + + args <- list( + url = url, + destfile = destfile, + mode = mode, + quiet = TRUE + ) + + if ("headers" %in% names(formals(utils::download.file))) { + headers <- renv_bootstrap_download_custom_headers(url) + if (length(headers) && is.character(headers)) + args$headers <- headers + } + + do.call(utils::download.file, args) + + } + + renv_bootstrap_download_custom_headers <- function(url) { + + headers <- getOption("renv.download.headers") + if (is.null(headers)) + return(character()) + + if (!is.function(headers)) + stopf("'renv.download.headers' is not a function") + + headers <- headers(url) + if (length(headers) == 0L) + return(character()) + + if (is.list(headers)) + headers <- unlist(headers, recursive = FALSE, use.names = TRUE) + + ok <- + is.character(headers) && + is.character(names(headers)) && + all(nzchar(names(headers))) + + if (!ok) + stop("invocation of 'renv.download.headers' did not return a named character vector") + + headers + + } + + renv_bootstrap_download_cran_latest <- function(version) { + + spec <- renv_bootstrap_download_cran_latest_find(version) + type <- spec$type + repos <- spec$repos + + baseurl <- utils::contrib.url(repos = repos, type = type) + ext <- if (identical(type, "source")) + ".tar.gz" + else if (Sys.info()[["sysname"]] == "Windows") + ".zip" + else + ".tgz" + name <- sprintf("renv_%s%s", version, ext) + url <- paste(baseurl, name, sep = "/") + + destfile <- file.path(tempdir(), name) + status <- tryCatch( + renv_bootstrap_download_impl(url, destfile), + condition = identity + ) + + if (inherits(status, "condition")) + return(FALSE) + + # report success and return + destfile + + } + + renv_bootstrap_download_cran_latest_find <- function(version) { + + # check whether binaries are supported on this system + binary <- + getOption("renv.bootstrap.binary", default = TRUE) && + !identical(.Platform$pkgType, "source") && + !identical(getOption("pkgType"), "source") && + Sys.info()[["sysname"]] %in% c("Darwin", "Windows") + + types <- c(if (binary) "binary", "source") + + # iterate over types + repositories + for (type in types) { + for (repos in renv_bootstrap_repos()) { + + # build arguments for utils::available.packages() call + args <- list(type = type, repos = repos) + + # add custom headers if available -- note that + # utils::available.packages() will pass this to download.file() + if ("headers" %in% names(formals(utils::download.file))) { + headers <- renv_bootstrap_download_custom_headers(repos) + if (length(headers) && is.character(headers)) + args$headers <- headers + } + + # retrieve package database + db <- tryCatch( + as.data.frame( + do.call(utils::available.packages, args), + stringsAsFactors = FALSE + ), + error = identity + ) + + if (inherits(db, "error")) + next + + # check for compatible entry + entry <- db[db$Package %in% "renv" & db$Version %in% version, ] + if (nrow(entry) == 0) + next + + # found it; return spec to caller + spec <- list(entry = entry, type = type, repos = repos) + return(spec) + + } + } + + # if we got here, we failed to find renv + fmt <- "renv %s is not available from your declared package repositories" + stop(sprintf(fmt, version)) + + } + + renv_bootstrap_download_cran_archive <- function(version) { + + name <- sprintf("renv_%s.tar.gz", version) + repos <- renv_bootstrap_repos() + urls <- file.path(repos, "src/contrib/Archive/renv", name) + destfile <- file.path(tempdir(), name) + + for (url in urls) { + + status <- tryCatch( + renv_bootstrap_download_impl(url, destfile), + condition = identity + ) + + if (identical(status, 0L)) + return(destfile) + + } + + return(FALSE) + + } + + renv_bootstrap_find <- function(version) { + + path <- renv_bootstrap_find_cache(version) + if (length(path) && file.exists(path)) { + catf("- Using renv %s from global package cache", version) + return(path) + } + + } + + renv_bootstrap_find_cache <- function(version) { + + md5 <- attr(version, "md5", exact = TRUE) + if (is.null(md5)) + return() + + # infer path to renv cache + cache <- Sys.getenv("RENV_PATHS_CACHE", unset = "") + if (!nzchar(cache)) { + root <- Sys.getenv("RENV_PATHS_ROOT", unset = NA) + if (!is.na(root)) + cache <- file.path(root, "cache") + } + + if (!nzchar(cache)) { + tools <- asNamespace("tools") + if (is.function(tools$R_user_dir)) { + root <- tools$R_user_dir("renv", "cache") + cache <- file.path(root, "cache") + } + } + + # start completing path to cache + file.path( + cache, + renv_bootstrap_cache_version(), + renv_bootstrap_platform_prefix(), + "renv", + version, + md5, + "renv" + ) + + } + + renv_bootstrap_download_tarball <- function(version) { + + # if the user has provided the path to a tarball via + # an environment variable, then use it + tarball <- Sys.getenv("RENV_BOOTSTRAP_TARBALL", unset = NA) + if (is.na(tarball)) + return() + + # allow directories + if (dir.exists(tarball)) { + name <- sprintf("renv_%s.tar.gz", version) + tarball <- file.path(tarball, name) + } + + # bail if it doesn't exist + if (!file.exists(tarball)) { + + # let the user know we weren't able to honour their request + fmt <- "- RENV_BOOTSTRAP_TARBALL is set (%s) but does not exist." + msg <- sprintf(fmt, tarball) + warning(msg) + + # bail + return() + + } + + catf("- Using local tarball '%s'.", tarball) + tarball + + } + + renv_bootstrap_github_token <- function() { + for (envvar in c("GITHUB_TOKEN", "GITHUB_PAT", "GH_TOKEN")) { + envval <- Sys.getenv(envvar, unset = NA) + if (!is.na(envval)) + return(envval) + } + } + + renv_bootstrap_download_github <- function(version) { + + enabled <- Sys.getenv("RENV_BOOTSTRAP_FROM_GITHUB", unset = "TRUE") + if (!identical(enabled, "TRUE")) + return(FALSE) + + # prepare download options + token <- renv_bootstrap_github_token() + if (is.null(token)) + token <- "" + + if (nzchar(Sys.which("curl")) && nzchar(token)) { + fmt <- "--location --fail --header \"Authorization: token %s\"" + extra <- sprintf(fmt, token) + saved <- options("download.file.method", "download.file.extra") + options(download.file.method = "curl", download.file.extra = extra) + on.exit(do.call(base::options, saved), add = TRUE) + } else if (nzchar(Sys.which("wget")) && nzchar(token)) { + fmt <- "--header=\"Authorization: token %s\"" + extra <- sprintf(fmt, token) + saved <- options("download.file.method", "download.file.extra") + options(download.file.method = "wget", download.file.extra = extra) + on.exit(do.call(base::options, saved), add = TRUE) + } + + url <- file.path("https://api.github.com/repos/rstudio/renv/tarball", version) + name <- sprintf("renv_%s.tar.gz", version) + destfile <- file.path(tempdir(), name) + + status <- tryCatch( + renv_bootstrap_download_impl(url, destfile), + condition = identity + ) + + if (!identical(status, 0L)) + return(FALSE) + + renv_bootstrap_download_augment(destfile) + + return(destfile) + + } + + # Add Sha to DESCRIPTION. This is stop gap until #890, after which we + # can use renv::install() to fully capture metadata. + renv_bootstrap_download_augment <- function(destfile) { + sha <- renv_bootstrap_git_extract_sha1_tar(destfile) + if (is.null(sha)) { + return() + } + + # Untar + tempdir <- tempfile("renv-github-") + on.exit(unlink(tempdir, recursive = TRUE), add = TRUE) + untar(destfile, exdir = tempdir) + pkgdir <- dir(tempdir, full.names = TRUE)[[1]] + + # Modify description + desc_path <- file.path(pkgdir, "DESCRIPTION") + desc_lines <- readLines(desc_path) + remotes_fields <- c( + "RemoteType: github", + "RemoteHost: api.github.com", + "RemoteRepo: renv", + "RemoteUsername: rstudio", + "RemotePkgRef: rstudio/renv", + paste("RemoteRef: ", sha), + paste("RemoteSha: ", sha) + ) + writeLines(c(desc_lines[desc_lines != ""], remotes_fields), con = desc_path) + + # Re-tar + local({ + old <- setwd(tempdir) + on.exit(setwd(old), add = TRUE) + + tar(destfile, compression = "gzip") + }) + invisible() + } + + # Extract the commit hash from a git archive. Git archives include the SHA1 + # hash as the comment field of the tarball pax extended header + # (see https://www.kernel.org/pub/software/scm/git/docs/git-archive.html) + # For GitHub archives this should be the first header after the default one + # (512 byte) header. + renv_bootstrap_git_extract_sha1_tar <- function(bundle) { + + # open the bundle for reading + # We use gzcon for everything because (from ?gzcon) + # > Reading from a connection which does not supply a 'gzip' magic + # > header is equivalent to reading from the original connection + conn <- gzcon(file(bundle, open = "rb", raw = TRUE)) + on.exit(close(conn)) + + # The default pax header is 512 bytes long and the first pax extended header + # with the comment should be 51 bytes long + # `52 comment=` (11 chars) + 40 byte SHA1 hash + len <- 0x200 + 0x33 + res <- rawToChar(readBin(conn, "raw", n = len)[0x201:len]) + + if (grepl("^52 comment=", res)) { + sub("52 comment=", "", res) + } else { + NULL + } + } + + renv_bootstrap_install <- function(version, tarball, library) { + + # attempt to install it into project library + dir.create(library, showWarnings = FALSE, recursive = TRUE) + output <- renv_bootstrap_install_impl(library, tarball) + + # check for successful install + status <- attr(output, "status") + if (is.null(status) || identical(status, 0L)) + return(status) + + # an error occurred; report it + header <- "installation of renv failed" + lines <- paste(rep.int("=", nchar(header)), collapse = "") + text <- paste(c(header, lines, output), collapse = "\n") + stop(text) + + } + + renv_bootstrap_install_impl <- function(library, tarball) { + + # invoke using system2 so we can capture and report output + bin <- R.home("bin") + exe <- if (Sys.info()[["sysname"]] == "Windows") "R.exe" else "R" + R <- file.path(bin, exe) + + args <- c( + "--vanilla", "CMD", "INSTALL", "--no-multiarch", + "-l", shQuote(path.expand(library)), + shQuote(path.expand(tarball)) + ) + + system2(R, args, stdout = TRUE, stderr = TRUE) + + } + + renv_bootstrap_platform_prefix_default <- function() { + + # read version component + version <- Sys.getenv("RENV_PATHS_VERSION", unset = "R-%v") + + # expand placeholders + placeholders <- list( + list("%v", format(getRversion()[1, 1:2])), + list("%V", format(getRversion()[1, 1:3])) + ) + + for (placeholder in placeholders) + version <- gsub(placeholder[[1L]], placeholder[[2L]], version, fixed = TRUE) + + # include SVN revision for development versions of R + # (to avoid sharing platform-specific artefacts with released versions of R) + devel <- + identical(R.version[["status"]], "Under development (unstable)") || + identical(R.version[["nickname"]], "Unsuffered Consequences") + + if (devel) + version <- paste(version, R.version[["svn rev"]], sep = "-r") + + version + + } + + renv_bootstrap_platform_prefix <- function() { + + # construct version prefix + version <- renv_bootstrap_platform_prefix_default() + + # build list of path components + components <- c(version, R.version$platform) + + # include prefix if provided by user + prefix <- renv_bootstrap_platform_prefix_impl() + if (!is.na(prefix) && nzchar(prefix)) + components <- c(prefix, components) + + # build prefix + paste(components, collapse = "/") + + } + + renv_bootstrap_platform_prefix_impl <- function() { + + # if an explicit prefix has been supplied, use it + prefix <- Sys.getenv("RENV_PATHS_PREFIX", unset = NA) + if (!is.na(prefix)) + return(prefix) + + # if the user has requested an automatic prefix, generate it + auto <- Sys.getenv("RENV_PATHS_PREFIX_AUTO", unset = NA) + if (is.na(auto) && getRversion() >= "4.4.0") + auto <- "TRUE" + + if (auto %in% c("TRUE", "True", "true", "1")) + return(renv_bootstrap_platform_prefix_auto()) + + # empty string on failure + "" + + } + + renv_bootstrap_platform_prefix_auto <- function() { + + prefix <- tryCatch(renv_bootstrap_platform_os(), error = identity) + if (inherits(prefix, "error") || prefix %in% "unknown") { + + msg <- paste( + "failed to infer current operating system", + "please file a bug report at https://github.com/rstudio/renv/issues", + sep = "; " + ) + + warning(msg) + + } + + prefix + + } + + renv_bootstrap_platform_os <- function() { + + sysinfo <- Sys.info() + sysname <- sysinfo[["sysname"]] + + # handle Windows + macOS up front + if (sysname == "Windows") + return("windows") + else if (sysname == "Darwin") + return("macos") + + # check for os-release files + for (file in c("/etc/os-release", "/usr/lib/os-release")) + if (file.exists(file)) + return(renv_bootstrap_platform_os_via_os_release(file, sysinfo)) + + # check for redhat-release files + if (file.exists("/etc/redhat-release")) + return(renv_bootstrap_platform_os_via_redhat_release()) + + "unknown" + + } + + renv_bootstrap_platform_os_via_os_release <- function(file, sysinfo) { + + # read /etc/os-release + release <- utils::read.table( + file = file, + sep = "=", + quote = c("\"", "'"), + col.names = c("Key", "Value"), + comment.char = "#", + stringsAsFactors = FALSE + ) + + vars <- as.list(release$Value) + names(vars) <- release$Key + + # get os name + os <- tolower(sysinfo[["sysname"]]) + + # read id + id <- "unknown" + for (field in c("ID", "ID_LIKE")) { + if (field %in% names(vars) && nzchar(vars[[field]])) { + id <- vars[[field]] + break + } + } + + # read version + version <- "unknown" + for (field in c("UBUNTU_CODENAME", "VERSION_CODENAME", "VERSION_ID", "BUILD_ID")) { + if (field %in% names(vars) && nzchar(vars[[field]])) { + version <- vars[[field]] + break + } + } + + # join together + paste(c(os, id, version), collapse = "-") + + } + + renv_bootstrap_platform_os_via_redhat_release <- function() { + + # read /etc/redhat-release + contents <- readLines("/etc/redhat-release", warn = FALSE) + + # infer id + id <- if (grepl("centos", contents, ignore.case = TRUE)) + "centos" + else if (grepl("redhat", contents, ignore.case = TRUE)) + "redhat" + else + "unknown" + + # try to find a version component (very hacky) + version <- "unknown" + + parts <- strsplit(contents, "[[:space:]]")[[1L]] + for (part in parts) { + + nv <- tryCatch(numeric_version(part), error = identity) + if (inherits(nv, "error")) + next + + version <- nv[1, 1] + break + + } + + paste(c("linux", id, version), collapse = "-") + + } + + renv_bootstrap_library_root_name <- function(project) { + + # use project name as-is if requested + asis <- Sys.getenv("RENV_PATHS_LIBRARY_ROOT_ASIS", unset = "FALSE") + if (asis) + return(basename(project)) + + # otherwise, disambiguate based on project's path + id <- substring(renv_bootstrap_hash_text(project), 1L, 8L) + paste(basename(project), id, sep = "-") + + } + + renv_bootstrap_library_root <- function(project) { + + prefix <- renv_bootstrap_profile_prefix() + + path <- Sys.getenv("RENV_PATHS_LIBRARY", unset = NA) + if (!is.na(path)) + return(paste(c(path, prefix), collapse = "/")) + + path <- renv_bootstrap_library_root_impl(project) + if (!is.null(path)) { + name <- renv_bootstrap_library_root_name(project) + return(paste(c(path, prefix, name), collapse = "/")) + } + + renv_bootstrap_paths_renv("library", project = project) + + } + + renv_bootstrap_library_root_impl <- function(project) { + + root <- Sys.getenv("RENV_PATHS_LIBRARY_ROOT", unset = NA) + if (!is.na(root)) + return(root) + + type <- renv_bootstrap_project_type(project) + if (identical(type, "package")) { + userdir <- renv_bootstrap_user_dir() + return(file.path(userdir, "library")) + } + + } + + renv_bootstrap_validate_version <- function(version, description = NULL) { + + # resolve description file + # + # avoid passing lib.loc to `packageDescription()` below, since R will + # use the loaded version of the package by default anyhow. note that + # this function should only be called after 'renv' is loaded + # https://github.com/rstudio/renv/issues/1625 + description <- description %||% packageDescription("renv") + + # check whether requested version 'version' matches loaded version of renv + sha <- attr(version, "sha", exact = TRUE) + valid <- if (!is.null(sha)) + renv_bootstrap_validate_version_dev(sha, description) + else + renv_bootstrap_validate_version_release(version, description) + + if (valid) + return(TRUE) + + # the loaded version of renv doesn't match the requested version; + # give the user instructions on how to proceed + dev <- identical(description[["RemoteType"]], "github") + remote <- if (dev) + paste("rstudio/renv", description[["RemoteSha"]], sep = "@") + else + paste("renv", description[["Version"]], sep = "@") + + # display both loaded version + sha if available + friendly <- renv_bootstrap_version_friendly( + version = description[["Version"]], + sha = if (dev) description[["RemoteSha"]] + ) + + fmt <- heredoc(" + renv %1$s was loaded from project library, but this project is configured to use renv %2$s. + - Use `renv::record(\"%3$s\")` to record renv %1$s in the lockfile. + - Use `renv::restore(packages = \"renv\")` to install renv %2$s into the project library. + ") + catf(fmt, friendly, renv_bootstrap_version_friendly(version), remote) + + FALSE + + } + + renv_bootstrap_validate_version_dev <- function(version, description) { + + expected <- description[["RemoteSha"]] + if (!is.character(expected)) + return(FALSE) + + pattern <- sprintf("^\\Q%s\\E", version) + grepl(pattern, expected, perl = TRUE) + + } + + renv_bootstrap_validate_version_release <- function(version, description) { + expected <- description[["Version"]] + is.character(expected) && identical(c(expected), c(version)) + } + + renv_bootstrap_hash_text <- function(text) { + + hashfile <- tempfile("renv-hash-") + on.exit(unlink(hashfile), add = TRUE) + + writeLines(text, con = hashfile) + tools::md5sum(hashfile) + + } + + renv_bootstrap_load <- function(project, libpath, version) { + + # try to load renv from the project library + if (!requireNamespace("renv", lib.loc = libpath, quietly = TRUE)) + return(FALSE) + + # warn if the version of renv loaded does not match + renv_bootstrap_validate_version(version) + + # execute renv load hooks, if any + hooks <- getHook("renv::autoload") + for (hook in hooks) + if (is.function(hook)) + tryCatch(hook(), error = warnify) + + # load the project + renv::load(project) + + TRUE + + } + + renv_bootstrap_profile_load <- function(project) { + + # if RENV_PROFILE is already set, just use that + profile <- Sys.getenv("RENV_PROFILE", unset = NA) + if (!is.na(profile) && nzchar(profile)) + return(profile) + + # check for a profile file (nothing to do if it doesn't exist) + path <- renv_bootstrap_paths_renv("profile", profile = FALSE, project = project) + if (!file.exists(path)) + return(NULL) + + # read the profile, and set it if it exists + contents <- readLines(path, warn = FALSE) + if (length(contents) == 0L) + return(NULL) + + # set RENV_PROFILE + profile <- contents[[1L]] + if (!profile %in% c("", "default")) + Sys.setenv(RENV_PROFILE = profile) + + profile + + } + + renv_bootstrap_profile_prefix <- function() { + profile <- renv_bootstrap_profile_get() + if (!is.null(profile)) + return(file.path("profiles", profile, "renv")) + } + + renv_bootstrap_profile_get <- function() { + profile <- Sys.getenv("RENV_PROFILE", unset = "") + renv_bootstrap_profile_normalize(profile) + } + + renv_bootstrap_profile_set <- function(profile) { + profile <- renv_bootstrap_profile_normalize(profile) + if (is.null(profile)) + Sys.unsetenv("RENV_PROFILE") + else + Sys.setenv(RENV_PROFILE = profile) + } + + renv_bootstrap_profile_normalize <- function(profile) { + + if (is.null(profile) || profile %in% c("", "default")) + return(NULL) + + profile + + } + + renv_bootstrap_path_absolute <- function(path) { + + substr(path, 1L, 1L) %in% c("~", "/", "\\") || ( + substr(path, 1L, 1L) %in% c(letters, LETTERS) && + substr(path, 2L, 3L) %in% c(":/", ":\\") + ) + + } + + renv_bootstrap_paths_renv <- function(..., profile = TRUE, project = NULL) { + renv <- Sys.getenv("RENV_PATHS_RENV", unset = "renv") + root <- if (renv_bootstrap_path_absolute(renv)) NULL else project + prefix <- if (profile) renv_bootstrap_profile_prefix() + components <- c(root, renv, prefix, ...) + paste(components, collapse = "/") + } + + renv_bootstrap_project_type <- function(path) { + + descpath <- file.path(path, "DESCRIPTION") + if (!file.exists(descpath)) + return("unknown") + + desc <- tryCatch( + read.dcf(descpath, all = TRUE), + error = identity + ) + + if (inherits(desc, "error")) + return("unknown") + + type <- desc$Type + if (!is.null(type)) + return(tolower(type)) + + package <- desc$Package + if (!is.null(package)) + return("package") + + "unknown" + + } + + renv_bootstrap_user_dir <- function() { + dir <- renv_bootstrap_user_dir_impl() + path.expand(chartr("\\", "/", dir)) + } + + renv_bootstrap_user_dir_impl <- function() { + + # use local override if set + override <- getOption("renv.userdir.override") + if (!is.null(override)) + return(override) + + # use R_user_dir if available + tools <- asNamespace("tools") + if (is.function(tools$R_user_dir)) + return(tools$R_user_dir("renv", "cache")) + + # try using our own backfill for older versions of R + envvars <- c("R_USER_CACHE_DIR", "XDG_CACHE_HOME") + for (envvar in envvars) { + root <- Sys.getenv(envvar, unset = NA) + if (!is.na(root)) + return(file.path(root, "R/renv")) + } + + # use platform-specific default fallbacks + if (Sys.info()[["sysname"]] == "Windows") + file.path(Sys.getenv("LOCALAPPDATA"), "R/cache/R/renv") + else if (Sys.info()[["sysname"]] == "Darwin") + "~/Library/Caches/org.R-project.R/R/renv" + else + "~/.cache/R/renv" + + } + + renv_bootstrap_version_friendly <- function(version, shafmt = NULL, sha = NULL) { + sha <- sha %||% attr(version, "sha", exact = TRUE) + parts <- c(version, sprintf(shafmt %||% " [sha: %s]", substring(sha, 1L, 7L))) + paste(parts, collapse = "") + } + + renv_bootstrap_exec <- function(project, libpath, version) { + if (!renv_bootstrap_load(project, libpath, version)) + renv_bootstrap_run(project, libpath, version) + } + + renv_bootstrap_run <- function(project, libpath, version) { + tryCatch( + renv_bootstrap_run_impl(project, libpath, version), + error = function(e) { + msg <- paste( + "failed to bootstrap renv: the project will not be loaded.", + paste("Reason:", conditionMessage(e)), + "Use `renv::activate()` to re-initialize the project.", + sep = "\n" + ) + warning(msg, call. = FALSE) + } + ) + } + + renv_bootstrap_run_impl <- function(project, libpath, version) { + + # perform bootstrap + bootstrap(version, libpath) + + # exit early if we're just testing bootstrap + if (!is.na(Sys.getenv("RENV_BOOTSTRAP_INSTALL_ONLY", unset = NA))) + return(TRUE) + + # try again to load + if (requireNamespace("renv", lib.loc = libpath, quietly = TRUE)) { + return(renv::load(project = project)) + } + + # failed to download or load renv; warn the user + msg <- c( + "Failed to find an renv installation: the project will not be loaded.", + "Use `renv::activate()` to re-initialize the project." + ) + + warning(paste(msg, collapse = "\n"), call. = FALSE) + + } + + renv_bootstrap_cache_version <- function() { + # NOTE: users should normally not override the cache version; + # this is provided just to make testing easier + Sys.getenv("RENV_CACHE_VERSION", unset = "v5") + } + + renv_bootstrap_cache_version_previous <- function() { + version <- renv_bootstrap_cache_version() + number <- as.integer(substring(version, 2L)) + paste("v", number - 1L, sep = "") + } + + renv_json_read <- function(file = NULL, text = NULL) { + + jlerr <- NULL + + # if jsonlite is loaded, use that instead + if ("jsonlite" %in% loadedNamespaces()) { + + json <- tryCatch(renv_json_read_jsonlite(file, text), error = identity) + if (!inherits(json, "error")) + return(json) + + jlerr <- json + + } + + # otherwise, fall back to the default JSON reader + json <- tryCatch(renv_json_read_default(file, text), error = identity) + if (!inherits(json, "error")) + return(json) + + # report an error + if (!is.null(jlerr)) + stop(jlerr) + else + stop(json) + + } + + renv_json_read_jsonlite <- function(file = NULL, text = NULL) { + text <- paste(text %||% readLines(file, warn = FALSE), collapse = "\n") + jsonlite::fromJSON(txt = text, simplifyVector = FALSE) + } + + renv_json_read_patterns <- function() { + + list( + + # objects + list("{", "\t\n\tobject(\t\n\t", TRUE), + list("}", "\t\n\t)\t\n\t", TRUE), + + # arrays + list("[", "\t\n\tarray(\t\n\t", TRUE), + list("]", "\n\t\n)\n\t\n", TRUE), + + # maps + list(":", "\t\n\t=\t\n\t", TRUE), + + # newlines + list("\\u000a", "\n", FALSE) + + ) + + } + + renv_json_read_envir <- function() { + + envir <- new.env(parent = emptyenv()) + + envir[["+"]] <- `+` + envir[["-"]] <- `-` + + envir[["object"]] <- function(...) { + result <- list(...) + names(result) <- as.character(names(result)) + result + } + + envir[["array"]] <- list + + envir[["true"]] <- TRUE + envir[["false"]] <- FALSE + envir[["null"]] <- NULL + + envir + + } + + renv_json_read_remap <- function(object, patterns) { + + # repair names if necessary + if (!is.null(names(object))) { + + nms <- names(object) + for (pattern in patterns) + nms <- gsub(pattern[[2L]], pattern[[1L]], nms, fixed = TRUE) + names(object) <- nms + + } + + # repair strings if necessary + if (is.character(object)) { + for (pattern in patterns) + object <- gsub(pattern[[2L]], pattern[[1L]], object, fixed = TRUE) + } + + # recurse for other objects + if (is.recursive(object)) + for (i in seq_along(object)) + object[i] <- list(renv_json_read_remap(object[[i]], patterns)) + + # return remapped object + object + + } + + renv_json_read_default <- function(file = NULL, text = NULL) { + + # read json text + text <- paste(text %||% readLines(file, warn = FALSE), collapse = "\n") + + # convert into something the R parser will understand + patterns <- renv_json_read_patterns() + transformed <- text + for (pattern in patterns) + transformed <- gsub(pattern[[1L]], pattern[[2L]], transformed, fixed = TRUE) + + # parse it + rfile <- tempfile("renv-json-", fileext = ".R") + on.exit(unlink(rfile), add = TRUE) + writeLines(transformed, con = rfile) + json <- parse(rfile, keep.source = FALSE, srcfile = NULL)[[1L]] + + # evaluate in safe environment + result <- eval(json, envir = renv_json_read_envir()) + + # fix up strings if necessary -- do so only with reversible patterns + patterns <- Filter(function(pattern) pattern[[3L]], patterns) + renv_json_read_remap(result, patterns) + + } + + + # load the renv profile, if any + renv_bootstrap_profile_load(project) + + # construct path to library root + root <- renv_bootstrap_library_root(project) + + # construct library prefix for platform + prefix <- renv_bootstrap_platform_prefix() + + # construct full libpath + libpath <- file.path(root, prefix) + + # run bootstrap code + renv_bootstrap_exec(project, libpath, version) + + invisible() + +}) diff --git a/blog/2026/property-tax-uplift/renv/settings.json b/blog/2026/property-tax-uplift/renv/settings.json new file mode 100644 index 0000000..46f2f31 --- /dev/null +++ b/blog/2026/property-tax-uplift/renv/settings.json @@ -0,0 +1,21 @@ +{ + "bioconductor.version": null, + "external.libraries": [], + "ignored.packages": [], + "lockfile.sanitize": true, + "package.dependency.fields": [ + "Imports", + "Depends", + "LinkingTo" + ], + "ppm.enabled": null, + "ppm.ignored.urls": [], + "r.version": null, + "snapshot.dev": false, + "snapshot.type": "implicit", + "use.cache": true, + "vcs.ignore.cellar": true, + "vcs.ignore.library": true, + "vcs.ignore.local": true, + "vcs.manage.ignores": true +} diff --git a/blog/2026/q1-building-permits/index.qmd b/blog/2026/q1-building-permits/index.qmd index b67823c..a19fb6e 100644 --- a/blog/2026/q1-building-permits/index.qmd +++ b/blog/2026/q1-building-permits/index.qmd @@ -194,9 +194,7 @@ Edmonton's [property assessment data](https://data.edmonton.ca/City-Administrati For background on the RS Zone and ZBR, see the [two-year review post](../zbr-two-year-review/index.qmd). -I want to project 2026 total numbers, but we only have Q1 data so far. -Similar to my [previous post in mid-2025](../../2025/real-rs-story/index.qmd), I estimate an annualization multiplier from historical data. For each year from 2009 to 2025, I calculate the ratio of full-year units to Q1 units, and use the median as the multiplier. -Any figure that shows 2026 projected numbers uses this simple adjustment. +I want to project 2026 total numbers, but we only have Q1 data so far. Similar to my [previous post in mid-2025](../../2025/real-rs-story/index.qmd), I estimate an annualization multiplier from historical data. For each year from 2009 to 2025, I calculate the ratio of full-year units to Q1 units, and use the median as the multiplier. Any figure that shows 2026 projected numbers uses this simple adjustment. ```{r} #| label: fig-q1-multiplier @@ -230,9 +228,7 @@ The median Q1 multiplier is **`r q1_multiplier`×**, as shown in @fig-q1-multipl ## Year-over-year Q1 comparison -The most direct way to compare Q1 2026 to prior years is to look at Q1 data across all years, stripping out seasonality entirely. @fig-q1-yoy-units shows units added in Q1 for each year since 2009, broken down by project type. -2026 is off to a strong start, with a steady number of homes permitted in Q1. -Similar to 2025, we continue to see steady growth of the 5-8 unit category, which is firmly established as an important part of Edmonton's housing supply. +The most direct way to compare Q1 2026 to prior years is to look at Q1 data across all years, stripping out seasonality entirely. @fig-q1-yoy-units shows units added in Q1 for each year since 2009, broken down by project type. 2026 is off to a strong start, with a steady number of homes permitted in Q1. Similar to 2025, we continue to see steady growth of the 5-8 unit category, which is firmly established as an important part of Edmonton's housing supply. ```{r} #| label: fig-q1-yoy-units @@ -305,8 +301,7 @@ ggplot(q1_by_type, aes(x = year, y = num_projects, fill = project_type)) + theme_jd(mode = "light") ``` -Looking at the number of homes by neighbourhood type, @fig-q1-yoy-nbhd shows continued historical levels of supply in mature neighbourhoods, driven by the 5-8 unit rowhome. -Outside the Henday, building permits have gone down in this Q1, though that could be due to the volatility of the large apartment category. +Looking at the number of homes by neighbourhood type, @fig-q1-yoy-nbhd shows continued historical levels of supply in mature neighbourhoods, driven by the 5-8 unit rowhome. Outside the Henday, building permits have gone down in this Q1, though that could be due to the volatility of the large apartment category. ```{r} #| label: fig-q1-yoy-nbhd @@ -352,8 +347,7 @@ ggplot(q1_by_nbhd_type, aes(x = year, y = total, fill = project_type)) + If we take Q1 as an early signal for the full year, @fig-annualized-units shows the historical full-year units added by project type, with 2026 projected from Q1 using the `r q1_multiplier`× adjustment. -We can see a projected dip from the high level of 2025, though 2026 would still be a strong year by historical standards. -We'll have to wait and see, a handful of large apartment projects could significantly move the needle on the total. +We can see a projected dip from the high level of 2025, though 2026 would still be a strong year by historical standards. We'll have to wait and see, a handful of large apartment projects could significantly move the needle on the total. ```{r} #| label: fig-annualized-units @@ -417,13 +411,7 @@ ggplot(plot_data, aes(x = year, y = total, fill = project_type)) + theme_jd(mode = "light") ``` -@fig-annualized-nbhd breaks the same projection down by neighbourhood type. -We can see that we are projected for another record year in mature neighbourhoods, once again driven by the 5-8 unit rowhome category. -2025 was not a blip: when given the option, a lot of people want to live more centrally, even if it means living in a rowhome instead of a detached house. -Why wouldn't they? They are close to transit, with more mature trees, more businesses within walking distance, and better access to jobs. Many also sit in neighbourhoods with more amenities and room in schools. -Moreover, according to a [report to Edmonton City Council on February 17](https://pub-edmonton.escribemeetings.com/Meeting.aspx?Id=213d47bf-00f0-44be-9efe-3598ae1b6ba4&Agenda=Agenda&lang=English&Item=45&Tab=attachments), 50% of units in rowhomes are over 1,000 square feet, making them a great option for families. -The myth that everyone wants a detached house with a yard in the suburbs should be dead at this point. -The rowhome is the new attainable home for Edmontonian families who want to live in mature neighbourhoods, and the data shows that they are choosing it in large numbers when given the option. +@fig-annualized-nbhd breaks the same projection down by neighbourhood type. We can see that we are projected for another record year in mature neighbourhoods, once again driven by the 5-8 unit rowhome category. 2025 was not a blip: when given the option, a lot of people want to live more centrally, even if it means living in a rowhome instead of a detached house. Why wouldn't they? They are close to transit, with more mature trees, more businesses within walking distance, and better access to jobs. Many also sit in neighbourhoods with more amenities and room in schools. Moreover, according to a [report to Edmonton City Council on February 17](https://pub-edmonton.escribemeetings.com/Meeting.aspx?Id=213d47bf-00f0-44be-9efe-3598ae1b6ba4&Agenda=Agenda&lang=English&Item=45&Tab=attachments), 50% of units in rowhomes are over 1,000 square feet, making them a great option for families. The myth that everyone wants a detached house with a yard in the suburbs should be dead at this point. The rowhome is the new attainable home for Edmontonian families who want to live in mature neighbourhoods, and the data shows that they are choosing it in large numbers when given the option. ```{r} #| label: fig-annualized-nbhd @@ -623,8 +611,7 @@ q1_2026_plexes_by_nbhd |> opt_stylize_jd() ``` -For comparison, @tbl-selected-neighbourhoods shows the same statistics for a hand-picked set of neighbourhoods that have been prominent in debates about RS Zone infill. -If one permit for a 5-8 unit rowhome in Q1 would "destroy" the character of neighbourhoods like Crestwood, one would wonder how fragile the character was to begin with. +For comparison, @tbl-selected-neighbourhoods shows the same statistics for a hand-picked set of neighbourhoods that have been prominent in debates about RS Zone infill. If one permit for a 5-8 unit rowhome in Q1 would "destroy" the character of neighbourhoods like Crestwood, one would wonder how fragile the character was to begin with. ```{r} #| label: tbl-selected-neighbourhoods @@ -747,8 +734,7 @@ cumulative_plexes_by_nbhd |> In 2025, projects with exactly eight units dominated the Fiveplex to Eightplex category in the RS Zone, a direct consequence of the eight-unit cap. Unlike the [previous analysis](../../2025/real-rs-story/index.qmd), which focused on 5–8 unit projects, @tbl-unit-breakdown covers all RS Zone permits from 1 to 8 units. We can see the most common unit counts are 1, 2, 4, and 8. However, the single biggest driver is the 8 unit rowhomes, providing around half of small-scale homes in mature RS-zoned neighbourhoods. -Given that 8-unit projects account for roughly half the small-scale supply, I continue to be glad that City Council chose not to reduce the number of units permitted to 6. -This is an evidence-backed choice that will pay dividends for years to come. +Given that 8-unit projects account for roughly half the small-scale supply, I continue to be glad that City Council chose not to reduce the number of units permitted to 6. This is an evidence-backed choice that will pay dividends for years to come. ```{r} #| label: tbl-unit-breakdown @@ -795,10 +781,7 @@ q1_unit_breakdown(2025) |> ## Building close to transit -2025 set a record for the proportion of homes permitted within 800m of transit. Is that trend continuing in 2026? @fig-ecdf-transit compares the cumulative distribution of Q1 homes by distance from the nearest LRT stop, across recent years. -Once again, we are on track for a record year for building homes near transit. -Within 800m of transit, the cumulative share of homes is `r scales::percent(pct_800m_q1_2026, accuracy=1)` in Q1 2026, compared to `r scales::percent(pct_800m_2025, accuracy=1)` in 2025. -The line for 2026 is above and to the left of the line for 2025, meaning homes are being built overall closer to transit in Q1 2026 than in 2025. +2025 set a record for the proportion of homes permitted within 800m of transit. Is that trend continuing in 2026? @fig-ecdf-transit compares the cumulative distribution of Q1 homes by distance from the nearest LRT stop, across recent years. Once again, we are on track for a record year for building homes near transit. Within 800m of transit, the cumulative share of homes is `r scales::percent(pct_800m_q1_2026, accuracy=1)` in Q1 2026, compared to `r scales::percent(pct_800m_2025, accuracy=1)` in 2025. The line for 2026 is above and to the left of the line for 2025, meaning homes are being built overall closer to transit in Q1 2026 than in 2025. ```{r} #| label: fig-ecdf-transit @@ -858,9 +841,7 @@ ggplot(filter(buffers, radius == "2km")) + ## Conclusions -2026 is shaping up to be another strong year for housing supply in Edmonton. -We are building more homes in mature neighbourhoods, more types of homes, more homes near transit, and an overall higher number of homes than historical norms. -The RS Zone continues to be a key part of this story, with the 5-8 unit rowhome category leading the way in mature neighbourhoods. The data continues to show that when given the option, people choose to live in more central locations, even if not in a single-detached home. +2026 is shaping up to be another strong year for housing supply in Edmonton. We are building more homes in mature neighbourhoods, more types of homes, more homes near transit, and an overall higher number of homes than historical norms. The RS Zone continues to be a key part of this story, with the 5-8 unit rowhome category leading the way in mature neighbourhoods. The data continues to show that when given the option, people choose to live in more central locations, even if not in a single-detached home. We're already seeing the effects of increased housing supply in Edmonton over the past two years. Rents are coming down and landlords are offering incentives. With even more supply on the way, especially in mature neighbourhoods, I am excited about the potential for more affordable, transit-accessible housing options for Edmontonian families in the years to come. diff --git a/blog/2026/q2-building-permits/.Rprofile b/blog/2026/q2-building-permits/.Rprofile new file mode 100644 index 0000000..81b960f --- /dev/null +++ b/blog/2026/q2-building-permits/.Rprofile @@ -0,0 +1 @@ +source("renv/activate.R") diff --git a/blog/2026/q2-building-permits/bike_lanes_by_classification.png b/blog/2026/q2-building-permits/bike_lanes_by_classification.png new file mode 100644 index 0000000..079c52d Binary files /dev/null and b/blog/2026/q2-building-permits/bike_lanes_by_classification.png differ diff --git a/blog/2026/q2-building-permits/explore_bike_lanes.R b/blog/2026/q2-building-permits/explore_bike_lanes.R new file mode 100644 index 0000000..223235a --- /dev/null +++ b/blog/2026/q2-building-permits/explore_bike_lanes.R @@ -0,0 +1,30 @@ +# Standalone exploration script: map all Edmonton bike lane network segments +# coloured by classification. Not sourced by index.qmd -- run manually with +# `Rscript explore_bike_lanes.R` from this directory. + +library(tidyverse) +library(sf) +library(mountainmathHelpers) +library(jdawangHelpers) + +options(nextzen_API_key = Sys.getenv("NEXTZEN_API_KEY")) + +bike_lanes <- get_edmonton_bike_lane_data( + cache_dir = Sys.getenv("EDMONTON_BP_CACHE_PATH") +) + +crs <- lambert_conformal_conic_at(bike_lanes) +bike_lanes <- st_transform(bike_lanes, crs) + +p <- ggplot(bike_lanes) + + layers_map_base(mode = "light", roads_type = "all") + + geom_sf(aes(colour = classification), linewidth = 0.5) + + theme_map(mode = "light") + + theme_jd(mode = "light") + + labs( + title = "Edmonton bike lane network by classification", + colour = "Classification", + caption = CAPTION_COE + ) + +ggsave("bike_lanes_by_classification.png", p, width = 10, height = 10, dpi = 150) \ No newline at end of file diff --git a/blog/2026/q2-building-permits/index.qmd b/blog/2026/q2-building-permits/index.qmd new file mode 100644 index 0000000..a0a95f8 --- /dev/null +++ b/blog/2026/q2-building-permits/index.qmd @@ -0,0 +1,997 @@ +--- +title: "2026 H1 Edmonton building permit report" +date: "2026-07-09" +author: "Jacob Dawang" +categories: [housing, edmonton, zoning] +description: "Edmonton building permits slowed through the first half of 2026, but the RS Zone rowhome keeps setting records." +link-external-newwindow: true +link-external-icon: false +execute: + cache: true +image: rowhouse.jpg +--- + +It's July, so it's time for another check-in on building permits in Edmonton. 2025 was a [record year](../zbr-two-year-review/index.qmd) for the missing middle and [Q1 2026](../q1-building-permits/index.qmd) looked like it might continue that momentum. With a full six months of data now in hand, the picture has shifted: overall permit activity has slowed, driven by a lull in large apartment projects. But look past the apartment category, and the RS Zone rowhome story keeps getting stronger. + +In the rest of this post, I compare H1 2026 permits year-over-year against prior H1s, project what a full 2026 might look like if this pace holds, look at which neighbourhoods are seeing the most RS Zone infill, and check whether Edmonton is continuing to build close to transit. New this quarter, I took a look at the cumulative number of homes permitted since the RS Zone took effect in January 2024, and how that supply is distributed across neighbourhood types. I also added a look at frequent bus walksheds and if rowhomes are built close to the frequent bus network. + +![A rowhouse I biked by in Forest Heights](rowhouse.jpg){#fig-rowhouse-image fig-alt="A rowhouse in Forest Heights" width="538"} + +## Key facts + +```{r} +#| label: key-facts-setup +#| include: false +library(tidyverse) +library(sf) +library(gt) +library(mountainmathHelpers) +library(tidytransit) +library(jdawangHelpers) +options( + cancensus.api_key = Sys.getenv("CM_API_KEY"), + cancensus.cache_path = Sys.getenv("CM_CACHE_PATH"), + tongfen.cache_path = Sys.getenv("TONGFEN_CACHE_PATH"), + nextzen_API_key = Sys.getenv("NEXTZEN_API_KEY") +) + +bp_raw <- get_edmonton_building_permit_data( + cache_dir = Sys.getenv("EDMONTON_BP_CACHE_PATH") +) +crs <- lambert_conformal_conic_at(bp_raw) +bp_raw <- st_transform(bp_raw, crs) + +bp <- bp_raw |> + filter(year < 2026 | (year == 2026 & month_number <= 6)) |> + filter_edmonton_residential() |> + filter(units_added >= 1, work_type != "(04) Excavation") |> + add_edmonton_project_type() |> + add_edmonton_suite_info() |> + add_edmonton_neighbourhood_type() + +# H1 data for all years (for YoY comparison and transit) +bp_h1 <- bp |> filter(month_number <= 6) + +# Historical H1 vs full-year ratios (for multiplier) +h1_ratios <- bp |> + st_drop_geometry() |> + filter(year < 2026) |> + group_by(year) |> + summarize( + full_year = sum(units_added), + h1 = sum(units_added[month_number <= 6]), + .groups = "drop" + ) |> + mutate(ratio = full_year / h1) + +h1_multiplier <- round(median(h1_ratios$ratio), 1) + +# H1 2026 totals +h1_2026_total <- bp_h1 |> + st_drop_geometry() |> + filter(year == 2026) |> + summarize(total = sum(units_added)) |> + pull(total) + +h1_2025_total <- bp_h1 |> + st_drop_geometry() |> + filter(year == 2025) |> + summarize(total = sum(units_added)) |> + pull(total) + +yoy_pct <- round((h1_2026_total / h1_2025_total - 1) * 100, 1) +annualized_2026 <- round(h1_2026_total * h1_multiplier) + +# Transit proximity for H1 2026 +future_stops <- read_sf("../../../data/future_lrt_stops.geojson") |> + filter( + !(stop_name %in% + c( + "Castle Downs Station", + "145 Ave Station", + "137 Ave Station", + "132 Ave Station" + )) + ) + +transit_stops <- load_edmonton_transit_stops( + gtfs_path = "../../../data/ca-alberta-edmonton-transit-system-gtfs-714.zip", + service_date = as.Date("2023-11-09"), + future_stops = future_stops, + crs = crs +) + +pct_800m_h1_2026 <- bp_h1 |> + filter(year == 2026, !st_is_empty(geometry)) |> + add_transit_distance(transit_stops) |> + st_drop_geometry() |> + summarize( + pct = sum(units_added[distance_from_lrt <= 0.8]) / sum(units_added) + ) |> + pull(pct) + +pct_800m_2025 <- bp |> + filter(year == 2025, !st_is_empty(geometry)) |> + add_transit_distance(transit_stops) |> + st_drop_geometry() |> + summarize( + pct = sum(units_added[distance_from_lrt <= 0.8]) / sum(units_added) + ) |> + pull(pct) + +# Top project type in H1 2026 +top_project_type <- bp_h1 |> + st_drop_geometry() |> + filter(year == 2026) |> + group_by(project_type) |> + summarize(total = sum(units_added), .groups = "drop") |> + slice_max(total, n = 1) |> + pull(project_type) +``` + +- Edmonton issued building permits for **`r scales::comma(h1_2026_total)`** homes in H1 2026. Annualized, that projects to roughly **`r scales::comma(annualized_2026)`** homes for the full year. + +- Homes permitted in H1 2026 is **`r abs(yoy_pct)`%`r if(yoy_pct >= 0) " higher" else " lower"`** than H1 2025, when `r scales::comma(h1_2025_total)` homes were permitted. + +- **`r top_project_type`** projects led all categories by homes added in H1 2026. + +- **`r scales::percent(pct_800m_h1_2026, accuracy=1)`** of homes were permitted within 800m of an existing or under-construction LRT stop in H1 2026, compared to `r scales::percent(pct_800m_2025, accuracy=1)` in 2025 (full year). + +## Data + +```{r} +#| label: data-load +# bp, bp_h1, transit_stops are already loaded in key-facts-setup chunk above + +# Assessment data for neighbourhood tables +assessment_rs <- read_sf( + "../../../data/Property Information (Current Calendar Year)_20260113/" +) |> + st_drop_geometry() |> + rename( + house_number = house_numb, + street_name = street_nam, + neighbourhood = neighbou_2 + ) |> + filter(zoning == "RS", !is.na(house_number)) |> + distinct(house_number, street_name, .keep_all = TRUE) + +# Neighbourhood → neighbourhood_type lookup from bp +nbhd_type_lookup <- bp |> + st_drop_geometry() |> + distinct(neighbourhood, neighbourhood_type) |> + filter(!is.na(neighbourhood_type)) + +assessment_rs <- assessment_rs |> + left_join(nbhd_type_lookup, by = "neighbourhood") + +# Population and ward data +wards <- read_sf( + "../../../data/City_of_Edmonton_-_Neighbourhoods_20260417.geojson" +) |> + st_drop_geometry() |> + select(neighbourhood = name, Ward = civic_ward_name) + +population_1971 <- read_csv( + "../../../data/population_1971.csv", + show_col_types = FALSE +) |> + select(neighbourhood = Neighbourhood, n_1971 = `Total - Age`) + +population_2021 <- read_csv( + "../../../data/population_2021.csv", + show_col_types = FALSE +) |> + distinct() |> + rename(neighbourhood = NEIGHBOURHOOD, n_2021 = `2021`) + +population_change <- population_2021 |> + full_join(population_1971, by = "neighbourhood") |> + left_join(wards, by = "neighbourhood") |> + replace_na(list(n_2021 = 0, n_1971 = 0)) |> + mutate(pct_change = n_2021 / n_1971 - 1) +``` + +Edmonton's [general building permit data](https://data.edmonton.ca/Urban-Planning-Economy/General-Building-Permits/24uj-dj8v/about_data) tracks building permits since 2009, with columns for building type, work type, location, units added, and more. Unlike the [Q1 post](../q1-building-permits/index.qmd), which used a manually downloaded shapefile snapshot, this post fetches permit data directly from Edmonton's Open Data API, filtered to H1 (January through June) to exclude incomplete July data. + +Edmonton's [property assessment data](https://data.edmonton.ca/City-Administration/Property-Assessment-Data-Current-Calendar-Year-/q7d6-ambg/about_data) provides one row per property with zoning and neighbourhood information, used to calculate how many RS-zoned properties exist per neighbourhood. + +For background on the RS Zone and ZBR, see the [two-year review post](../zbr-two-year-review/index.qmd). + +Similar to my [Q1 post](../q1-building-permits/index.qmd), to annualize the 2026 H1 numbers to the full year, I estimate an annualization multiplier from historical data. For each year from 2009 to 2025, I calculate the ratio of full-year units to H1 units, and use the median as the multiplier. + +```{r} +#| label: fig-h1-multiplier +#| fig-cap: "Historical ratio of full-year to H1 residential building permit units" +ggplot(h1_ratios, aes(x = year, y = ratio)) + + geom_line(linewidth = 1) + + geom_point() + + geom_hline( + yintercept = h1_multiplier, + linetype = "dashed", + colour = "grey60" + ) + + annotate( + "text", + x = 2015, + y = h1_multiplier + 0.3, + label = paste0("Median: ", h1_multiplier), + size = 3.5 + ) + + labs( + title = "Ratio of full-year to H1 residential building permit units", + subtitle = "2009-2025", + x = "Year", + y = "Full-year / H1 ratio", + caption = CAPTION_COE + ) + + theme_jd(mode = "light") +``` + +The median H1 multiplier is `r h1_multiplier`×, as shown in @fig-h1-multiplier, meaning a full year typically produces `r h1_multiplier` times the homes permitted in H1 alone. All 2026 projections in this post use this multiplier. + +## Year-over-year H1 comparison + +The most direct way to compare H1 2026 to prior years is to look at H1 data across all years, stripping out seasonality entirely. @fig-h1-yoy-units shows units added in H1 for each year since 2009, broken down by project type. The overall dip is visible, but it's driven by the 9+ Apartment category, can vary year to year depending on when a handful of large projects happen to get building permits. The 5-8 unit rowhome, by contrast, keeps climbing, continuing the trend we've seen since ZBR came into effect. + +```{r} +#| label: fig-h1-yoy-units +#| fig-cap: "Total homes permitted in H1 by project type, 2009–2026" +#| fig-subcap: ["Line plot", "Area plot"] +h1_by_type <- bp_h1 |> + st_drop_geometry() |> + group_by(year, project_type, .drop = FALSE) |> + summarize(total = sum(units_added), num_projects = n(), .groups = "drop") + +ggplot(h1_by_type, aes(x = year, y = total, colour = project_type)) + + geom_line(linewidth = 1) + + geom_point() + + scale_y_continuous(labels = scales::label_comma()) + + labs( + title = "Homes permitted by project type", + subtitle = "H1 building permits, 2009–2026", + colour = "Project type", + x = "Year", + y = "Homes permitted", + caption = CAPTION_COE + ) + + theme_jd(mode = "light") + +ggplot(h1_by_type, aes(x = year, y = total, fill = project_type)) + + geom_area() + + scale_y_continuous(labels = scales::label_comma()) + + labs( + title = "Homes permitted by project type", + subtitle = "H1 building permits, 2009–2026", + fill = "Project type", + x = "Year", + y = "Homes permitted", + caption = CAPTION_COE + ) + + theme_jd(mode = "light") +``` + +@fig-h1-yoy-permits shows the same H1 data as raw permit counts rather than units, a complementary view for understanding how many discrete projects are driving each category. + +```{r} +#| label: fig-h1-yoy-permits +#| fig-cap: "Number of building permits issued in H1 by project type, 2009–2026" +#| fig-subcap: ["Line plot", "Area plot"] +ggplot(h1_by_type, aes(x = year, y = num_projects, colour = project_type)) + + geom_line(linewidth = 1) + + geom_point() + + scale_y_continuous(labels = scales::label_comma()) + + labs( + title = "Building permits issued by project type", + subtitle = "H1 building permits, 2009–2026", + colour = "Project type", + x = "Year", + y = "Number of permits", + caption = CAPTION_COE + ) + + theme_jd(mode = "light") + +ggplot(h1_by_type, aes(x = year, y = num_projects, fill = project_type)) + + geom_area() + + scale_y_continuous(labels = scales::label_comma()) + + labs( + title = "Building permits issued by project type", + subtitle = "H1 building permits, 2009–2026", + fill = "Project type", + x = "Year", + y = "Number of permits", + caption = CAPTION_COE + ) + + theme_jd(mode = "light") +``` + +Looking at the number of homes by neighbourhood type, @fig-h1-yoy-nbhd shows that mature neighbourhoods held up best in H1 2026, again driven by the 5-8 unit rowhome. The areas between the mature core and the Henday saw the sharpest pullback, largely reflecting fewer large apartment permits in those neighbourhoods this year so far. + +```{r} +#| label: fig-h1-yoy-nbhd +#| fig-cap: "Total homes permitted in H1 by neighbourhood type, 2009–2026" +#| fig-subcap: ["Line plot", "Area plot"] +h1_by_nbhd_type <- bp_h1 |> + st_drop_geometry() |> + filter(!is.na(neighbourhood_type)) |> + group_by(year, neighbourhood_type, project_type, .drop = FALSE) |> + summarize(total = sum(units_added), .groups = "drop") + +ggplot(h1_by_nbhd_type, aes(x = year, y = total, colour = project_type)) + + geom_line(linewidth = 1) + + geom_point() + + scale_y_continuous(labels = scales::label_comma()) + + facet_wrap(vars(neighbourhood_type)) + + labs( + title = "Homes permitted by neighbourhood type and project type", + subtitle = "H1 building permits, 2009–2026", + colour = "Project type", + x = "Year", + y = "Homes permitted", + caption = CAPTION_COE + ) + + theme_jd(mode = "light") + +ggplot(h1_by_nbhd_type, aes(x = year, y = total, fill = project_type)) + + geom_area() + + scale_y_continuous(labels = scales::label_comma()) + + facet_wrap(vars(neighbourhood_type)) + + labs( + title = "Homes permitted by neighbourhood type and project type", + subtitle = "H1 building permits, 2009–2026", + fill = "Project type", + x = "Year", + y = "Homes permitted", + caption = CAPTION_COE + ) + + theme_jd(mode = "light") +``` + +## Projecting 2026 from H1 data + +With half of the year under our belt, we can make a good guess as to how the rest of the year is trending. \@fig-annualized-units shows the full-year units added by project type, with 2026 projected from H1 using the `r h1_multiplier`× adjustment. + +The total projection lands below 2025's record, closer to 2024 levels. That's still a strong year, just not another record. As always, a handful of large apartment projects in the second half of the year could move this projection significantly. + +```{r} +#| label: fig-annualized-units +#| fig-cap: "Total homes permitted by project type, 2009–2025 (full year) and 2026 (projected from H1)" +#| fig-subcap: ["Line plot", "Area plot"] +annual_by_type <- bp |> + st_drop_geometry() |> + filter(year < 2026) |> + group_by(year, project_type, .drop = FALSE) |> + summarize(total = sum(units_added), num_projects = n(), .groups = "drop") + +projected_2026 <- bp_h1 |> + st_drop_geometry() |> + filter(year == 2026) |> + group_by(year, project_type, .drop = FALSE) |> + summarize( + total = sum(units_added) * h1_multiplier, + num_projects = n() * h1_multiplier, + .groups = "drop" + ) |> + mutate(projected = TRUE) + +plot_data <- bind_rows( + mutate(annual_by_type, projected = FALSE), + projected_2026 +) + +ggplot(plot_data, aes(x = year, y = total, colour = project_type)) + + geom_line(linewidth = 1) + + geom_point() + + scale_y_continuous(labels = scales::label_comma()) + + labs( + title = "Homes permitted by project type", + subtitle = paste0( + "Full year 2009–2025; 2026 projected from H1 (×", + h1_multiplier, + ")" + ), + colour = "Project type", + x = "Year", + y = "Homes permitted", + caption = CAPTION_COE + ) + + theme_jd(mode = "light") + +ggplot(plot_data, aes(x = year, y = total, fill = project_type)) + + geom_area() + + scale_y_continuous(labels = scales::label_comma()) + + labs( + title = "Homes permitted by project type", + subtitle = paste0( + "Full year 2009–2025; 2026 projected from H1 (×", + h1_multiplier, + ")" + ), + fill = "Project type", + x = "Year", + y = "Homes permitted", + caption = CAPTION_COE + ) + + theme_jd(mode = "light") +``` + +@fig-annualized-nbhd breaks the same projection down by neighbourhood type. Mature neighbourhoods are still projected to drive a significant amount of Edmonton's housing supply, driven by by the 5-8 unit rowhome category. While there has been anecdotes and discourse on social media about landlords of new rowhomes needing to lower rent to find tenants, it seems like we have not yet hit the rent floor where building permits will slow down. We are still playing catchup on years of suppressed demand to live centrally. + +The slowdown shows up mostly outside the mature core, where the apartment pipeline has thinned out this year. Nevertheless, the supply of homes outside the Henday is on track to remain relatively strong. + +```{r} +#| label: fig-annualized-nbhd +#| fig-cap: "Homes permitted by neighbourhood type, 2009–2025 (full year) and 2026 (projected from H1)" +#| fig-subcap: ["Line plot", "Area plot"] +#| classes: preview-image +annual_nbhd <- bp |> + st_drop_geometry() |> + filter(year < 2026, !is.na(neighbourhood_type)) |> + group_by(year, neighbourhood_type, project_type, .drop = FALSE) |> + summarize(total = sum(units_added), .groups = "drop") |> + mutate(projected = FALSE) + +projected_2026_nbhd <- bp_h1 |> + st_drop_geometry() |> + filter(year == 2026, !is.na(neighbourhood_type)) |> + group_by(year, neighbourhood_type, project_type, .drop = FALSE) |> + summarize(total = sum(units_added) * h1_multiplier, .groups = "drop") |> + mutate(projected = TRUE) + +plot_nbhd <- bind_rows(annual_nbhd, projected_2026_nbhd) + +ggplot(plot_nbhd, aes(x = year, y = total, colour = project_type)) + + geom_line(linewidth = 1) + + geom_point() + + scale_y_continuous(labels = scales::label_comma()) + + facet_wrap(vars(neighbourhood_type)) + + labs( + title = "Homes permitted by neighbourhood type and project type", + subtitle = paste0( + "Full year 2009–2025; 2026 projected from H1 (×", + h1_multiplier, + ")" + ), + colour = "Project type", + x = "Year", + y = "Homes permitted", + caption = CAPTION_COE + ) + + theme_jd(mode = "light") + +ggplot(plot_nbhd, aes(x = year, y = total, fill = project_type)) + + geom_area() + + scale_y_continuous(labels = scales::label_comma()) + + facet_wrap(vars(neighbourhood_type)) + + labs( + title = "Homes permitted by neighbourhood type and project type", + subtitle = paste0( + "Full year 2009–2025; 2026 projected from H1 (×", + h1_multiplier, + ")" + ), + fill = "Project type", + x = "Year", + y = "Homes permitted", + caption = CAPTION_COE + ) + + theme_jd(mode = "light") +``` + +## Cumulative homes since the RS Zone took effect + +Year-over-year comparisons and full-year projections are useful for tracking momentum, but they don't answer a simpler question: how many homes has the RS Zone actually delivered since it took effect? @fig-cumulative-nbhd tracks the running total of homes permitted each month since January 2024, split by neighbourhood type. + +```{r} +#| label: fig-cumulative-nbhd +#| fig-cap: "Cumulative homes permitted by neighbourhood type since the RS Zone took effect (Jan 2024)" +cumulative_since_zbr <- bp |> + st_drop_geometry() |> + filter(year >= 2024, !is.na(neighbourhood_type)) |> + mutate(month = make_date(year, month_number, 1)) |> + group_by(neighbourhood_type, month) |> + summarize(units = sum(units_added), .groups = "drop") |> + complete( + neighbourhood_type, + month = seq(make_date(2024, 1, 1), make_date(2026, 6, 1), by = "month"), + fill = list(units = 0) + ) |> + arrange(month) |> + group_by(neighbourhood_type) |> + mutate(cumulative = cumsum(units)) |> + ungroup() + +total_homes_since_zbr <- cumulative_since_zbr |> + filter(month == max(month)) |> + summarize(total = sum(cumulative)) |> + pull(total) + +mature_share_since_zbr <- cumulative_since_zbr |> + filter(month == max(month)) |> + summarize( + pct = cumulative[neighbourhood_type == "Mature"] / sum(cumulative) + ) |> + pull(pct) + +ggplot( + cumulative_since_zbr, + aes(x = month, y = cumulative, colour = neighbourhood_type) +) + + geom_line(linewidth = 1) + + scale_x_date(date_labels = "%b %Y", date_breaks = "6 months") + + scale_y_continuous(labels = scales::label_comma()) + + labs( + title = "Cumulative homes permitted since the RS Zone took effect", + subtitle = "By neighbourhood type, Jan 2024 – Jun 2026", + colour = "Neighbourhood type", + x = NULL, + y = "Cumulative homes permitted", + caption = CAPTION_COE + ) + + theme_jd(mode = "light") +``` + +Outside Henday still adds the most homes in raw terms, no surprise, since suburban subdivisions have plenty of vacant land left to build on. But watch the shape of the lines: mature neighbourhoods durably overtook the areas between the mature core and the Henday back in March 2025, and have kept climbing at a steeper pace ever since. Since January 2024, Edmonton has permitted `r scales::comma(total_homes_since_zbr)` homes, and `r scales::percent(mature_share_since_zbr, accuracy=1)` of them landed in mature neighbourhoods. + +## Top neighbourhoods for RS infill + +Where is the infill actually happening? And how does the level of activity compare to the total number of properties in each neighbourhood? + +@tbl-rs-nbhd-type shows the H1 2026 5–8 unit RS Zone permit activity by neighbourhood type, compared to the total number of RS-zoned properties. Even cumulatively over six months, the share of properties being redeveloped remains small. Once again: incremental growth. + +```{r} +#| label: tbl-rs-nbhd-type +#| tbl-cap: "RS Zone 5–8 unit permits vs total properties by neighbourhood type, H1 2026" +n_plexes_h1_2026 <- bp_h1 |> + st_drop_geometry() |> + filter( + year == 2026, + zoning == "RS", + between(units_added, 5, 8) + ) |> + group_by(neighbourhood_type) |> + summarize( + n_permits = n(), + total_units = sum(units_added), + .groups = "drop" + ) |> + mutate( + n_permits_projected = n_permits * h1_multiplier, + total_units_projected = total_units * h1_multiplier + ) + +n_assessed_rs_by_type <- assessment_rs |> + filter(!is.na(neighbourhood_type)) |> + group_by(neighbourhood_type) |> + summarize(n_properties = n(), .groups = "drop") + + +n_assessed_rs_by_type |> + left_join(n_plexes_h1_2026, by = "neighbourhood_type") |> + replace_na(list( + n_permits = 0, + total_units = 0, + n_permits_projected = 0, + total_units_projected = 0 + )) |> + mutate( + pct = n_permits / n_properties, + pct_projected = n_permits_projected / n_properties + ) |> + gt() |> + cols_move(n_properties, after = n_permits) |> + cols_move(pct, after = n_properties) |> + cols_move(pct_projected, after = n_permits_projected) |> + cols_align("left", columns = neighbourhood_type) |> + fmt_percent(columns = c(pct, pct_projected), decimals = 2) |> + fmt_integer( + columns = c( + n_permits, + n_properties, + total_units, + n_permits_projected, + total_units_projected, + ) + ) |> + cols_label( + neighbourhood_type = "Neighbourhood type", + n_properties = "RS-zoned properties", + n_permits = "Permits", + total_units = "Homes added", + pct = "% redeveloped", + n_permits_projected = "Permits", + total_units_projected = "Homes added", + pct_projected = "% redeveloped", + ) |> + tab_spanner(label = "H1 2026", columns = c(n_permits, total_units, pct)) |> + tab_spanner( + label = paste0("Projected 2026 (H1 ×", h1_multiplier, ")"), + columns = c(n_permits_projected, total_units_projected, pct_projected) + ) |> + tab_header( + title = "RS Zone intensity by neighbourhood type", + subtitle = "H1 2026, and projected 2026" + ) |> + finalize_gt() |> + opt_stylize_jd() +``` + +@tbl-top-neighbourhoods shows the top neighbourhoods by H1 2026 5–8 unit RS permit volume. These are the neighbourhoods where ZBR's effects are most visible right now. The west end neighbourhoods along the Valley Line West, and Prince Charles, continue to be popular, but as we will see in a map in @sec-transit, we're starting to see more development along the already-completed Valley Line East. + +```{r} +#| label: tbl-top-neighbourhoods +#| tbl-cap: "Top neighbourhoods by H1 2026 5–8 unit RS permits" +#| column: page +n_rs_by_nbhd <- assessment_rs |> + group_by(neighbourhood) |> + summarize(n_properties = n(), .groups = "drop") + +h1_2026_plexes_by_nbhd <- bp_h1 |> + st_drop_geometry() |> + filter( + year == 2026, + zoning == "RS", + between(units_added, 5, 8) + ) |> + group_by(neighbourhood) |> + summarize(n_permits = n(), units_added = sum(units_added), .groups = "drop") + +h1_2026_plexes_by_nbhd |> + left_join(n_rs_by_nbhd, by = "neighbourhood") |> + left_join(population_change, by = "neighbourhood") |> + mutate( + neighbourhood = str_to_title(neighbourhood), + pct_redevelop = n_permits / n_properties + ) |> + slice_max(n_permits, n = 5) |> + arrange(desc(n_permits)) |> + select(-Ward) |> + gt() |> + cols_move(n_properties, after = n_permits) |> + cols_move(pct_redevelop, after = n_properties) |> + cols_move(units_added, after = pct_redevelop) |> + cols_label( + neighbourhood = "Neighbourhood", + n_permits = "Permits", + units_added = "Homes added", + n_properties = "RS properties", + pct_redevelop = "% redeveloped", + n_2021 = "Population 2021", + n_1971 = "Population 1971", + pct_change = "Pop. change" + ) |> + fmt_integer( + columns = c(n_permits, units_added, n_properties, n_2021, n_1971) + ) |> + fmt_percent(columns = c(pct_redevelop, pct_change), decimals = 1) |> + tab_header( + title = "Top neighbourhoods by H1 2026 5–8 unit RS permits", + subtitle = "H1 2026 building permits" + ) |> + finalize_gt() |> + opt_stylize_jd() +``` + +Of course, @tbl-selected-neighbourhoods is the usual table for selected neighbourhoods that have been prominent in debates about RS Zone infill. Another 0.3% of properties redeveloped in Crestwood! + +```{r} +#| label: tbl-selected-neighbourhoods +#| tbl-cap: "Selected neighbourhood 5–8 unit RS profiles, H1 2026" +#| column: page +selected_nbhds <- c( + "GLENWOOD", + "GROVENOR", + "BRITANNIA YOUNGSTOWN", + "WESTMOUNT", + "MCKERNAN", + "BELGRAVIA", + "CRESTWOOD", + "PARKVIEW" +) + +h1_2026_plexes_by_nbhd |> + right_join( + tibble(neighbourhood = selected_nbhds), + by = "neighbourhood" + ) |> + replace_na(list(n_permits = 0, units_added = 0)) |> + left_join(n_rs_by_nbhd, by = "neighbourhood") |> + left_join(population_change, by = "neighbourhood") |> + mutate( + neighbourhood = str_to_title(neighbourhood), + pct_redevelop = n_permits / n_properties + ) |> + select(-Ward) |> + arrange(neighbourhood) |> + gt() |> + cols_move(n_properties, after = n_permits) |> + cols_move(pct_redevelop, after = n_properties) |> + cols_move(units_added, after = pct_redevelop) |> + cols_label( + neighbourhood = "Neighbourhood", + n_permits = "Permits", + units_added = "Homes added", + n_properties = "RS properties", + pct_redevelop = "% redeveloped", + n_2021 = "Population 2021", + n_1971 = "Population 1971", + pct_change = "Pop. change" + ) |> + fmt_integer( + columns = c(n_permits, units_added, n_properties, n_2021, n_1971) + ) |> + fmt_percent(columns = c(pct_redevelop, pct_change), decimals = 1) |> + tab_header( + title = "Selected neighbourhood 5–8 unit RS profiles", + subtitle = "H1 2026 building permits" + ) |> + finalize_gt() |> + opt_stylize_jd() +``` + +@tbl-cumulative-neighbourhoods is an interactive table with cumulative 2024 + 2025 + H1 2026 activity for all neighbourhoods. You can search for your neighbourhood, or sort by any column. + +```{r} +#| label: tbl-cumulative-neighbourhoods +#| tbl-cap: "Cumulative RS infill by neighbourhood, 2024–H1 2026 (interactive)" +#| column: page +cumulative_plexes_by_nbhd <- bp |> + st_drop_geometry() |> + filter( + year >= 2024, + zoning == "RS", + between(units_added, 5, 8) + ) |> + group_by( + nbhd_f = fct(neighbourhood, levels = unique(bp$neighbourhood)), + .drop = FALSE + ) |> + summarize( + n_permits = n(), + units_added = sum(units_added), + .groups = "drop" + ) |> + mutate(neighbourhood = as.character(nbhd_f), .keep = "unused") + +cumulative_plexes_by_nbhd |> + left_join(n_rs_by_nbhd, by = "neighbourhood") |> + left_join(population_change, by = "neighbourhood") |> + filter(!is.na(n_properties)) |> + mutate( + neighbourhood = str_to_title(neighbourhood), + pct_redevelop = n_permits / n_properties + ) |> + arrange(neighbourhood) |> + gt() |> + cols_move(Ward, after = neighbourhood) |> + cols_move(n_properties, after = n_permits) |> + cols_move(pct_redevelop, after = n_properties) |> + cols_move(units_added, after = pct_redevelop) |> + cols_label( + neighbourhood = "Neighbourhood", + Ward = "Ward", + n_permits = "Permits", + units_added = "Homes added", + n_properties = "RS properties", + pct_redevelop = "% redeveloped", + n_2021 = "Population 2021", + n_1971 = "Population 1971", + pct_change = "Pop. change" + ) |> + fmt_integer( + columns = c(n_permits, units_added, n_properties, n_2021, n_1971) + ) |> + fmt_percent(columns = c(pct_redevelop, pct_change), decimals = 1) |> + tab_header( + title = "Cumulative 5–8 unit RS permits by neighbourhood", + subtitle = "2024 + 2025 + H1 2026 building permits" + ) |> + finalize_gt(interactive = TRUE) |> + opt_stylize_jd() |> + sub_missing() +``` + +## The eight-unit concentration + +In 2025, projects with exactly eight units dominated the Fiveplex to Eightplex category in the RS Zone, a direct consequence of the eight-unit cap. @tbl-unit-breakdown covers all RS Zone permits from 1 to 8 units, comparing H1 2025 to H1 2026. The eight-unit rowhome has only become more dominant: it now accounts for a larger share of small-scale homes than it did a year ago, even as most other categories cooled off. + +Given that 8-unit projects continue to account for the largest share of small-scale supply, I am glad that City Council chose not to reduce the number of units permitted to 6. This is an evidence-backed choice that keeps paying dividends. + +```{r} +#| label: tbl-unit-breakdown +#| tbl-cap: "RS Zone 1-8 unit permits by exact unit count, H1 2025 vs H1 2026" +h1_unit_breakdown <- function(yr) { + bp_h1 |> + st_drop_geometry() |> + filter(year == yr, zoning == "RS", between(units_added, 1, 8)) |> + group_by(units_added) |> + summarize( + n_permits = n(), + total_units = sum(units_added), + .groups = "drop" + ) |> + rename_with(~ paste0(., "_", yr), c(n_permits, total_units)) +} + +h1_unit_breakdown(2025) |> + full_join(h1_unit_breakdown(2026), by = "units_added") |> + replace_na(list( + n_permits_2025 = 0, + total_units_2025 = 0, + n_permits_2026 = 0, + total_units_2026 = 0 + )) |> + arrange(units_added) |> + gt(rowname_col = "units_added") |> + cols_label( + n_permits_2025 = "Permits (H1 2025)", + total_units_2025 = "Homes (H1 2025)", + n_permits_2026 = "Permits (H1 2026)", + total_units_2026 = "Homes (H1 2026)" + ) |> + tab_stubhead("Units per permit") |> + fmt_integer(columns = everything()) |> + tab_header( + title = "RS Zone: permits by unit count", + subtitle = "H1 2025 vs. H1 2026" + ) |> + grand_summary_rows(fns = "sum") |> + finalize_gt() |> + opt_stylize_jd() +``` + +## Building close to transit {#sec-transit} + +2025 set a record for the proportion of homes permitted within 800m of transit. So far, 2026 is right in line with last year. @fig-ecdf-transit compares the cumulative distribution of H1 homes by distance from the nearest LRT stop, across recent years. H1 2026 is running in line with H1 2025, not the record pace 2025 ultimately closed the year at. + +Within 800m of transit, the cumulative share of homes is `r scales::percent(pct_800m_h1_2026, accuracy=1)` in H1 2026, compared to `r scales::percent(pct_800m_2025, accuracy=1)` in 2025 (full year). + +```{r} +#| label: fig-ecdf-transit +#| fig-cap: "Cumulative distribution of H1 homes by distance from nearest LRT stop" +bp |> + filter(!st_is_empty(geometry)) |> + add_transit_distance(transit_stops) |> + add_ecdf_by_distance(group_var = year) |> + st_drop_geometry() |> + ggplot() + + layers_transit_ecdf(colour_var = year, x_max = 8) + + labs( + title = "Where are homes being built relative to LRT?", + subtitle = "Cumulative distribution of homes by distance from nearest LRT stop", + x = "Distance from nearest LRT stop (km)", + y = "Cumulative share of homes", + colour = "Year", + caption = CAPTION_COE + ) + + theme_jd(mode = "light") +``` + +@fig-rowhome-lrt-dist-map shows that the 5-8 unit rowhomes continue to trace the path of the LRT. While we continue to see a lot of infill in the west end, the Valley Line East is starting to see more activity as well. I am glad to see this given some [less than ideal district plans](../../2023/avonmore-stop/index.qmd) for some of the stops along the Valley Line East. + +```{r} +#| label: fig-rowhome-lrt-dist-map +#| fig-cap: "Map of H1 2026 5–8 unit RS Zone permits relative to LRT" +buffers <- make_transit_buffers(transit_stops, radii_km = c(0.8, 1.5, 2)) + +ggplot(filter(buffers, radius == "2km")) + + layers_map_base(mode = "light", roads_type = "all") + + geom_sf( + data = buffers, + mapping = aes(linetype = radius), + colour = "firebrick" + ) + + scale_linetype_manual( + values = c("0.8km" = "dotted", "1.5km" = "dashed", "2km" = "solid") + ) + + geom_sf( + data = filter( + bp_h1, + year == 2026, + zoning == "RS", + between(units_added, 5, 8) + ), + size = 0.5, + colour = "steelblue" + ) + + geom_sf(data = transit_stops, shape = 21, colour = "firebrick", fill = NA) + + theme_map(mode = "light") + + labs( + title = "Map of all H1 2026 5–8 unit building permits in the RS Zone", + caption = CAPTION_COE + ) +``` + +### Beyond LRT: the frequent bus network + +LRT isn't Edmonton's only high-quality transit. ETS's Frequent Network, routes 1 through 9, is scheduled to run every 15 minutes throughout the day, seven days a week. Because buses have a shorter effective walkshed than LRT, I use a 400m threshold for frequent bus stops instead of the 800m threshold used for LRT throughout this post. @fig-ecdf-frequent-transit shows the same cumulative-distribution view as @fig-ecdf-transit, but for each home's raw distance to the nearer of LRT or a frequent bus stop, so you can directly see how much closer homes get once frequent buses are counted alongside LRT. Both walking thresholds are marked on the chart. + +```{r} +#| label: frequent-bus-setup +frequent_bus_stops <- get_edmonton_frequent_bus_stops( + gtfs_path = "../../../data/ca-alberta-edmonton-transit-system-gtfs-714.zip", + service_date = as.Date("2023-11-09"), + crs = crs +) + +bp_h1_2026_transit <- bp_h1 |> + filter(year == 2026, !st_is_empty(geometry)) |> + add_frequent_transit_distance(transit_stops, frequent_bus_stops) + +pct_frequent_transit_h1_2026 <- bp_h1_2026_transit |> + st_drop_geometry() |> + summarize( + pct = sum( + units_added[distance_from_lrt <= 0.8 | distance_from_frequent_bus <= 0.4] + ) / + sum(units_added) + ) |> + pull(pct) +``` + +```{r} +#| label: fig-ecdf-frequent-transit +#| fig-cap: "Cumulative distribution of H1 homes by raw distance to nearest LRT or frequent bus stop" +bp |> + filter(!st_is_empty(geometry)) |> + add_frequent_transit_distance(transit_stops, frequent_bus_stops) |> + add_frequent_transit_ecdf_by_distance(group_var = year) |> + st_drop_geometry() |> + ggplot() + + layers_frequent_transit_ecdf(colour_var = year, x_max = 8) + + labs( + title = "Where are homes being built relative to frequent transit?", + subtitle = "Cumulative distribution of homes by distance to nearest LRT or frequent bus stop", + x = "Distance from nearest LRT or frequent bus stop (km)", + y = "Cumulative share of homes", + colour = "Year", + caption = CAPTION_COE + ) + + theme_jd(mode = "light") +``` + +Counting the frequent bus network alongside LRT meaningfully expands how much of H1 2026's housing supply counts as close to high-quality transit: `r scales::percent(pct_frequent_transit_h1_2026, accuracy=1)` of homes were within 800m of LRT or 400m of a frequent bus stop, compared to `r scales::percent(pct_800m_h1_2026, accuracy=1)` for LRT alone. @fig-rowhome-frequent-transit-map shows both networks together, with LRT stops and their 800m radius in red and frequent bus stops and their 400m radius in orange. The frequent bus network fills in a lot of the gaps between LRT lines, especially along the west end and mature north-side neighbourhoods that aren't within easy walking distance of a station. + +```{r} +#| label: fig-rowhome-frequent-transit-map +#| fig-cap: "Map of H1 2026 5–8 unit RS Zone permits relative to LRT and the frequent bus network" +#| fig-width: 9 +#| fig-height: 6.5 +lrt_buffers <- make_transit_buffers(transit_stops, radii_km = 0.8) +bus_buffers <- make_transit_buffers(frequent_bus_stops, radii_km = 0.4) + +ggplot(bind_rows(lrt_buffers, bus_buffers)) + + layers_map_base(mode = "light", roads_type = "all") + + geom_sf(data = bus_buffers, colour = "darkorange", linewidth = 0.3) + + geom_sf(data = lrt_buffers, colour = "firebrick", linewidth = 0.3) + + geom_sf( + data = filter( + bp_h1, + year == 2026, + zoning == "RS", + between(units_added, 5, 8) + ), + size = 0.5, + colour = "steelblue" + ) + + theme_map(mode = "light") + + labs( + title = str_wrap( + "Map of all H1 2026 5–8 unit building permits, LRT, and the frequent bus network", + width = 55 + ), + subtitle = str_wrap( + "LRT stops and 800m radius in red, frequent bus stops and 400m radius in orange", + width = 60 + ), + caption = CAPTION_COE + ) +``` + +## Conclusions + +Overall building permit activity slowed in H1 2026 compared to 2025's record pace, but nearly all of that slowdown is explained by fewer large apartment projects, a category that has always been lumpy and unpredictable from year to year. Look at the RS Zone specifically, and the story is unambiguously positive: the 5-8 unit rowhome category continue to produce, mature neighbourhoods held up best of any area of the city, and the eight-unit rowhome is more dominant than ever within the small-scale category. + +We're already seeing the effects of increased housing supply in Edmonton over the past two years. Rents are coming down and landlords are offering incentives. Whether 2026 matches 2025's record total or not, the RS Zone continues to quietly deliver more homes in mature, transit-accessible neighbourhoods every quarter. + +The data continues to make the case for the RS Zone. Even in a slower year for permits overall, the policies that unlocked the missing middle keep producing results. 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Broom provides three verbs that each provide different types of information about a model. tidy() summarizes information about model components such as coefficients of a regression. glance() reports information about an entire model, such as goodness of fit measures like AIC and BIC. augment() adds information about individual observations to a dataset, such as fitted values or influence measures.", + "License": "MIT + file LICENSE", + "URL": "https://broom.tidymodels.org/, https://github.com/tidymodels/broom", + "BugReports": "https://github.com/tidymodels/broom/issues", + "Depends": [ + "R (>= 4.1)" + ], + "Imports": [ + "backports", + "cli", + "dplyr (>= 1.0.0)", + "generics (>= 0.0.2)", + "glue", + "lifecycle", + "purrr", + "rlang (>= 1.1.0)", + "stringr", + "tibble (>= 3.0.0)", + "tidyr (>= 1.0.0)" + ], + "Suggests": [ + "AER", + "AUC", + "bbmle", + "betareg (>= 3.2-1)", + "biglm", + "binGroup", + "boot", + "btergm (>= 1.10.6)", + "car (>= 3.1-2)", + "carData", + "caret", + 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Gray [ctb], Shabbh E. Banks [ctb], Serina Robinson [ctb], Roger Bivand [ctb], Riinu Ots [ctb], Nicholas Williams [ctb], Nina Jakobsen [ctb], Michael Weylandt [ctb], Lisa Lendway [ctb], Karl Hailperin [ctb], Josue Rodriguez [ctb], Jenny Bryan [ctb], Chris Jarvis [ctb], Greg Macfarlane [ctb], Brian Mannakee [ctb], Drew Tyre [ctb], Shreyas Singh [ctb], Laurens Geffert [ctb], Hong Ooi [ctb], Henrik Bengtsson [ctb], Eduard Szocs [ctb], David Hugh-Jones [ctb], Matthieu Stigler [ctb], Hugo Tavares [ctb] (ORCID: ), R. Willem Vervoort [ctb], Brenton M. Wiernik [ctb], Josh Yamamoto [ctb], Jasme Lee [ctb], Taren Sanders [ctb] (ORCID: ), Ilaria Prosdocimi [ctb] (ORCID: ), Daniel D. Sjoberg [ctb] (ORCID: ), Alex Reinhart [ctb] (ORCID: )", + "Maintainer": "Emil Hvitfeldt ", + "Repository": "CRAN" + }, + "bslib": { + "Package": "bslib", + "Version": "0.11.0", + "Source": "Repository", + "Title": "Custom 'Bootstrap' 'Sass' Themes for 'shiny' and 'rmarkdown'", + "Authors@R": "c( person(\"Carson\", \"Sievert\", , \"carson@posit.co\", role = c(\"aut\", \"cre\"), comment = c(ORCID = \"0000-0002-4958-2844\")), person(\"Joe\", \"Cheng\", , \"joe@posit.co\", role = \"aut\"), person(\"Garrick\", \"Aden-Buie\", , \"garrick@posit.co\", role = \"aut\", comment = c(ORCID = \"0000-0002-7111-0077\")), person(\"Posit Software, PBC\", role = c(\"cph\", \"fnd\")), person(, \"Bootstrap contributors\", role = \"ctb\", comment = \"Bootstrap library\"), person(, \"Twitter, Inc\", role = \"cph\", comment = \"Bootstrap library\"), person(\"Javi\", \"Aguilar\", role = c(\"ctb\", \"cph\"), comment = \"Bootstrap colorpicker library\"), person(\"Thomas\", \"Park\", role = c(\"ctb\", \"cph\"), comment = \"Bootswatch library\"), person(, \"PayPal\", role = c(\"ctb\", \"cph\"), comment = \"Bootstrap accessibility plugin\") )", + "Description": "Simplifies custom 'CSS' styling of both 'shiny' and 'rmarkdown' via 'Bootstrap' 'Sass'. 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Most R users don't need to use this package directly, but other R packages (e.g. 'shiny', 'rmarkdown', etc.) depend on this package to avoid bundling redundant copies of 'jQuery'.", + "License": "MIT + file LICENSE", + "Encoding": "UTF-8", + "Config/testthat/edition": "3", + "RoxygenNote": "7.0.2", + "Imports": [ + "htmltools" + ], + "Suggests": [ + "testthat" + ], + "NeedsCompilation": "no", + "Author": "Carson Sievert [aut, cre] (), Joe Cheng [aut], RStudio [cph], jQuery Foundation [cph] (jQuery library and jQuery UI library), jQuery contributors [ctb, cph] (jQuery library; authors listed in inst/lib/jquery-AUTHORS.txt)", + "Maintainer": "Carson Sievert ", + "Repository": "CRAN" + }, + "jsonify": { + "Package": "jsonify", + "Version": "1.2.3", + "Source": "Repository", + "Type": "Package", + "Title": "Convert Between 'R' Objects and Javascript Object Notation (JSON)", + "Date": "2025-11-24", + "Authors@R": "c( person(\"David\", \"Cooley\", ,\"dcooley@symbolix.com.au\", role = c(\"aut\", \"cre\")), person(\"Chris\", \"Muir\", role = \"ctb\"), person(\"Brendan\", \"Knapp\", role = \"ctb\", comment = c(ORCID = \"0000-0003-3284-4972\")) )", + "Description": "Conversions between 'R' objects and Javascript Object Notation (JSON) using the 'rapidjsonr' library .", + "License": "MIT + file LICENSE", + "Depends": [ + "R (>= 4.0.0)" + ], + "Imports": [ + "Rcpp (>= 1.1.0)" + ], + "LinkingTo": [ + "rapidjsonr (>= 1.2.1)", + "Rcpp" + ], + "RoxygenNote": "7.3.2", + "Suggests": [ + "covr", + "testthat", + "knitr", + "rmarkdown" + ], + "Encoding": "UTF-8", + "URL": "https://symbolixau.github.io/jsonify/, https://github.com/SymbolixAU/jsonify", + "BugReports": "https://github.com/SymbolixAU/jsonify/issues", + "NeedsCompilation": "yes", + "Author": "David Cooley [aut, cre], Chris Muir [ctb], Brendan Knapp [ctb] (ORCID: )", + "Maintainer": "David Cooley ", + "Repository": "CRAN" + }, + "jsonlite": { + "Package": "jsonlite", + "Version": "2.0.0", + "Source": "Repository", + "Title": "A Simple and Robust JSON Parser and Generator for R", + "License": "MIT + file LICENSE", + "Depends": [ + "methods" + ], + "Authors@R": "c( person(\"Jeroen\", \"Ooms\", role = c(\"aut\", \"cre\"), email = \"jeroenooms@gmail.com\", comment = c(ORCID = \"0000-0002-4035-0289\")), person(\"Duncan\", \"Temple Lang\", role = \"ctb\"), person(\"Lloyd\", \"Hilaiel\", role = \"cph\", comment=\"author of bundled libyajl\"))", + "URL": "https://jeroen.r-universe.dev/jsonlite https://arxiv.org/abs/1403.2805", + "BugReports": "https://github.com/jeroen/jsonlite/issues", + "Maintainer": "Jeroen Ooms ", + "VignetteBuilder": "knitr, R.rsp", + "Description": "A reasonably fast JSON parser and generator, optimized for statistical data and the web. 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A prime example of this is HTML email. This transformation involves moving the CSS and associated formatting instructions from the style block in the head of your document into the body of the HTML. Many prominent email clients require integrated styles in HTML email; otherwise a received HTML email will be displayed without any styling. This package will quickly and precisely perform these CSS transformations when given HTML text and it does so by using the JavaScript 'juice' library.", + "License": "MIT + file LICENSE", + "URL": "https://github.com/rich-iannone/juicyjuice", + "BugReports": "https://github.com/rich-iannone/juicyjuice/issues", + "Encoding": "UTF-8", + "RoxygenNote": "7.2.1", + "Imports": [ + "V8 (>= 4.2.0)" + ], + "Suggests": [ + "testthat (>= 3.0.0)" + ], + "Config/testthat/edition": "3", + "NeedsCompilation": "no", + "Author": "Richard Iannone [aut, cre, cph] (), Automattic [cph] (juice library), juice contributors [ctb] (juice library)", + "Maintainer": "Richard Iannone ", + "Repository": "CRAN" + }, + "knitr": { + "Package": "knitr", + "Version": "1.51", + "Source": "Repository", + "Type": "Package", + "Title": "A General-Purpose Package for Dynamic Report Generation in R", + "Authors@R": "c( person(\"Yihui\", \"Xie\", role = c(\"aut\", \"cre\"), email = \"xie@yihui.name\", comment = c(ORCID = 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The function rst2pdf() requires rst2pdf (https://github.com/rst2pdf/rst2pdf).", + "Collate": "'block.R' 'cache.R' 'citation.R' 'hooks-html.R' 'plot.R' 'utils.R' 'defaults.R' 'concordance.R' 'engine.R' 'highlight.R' 'themes.R' 'header.R' 'hooks-asciidoc.R' 'hooks-chunk.R' 'hooks-extra.R' 'hooks-latex.R' 'hooks-md.R' 'hooks-rst.R' 'hooks-textile.R' 'hooks.R' 'otel.R' 'output.R' 'package.R' 'pandoc.R' 'params.R' 'parser.R' 'pattern.R' 'rocco.R' 'spin.R' 'table.R' 'template.R' 'utils-conversion.R' 'utils-rd2html.R' 'utils-string.R' 'utils-sweave.R' 'utils-upload.R' 'utils-vignettes.R' 'zzz.R'", + "RoxygenNote": "7.3.3", + "NeedsCompilation": "no", + "Author": "Yihui Xie [aut, cre] (ORCID: , URL: https://yihui.org), Abhraneel Sarma [ctb], Adam Vogt [ctb], Alastair Andrew [ctb], Alex Zvoleff [ctb], Amar Al-Zubaidi [ctb], Andre Simon [ctb] (the CSS files under inst/themes/ were derived from the Highlight package http://www.andre-simon.de), Aron Atkins [ctb], Aaron Wolen [ctb], Ashley Manton [ctb], Atsushi Yasumoto [ctb] (ORCID: ), Ben Baumer [ctb], Brian Diggs [ctb], Brian Zhang [ctb], Bulat Yapparov [ctb], Cassio Pereira [ctb], Christophe Dervieux [ctb], David Hall [ctb], David Hugh-Jones [ctb], David Robinson [ctb], Doug Hemken [ctb], Duncan Murdoch [ctb], Elio Campitelli [ctb], Ellis Hughes [ctb], Emily Riederer [ctb], Fabian Hirschmann [ctb], Fitch Simeon [ctb], Forest Fang [ctb], Frank E Harrell Jr [ctb] (the Sweavel package at inst/misc/Sweavel.sty), Garrick Aden-Buie [ctb], Gregoire Detrez [ctb], Hadley Wickham [ctb], Hao Zhu [ctb], Heewon Jeon [ctb], Henrik Bengtsson [ctb], Hiroaki Yutani [ctb], Ian Lyttle [ctb], Hodges Daniel [ctb], Jacob Bien [ctb], Jake Burkhead [ctb], James Manton [ctb], Jared Lander [ctb], Jason Punyon [ctb], Javier Luraschi [ctb], Jeff Arnold [ctb], Jenny Bryan [ctb], Jeremy Ashkenas [ctb, cph] (the CSS file at inst/misc/docco-classic.css), Jeremy Stephens [ctb], Jim Hester [ctb], Joe Cheng [ctb], Johannes Ranke [ctb], John Honaker [ctb], John Muschelli [ctb], Jonathan Keane [ctb], JJ Allaire [ctb], Johan Toloe [ctb], Jonathan Sidi [ctb], Joseph Larmarange [ctb], Julien Barnier [ctb], Kaiyin Zhong [ctb], Kamil Slowikowski [ctb], Karl Forner [ctb], Kevin K. 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Kamvar [ctb] (ORCID: ), Posit Software, PBC [cph, fnd]", + "Maintainer": "Yihui Xie ", + "Repository": "CRAN" + }, + "labeling": { + "Package": "labeling", + "Version": "0.4.3", + "Source": "Repository", + "Type": "Package", + "Title": "Axis Labeling", + "Date": "2023-08-29", + "Author": "Justin Talbot,", + "Maintainer": "Nuno Sempere ", + "Description": "Functions which provide a range of axis labeling algorithms.", + "License": "MIT + file LICENSE | Unlimited", + "Collate": "'labeling.R'", + "NeedsCompilation": "no", + "Imports": [ + "stats", + "graphics" + ], + "Repository": "CRAN" + }, + "lattice": { + "Package": "lattice", + "Version": "0.22-9", + "Source": "Repository", + "Date": "2026-02-03", + "Priority": "recommended", + "Title": "Trellis Graphics for R", + "Authors@R": "c(person(\"Deepayan\", \"Sarkar\", role = c(\"aut\", \"cre\"), email = \"deepayan.sarkar@r-project.org\", comment = c(ORCID = \"0000-0003-4107-1553\")), person(\"Felix\", \"Andrews\", role = \"ctb\"), person(\"Kevin\", \"Wright\", role = \"ctb\", comment = \"documentation\"), person(\"Neil\", \"Klepeis\", role = \"ctb\"), person(\"Johan\", \"Larsson\", role = \"ctb\", comment = \"miscellaneous improvements\"), person(\"Zhijian (Jason)\", \"Wen\", role = \"cph\", comment = \"filled contour code\"), person(\"Paul\", \"Murrell\", role = \"ctb\", email = \"paul@stat.auckland.ac.nz\"), person(\"Stefan\", \"Eng\", role = \"ctb\", comment = \"violin plot improvements\"), person(\"Achim\", \"Zeileis\", role = \"ctb\", comment = \"modern colors\"), person(\"Alexandre\", \"Courtiol\", role = \"ctb\", comment = \"generics for larrows, lpolygon, lrect and lsegments\") )", + "Description": "A powerful and elegant high-level data visualization system inspired by Trellis graphics, with an emphasis on multivariate data. Lattice is sufficient for typical graphics needs, and is also flexible enough to handle most nonstandard requirements. 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These maps can be used directly from the R console, from 'RStudio', in Shiny applications and R Markdown documents.", + "License": "MIT + file LICENSE", + "URL": "https://rstudio.github.io/leaflet/, https://github.com/rstudio/leaflet", + "BugReports": "https://github.com/rstudio/leaflet/issues", + "Depends": [ + "R (>= 3.5)" + ], + "Imports": [ + "crosstalk", + "htmltools", + "htmlwidgets (>= 1.5.4)", + "jquerylib", + "leaflet.providers (>= 2.0.0)", + "magrittr", + "methods", + "png", + "raster (>= 3.6.3)", + "RColorBrewer", + "rlang", + "scales (>= 1.0.0)", + "sf (>= 0.9-6)", + "stats", + "viridisLite", + "xfun" + ], + "Suggests": [ + "knitr", + "maps", + "purrr", + "R6", + "RJSONIO", + "rmarkdown", + "s2", + "shiny (>= 1.0.0)", + "sp", + "terra", + "testthat (>= 3.0.0)" + ], + "Config/Needs/website": "dplyr, ncdf4, rnaturalearth, tidyverse/tidytemplate", + "Config/testthat/edition": "3", + "Encoding": "UTF-8", + "LazyData": "true", + "RoxygenNote": "7.3.2", + "NeedsCompilation": "no", + "Author": "Joe Cheng [aut], Barret Schloerke [aut] (ORCID: ), Bhaskar Karambelkar [aut], Yihui Xie [aut], Garrick Aden-Buie [aut, cre] (ORCID: ), Hadley Wickham [ctb], Kenton Russell [ctb], Kent Johnson [ctb], Vladimir Agafonkin [ctb, cph] (Leaflet library), CloudMade [cph] (Leaflet library), Leaflet contributors [ctb] (Leaflet library), Brandon Copeland [ctb, cph] (leaflet-measure plugin), Joerg Dietrich [ctb, cph] (Leaflet.Terminator plugin), Benjamin Becquet [ctb, cph] (Leaflet.MagnifyingGlass plugin), Norkart AS [ctb, cph] (Leaflet.MiniMap plugin), L. 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Additionally, 'leaflet.providers' enables users to retrieve up-to-date provider information between package updates.", + "License": "BSD_2_clause + file LICENSE", + "URL": "https://rstudio.github.io/leaflet.providers/, https://github.com/rstudio/leaflet.providers", + "BugReports": "https://github.com/rstudio/leaflet.providers/issues", + "Depends": [ + "R (>= 2.10)" + ], + "Imports": [ + "htmltools" + ], + "Suggests": [ + "jsonlite", + "testthat (>= 3.0.0)", + "V8" + ], + "Config/Needs/website": "tidyverse/tidytemplate", + "Config/testthat/edition": "3", + "Encoding": "UTF-8", + "Language": "en-US", + "RoxygenNote": "7.3.3", + "Collate": "'providers_data.R' 'get_current_providers.R' 'leaflet.providers-package.R' 'zzz.R'", + "NeedsCompilation": "no", + "Author": "Leslie Huang [aut], Barret Schloerke [ctb, cre] (ORCID: ), Leaflet Providers contributors [ctb, cph] (Leaflet Providers plugin), Posit Software, PBC [cph, fnd] (ROR: )", + "Maintainer": "Barret Schloerke ", + "Repository": "CRAN" + }, + "lifecycle": { + "Package": "lifecycle", + "Version": "1.0.5", + "Source": "Repository", + "Title": "Manage the Life Cycle of your Package Functions", + "Authors@R": "c( person(\"Lionel\", \"Henry\", , \"lionel@posit.co\", role = c(\"aut\", \"cre\")), person(\"Hadley\", \"Wickham\", , \"hadley@posit.co\", role = \"aut\", comment = c(ORCID = \"0000-0003-4757-117X\")), person(\"Posit Software, PBC\", role = c(\"cph\", \"fnd\")) )", + "Description": "Manage the life cycle of your exported functions with shared conventions, documentation badges, and user-friendly deprecation warnings.", + "License": "MIT + file LICENSE", + "URL": "https://lifecycle.r-lib.org/, https://github.com/r-lib/lifecycle", + "BugReports": "https://github.com/r-lib/lifecycle/issues", + "Depends": [ + "R (>= 3.6)" + ], + "Imports": [ + "cli (>= 3.4.0)", + "rlang (>= 1.1.0)" + ], + "Suggests": [ + "covr", + "knitr", + "lintr (>= 3.1.0)", + "rmarkdown", + "testthat (>= 3.0.1)", + "tibble", + "tidyverse", + "tools", + "vctrs", + "withr", + "xml2" + ], + "VignetteBuilder": "knitr", + "Config/Needs/website": "tidyverse/tidytemplate, usethis", + "Config/testthat/edition": "3", + "Encoding": "UTF-8", + "RoxygenNote": "7.3.3", + "NeedsCompilation": "no", + "Author": "Lionel Henry [aut, cre], Hadley Wickham [aut] (ORCID: ), Posit Software, PBC [cph, fnd]", + "Maintainer": "Lionel Henry ", + "Repository": "CRAN" + }, + "litedown": { + "Package": "litedown", + "Version": "0.9", + "Source": "Repository", + "Type": "Package", + "Title": "A Lightweight Version of R Markdown", + "Authors@R": "c( person(\"Yihui\", \"Xie\", role = c(\"aut\", \"cre\"), email = \"xie@yihui.name\", comment = c(ORCID = \"0000-0003-0645-5666\", URL = \"https://yihui.org\")), person(\"Tim\", \"Taylor\", role = \"ctb\", comment = c(ORCID = \"0000-0002-8587-7113\")), person() )", + "Description": "Render R Markdown to Markdown (without using 'knitr'), and Markdown to lightweight HTML or 'LaTeX' documents with the 'commonmark' package (instead of 'Pandoc'). Some missing Markdown features in 'commonmark' are also supported, such as raw HTML or 'LaTeX' blocks, 'LaTeX' math, superscripts, subscripts, footnotes, element attributes, and appendices, but not all 'Pandoc' Markdown features are (or will be) supported. With additional JavaScript and CSS, you can also create HTML slides and articles. This package can be viewed as a trimmed-down version of R Markdown and 'knitr'. It does not aim at rich Markdown features or a large variety of output formats (the primary formats are HTML and 'LaTeX'). Book and website projects of multiple input documents are also supported.", + "Depends": [ + "R (>= 3.2.0)" + ], + "Imports": [ + "utils", + "commonmark (>= 2.0.0)", + "xfun (>= 0.55)" + ], + "Suggests": [ + "rbibutils", + "rstudioapi", + "tinytex" + ], + "License": "MIT + file LICENSE", + "URL": "https://github.com/yihui/litedown", + "BugReports": "https://github.com/yihui/litedown/issues", + "VignetteBuilder": "litedown", + "RoxygenNote": "7.3.3", + "Encoding": "UTF-8", + "NeedsCompilation": "no", + "Author": "Yihui Xie [aut, cre] (ORCID: , URL: https://yihui.org), Tim Taylor [ctb] (ORCID: )", + "Maintainer": "Yihui Xie ", + "Repository": "CRAN" + }, + "lubridate": { + "Package": "lubridate", + "Version": "1.9.5", + "Source": "Repository", + "Type": "Package", + "Title": "Make Dealing with Dates a Little Easier", + "Authors@R": "c( person(\"Vitalie\", \"Spinu\", , \"spinuvit@gmail.com\", role = c(\"aut\", \"cre\")), person(\"Garrett\", \"Grolemund\", role = \"aut\"), person(\"Hadley\", \"Wickham\", role = \"aut\"), person(\"Davis\", \"Vaughan\", role = \"ctb\"), person(\"Ian\", \"Lyttle\", role = \"ctb\"), person(\"Imanuel\", \"Costigan\", role = \"ctb\"), person(\"Jason\", \"Law\", role = \"ctb\"), person(\"Doug\", \"Mitarotonda\", role = \"ctb\"), person(\"Joseph\", \"Larmarange\", role = \"ctb\"), person(\"Jonathan\", \"Boiser\", role = \"ctb\"), person(\"Chel Hee\", \"Lee\", role = \"ctb\") )", + "Maintainer": "Vitalie Spinu ", + "Description": "Functions to work with date-times and time-spans: fast and user friendly parsing of date-time data, extraction and updating of components of a date-time (years, months, days, hours, minutes, and seconds), algebraic manipulation on date-time and time-span objects. 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[cph] (Original s2geometry.io source code)", + "Maintainer": "Edzer Pebesma ", + "Repository": "P3M" + }, + "sass": { + "Package": "sass", + "Version": "0.4.10", + "Source": "Repository", + "Type": "Package", + "Title": "Syntactically Awesome Style Sheets ('Sass')", + "Description": "An 'SCSS' compiler, powered by the 'LibSass' library. With this, R developers can use variables, inheritance, and functions to generate dynamic style sheets. 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equivalent XPath expression. This allows us to use CSS selectors when working with the XML package as it can only evaluate XPath expressions. Also provided are convenience functions useful for using CSS selectors on XML nodes. This package is a port of the Python package 'cssselect' ().", + "NeedsCompilation": "no", + "Author": "Simon Potter [aut, trl, cre], Simon Sapin [aut], Ian Bicking [aut]", + "Maintainer": "Simon Potter ", + "Repository": "P3M" + }, + "sf": { + "Package": "sf", + "Version": "1.1-1", + "Source": "Repository", + "Title": "Simple Features for R", + "Authors@R": "c(person(given = \"Edzer\", family = \"Pebesma\", role = c(\"aut\", \"cre\"), email = \"edzer.pebesma@uni-muenster.de\", comment = c(ORCID = \"0000-0001-8049-7069\")), person(given = \"Roger\", family = \"Bivand\", role = \"ctb\", comment = c(ORCID = \"0000-0003-2392-6140\")), person(given = \"Etienne\", family = \"Racine\", role = \"ctb\"), person(given = \"Michael\", family = \"Sumner\", role = \"ctb\"), person(given = \"Ian\", family = \"Cook\", role = \"ctb\"), person(given = \"Tim\", family = \"Keitt\", role = \"ctb\"), person(given = \"Robin\", family = \"Lovelace\", role = \"ctb\"), person(given = \"Hadley\", family = \"Wickham\", role = \"ctb\"), person(given = \"Jeroen\", family = \"Ooms\", role = \"ctb\", comment = c(ORCID = \"0000-0002-4035-0289\")), person(given = \"Kirill\", family = \"M\\u00fcller\", role = \"ctb\"), person(given = \"Thomas Lin\", family = \"Pedersen\", role = \"ctb\"), person(given = \"Dan\", family = \"Baston\", role = \"ctb\"), person(given = \"Dewey\", family = \"Dunnington\", role = \"ctb\", comment = c(ORCID = \"0000-0002-9415-4582\")), person(given = \"Alexandre\", family = \"Courtiol\", role = \"ctb\", comment = c(ORCID = \"0000-0003-0637-2959\")) )", + "Description": "Support for simple feature access, a standardized way to encode and analyze spatial vector data. Binds to 'GDAL' for reading and writing data, to 'GEOS' for geometrical operations, and to 'PROJ' for projection conversions and datum transformations. Uses by default the 's2' package for geometry operations on geodetic (long/lat degree) coordinates.", + "License": "GPL-2 | MIT + file LICENSE", + "URL": "https://r-spatial.github.io/sf/, https://github.com/r-spatial/sf", + "BugReports": "https://github.com/r-spatial/sf/issues", + "Depends": [ + "methods", + "R (>= 4.1.0)" + ], + "Imports": [ + "classInt (>= 0.4-1)", + "DBI (>= 0.8)", + "graphics", + "grDevices", + "grid", + "s2 (>= 1.1.0)", + "stats", + "tools", + "units (>= 0.7-0)", + "utils" + ], + "Suggests": [ + "blob", + "nanoarrow", + "covr", + "dplyr (>= 1.0.0)", + "ggplot2", + "knitr", + "lwgeom (>= 0.2-14)", + "maps", + "mapview", + "Matrix", + "microbenchmark", + "odbc", + "pbapply", + "pillar", + "pool", + "raster", + "rlang", + "rmarkdown", + "RPostgres (>= 1.1.0)", + "RPostgreSQL", + "RSQLite", + "sp (>= 1.2-4)", + "spatstat (>= 2.0-1)", + "spatstat.geom", + "spatstat.random", + "spatstat.linnet", + "spatstat.utils", + "stars (>= 0.6-0)", + "terra", + "testthat (>= 3.0.0)", + "tibble (>= 1.4.1)", + "tidyr (>= 1.2.0)", + "tidyselect (>= 1.0.0)", + "tmap (>= 2.0)", + "vctrs", + "wk (>= 0.9.0)" + ], + "LinkingTo": [ + "Rcpp" + ], + "VignetteBuilder": "knitr", + "Encoding": "UTF-8", + "Config/testthat/edition": "2", + "Config/needs/coverage": "XML", + "SystemRequirements": "GDAL (>= 2.0.1), GEOS (>= 3.4.0), PROJ (>= 4.8.0), sqlite3", + "Collate": "'RcppExports.R' 'init.R' 'import-standalone-s3-register.R' 'crs.R' 'bbox.R' 'read.R' 'db.R' 'sfc.R' 'sfg.R' 'sf.R' 'bind.R' 'wkb.R' 'wkt.R' 'plot.R' 'geom-measures.R' 'geom-predicates.R' 'geom-transformers.R' 'transform.R' 'proj.R' 'sp.R' 'grid.R' 'arith.R' 'tidyverse.R' 'tidyverse-vctrs.R' 'cast_sfg.R' 'cast_sfc.R' 'graticule.R' 'datasets.R' 'aggregate.R' 'agr.R' 'maps.R' 'join.R' 'sample.R' 'valid.R' 'collection_extract.R' 'jitter.R' 'sgbp.R' 'spatstat.R' 'stars.R' 'crop.R' 'gdal_utils.R' 'nearest.R' 'normalize.R' 'sf-package.R' 'defunct.R' 'z_range.R' 'm_range.R' 'shift_longitude.R' 'make_grid.R' 's2.R' 'terra.R' 'geos-overlayng.R' 'break_antimeridian.R'", + "Config/roxygen2/version": "8.0.0", + "NeedsCompilation": "yes", + "Author": "Edzer Pebesma [aut, cre] (ORCID: ), Roger Bivand [ctb] (ORCID: ), Etienne Racine [ctb], Michael Sumner [ctb], Ian Cook [ctb], Tim Keitt [ctb], Robin Lovelace [ctb], Hadley Wickham [ctb], Jeroen Ooms [ctb] (ORCID: ), Kirill Müller [ctb], Thomas Lin Pedersen [ctb], Dan Baston [ctb], Dewey Dunnington [ctb] (ORCID: ), Alexandre Courtiol [ctb] (ORCID: )", + "Maintainer": "Edzer Pebesma ", + "Repository": "P3M" + }, + "sfheaders": { + "Package": "sfheaders", + "Version": "0.4.5", + "Source": "Repository", + "Type": "Package", + "Title": "Converts Between R Objects and Simple Feature Objects", + "Date": "2025-11-24", + "Authors@R": "c( person(\"David\", \"Cooley\", ,\"david.cooley.au@gmail.com\", role = c(\"aut\", \"cre\")), person(given = \"Michael\", family = \"Sumner\", role = \"ctb\") )", + "Description": "Converts between R and Simple Feature 'sf' objects, without depending on the Simple Feature library. Conversion functions are available at both the R level, and through 'Rcpp'.", + "License": "MIT + file LICENSE", + "URL": "https://dcooley.github.io/sfheaders/", + "BugReports": "https://github.com/dcooley/sfheaders/issues", + "Encoding": "UTF-8", + "RoxygenNote": "7.3.2", + "Depends": [ + "R (>= 3.0.2)" + ], + "LinkingTo": [ + "geometries (>= 0.2.5)", + "Rcpp" + ], + "Imports": [ + "Rcpp (>= 1.1.0)" + ], + "Suggests": [ + "covr", + "knitr", + "testthat" + ], + "NeedsCompilation": "yes", + "Author": "David Cooley [aut, cre], Michael Sumner [ctb]", + "Maintainer": "David Cooley ", + "Repository": "CRAN" + }, + "slippymath": { + "Package": "slippymath", + "Version": "0.3.1", + "Source": "Repository", + "Title": "Slippy Map Tile Tools", + "Authors@R": "c( person(\"Miles\", \"McBain\", email = \"miles.mcbain@gmail.com\", role = c(\"aut\", \"cre\"), comment = c(ORCID = \"0000-0003-2865-2548\")), person(\"Michael\",\"Sumner\", email = \"mdsumner@gmail.com\", role = c(\"aut\")))", + "Description": "Provides functions for performing common tasks when working with slippy map tile service APIs e.g. Google maps, Open Street Map, Mapbox, Stamen, among others. Functionality includes converting from latitude and longitude to tile numbers, determining tile bounding boxes, and compositing tiles to a georeferenced raster image.", + "Depends": [ + "R (>= 3.5.0)" + ], + "License": "MIT + file LICENSE", + "URL": "https://www.github.com/milesmcbain/slippymath", + "BugReports": "https://www.github.com/milesmcbain/slippymath/issues", + "Encoding": "UTF-8", + "LazyData": "true", + "Imports": [ + "raster", + "purrr", + "stats", + "png" + ], + "Suggests": [ + "testthat", + "knitr", + "rmarkdown" + ], + "RoxygenNote": "6.1.1", + "VignetteBuilder": "knitr", + "NeedsCompilation": "no", + "Author": "Miles McBain [aut, cre] (), Michael Sumner [aut]", + "Maintainer": "Miles McBain ", + "Repository": "CRAN" + }, + "sp": { + "Package": "sp", + "Version": "2.2-1", + "Source": "Repository", + "Title": "Classes and Methods for Spatial Data", + "Authors@R": "c(person(\"Edzer\", \"Pebesma\", role = c(\"aut\", \"cre\"), email = \"edzer.pebesma@uni-muenster.de\"), person(\"Roger\", \"Bivand\", role = \"aut\", email = \"Roger.Bivand@nhh.no\"), person(\"Barry\", \"Rowlingson\", role = \"ctb\"), person(\"Virgilio\", \"Gomez-Rubio\", role = \"ctb\"), person(\"Robert\", \"Hijmans\", role = \"ctb\"), person(\"Michael\", \"Sumner\", role = \"ctb\"), person(\"Don\", \"MacQueen\", role = \"ctb\"), person(\"Jim\", \"Lemon\", role = \"ctb\"), person(\"Finn\", \"Lindgren\", role = \"ctb\"), person(\"Josh\", \"O'Brien\", role = \"ctb\"), person(\"Joseph\", \"O'Rourke\", role = \"ctb\"), person(\"Patrick\", \"Hausmann\", role = \"ctb\"), person(\"Sebastian\", \"Meyer\", role = \"ctb\"))", + "Depends": [ + "R (>= 3.5.0)", + "methods" + ], + "Imports": [ + "utils", + "stats", + "graphics", + "grDevices", + "lattice", + "grid" + ], + "Suggests": [ + "RColorBrewer", + "gstat", + "deldir", + "knitr", + "maps", + "mapview", + "rmarkdown", + "sf", + "terra", + "raster" + ], + "Description": "Classes and methods for spatial data; the classes document where the spatial location information resides, for 2D or 3D data. Utility functions are provided, e.g. for plotting data as maps, spatial selection, as well as methods for retrieving coordinates, for subsetting, print, summary, etc. From this version, 'rgdal', 'maptools', and 'rgeos' are no longer used at all, see for details.", + "License": "GPL (>= 2)", + "URL": "https://github.com/edzer/sp/ https://edzer.github.io/sp/", + "BugReports": "https://github.com/edzer/sp/issues", + "Collate": "bpy.colors.R AAA.R Class-CRS.R CRS-methods.R Class-Spatial.R Spatial-methods.R projected.R Class-SpatialPoints.R SpatialPoints-methods.R Class-SpatialPointsDataFrame.R SpatialPointsDataFrame-methods.R Class-SpatialMultiPoints.R SpatialMultiPoints-methods.R Class-SpatialMultiPointsDataFrame.R SpatialMultiPointsDataFrame-methods.R Class-GridTopology.R Class-SpatialGrid.R Class-SpatialGridDataFrame.R Class-SpatialLines.R SpatialLines-methods.R Class-SpatialLinesDataFrame.R SpatialLinesDataFrame-methods.R Class-SpatialPolygons.R Class-SpatialPolygonsDataFrame.R SpatialPolygons-methods.R SpatialPolygonsDataFrame-methods.R GridTopology-methods.R SpatialGrid-methods.R SpatialGridDataFrame-methods.R SpatialPolygons-internals.R point.in.polygon.R SpatialPolygons-displayMethods.R zerodist.R image.R stack.R bubble.R mapasp.R select.spatial.R gridded.R asciigrid.R spplot.R over.R spsample.R recenter.R dms.R gridlines.R spdists.R rbind.R flipSGDF.R chfids.R loadmeuse.R compassRose.R surfaceArea.R spOptions.R subset.R disaggregate.R sp_spat1.R merge.R aggregate.R elide.R sp2Mondrian.R", + "VignetteBuilder": "knitr", + "NeedsCompilation": "yes", + "Author": "Edzer Pebesma [aut, cre], Roger Bivand [aut], Barry Rowlingson [ctb], Virgilio Gomez-Rubio [ctb], Robert Hijmans [ctb], Michael Sumner [ctb], Don MacQueen [ctb], Jim Lemon [ctb], Finn Lindgren [ctb], Josh O'Brien [ctb], Joseph O'Rourke [ctb], Patrick Hausmann [ctb], Sebastian Meyer [ctb]", + "Maintainer": "Edzer Pebesma ", + "Repository": "CRAN" + }, + "stringi": { + "Package": "stringi", + "Version": "1.8.7", + "Source": "Repository", + "Date": "2025-03-27", + "Title": "Fast and Portable Character String Processing Facilities", + "Description": "A collection of character string/text/natural language processing tools for pattern searching (e.g., with 'Java'-like regular expressions or the 'Unicode' collation algorithm), random string generation, case mapping, string transliteration, concatenation, sorting, padding, wrapping, Unicode normalisation, date-time formatting and parsing, and many more. They are fast, consistent, convenient, and - thanks to 'ICU' (International Components for Unicode) - portable across all locales and platforms. Documentation about 'stringi' is provided via its website at and the paper by Gagolewski (2022, ).", + "URL": "https://stringi.gagolewski.com/, https://github.com/gagolews/stringi, https://icu.unicode.org/", + "BugReports": "https://github.com/gagolews/stringi/issues", + "SystemRequirements": "ICU4C (>= 61, optional)", + "Type": "Package", + "Depends": [ + "R (>= 3.4)" + ], + "Imports": [ + "tools", + "utils", + "stats" + ], + "Biarch": "TRUE", + "License": "file LICENSE", + "Authors@R": "c(person(given = \"Marek\", family = \"Gagolewski\", role = c(\"aut\", \"cre\", \"cph\"), email = \"marek@gagolewski.com\", comment = c(ORCID = \"0000-0003-0637-6028\")), person(given = \"Bartek\", family = \"Tartanus\", role = \"ctb\"), person(\"Unicode, Inc. and others\", role=\"ctb\", comment = \"ICU4C source code, Unicode Character Database\") )", + "RoxygenNote": "7.3.2", + "Encoding": "UTF-8", + "NeedsCompilation": "yes", + "Author": "Marek Gagolewski [aut, cre, cph] (), Bartek Tartanus [ctb], Unicode, Inc. and others [ctb] (ICU4C source code, Unicode Character Database)", + "Maintainer": "Marek Gagolewski ", + "License_is_FOSS": "yes", + "Repository": "CRAN" + }, + "stringr": { + "Package": "stringr", + "Version": "1.6.0", + "Source": "Repository", + "Title": "Simple, Consistent Wrappers for Common String Operations", + "Authors@R": "c( person(\"Hadley\", \"Wickham\", , \"hadley@posit.co\", role = c(\"aut\", \"cre\", \"cph\")), person(\"Posit Software, PBC\", role = c(\"cph\", \"fnd\")) )", + "Description": "A consistent, simple and easy to use set of wrappers around the fantastic 'stringi' package. All function and argument names (and positions) are consistent, all functions deal with \"NA\"'s and zero length vectors in the same way, and the output from one function is easy to feed into the input of another.", + "License": "MIT + file LICENSE", + "URL": "https://stringr.tidyverse.org, https://github.com/tidyverse/stringr", + "BugReports": "https://github.com/tidyverse/stringr/issues", + "Depends": [ + "R (>= 4.1.0)" + ], + "Imports": [ + "cli", + "glue (>= 1.6.1)", + "lifecycle (>= 1.0.3)", + "magrittr", + "rlang (>= 1.0.0)", + "stringi (>= 1.5.3)", + "vctrs (>= 0.4.0)" + ], + "Suggests": [ + "covr", + "dplyr", + "gt", + "htmltools", + "htmlwidgets", + "knitr", + "rmarkdown", + "testthat (>= 3.0.0)", + "tibble" + ], + "VignetteBuilder": "knitr", + "Config/Needs/website": "tidyverse/tidytemplate", + "Config/potools/style": "explicit", + "Config/testthat/edition": "3", + "Encoding": "UTF-8", + "LazyData": "true", + "RoxygenNote": "7.3.3", + "NeedsCompilation": "no", + "Author": "Hadley Wickham [aut, cre, cph], Posit Software, PBC [cph, fnd]", + "Maintainer": "Hadley Wickham ", + "Repository": "CRAN" + }, + "sys": { + "Package": "sys", + "Version": "3.4.3", + "Source": "Repository", + "Type": "Package", + "Title": "Powerful and Reliable Tools for Running System Commands in R", + "Authors@R": "c(person(\"Jeroen\", \"Ooms\", role = c(\"aut\", \"cre\"), email = \"jeroenooms@gmail.com\", comment = c(ORCID = \"0000-0002-4035-0289\")), person(\"Gábor\", \"Csárdi\", , \"csardi.gabor@gmail.com\", role = \"ctb\"))", + "Description": "Drop-in replacements for the base system2() function with fine control and consistent behavior across platforms. Supports clean interruption, timeout, background tasks, and streaming STDIN / STDOUT / STDERR over binary or text connections. Arguments on Windows automatically get encoded and quoted to work on different locales.", + "License": "MIT + file LICENSE", + "URL": "https://jeroen.r-universe.dev/sys", + "BugReports": "https://github.com/jeroen/sys/issues", + "Encoding": "UTF-8", + "RoxygenNote": "7.1.1", + "Suggests": [ + "unix (>= 1.4)", + "spelling", + "testthat" + ], + "Language": "en-US", + "NeedsCompilation": "yes", + "Author": "Jeroen Ooms [aut, cre] (), Gábor Csárdi [ctb]", + "Maintainer": "Jeroen Ooms ", + "Repository": "CRAN" + }, + "systemfonts": { + "Package": "systemfonts", + "Version": "1.3.2", + "Source": "Repository", + "Type": "Package", + "Title": "System Native Font Finding", + "Authors@R": "c( person(\"Thomas Lin\", \"Pedersen\", , \"thomas.pedersen@posit.co\", role = c(\"aut\", \"cre\"), comment = c(ORCID = \"0000-0002-5147-4711\")), person(\"Jeroen\", \"Ooms\", , \"jeroen@berkeley.edu\", role = \"aut\", comment = c(ORCID = \"0000-0002-4035-0289\")), person(\"Devon\", \"Govett\", role = \"aut\", comment = \"Author of font-manager\"), person(\"Posit Software, PBC\", role = c(\"cph\", \"fnd\"), comment = c(ROR = \"03wc8by49\")) )", + "Description": "Provides system native access to the font catalogue. As font handling varies between systems it is difficult to correctly locate installed fonts across different operating systems. The 'systemfonts' package provides bindings to the native libraries on Windows, macOS and Linux for finding font files that can then be used further by e.g. graphic devices. The main use is intended to be from compiled code but 'systemfonts' also provides access from R.", + "License": "MIT + file LICENSE", + "URL": "https://github.com/r-lib/systemfonts, https://systemfonts.r-lib.org", + "BugReports": "https://github.com/r-lib/systemfonts/issues", + "Depends": [ + "R (>= 3.2.0)" + ], + "Imports": [ + "base64enc", + "grid", + "jsonlite", + "lifecycle", + "tools", + "utils" + ], + "Suggests": [ + "covr", + "farver", + "ggplot2", + "graphics", + "knitr", + "ragg", + "rmarkdown", + "svglite", + "testthat (>= 2.1.0)" + ], + "LinkingTo": [ + "cpp11 (>= 0.2.1)" + ], + "VignetteBuilder": "knitr", + "Config/build/compilation-database": "true", + "Config/Needs/website": "tidyverse/tidytemplate", + "Config/usethis/last-upkeep": "2025-04-23", + "Encoding": "UTF-8", + "RoxygenNote": "7.3.2", + "SystemRequirements": "fontconfig, freetype2", + "NeedsCompilation": "yes", + "Author": "Thomas Lin Pedersen [aut, cre] (ORCID: ), Jeroen Ooms [aut] (ORCID: ), Devon Govett [aut] (Author of font-manager), Posit Software, PBC [cph, fnd] (ROR: )", + "Maintainer": "Thomas Lin Pedersen ", + "Repository": "CRAN" + }, + "terra": { + "Package": "terra", + "Version": "1.9-34", + "Source": "Repository", + "Type": "Package", + "Title": "Spatial Data Analysis", + "Date": "2026-06-18", + "Depends": [ + "R (>= 3.5.0)", + "methods" + ], + "Suggests": [ + "parallel", + "tinytest", + "ncdf4", + "sf (>= 0.9-8)", + "igraph", + "deldir", + "XML", + "leaflet (>= 2.2.1)", + "htmlwidgets", + "future", + "future.apply" + ], + "LinkingTo": [ + "Rcpp" + ], + "Imports": [ + "Rcpp (>= 1.0-10)" + ], + "SystemRequirements": "C++17, GDAL (>= 2.2.3), GEOS (>= 3.4.0), PROJ (>= 4.9.3), TBB, sqlite3", + "Encoding": "UTF-8", + "Language": "en-US", + "Maintainer": "Robert J. Hijmans ", + "Description": "Methods for spatial data analysis with vector (points, lines, polygons) and raster (grid) data. Methods for vector data include geometric operations such as intersect and buffer. Raster methods include local, focal, global, zonal and geometric operations. The predict and interpolate methods facilitate the use of regression type (interpolation, machine learning) models for spatial prediction, including with satellite remote sensing data. Processing of very large files is supported. See the manual and tutorials on to get started.", + "License": "GPL (>= 3)", + "URL": "https://rspatial.org/, https://rspatial.github.io/terra/", + "BugReports": "https://github.com/rspatial/terra/issues", + "LazyLoad": "yes", + "Authors@R": "c( person(\"Robert J.\", \"Hijmans\", role=c(\"cre\", \"aut\"), email=\"r.hijmans@gmail.com\", comment=c(ORCID=\"0000-0001-5872-2872\")),\t\t\t person(\"Andrew\", \"Brown\", role=\"aut\", comment=c(ORCID=\"0000-0002-4565-533X\")), person(\"Márcia\", \"Barbosa\", role=\"aut\", comment=c(ORCID=\"0000-0001-8972-7713\")), person(\"Krzysztof\", \"Dyba\", role=\"ctb\", comment=c(ORCID=\"0000-0002-8614-3816\")), person(\"Roger\", \"Bivand\", role=\"ctb\", comment=c(ORCID=\"0000-0003-2392-6140\")), person(\"Michael\", \"Chirico\", role=\"ctb\", comment=c(ORCID=\"0000-0003-0787-087X\")), person(\"Emanuele\", \"Cordano\", role=\"ctb\",comment=c(ORCID=\"0000-0002-3508-5898\")), person(\"Edzer\", \"Pebesma\", role=\"ctb\", comment=c(ORCID=\"0000-0001-8049-7069\")), person(\"Barry\", \"Rowlingson\", role=\"ctb\", comment=c(ORCID=\"0000-0002-8586-6625\")), person(\"Michael D.\", \"Sumner\", role=\"ctb\", comment=c(ORCID=\"0000-0002-2471-7511\")))", + "NeedsCompilation": "yes", + "Author": "Robert J. Hijmans [cre, aut] (ORCID: ), Andrew Brown [aut] (ORCID: ), Márcia Barbosa [aut] (ORCID: ), Krzysztof Dyba [ctb] (ORCID: ), Roger Bivand [ctb] (ORCID: ), Michael Chirico [ctb] (ORCID: ), Emanuele Cordano [ctb] (ORCID: ), Edzer Pebesma [ctb] (ORCID: ), Barry Rowlingson [ctb] (ORCID: ), Michael D. Sumner [ctb] (ORCID: )", + "Repository": "P3M" + }, + "textshaping": { + "Package": "textshaping", + "Version": "1.0.5", + "Source": "Repository", + "Title": "Bindings to the 'HarfBuzz' and 'Fribidi' Libraries for Text Shaping", + "Authors@R": "c( person(\"Thomas Lin\", \"Pedersen\", , \"thomas.pedersen@posit.co\", role = c(\"cre\", \"aut\"), comment = c(ORCID = \"0000-0002-5147-4711\")), person(\"Posit Software, PBC\", role = c(\"cph\", \"fnd\"), comment = c(ROR = \"03wc8by49\")) )", + "Description": "Provides access to the text shaping functionality in the 'HarfBuzz' library and the bidirectional algorithm in the 'Fribidi' library. 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All functions are designed to be both fast and entirely vectorised. It is intended to be useful for people dealing with web-related datasets, such as server-side logs, although may be useful for other situations involving large sets of URLs.", + "License": "MIT + file LICENSE", + "LazyData": "TRUE", + "LinkingTo": [ + "Rcpp" + ], + "Imports": [ + "Rcpp", + "methods", + "triebeard" + ], + "Suggests": [ + "testthat", + "knitr" + ], + "URL": "https://github.com/Ironholds/urltools/", + "BugReports": "https://github.com/Ironholds/urltools/issues", + "VignetteBuilder": "knitr", + "RoxygenNote": "6.1.1", + "Encoding": "UTF-8", + "Depends": [ + "R (>= 2.10)" + ], + "NeedsCompilation": "yes", + "Repository": "CRAN", + "Author": "Os Keyes [aut, cre], Jay Jacobs [aut], Drew Schmidt [aut], Mark Greenaway [ctb], Bob Rudis [ctb], Alex Pinto [ctb], Maryam Khezrzadeh [ctb], Peter Meilstrup [ctb], Adam M. 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Well-known binary is compact and fast to parse; well-known text is human-readable and is useful for writing tests. These formats are useful in R only if the information they contain can be accessed in R, for which high-performance functions are provided here.", + "License": "MIT + file LICENSE", + "Encoding": "UTF-8", + "RoxygenNote": "7.3.2", + "Suggests": [ + "testthat (>= 3.0.0)", + "vctrs (>= 0.3.0)", + "sf", + "tibble", + "readr" + ], + "URL": "https://paleolimbot.github.io/wk/, https://github.com/paleolimbot/wk", + "BugReports": "https://github.com/paleolimbot/wk/issues", + "Config/testthat/edition": "3", + "Depends": [ + "R (>= 2.10)" + ], + "LazyData": "true", + "NeedsCompilation": "yes", + "Author": "Dewey Dunnington [aut, cre] (ORCID: ), Edzer Pebesma [aut] (ORCID: ), Anthony North [ctb]", + "Repository": "CRAN" + }, + "xfun": { + "Package": "xfun", + "Version": "0.59", + "Source": "Repository", + "Type": "Package", + "Title": "Supporting Functions for Packages Maintained by 'Yihui Xie'", + "Authors@R": "c( person(\"Yihui\", \"Xie\", role = c(\"aut\", \"cre\", \"cph\"), email = \"xie@yihui.name\", comment = c(ORCID = \"0000-0003-0645-5666\", URL = \"https://yihui.org\")), person(\"Wush\", \"Wu\", role = \"ctb\"), person(\"Daijiang\", \"Li\", role = \"ctb\"), person(\"Xianying\", \"Tan\", role = \"ctb\"), person(\"Salim\", \"Brüggemann\", role = \"ctb\", email = \"salim-b@pm.me\", comment = c(ORCID = \"0000-0002-5329-5987\")), person(\"Christophe\", \"Dervieux\", role = \"ctb\"), person() )", + "Description": "Miscellaneous functions commonly used in other packages maintained by 'Yihui Xie'.", + "Depends": [ + "R (>= 3.2.0)" + ], + "Imports": [ + "grDevices", + "stats", + "tools" + ], + "Suggests": [ + "testit", + "parallel", + "codetools", + "methods", + "rstudioapi", + "tinytex (>= 0.30)", + "mime", + "litedown (>= 0.6)", + "commonmark", + "knitr (>= 1.50)", + "remotes", + "pak", + "curl", + "xml2", + "jsonlite", + "magick", + "yaml", + "data.table", + "qs2" + ], + "License": "MIT + file LICENSE", + "URL": "https://github.com/yihui/xfun", + "BugReports": "https://github.com/yihui/xfun/issues", + "Encoding": "UTF-8", + "VignetteBuilder": "litedown", + "Config/roxygen2/version": "8.0.0", + "NeedsCompilation": "yes", + "Author": "Yihui Xie [aut, cre, cph] (ORCID: , URL: https://yihui.org), Wush Wu [ctb], Daijiang Li [ctb], Xianying Tan [ctb], Salim Brüggemann [ctb] (ORCID: ), Christophe Dervieux [ctb]", + "Maintainer": "Yihui Xie ", + "Repository": "P3M" + }, + "xml2": { + "Package": "xml2", + "Version": "1.6.0", + "Source": "Repository", + "Title": "Parse XML", + "Authors@R": "c( person(\"Hadley\", \"Wickham\", role = \"aut\"), person(\"Jim\", \"Hester\", role = \"aut\"), person(\"Jeroen\", \"Ooms\", email = \"jeroenooms@gmail.com\", role = c(\"aut\", \"cre\")), person(\"Posit Software, PBC\", role = c(\"cph\", \"fnd\")), person(\"R Foundation\", role = \"ctb\", comment = \"Copy of R-project homepage cached as example\") )", + "Description": "Bindings to 'libxml2' for working with XML data using a simple, consistent interface based on 'XPath' expressions. Also supports XML schema validation; for 'XSLT' transformations see the 'xslt' package.", + "License": "MIT + file LICENSE", + "URL": "https://xml2.r-lib.org, https://r-lib.r-universe.dev/xml2", + "BugReports": "https://github.com/r-lib/xml2/issues", + "Depends": [ + "R (>= 3.6.0)" + ], + "Imports": [ + "cli", + "methods", + "rlang (>= 1.1.0)" + ], + "Suggests": [ + "covr", + "curl", + "httr", + "knitr", + "mockery", + "rmarkdown", + "testthat (>= 3.2.0)", + "xslt" + ], + "VignetteBuilder": "knitr", + "Config/Needs/website": "tidyverse/tidytemplate", + "Encoding": "UTF-8", + "RoxygenNote": "7.3.3", + "SystemRequirements": "libxml2: libxml2-dev (deb), libxml2-devel (rpm)", + "Collate": "'S4.R' 'as_list.R' 'xml_parse.R' 'as_xml_document.R' 'classes.R' 'format.R' 'import-standalone-obj-type.R' 'import-standalone-purrr.R' 'import-standalone-types-check.R' 'init.R' 'nodeset_apply.R' 'paths.R' 'utils.R' 'xml2-package.R' 'xml_attr.R' 'xml_children.R' 'xml_document.R' 'xml_find.R' 'xml_missing.R' 'xml_modify.R' 'xml_name.R' 'xml_namespaces.R' 'xml_node.R' 'xml_nodeset.R' 'xml_path.R' 'xml_schema.R' 'xml_serialize.R' 'xml_structure.R' 'xml_text.R' 'xml_type.R' 'xml_url.R' 'xml_write.R'", + "Config/testthat/edition": "3", + "NeedsCompilation": "yes", + "Author": "Hadley Wickham [aut], Jim Hester [aut], Jeroen Ooms [aut, cre], Posit Software, PBC [cph, fnd], R Foundation [ctb] (Copy of R-project homepage cached as example)", + "Maintainer": "Jeroen Ooms ", + "Repository": "P3M" + }, + "yaml": { + "Package": "yaml", + "Version": "2.3.12", + "Source": "Repository", + "Type": "Package", + "Title": "Methods to Convert R Data to YAML and Back", + "Authors@R": "c( person(\"Hadley\", \"Wickham\", , \"hadley@posit.co\", role = \"cre\", comment = c(ORCID = \"0000-0003-4757-117X\")), person(\"Shawn\", \"Garbett\", , \"shawn.garbett@vumc.org\", role = \"ctb\", comment = c(ORCID = \"0000-0003-4079-5621\")), person(\"Jeremy\", \"Stephens\", role = c(\"aut\", \"ctb\")), person(\"Kirill\", \"Simonov\", role = \"aut\"), person(\"Yihui\", \"Xie\", role = \"ctb\", comment = c(ORCID = \"0000-0003-0645-5666\")), person(\"Zhuoer\", \"Dong\", role = \"ctb\"), person(\"Jeffrey\", \"Horner\", role = \"ctb\"), person(\"reikoch\", role = \"ctb\"), person(\"Will\", \"Beasley\", role = \"ctb\", comment = c(ORCID = \"0000-0002-5613-5006\")), person(\"Brendan\", \"O'Connor\", role = \"ctb\"), person(\"Michael\", \"Quinn\", role = \"ctb\"), person(\"Charlie\", \"Gao\", role = \"ctb\"), person(c(\"Gregory\", \"R.\"), \"Warnes\", role = \"ctb\"), person(c(\"Zhian\", \"N.\"), \"Kamvar\", role = \"ctb\") )", + "Description": "Implements the 'libyaml' 'YAML' 1.1 parser and emitter () for R.", + "License": "BSD_3_clause + file LICENSE", + "URL": "https://yaml.r-lib.org, https://github.com/r-lib/yaml/", + "BugReports": "https://github.com/r-lib/yaml/issues", + "Suggests": [ + "knitr", + "rmarkdown", + "testthat (>= 3.0.0)" + ], + "Config/testthat/edition": "3", + "Config/Needs/website": "tidyverse/tidytemplate", + "Encoding": "UTF-8", + "RoxygenNote": "7.3.3", + "VignetteBuilder": "knitr", + "NeedsCompilation": "yes", + "Author": "Hadley Wickham [cre] (ORCID: ), Shawn Garbett [ctb] (ORCID: ), Jeremy Stephens [aut, ctb], Kirill Simonov [aut], Yihui Xie [ctb] (ORCID: ), Zhuoer Dong [ctb], Jeffrey Horner [ctb], reikoch [ctb], Will Beasley [ctb] (ORCID: ), Brendan O'Connor [ctb], Michael Quinn [ctb], Charlie Gao [ctb], Gregory R. Warnes [ctb], Zhian N. Kamvar [ctb]", + "Maintainer": "Hadley Wickham ", + "Repository": "CRAN" + }, + "zip": { + "Package": "zip", + "Version": "3.0.0", + "Source": "Repository", + "Title": "Cross-Platform 'zip' Compression", + "Authors@R": "c( person(\"Gábor\", \"Csárdi\", , \"csardi.gabor@gmail.com\", role = c(\"aut\", \"cre\")), person(\"Kuba\", \"Podgórski\", role = \"ctb\"), person(\"Rich\", \"Geldreich\", role = \"ctb\"), person(\"Arm Limited\", role = c(\"ctb\", \"cph\"), comment = \"bundled Mbed TLS crypto subset in src/mbedtls/ (Apache-2.0)\"), person(\"Posit Software, PBC\", role = c(\"cph\", \"fnd\"), comment = c(ROR = \"03wc8by49\")) )", + "Description": "Cross-Platform 'zip' Compression Library. A replacement for the 'zip' function, that does not require any additional external tools on any platform.", + "License": "MIT + file LICENSE", + "URL": "https://github.com/r-lib/zip, https://r-lib.github.io/zip/", + "BugReports": "https://github.com/r-lib/zip/issues", + "LinkingTo": [ + "cli" + ], + "Suggests": [ + "callr", + "cli", + "curl", + "pillar", + "processx", + "R6", + "testthat", + "webfakes", + "withr" + ], + "Config/Needs/website": "tidyverse/tidytemplate", + "Config/testthat/edition": "3", + "Config/testthat/parallel": "true", + "Config/testthat/start-first": "large-files, http", + "Config/usethis/last-upkeep": "2025-05-07", + "Encoding": "UTF-8", + "Config/roxygen2/version": "8.0.0", + "NeedsCompilation": "yes", + "Author": "Gábor Csárdi [aut, cre], Kuba Podgórski [ctb], Rich Geldreich [ctb], Arm Limited [ctb, cph] (bundled Mbed TLS crypto subset in src/mbedtls/ (Apache-2.0)), Posit Software, PBC [cph, fnd] (ROR: )", + "Maintainer": "Gábor Csárdi ", + "Repository": "P3M" + } + } +} diff --git a/blog/2026/q2-building-permits/renv/.gitignore b/blog/2026/q2-building-permits/renv/.gitignore new file mode 100644 index 0000000..0ec0cbb --- /dev/null +++ b/blog/2026/q2-building-permits/renv/.gitignore @@ -0,0 +1,7 @@ +library/ +local/ +cellar/ +lock/ +python/ +sandbox/ +staging/ diff --git a/blog/2026/q2-building-permits/renv/activate.R b/blog/2026/q2-building-permits/renv/activate.R new file mode 100644 index 0000000..20ffd44 --- /dev/null +++ b/blog/2026/q2-building-permits/renv/activate.R @@ -0,0 +1,1438 @@ + +local({ + + # the requested version of renv + version <- "1.2.3" + attr(version, "md5") <- "1bd9f58e1cfe27ce035933937c6f03de" + attr(version, "sha") <- NULL + + # the project directory + project <- Sys.getenv("RENV_PROJECT") + if (!nzchar(project)) + project <- getwd() + + # use start-up diagnostics if enabled + diagnostics <- Sys.getenv("RENV_STARTUP_DIAGNOSTICS", unset = "FALSE") + if (diagnostics) { + start <- Sys.time() + profile <- tempfile("renv-startup-", fileext = ".Rprof") + utils::Rprof(profile) + on.exit({ + utils::Rprof(NULL) + elapsed <- signif(difftime(Sys.time(), start, units = "auto"), digits = 2L) + writeLines(sprintf("- renv took %s to run the autoloader.", format(elapsed))) + writeLines(sprintf("- Profile: %s", profile)) + print(utils::summaryRprof(profile)) + }, add = TRUE) + } + + # figure out whether the autoloader is enabled + enabled <- local({ + + # first, check config option + override <- getOption("renv.config.autoloader.enabled") + if (!is.null(override)) + return(override) + + # if we're being run in a context where R_LIBS is already set, + # don't load -- presumably we're being run as a sub-process and + # the parent process has already set up library paths for us + rcmd <- Sys.getenv("R_CMD", unset = NA) + rlibs <- Sys.getenv("R_LIBS", unset = NA) + if (!is.na(rlibs) && !is.na(rcmd)) + return(FALSE) + + # next, check environment variables + # prefer using the configuration one in the future + envvars <- c( + "RENV_CONFIG_AUTOLOADER_ENABLED", + "RENV_AUTOLOADER_ENABLED", + "RENV_ACTIVATE_PROJECT" + ) + + for (envvar in envvars) { + envval <- Sys.getenv(envvar, unset = NA) + if (!is.na(envval)) + return(tolower(envval) %in% c("true", "t", "1")) + } + + # enable by default + TRUE + + }) + + # bail if we're not enabled + if (!enabled) { + + # if we're not enabled, we might still need to manually load + # the user profile here + profile <- Sys.getenv("R_PROFILE_USER", unset = "~/.Rprofile") + if (file.exists(profile)) { + cfg <- Sys.getenv("RENV_CONFIG_USER_PROFILE", unset = "TRUE") + if (tolower(cfg) %in% c("true", "t", "1")) + sys.source(profile, envir = globalenv()) + } + + return(FALSE) + + } + + # avoid recursion + if (identical(getOption("renv.autoloader.running"), TRUE)) { + warning("ignoring recursive attempt to run renv autoloader") + return(invisible(TRUE)) + } + + # signal that we're loading renv during R startup + options(renv.autoloader.running = TRUE) + on.exit(options(renv.autoloader.running = NULL), add = TRUE) + + # signal that we've consented to use renv + options(renv.consent = TRUE) + + # load the 'utils' package eagerly -- this ensures that renv shims, which + # mask 'utils' packages, will come first on the search path + library(utils, lib.loc = .Library) + + # unload renv if it's already been loaded + if ("renv" %in% loadedNamespaces()) + unloadNamespace("renv") + + # load bootstrap tools + ansify <- function(text) { + if (renv_ansify_enabled()) + renv_ansify_enhanced(text) + else + renv_ansify_default(text) + } + + renv_ansify_enabled <- function() { + + override <- Sys.getenv("RENV_ANSIFY_ENABLED", unset = NA) + if (!is.na(override)) + return(as.logical(override)) + + pane <- Sys.getenv("RSTUDIO_CHILD_PROCESS_PANE", unset = NA) + if (identical(pane, "build")) + return(FALSE) + + testthat <- Sys.getenv("TESTTHAT", unset = "false") + if (tolower(testthat) %in% "true") + return(FALSE) + + iderun <- Sys.getenv("R_CLI_HAS_HYPERLINK_IDE_RUN", unset = "false") + if (tolower(iderun) %in% "false") + return(FALSE) + + TRUE + + } + + renv_ansify_default <- function(text) { + text + } + + renv_ansify_enhanced <- function(text) { + + # R help links + pattern <- "`\\?(renv::(?:[^`])+)`" + replacement <- "`\033]8;;x-r-help:\\1\a?\\1\033]8;;\a`" + text <- gsub(pattern, replacement, text, perl = TRUE) + + # runnable code + pattern <- "`(renv::(?:[^`])+)`" + replacement <- "`\033]8;;x-r-run:\\1\a\\1\033]8;;\a`" + text <- gsub(pattern, replacement, text, perl = TRUE) + + # return ansified text + text + + } + + renv_ansify_init <- function() { + + envir <- renv_envir_self() + if (renv_ansify_enabled()) + assign("ansify", renv_ansify_enhanced, envir = envir) + else + assign("ansify", renv_ansify_default, envir = envir) + + } + + `%||%` <- function(x, y) { + if (is.null(x)) y else x + } + + catf <- function(fmt, ..., appendLF = TRUE) { + + quiet <- getOption("renv.bootstrap.quiet", default = FALSE) + if (quiet) + return(invisible()) + + # also check for config environment variables that should suppress messages + # https://github.com/rstudio/renv/issues/2214 + enabled <- Sys.getenv("RENV_CONFIG_STARTUP_QUIET", unset = NA) + if (!is.na(enabled) && tolower(enabled) %in% c("true", "1")) + return(invisible()) + + enabled <- Sys.getenv("RENV_CONFIG_SYNCHRONIZED_CHECK", unset = NA) + if (!is.na(enabled) && tolower(enabled) %in% c("false", "0")) + return(invisible()) + + msg <- sprintf(fmt, ...) + cat(msg, file = stdout(), sep = if (appendLF) "\n" else "") + + invisible(msg) + + } + + header <- function(label, + ..., + prefix = "#", + suffix = "-", + n = min(getOption("width"), 78)) + { + label <- sprintf(label, ...) + n <- max(n - nchar(label) - nchar(prefix) - 2L, 8L) + if (n <= 0) + return(paste(prefix, label)) + + tail <- paste(rep.int(suffix, n), collapse = "") + paste0(prefix, " ", label, " ", tail) + + } + + heredoc <- function(text, leave = 0) { + + # remove leading, trailing whitespace + trimmed <- gsub("^\\s*\\n|\\n\\s*$", "", text) + + # split into lines + lines <- strsplit(trimmed, "\n", fixed = TRUE)[[1L]] + + # compute common indent + indent <- regexpr("[^[:space:]]", lines) + common <- min(setdiff(indent, -1L)) - leave + text <- paste(substring(lines, common), collapse = "\n") + + # substitute in ANSI links for executable renv code + ansify(text) + + } + + bootstrap <- function(version, library) { + + friendly <- renv_bootstrap_version_friendly(version) + section <- header(sprintf("Bootstrapping renv %s", friendly)) + catf(section) + + # ensure the target library path exists; required for file.copy(..., recursive = TRUE) + dir.create(library, showWarnings = FALSE, recursive = TRUE) + + # try to install renv from cache + md5 <- attr(version, "md5", exact = TRUE) + if (length(md5)) { + pkgpath <- renv_bootstrap_find(version) + if (length(pkgpath) && file.exists(pkgpath)) { + ok <- file.copy(pkgpath, library, recursive = TRUE) + if (isTRUE(ok)) + return(invisible()) + } + } + + # attempt to download renv + catf("- Downloading renv ... ", appendLF = FALSE) + withCallingHandlers( + tarball <- renv_bootstrap_download(version), + error = function(err) { + catf("FAILED") + stop("failed to download:\n", conditionMessage(err)) + } + ) + catf("OK") + on.exit(unlink(tarball), add = TRUE) + + # now attempt to install + catf("- Installing renv ... ", appendLF = FALSE) + withCallingHandlers( + status <- renv_bootstrap_install(version, tarball, library), + error = function(err) { + catf("FAILED") + stop("failed to install:\n", conditionMessage(err)) + } + ) + catf("OK") + + # add empty line to break up bootstrapping from normal output + catf("") + return(invisible()) + } + + renv_bootstrap_tests_running <- function() { + getOption("renv.tests.running", default = FALSE) + } + + renv_bootstrap_repos <- function() { + + # get CRAN repository + cran <- getOption("renv.repos.cran", "https://cloud.r-project.org") + + # check for repos override + repos <- Sys.getenv("RENV_CONFIG_REPOS_OVERRIDE", unset = NA) + if (!is.na(repos)) { + + # split on ';' if present + parts <- strsplit(repos, ";", fixed = TRUE)[[1L]] + + # split into named repositories if present + idx <- regexpr("=", parts, fixed = TRUE) + keys <- substring(parts, 1L, idx - 1L) + vals <- substring(parts, idx + 1L) + names(vals) <- keys + + # if we have a single unnamed repository, call it CRAN + if (length(vals) == 1L && identical(keys, "")) + names(vals) <- "CRAN" + + return(vals) + + } + + # check for lockfile repositories + repos <- tryCatch(renv_bootstrap_repos_lockfile(), error = identity) + if (!inherits(repos, "error") && length(repos)) + return(repos) + + # retrieve current repos + repos <- getOption("repos") + + # ensure @CRAN@ entries are resolved + repos[repos == "@CRAN@"] <- cran + + # add in renv.bootstrap.repos if set + default <- c(FALLBACK = "https://cloud.r-project.org") + extra <- getOption("renv.bootstrap.repos", default = default) + repos <- c(repos, extra) + + # remove duplicates that might've snuck in + dupes <- duplicated(repos) | duplicated(names(repos)) + repos[!dupes] + + } + + renv_bootstrap_repos_lockfile <- function() { + + lockpath <- Sys.getenv("RENV_PATHS_LOCKFILE", unset = "renv.lock") + if (!file.exists(lockpath)) + return(NULL) + + lockfile <- tryCatch(renv_json_read(lockpath), error = identity) + if (inherits(lockfile, "error")) { + warning(lockfile) + return(NULL) + } + + repos <- lockfile$R$Repositories + if (length(repos) == 0) + return(NULL) + + keys <- vapply(repos, `[[`, "Name", FUN.VALUE = character(1)) + vals <- vapply(repos, `[[`, "URL", FUN.VALUE = character(1)) + names(vals) <- keys + + return(vals) + + } + + renv_bootstrap_download <- function(version) { + + sha <- attr(version, "sha", exact = TRUE) + + methods <- if (!is.null(sha)) { + + # attempting to bootstrap a development version of renv + c( + function() renv_bootstrap_download_tarball(sha), + function() renv_bootstrap_download_github(sha) + ) + + } else { + + # attempting to bootstrap a release version of renv + c( + function() renv_bootstrap_download_tarball(version), + function() renv_bootstrap_download_cran_latest(version), + function() renv_bootstrap_download_cran_archive(version) + ) + + } + + for (method in methods) { + path <- tryCatch(method(), error = identity) + if (is.character(path) && file.exists(path)) + return(path) + } + + stop("All download methods failed") + + } + + renv_bootstrap_download_impl <- function(url, destfile) { + + mode <- "wb" + + # https://bugs.r-project.org/bugzilla/show_bug.cgi?id=17715 + fixup <- + Sys.info()[["sysname"]] == "Windows" && + substring(url, 1L, 5L) == "file:" + + if (fixup) + mode <- "w+b" + + args <- list( + url = url, + destfile = destfile, + mode = mode, + quiet = TRUE + ) + + if ("headers" %in% names(formals(utils::download.file))) { + headers <- renv_bootstrap_download_custom_headers(url) + if (length(headers) && is.character(headers)) + args$headers <- headers + } + + do.call(utils::download.file, args) + + } + + renv_bootstrap_download_custom_headers <- function(url) { + + headers <- getOption("renv.download.headers") + if (is.null(headers)) + return(character()) + + if (!is.function(headers)) + stopf("'renv.download.headers' is not a function") + + headers <- headers(url) + if (length(headers) == 0L) + return(character()) + + if (is.list(headers)) + headers <- unlist(headers, recursive = FALSE, use.names = TRUE) + + ok <- + is.character(headers) && + is.character(names(headers)) && + all(nzchar(names(headers))) + + if (!ok) + stop("invocation of 'renv.download.headers' did not return a named character vector") + + headers + + } + + renv_bootstrap_download_cran_latest <- function(version) { + + spec <- renv_bootstrap_download_cran_latest_find(version) + type <- spec$type + repos <- spec$repos + + baseurl <- utils::contrib.url(repos = repos, type = type) + ext <- if (identical(type, "source")) + ".tar.gz" + else if (Sys.info()[["sysname"]] == "Windows") + ".zip" + else + ".tgz" + name <- sprintf("renv_%s%s", version, ext) + url <- paste(baseurl, name, sep = "/") + + destfile <- file.path(tempdir(), name) + status <- tryCatch( + renv_bootstrap_download_impl(url, destfile), + condition = identity + ) + + if (inherits(status, "condition")) + return(FALSE) + + # report success and return + destfile + + } + + renv_bootstrap_download_cran_latest_find <- function(version) { + + # check whether binaries are supported on this system + binary <- + getOption("renv.bootstrap.binary", default = TRUE) && + !identical(.Platform$pkgType, "source") && + !identical(getOption("pkgType"), "source") && + Sys.info()[["sysname"]] %in% c("Darwin", "Windows") + + types <- c(if (binary) "binary", "source") + + # iterate over types + repositories + for (type in types) { + for (repos in renv_bootstrap_repos()) { + + # build arguments for utils::available.packages() call + args <- list(type = type, repos = repos) + + # add custom headers if available -- note that + # utils::available.packages() will pass this to download.file() + if ("headers" %in% names(formals(utils::download.file))) { + headers <- renv_bootstrap_download_custom_headers(repos) + if (length(headers) && is.character(headers)) + args$headers <- headers + } + + # retrieve package database + db <- tryCatch( + as.data.frame( + do.call(utils::available.packages, args), + stringsAsFactors = FALSE + ), + error = identity + ) + + if (inherits(db, "error")) + next + + # check for compatible entry + entry <- db[db$Package %in% "renv" & db$Version %in% version, ] + if (nrow(entry) == 0) + next + + # found it; return spec to caller + spec <- list(entry = entry, type = type, repos = repos) + return(spec) + + } + } + + # if we got here, we failed to find renv + fmt <- "renv %s is not available from your declared package repositories" + stop(sprintf(fmt, version)) + + } + + renv_bootstrap_download_cran_archive <- function(version) { + + name <- sprintf("renv_%s.tar.gz", version) + repos <- renv_bootstrap_repos() + urls <- file.path(repos, "src/contrib/Archive/renv", name) + destfile <- file.path(tempdir(), name) + + for (url in urls) { + + status <- tryCatch( + renv_bootstrap_download_impl(url, destfile), + condition = identity + ) + + if (identical(status, 0L)) + return(destfile) + + } + + return(FALSE) + + } + + renv_bootstrap_find <- function(version) { + + path <- renv_bootstrap_find_cache(version) + if (length(path) && file.exists(path)) { + catf("- Using renv %s from global package cache", version) + return(path) + } + + } + + renv_bootstrap_find_cache <- function(version) { + + md5 <- attr(version, "md5", exact = TRUE) + if (is.null(md5)) + return() + + # infer path to renv cache + cache <- Sys.getenv("RENV_PATHS_CACHE", unset = "") + if (!nzchar(cache)) { + root <- Sys.getenv("RENV_PATHS_ROOT", unset = NA) + if (!is.na(root)) + cache <- file.path(root, "cache") + } + + if (!nzchar(cache)) { + tools <- asNamespace("tools") + if (is.function(tools$R_user_dir)) { + root <- tools$R_user_dir("renv", "cache") + cache <- file.path(root, "cache") + } + } + + # start completing path to cache + file.path( + cache, + renv_bootstrap_cache_version(), + renv_bootstrap_platform_prefix(), + "renv", + version, + md5, + "renv" + ) + + } + + renv_bootstrap_download_tarball <- function(version) { + + # if the user has provided the path to a tarball via + # an environment variable, then use it + tarball <- Sys.getenv("RENV_BOOTSTRAP_TARBALL", unset = NA) + if (is.na(tarball)) + return() + + # allow directories + if (dir.exists(tarball)) { + name <- sprintf("renv_%s.tar.gz", version) + tarball <- file.path(tarball, name) + } + + # bail if it doesn't exist + if (!file.exists(tarball)) { + + # let the user know we weren't able to honour their request + fmt <- "- RENV_BOOTSTRAP_TARBALL is set (%s) but does not exist." + msg <- sprintf(fmt, tarball) + warning(msg) + + # bail + return() + + } + + catf("- Using local tarball '%s'.", tarball) + tarball + + } + + renv_bootstrap_github_token <- function() { + for (envvar in c("GITHUB_TOKEN", "GITHUB_PAT", "GH_TOKEN")) { + envval <- Sys.getenv(envvar, unset = NA) + if (!is.na(envval)) + return(envval) + } + } + + renv_bootstrap_download_github <- function(version) { + + enabled <- Sys.getenv("RENV_BOOTSTRAP_FROM_GITHUB", unset = "TRUE") + if (!identical(enabled, "TRUE")) + return(FALSE) + + # prepare download options + token <- renv_bootstrap_github_token() + if (is.null(token)) + token <- "" + + if (nzchar(Sys.which("curl")) && nzchar(token)) { + fmt <- "--location --fail --header \"Authorization: token %s\"" + extra <- sprintf(fmt, token) + saved <- options("download.file.method", "download.file.extra") + options(download.file.method = "curl", download.file.extra = extra) + on.exit(do.call(base::options, saved), add = TRUE) + } else if (nzchar(Sys.which("wget")) && nzchar(token)) { + fmt <- "--header=\"Authorization: token %s\"" + extra <- sprintf(fmt, token) + saved <- options("download.file.method", "download.file.extra") + options(download.file.method = "wget", download.file.extra = extra) + on.exit(do.call(base::options, saved), add = TRUE) + } + + url <- file.path("https://api.github.com/repos/rstudio/renv/tarball", version) + name <- sprintf("renv_%s.tar.gz", version) + destfile <- file.path(tempdir(), name) + + status <- tryCatch( + renv_bootstrap_download_impl(url, destfile), + condition = identity + ) + + if (!identical(status, 0L)) + return(FALSE) + + renv_bootstrap_download_augment(destfile) + + return(destfile) + + } + + # Add Sha to DESCRIPTION. This is stop gap until #890, after which we + # can use renv::install() to fully capture metadata. + renv_bootstrap_download_augment <- function(destfile) { + sha <- renv_bootstrap_git_extract_sha1_tar(destfile) + if (is.null(sha)) { + return() + } + + # Untar + tempdir <- tempfile("renv-github-") + on.exit(unlink(tempdir, recursive = TRUE), add = TRUE) + untar(destfile, exdir = tempdir) + pkgdir <- dir(tempdir, full.names = TRUE)[[1]] + + # Modify description + desc_path <- file.path(pkgdir, "DESCRIPTION") + desc_lines <- readLines(desc_path) + remotes_fields <- c( + "RemoteType: github", + "RemoteHost: api.github.com", + "RemoteRepo: renv", + "RemoteUsername: rstudio", + "RemotePkgRef: rstudio/renv", + paste("RemoteRef: ", sha), + paste("RemoteSha: ", sha) + ) + writeLines(c(desc_lines[desc_lines != ""], remotes_fields), con = desc_path) + + # Re-tar + local({ + old <- setwd(tempdir) + on.exit(setwd(old), add = TRUE) + + tar(destfile, compression = "gzip") + }) + invisible() + } + + # Extract the commit hash from a git archive. Git archives include the SHA1 + # hash as the comment field of the tarball pax extended header + # (see https://www.kernel.org/pub/software/scm/git/docs/git-archive.html) + # For GitHub archives this should be the first header after the default one + # (512 byte) header. + renv_bootstrap_git_extract_sha1_tar <- function(bundle) { + + # open the bundle for reading + # We use gzcon for everything because (from ?gzcon) + # > Reading from a connection which does not supply a 'gzip' magic + # > header is equivalent to reading from the original connection + conn <- gzcon(file(bundle, open = "rb", raw = TRUE)) + on.exit(close(conn)) + + # The default pax header is 512 bytes long and the first pax extended header + # with the comment should be 51 bytes long + # `52 comment=` (11 chars) + 40 byte SHA1 hash + len <- 0x200 + 0x33 + res <- rawToChar(readBin(conn, "raw", n = len)[0x201:len]) + + if (grepl("^52 comment=", res)) { + sub("52 comment=", "", res) + } else { + NULL + } + } + + renv_bootstrap_install <- function(version, tarball, library) { + + # attempt to install it into project library + dir.create(library, showWarnings = FALSE, recursive = TRUE) + output <- renv_bootstrap_install_impl(library, tarball) + + # check for successful install + status <- attr(output, "status") + if (is.null(status) || identical(status, 0L)) + return(status) + + # an error occurred; report it + header <- "installation of renv failed" + lines <- paste(rep.int("=", nchar(header)), collapse = "") + text <- paste(c(header, lines, output), collapse = "\n") + stop(text) + + } + + renv_bootstrap_install_impl <- function(library, tarball) { + + # invoke using system2 so we can capture and report output + bin <- R.home("bin") + exe <- if (Sys.info()[["sysname"]] == "Windows") "R.exe" else "R" + R <- file.path(bin, exe) + + args <- c( + "--vanilla", "CMD", "INSTALL", "--no-multiarch", + "-l", shQuote(path.expand(library)), + shQuote(path.expand(tarball)) + ) + + system2(R, args, stdout = TRUE, stderr = TRUE) + + } + + renv_bootstrap_platform_prefix_default <- function() { + + # read version component + version <- Sys.getenv("RENV_PATHS_VERSION", unset = "R-%v") + + # expand placeholders + placeholders <- list( + list("%v", format(getRversion()[1, 1:2])), + list("%V", format(getRversion()[1, 1:3])) + ) + + for (placeholder in placeholders) + version <- gsub(placeholder[[1L]], placeholder[[2L]], version, fixed = TRUE) + + # include SVN revision for development versions of R + # (to avoid sharing platform-specific artefacts with released versions of R) + devel <- + identical(R.version[["status"]], "Under development (unstable)") || + identical(R.version[["nickname"]], "Unsuffered Consequences") + + if (devel) + version <- paste(version, R.version[["svn rev"]], sep = "-r") + + version + + } + + renv_bootstrap_platform_prefix <- function() { + + # construct version prefix + version <- renv_bootstrap_platform_prefix_default() + + # build list of path components + components <- c(version, R.version$platform) + + # include prefix if provided by user + prefix <- renv_bootstrap_platform_prefix_impl() + if (!is.na(prefix) && nzchar(prefix)) + components <- c(prefix, components) + + # build prefix + paste(components, collapse = "/") + + } + + renv_bootstrap_platform_prefix_impl <- function() { + + # if an explicit prefix has been supplied, use it + prefix <- Sys.getenv("RENV_PATHS_PREFIX", unset = NA) + if (!is.na(prefix)) + return(prefix) + + # if the user has requested an automatic prefix, generate it + auto <- Sys.getenv("RENV_PATHS_PREFIX_AUTO", unset = NA) + if (is.na(auto) && getRversion() >= "4.4.0") + auto <- "TRUE" + + if (auto %in% c("TRUE", "True", "true", "1")) + return(renv_bootstrap_platform_prefix_auto()) + + # empty string on failure + "" + + } + + renv_bootstrap_platform_prefix_auto <- function() { + + prefix <- tryCatch(renv_bootstrap_platform_os(), error = identity) + if (inherits(prefix, "error") || prefix %in% "unknown") { + + msg <- paste( + "failed to infer current operating system", + "please file a bug report at https://github.com/rstudio/renv/issues", + sep = "; " + ) + + warning(msg) + + } + + prefix + + } + + renv_bootstrap_platform_os <- function() { + + sysinfo <- Sys.info() + sysname <- sysinfo[["sysname"]] + + # handle Windows + macOS up front + if (sysname == "Windows") + return("windows") + else if (sysname == "Darwin") + return("macos") + + # check for os-release files + for (file in c("/etc/os-release", "/usr/lib/os-release")) + if (file.exists(file)) + return(renv_bootstrap_platform_os_via_os_release(file, sysinfo)) + + # check for redhat-release files + if (file.exists("/etc/redhat-release")) + return(renv_bootstrap_platform_os_via_redhat_release()) + + "unknown" + + } + + renv_bootstrap_platform_os_via_os_release <- function(file, sysinfo) { + + # read /etc/os-release + release <- utils::read.table( + file = file, + sep = "=", + quote = c("\"", "'"), + col.names = c("Key", "Value"), + comment.char = "#", + stringsAsFactors = FALSE + ) + + vars <- as.list(release$Value) + names(vars) <- release$Key + + # get os name + os <- tolower(sysinfo[["sysname"]]) + + # read id + id <- "unknown" + for (field in c("ID", "ID_LIKE")) { + if (field %in% names(vars) && nzchar(vars[[field]])) { + id <- vars[[field]] + break + } + } + + # read version + version <- "unknown" + for (field in c("UBUNTU_CODENAME", "VERSION_CODENAME", "VERSION_ID", "BUILD_ID")) { + if (field %in% names(vars) && nzchar(vars[[field]])) { + version <- vars[[field]] + break + } + } + + # join together + paste(c(os, id, version), collapse = "-") + + } + + renv_bootstrap_platform_os_via_redhat_release <- function() { + + # read /etc/redhat-release + contents <- readLines("/etc/redhat-release", warn = FALSE) + + # infer id + id <- if (grepl("centos", contents, ignore.case = TRUE)) + "centos" + else if (grepl("redhat", contents, ignore.case = TRUE)) + "redhat" + else + "unknown" + + # try to find a version component (very hacky) + version <- "unknown" + + parts <- strsplit(contents, "[[:space:]]")[[1L]] + for (part in parts) { + + nv <- tryCatch(numeric_version(part), error = identity) + if (inherits(nv, "error")) + next + + version <- nv[1, 1] + break + + } + + paste(c("linux", id, version), collapse = "-") + + } + + renv_bootstrap_library_root_name <- function(project) { + + # use project name as-is if requested + asis <- Sys.getenv("RENV_PATHS_LIBRARY_ROOT_ASIS", unset = "FALSE") + if (asis) + return(basename(project)) + + # otherwise, disambiguate based on project's path + id <- substring(renv_bootstrap_hash_text(project), 1L, 8L) + paste(basename(project), id, sep = "-") + + } + + renv_bootstrap_library_root <- function(project) { + + prefix <- renv_bootstrap_profile_prefix() + + path <- Sys.getenv("RENV_PATHS_LIBRARY", unset = NA) + if (!is.na(path)) + return(paste(c(path, prefix), collapse = "/")) + + path <- renv_bootstrap_library_root_impl(project) + if (!is.null(path)) { + name <- renv_bootstrap_library_root_name(project) + return(paste(c(path, prefix, name), collapse = "/")) + } + + renv_bootstrap_paths_renv("library", project = project) + + } + + renv_bootstrap_library_root_impl <- function(project) { + + root <- Sys.getenv("RENV_PATHS_LIBRARY_ROOT", unset = NA) + if (!is.na(root)) + return(root) + + type <- renv_bootstrap_project_type(project) + if (identical(type, "package")) { + userdir <- renv_bootstrap_user_dir() + return(file.path(userdir, "library")) + } + + } + + renv_bootstrap_validate_version <- function(version, description = NULL) { + + # resolve description file + # + # avoid passing lib.loc to `packageDescription()` below, since R will + # use the loaded version of the package by default anyhow. note that + # this function should only be called after 'renv' is loaded + # https://github.com/rstudio/renv/issues/1625 + description <- description %||% packageDescription("renv") + + # check whether requested version 'version' matches loaded version of renv + sha <- attr(version, "sha", exact = TRUE) + valid <- if (!is.null(sha)) + renv_bootstrap_validate_version_dev(sha, description) + else + renv_bootstrap_validate_version_release(version, description) + + if (valid) + return(TRUE) + + # the loaded version of renv doesn't match the requested version; + # give the user instructions on how to proceed + dev <- identical(description[["RemoteType"]], "github") + remote <- if (dev) + paste("rstudio/renv", description[["RemoteSha"]], sep = "@") + else + paste("renv", description[["Version"]], sep = "@") + + # display both loaded version + sha if available + friendly <- renv_bootstrap_version_friendly( + version = description[["Version"]], + sha = if (dev) description[["RemoteSha"]] + ) + + fmt <- heredoc(" + renv %1$s was loaded from project library, but this project is configured to use renv %2$s. + - Use `renv::record(\"%3$s\")` to record renv %1$s in the lockfile. + - Use `renv::restore(packages = \"renv\")` to install renv %2$s into the project library. + ") + catf(fmt, friendly, renv_bootstrap_version_friendly(version), remote) + + FALSE + + } + + renv_bootstrap_validate_version_dev <- function(version, description) { + + expected <- description[["RemoteSha"]] + if (!is.character(expected)) + return(FALSE) + + pattern <- sprintf("^\\Q%s\\E", version) + grepl(pattern, expected, perl = TRUE) + + } + + renv_bootstrap_validate_version_release <- function(version, description) { + expected <- description[["Version"]] + is.character(expected) && identical(c(expected), c(version)) + } + + renv_bootstrap_hash_text <- function(text) { + + hashfile <- tempfile("renv-hash-") + on.exit(unlink(hashfile), add = TRUE) + + writeLines(text, con = hashfile) + tools::md5sum(hashfile) + + } + + renv_bootstrap_load <- function(project, libpath, version) { + + # try to load renv from the project library + if (!requireNamespace("renv", lib.loc = libpath, quietly = TRUE)) + return(FALSE) + + # warn if the version of renv loaded does not match + renv_bootstrap_validate_version(version) + + # execute renv load hooks, if any + hooks <- getHook("renv::autoload") + for (hook in hooks) + if (is.function(hook)) + tryCatch(hook(), error = warnify) + + # load the project + renv::load(project) + + TRUE + + } + + renv_bootstrap_profile_load <- function(project) { + + # if RENV_PROFILE is already set, just use that + profile <- Sys.getenv("RENV_PROFILE", unset = NA) + if (!is.na(profile) && nzchar(profile)) + return(profile) + + # check for a profile file (nothing to do if it doesn't exist) + path <- renv_bootstrap_paths_renv("profile", profile = FALSE, project = project) + if (!file.exists(path)) + return(NULL) + + # read the profile, and set it if it exists + contents <- readLines(path, warn = FALSE) + if (length(contents) == 0L) + return(NULL) + + # set RENV_PROFILE + profile <- contents[[1L]] + if (!profile %in% c("", "default")) + Sys.setenv(RENV_PROFILE = profile) + + profile + + } + + renv_bootstrap_profile_prefix <- function() { + profile <- renv_bootstrap_profile_get() + if (!is.null(profile)) + return(file.path("profiles", profile, "renv")) + } + + renv_bootstrap_profile_get <- function() { + profile <- Sys.getenv("RENV_PROFILE", unset = "") + renv_bootstrap_profile_normalize(profile) + } + + renv_bootstrap_profile_set <- function(profile) { + profile <- renv_bootstrap_profile_normalize(profile) + if (is.null(profile)) + Sys.unsetenv("RENV_PROFILE") + else + Sys.setenv(RENV_PROFILE = profile) + } + + renv_bootstrap_profile_normalize <- function(profile) { + + if (is.null(profile) || profile %in% c("", "default")) + return(NULL) + + profile + + } + + renv_bootstrap_path_absolute <- function(path) { + + substr(path, 1L, 1L) %in% c("~", "/", "\\") || ( + substr(path, 1L, 1L) %in% c(letters, LETTERS) && + substr(path, 2L, 3L) %in% c(":/", ":\\") + ) + + } + + renv_bootstrap_paths_renv <- function(..., profile = TRUE, project = NULL) { + renv <- Sys.getenv("RENV_PATHS_RENV", unset = "renv") + root <- if (renv_bootstrap_path_absolute(renv)) NULL else project + prefix <- if (profile) renv_bootstrap_profile_prefix() + components <- c(root, renv, prefix, ...) + paste(components, collapse = "/") + } + + renv_bootstrap_project_type <- function(path) { + + descpath <- file.path(path, "DESCRIPTION") + if (!file.exists(descpath)) + return("unknown") + + desc <- tryCatch( + read.dcf(descpath, all = TRUE), + error = identity + ) + + if (inherits(desc, "error")) + return("unknown") + + type <- desc$Type + if (!is.null(type)) + return(tolower(type)) + + package <- desc$Package + if (!is.null(package)) + return("package") + + "unknown" + + } + + renv_bootstrap_user_dir <- function() { + dir <- renv_bootstrap_user_dir_impl() + path.expand(chartr("\\", "/", dir)) + } + + renv_bootstrap_user_dir_impl <- function() { + + # use local override if set + override <- getOption("renv.userdir.override") + if (!is.null(override)) + return(override) + + # use R_user_dir if available + tools <- asNamespace("tools") + if (is.function(tools$R_user_dir)) + return(tools$R_user_dir("renv", "cache")) + + # try using our own backfill for older versions of R + envvars <- c("R_USER_CACHE_DIR", "XDG_CACHE_HOME") + for (envvar in envvars) { + root <- Sys.getenv(envvar, unset = NA) + if (!is.na(root)) + return(file.path(root, "R/renv")) + } + + # use platform-specific default fallbacks + if (Sys.info()[["sysname"]] == "Windows") + file.path(Sys.getenv("LOCALAPPDATA"), "R/cache/R/renv") + else if (Sys.info()[["sysname"]] == "Darwin") + "~/Library/Caches/org.R-project.R/R/renv" + else + "~/.cache/R/renv" + + } + + renv_bootstrap_version_friendly <- function(version, shafmt = NULL, sha = NULL) { + sha <- sha %||% attr(version, "sha", exact = TRUE) + parts <- c(version, sprintf(shafmt %||% " [sha: %s]", substring(sha, 1L, 7L))) + paste(parts, collapse = "") + } + + renv_bootstrap_exec <- function(project, libpath, version) { + if (!renv_bootstrap_load(project, libpath, version)) + renv_bootstrap_run(project, libpath, version) + } + + renv_bootstrap_run <- function(project, libpath, version) { + tryCatch( + renv_bootstrap_run_impl(project, libpath, version), + error = function(e) { + msg <- paste( + "failed to bootstrap renv: the project will not be loaded.", + paste("Reason:", conditionMessage(e)), + "Use `renv::activate()` to re-initialize the project.", + sep = "\n" + ) + warning(msg, call. = FALSE) + } + ) + } + + renv_bootstrap_run_impl <- function(project, libpath, version) { + + # perform bootstrap + bootstrap(version, libpath) + + # exit early if we're just testing bootstrap + if (!is.na(Sys.getenv("RENV_BOOTSTRAP_INSTALL_ONLY", unset = NA))) + return(TRUE) + + # try again to load + if (requireNamespace("renv", lib.loc = libpath, quietly = TRUE)) { + return(renv::load(project = project)) + } + + # failed to download or load renv; warn the user + msg <- c( + "Failed to find an renv installation: the project will not be loaded.", + "Use `renv::activate()` to re-initialize the project." + ) + + warning(paste(msg, collapse = "\n"), call. = FALSE) + + } + + renv_bootstrap_cache_version <- function() { + # NOTE: users should normally not override the cache version; + # this is provided just to make testing easier + Sys.getenv("RENV_CACHE_VERSION", unset = "v5") + } + + renv_bootstrap_cache_version_previous <- function() { + version <- renv_bootstrap_cache_version() + number <- as.integer(substring(version, 2L)) + paste("v", number - 1L, sep = "") + } + + renv_json_read <- function(file = NULL, text = NULL) { + + jlerr <- NULL + + # if jsonlite is loaded, use that instead + if ("jsonlite" %in% loadedNamespaces()) { + + json <- tryCatch(renv_json_read_jsonlite(file, text), error = identity) + if (!inherits(json, "error")) + return(json) + + jlerr <- json + + } + + # otherwise, fall back to the default JSON reader + json <- tryCatch(renv_json_read_default(file, text), error = identity) + if (!inherits(json, "error")) + return(json) + + # report an error + if (!is.null(jlerr)) + stop(jlerr) + else + stop(json) + + } + + renv_json_read_jsonlite <- function(file = NULL, text = NULL) { + text <- paste(text %||% readLines(file, warn = FALSE), collapse = "\n") + jsonlite::fromJSON(txt = text, simplifyVector = FALSE) + } + + renv_json_read_patterns <- function() { + + list( + + # objects + list("{", "\t\n\tobject(\t\n\t", TRUE), + list("}", "\t\n\t)\t\n\t", TRUE), + + # arrays + list("[", "\t\n\tarray(\t\n\t", TRUE), + list("]", "\n\t\n)\n\t\n", TRUE), + + # maps + list(":", "\t\n\t=\t\n\t", TRUE), + + # newlines + list("\\u000a", "\n", FALSE) + + ) + + } + + renv_json_read_envir <- function() { + + envir <- new.env(parent = emptyenv()) + + envir[["+"]] <- `+` + envir[["-"]] <- `-` + + envir[["object"]] <- function(...) { + result <- list(...) + names(result) <- as.character(names(result)) + result + } + + envir[["array"]] <- list + + envir[["true"]] <- TRUE + envir[["false"]] <- FALSE + envir[["null"]] <- NULL + + envir + + } + + renv_json_read_remap <- function(object, patterns) { + + # repair names if necessary + if (!is.null(names(object))) { + + nms <- names(object) + for (pattern in patterns) + nms <- gsub(pattern[[2L]], pattern[[1L]], nms, fixed = TRUE) + names(object) <- nms + + } + + # repair strings if necessary + if (is.character(object)) { + for (pattern in patterns) + object <- gsub(pattern[[2L]], pattern[[1L]], object, fixed = TRUE) + } + + # recurse for other objects + if (is.recursive(object)) + for (i in seq_along(object)) + object[i] <- list(renv_json_read_remap(object[[i]], patterns)) + + # return remapped object + object + + } + + renv_json_read_default <- function(file = NULL, text = NULL) { + + # read json text + text <- paste(text %||% readLines(file, warn = FALSE), collapse = "\n") + + # convert into something the R parser will understand + patterns <- renv_json_read_patterns() + transformed <- text + for (pattern in patterns) + transformed <- gsub(pattern[[1L]], pattern[[2L]], transformed, fixed = TRUE) + + # parse it + rfile <- tempfile("renv-json-", fileext = ".R") + on.exit(unlink(rfile), add = TRUE) + writeLines(transformed, con = rfile) + json <- parse(rfile, keep.source = FALSE, srcfile = NULL)[[1L]] + + # evaluate in safe environment + result <- eval(json, envir = renv_json_read_envir()) + + # fix up strings if necessary -- do so only with reversible patterns + patterns <- Filter(function(pattern) pattern[[3L]], patterns) + renv_json_read_remap(result, patterns) + + } + + + # load the renv profile, if any + renv_bootstrap_profile_load(project) + + # construct path to library root + root <- renv_bootstrap_library_root(project) + + # construct library prefix for platform + prefix <- renv_bootstrap_platform_prefix() + + # construct full libpath + libpath <- file.path(root, prefix) + + # run bootstrap code + renv_bootstrap_exec(project, libpath, version) + + invisible() + +}) diff --git a/blog/2026/q2-building-permits/renv/settings.json 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b/renv/.gitignore new file mode 100644 index 0000000..0ec0cbb --- /dev/null +++ b/renv/.gitignore @@ -0,0 +1,7 @@ +library/ +local/ +cellar/ +lock/ +python/ +sandbox/ +staging/ diff --git a/renv/activate.R b/renv/activate.R new file mode 100644 index 0000000..2435da9 --- /dev/null +++ b/renv/activate.R @@ -0,0 +1,1438 @@ + +local({ + + # the requested version of renv + version <- "1.2.3" + attr(version, "md5") <- NULL + attr(version, "sha") <- NULL + + # the project directory + project <- Sys.getenv("RENV_PROJECT") + if (!nzchar(project)) + project <- getwd() + + # use start-up diagnostics if enabled + diagnostics <- Sys.getenv("RENV_STARTUP_DIAGNOSTICS", unset = "FALSE") + if (diagnostics) { + start <- Sys.time() + profile <- tempfile("renv-startup-", fileext = ".Rprof") + utils::Rprof(profile) + on.exit({ + utils::Rprof(NULL) + elapsed <- signif(difftime(Sys.time(), start, units = "auto"), digits = 2L) + writeLines(sprintf("- renv took %s to run the autoloader.", format(elapsed))) + writeLines(sprintf("- Profile: %s", profile)) + print(utils::summaryRprof(profile)) + }, add = TRUE) + } + + # figure out whether the autoloader is enabled + enabled <- local({ + + # first, check config option + override <- getOption("renv.config.autoloader.enabled") + if (!is.null(override)) + return(override) + + # if we're being run in a context where R_LIBS is already set, + # don't load -- presumably we're being run as a sub-process and + # the parent process has already set up library paths for us + rcmd <- Sys.getenv("R_CMD", unset = NA) + rlibs <- Sys.getenv("R_LIBS", unset = NA) + if (!is.na(rlibs) && !is.na(rcmd)) + return(FALSE) + + # next, check environment variables + # prefer using the configuration one in the future + envvars <- c( + "RENV_CONFIG_AUTOLOADER_ENABLED", + "RENV_AUTOLOADER_ENABLED", + "RENV_ACTIVATE_PROJECT" + ) + + for (envvar in envvars) { + envval <- Sys.getenv(envvar, unset = NA) + if (!is.na(envval)) + return(tolower(envval) %in% c("true", "t", "1")) + } + + # enable by default + TRUE + + }) + + # bail if we're not enabled + if (!enabled) { + + # if we're not enabled, we might still need to manually load + # the user profile here + profile <- Sys.getenv("R_PROFILE_USER", unset = "~/.Rprofile") + if (file.exists(profile)) { + cfg <- Sys.getenv("RENV_CONFIG_USER_PROFILE", unset = "TRUE") + if (tolower(cfg) %in% c("true", "t", "1")) + sys.source(profile, envir = globalenv()) + } + + return(FALSE) + + } + + # avoid recursion + if (identical(getOption("renv.autoloader.running"), TRUE)) { + warning("ignoring recursive attempt to run renv autoloader") + return(invisible(TRUE)) + } + + # signal that we're loading renv during R startup + options(renv.autoloader.running = TRUE) + on.exit(options(renv.autoloader.running = NULL), add = TRUE) + + # signal that we've consented to use renv + options(renv.consent = TRUE) + + # load the 'utils' package eagerly -- this ensures that renv shims, which + # mask 'utils' packages, will come first on the search path + library(utils, lib.loc = .Library) + + # unload renv if it's already been loaded + if ("renv" %in% loadedNamespaces()) + unloadNamespace("renv") + + # load bootstrap tools + ansify <- function(text) { + if (renv_ansify_enabled()) + renv_ansify_enhanced(text) + else + renv_ansify_default(text) + } + + renv_ansify_enabled <- function() { + + override <- Sys.getenv("RENV_ANSIFY_ENABLED", unset = NA) + if (!is.na(override)) + return(as.logical(override)) + + pane <- Sys.getenv("RSTUDIO_CHILD_PROCESS_PANE", unset = NA) + if (identical(pane, "build")) + return(FALSE) + + testthat <- Sys.getenv("TESTTHAT", unset = "false") + if (tolower(testthat) %in% "true") + return(FALSE) + + iderun <- Sys.getenv("R_CLI_HAS_HYPERLINK_IDE_RUN", unset = "false") + if (tolower(iderun) %in% "false") + return(FALSE) + + TRUE + + } + + renv_ansify_default <- function(text) { + text + } + + renv_ansify_enhanced <- function(text) { + + # R help links + pattern <- "`\\?(renv::(?:[^`])+)`" + replacement <- "`\033]8;;x-r-help:\\1\a?\\1\033]8;;\a`" + text <- gsub(pattern, replacement, text, perl = TRUE) + + # runnable code + pattern <- "`(renv::(?:[^`])+)`" + replacement <- "`\033]8;;x-r-run:\\1\a\\1\033]8;;\a`" + text <- gsub(pattern, replacement, text, perl = TRUE) + + # return ansified text + text + + } + + renv_ansify_init <- function() { + + envir <- renv_envir_self() + if (renv_ansify_enabled()) + assign("ansify", renv_ansify_enhanced, envir = envir) + else + assign("ansify", renv_ansify_default, envir = envir) + + } + + `%||%` <- function(x, y) { + if (is.null(x)) y else x + } + + catf <- function(fmt, ..., appendLF = TRUE) { + + quiet <- getOption("renv.bootstrap.quiet", default = FALSE) + if (quiet) + return(invisible()) + + # also check for config environment variables that should suppress messages + # https://github.com/rstudio/renv/issues/2214 + enabled <- Sys.getenv("RENV_CONFIG_STARTUP_QUIET", unset = NA) + if (!is.na(enabled) && tolower(enabled) %in% c("true", "1")) + return(invisible()) + + enabled <- Sys.getenv("RENV_CONFIG_SYNCHRONIZED_CHECK", unset = NA) + if (!is.na(enabled) && tolower(enabled) %in% c("false", "0")) + return(invisible()) + + msg <- sprintf(fmt, ...) + cat(msg, file = stdout(), sep = if (appendLF) "\n" else "") + + invisible(msg) + + } + + header <- function(label, + ..., + prefix = "#", + suffix = "-", + n = min(getOption("width"), 78)) + { + label <- sprintf(label, ...) + n <- max(n - nchar(label) - nchar(prefix) - 2L, 8L) + if (n <= 0) + return(paste(prefix, label)) + + tail <- paste(rep.int(suffix, n), collapse = "") + paste0(prefix, " ", label, " ", tail) + + } + + heredoc <- function(text, leave = 0) { + + # remove leading, trailing whitespace + trimmed <- gsub("^\\s*\\n|\\n\\s*$", "", text) + + # split into lines + lines <- strsplit(trimmed, "\n", fixed = TRUE)[[1L]] + + # compute common indent + indent <- regexpr("[^[:space:]]", lines) + common <- min(setdiff(indent, -1L)) - leave + text <- paste(substring(lines, common), collapse = "\n") + + # substitute in ANSI links for executable renv code + ansify(text) + + } + + bootstrap <- function(version, library) { + + friendly <- renv_bootstrap_version_friendly(version) + section <- header(sprintf("Bootstrapping renv %s", friendly)) + catf(section) + + # ensure the target library path exists; required for file.copy(..., recursive = TRUE) + dir.create(library, showWarnings = FALSE, recursive = TRUE) + + # try to install renv from cache + md5 <- attr(version, "md5", exact = TRUE) + if (length(md5)) { + pkgpath <- renv_bootstrap_find(version) + if (length(pkgpath) && file.exists(pkgpath)) { + ok <- file.copy(pkgpath, library, recursive = TRUE) + if (isTRUE(ok)) + return(invisible()) + } + } + + # attempt to download renv + catf("- Downloading renv ... ", appendLF = FALSE) + withCallingHandlers( + tarball <- renv_bootstrap_download(version), + error = function(err) { + catf("FAILED") + stop("failed to download:\n", conditionMessage(err)) + } + ) + catf("OK") + on.exit(unlink(tarball), add = TRUE) + + # now attempt to install + catf("- Installing renv ... ", appendLF = FALSE) + withCallingHandlers( + status <- renv_bootstrap_install(version, tarball, library), + error = function(err) { + catf("FAILED") + stop("failed to install:\n", conditionMessage(err)) + } + ) + catf("OK") + + # add empty line to break up bootstrapping from normal output + catf("") + return(invisible()) + } + + renv_bootstrap_tests_running <- function() { + getOption("renv.tests.running", default = FALSE) + } + + renv_bootstrap_repos <- function() { + + # get CRAN repository + cran <- getOption("renv.repos.cran", "https://cloud.r-project.org") + + # check for repos override + repos <- Sys.getenv("RENV_CONFIG_REPOS_OVERRIDE", unset = NA) + if (!is.na(repos)) { + + # split on ';' if present + parts <- strsplit(repos, ";", fixed = TRUE)[[1L]] + + # split into named repositories if present + idx <- regexpr("=", parts, fixed = TRUE) + keys <- substring(parts, 1L, idx - 1L) + vals <- substring(parts, idx + 1L) + names(vals) <- keys + + # if we have a single unnamed repository, call it CRAN + if (length(vals) == 1L && identical(keys, "")) + names(vals) <- "CRAN" + + return(vals) + + } + + # check for lockfile repositories + repos <- tryCatch(renv_bootstrap_repos_lockfile(), error = identity) + if (!inherits(repos, "error") && length(repos)) + return(repos) + + # retrieve current repos + repos <- getOption("repos") + + # ensure @CRAN@ entries are resolved + repos[repos == "@CRAN@"] <- cran + + # add in renv.bootstrap.repos if set + default <- c(FALLBACK = "https://cloud.r-project.org") + extra <- getOption("renv.bootstrap.repos", default = default) + repos <- c(repos, extra) + + # remove duplicates that might've snuck in + dupes <- duplicated(repos) | duplicated(names(repos)) + repos[!dupes] + + } + + renv_bootstrap_repos_lockfile <- function() { + + lockpath <- Sys.getenv("RENV_PATHS_LOCKFILE", unset = "renv.lock") + if (!file.exists(lockpath)) + return(NULL) + + lockfile <- tryCatch(renv_json_read(lockpath), error = identity) + if (inherits(lockfile, "error")) { + warning(lockfile) + return(NULL) + } + + repos <- lockfile$R$Repositories + if (length(repos) == 0) + return(NULL) + + keys <- vapply(repos, `[[`, "Name", FUN.VALUE = character(1)) + vals <- vapply(repos, `[[`, "URL", FUN.VALUE = character(1)) + names(vals) <- keys + + return(vals) + + } + + renv_bootstrap_download <- function(version) { + + sha <- attr(version, "sha", exact = TRUE) + + methods <- if (!is.null(sha)) { + + # attempting to bootstrap a development version of renv + c( + function() renv_bootstrap_download_tarball(sha), + function() renv_bootstrap_download_github(sha) + ) + + } else { + + # attempting to bootstrap a release version of renv + c( + function() renv_bootstrap_download_tarball(version), + function() renv_bootstrap_download_cran_latest(version), + function() renv_bootstrap_download_cran_archive(version) + ) + + } + + for (method in methods) { + path <- tryCatch(method(), error = identity) + if (is.character(path) && file.exists(path)) + return(path) + } + + stop("All download methods failed") + + } + + renv_bootstrap_download_impl <- function(url, destfile) { + + mode <- "wb" + + # https://bugs.r-project.org/bugzilla/show_bug.cgi?id=17715 + fixup <- + Sys.info()[["sysname"]] == "Windows" && + substring(url, 1L, 5L) == "file:" + + if (fixup) + mode <- "w+b" + + args <- list( + url = url, + destfile = destfile, + mode = mode, + quiet = TRUE + ) + + if ("headers" %in% names(formals(utils::download.file))) { + headers <- renv_bootstrap_download_custom_headers(url) + if (length(headers) && is.character(headers)) + args$headers <- headers + } + + do.call(utils::download.file, args) + + } + + renv_bootstrap_download_custom_headers <- function(url) { + + headers <- getOption("renv.download.headers") + if (is.null(headers)) + return(character()) + + if (!is.function(headers)) + stopf("'renv.download.headers' is not a function") + + headers <- headers(url) + if (length(headers) == 0L) + return(character()) + + if (is.list(headers)) + headers <- unlist(headers, recursive = FALSE, use.names = TRUE) + + ok <- + is.character(headers) && + is.character(names(headers)) && + all(nzchar(names(headers))) + + if (!ok) + stop("invocation of 'renv.download.headers' did not return a named character vector") + + headers + + } + + renv_bootstrap_download_cran_latest <- function(version) { + + spec <- renv_bootstrap_download_cran_latest_find(version) + type <- spec$type + repos <- spec$repos + + baseurl <- utils::contrib.url(repos = repos, type = type) + ext <- if (identical(type, "source")) + ".tar.gz" + else if (Sys.info()[["sysname"]] == "Windows") + ".zip" + else + ".tgz" + name <- sprintf("renv_%s%s", version, ext) + url <- paste(baseurl, name, sep = "/") + + destfile <- file.path(tempdir(), name) + status <- tryCatch( + renv_bootstrap_download_impl(url, destfile), + condition = identity + ) + + if (inherits(status, "condition")) + return(FALSE) + + # report success and return + destfile + + } + + renv_bootstrap_download_cran_latest_find <- function(version) { + + # check whether binaries are supported on this system + binary <- + getOption("renv.bootstrap.binary", default = TRUE) && + !identical(.Platform$pkgType, "source") && + !identical(getOption("pkgType"), "source") && + Sys.info()[["sysname"]] %in% c("Darwin", "Windows") + + types <- c(if (binary) "binary", "source") + + # iterate over types + repositories + for (type in types) { + for (repos in renv_bootstrap_repos()) { + + # build arguments for utils::available.packages() call + args <- list(type = type, repos = repos) + + # add custom headers if available -- note that + # utils::available.packages() will pass this to download.file() + if ("headers" %in% names(formals(utils::download.file))) { + headers <- renv_bootstrap_download_custom_headers(repos) + if (length(headers) && is.character(headers)) + args$headers <- headers + } + + # retrieve package database + db <- tryCatch( + as.data.frame( + do.call(utils::available.packages, args), + stringsAsFactors = FALSE + ), + error = identity + ) + + if (inherits(db, "error")) + next + + # check for compatible entry + entry <- db[db$Package %in% "renv" & db$Version %in% version, ] + if (nrow(entry) == 0) + next + + # found it; return spec to caller + spec <- list(entry = entry, type = type, repos = repos) + return(spec) + + } + } + + # if we got here, we failed to find renv + fmt <- "renv %s is not available from your declared package repositories" + stop(sprintf(fmt, version)) + + } + + renv_bootstrap_download_cran_archive <- function(version) { + + name <- sprintf("renv_%s.tar.gz", version) + repos <- renv_bootstrap_repos() + urls <- file.path(repos, "src/contrib/Archive/renv", name) + destfile <- file.path(tempdir(), name) + + for (url in urls) { + + status <- tryCatch( + renv_bootstrap_download_impl(url, destfile), + condition = identity + ) + + if (identical(status, 0L)) + return(destfile) + + } + + return(FALSE) + + } + + renv_bootstrap_find <- function(version) { + + path <- renv_bootstrap_find_cache(version) + if (length(path) && file.exists(path)) { + catf("- Using renv %s from global package cache", version) + return(path) + } + + } + + renv_bootstrap_find_cache <- function(version) { + + md5 <- attr(version, "md5", exact = TRUE) + if (is.null(md5)) + return() + + # infer path to renv cache + cache <- Sys.getenv("RENV_PATHS_CACHE", unset = "") + if (!nzchar(cache)) { + root <- Sys.getenv("RENV_PATHS_ROOT", unset = NA) + if (!is.na(root)) + cache <- file.path(root, "cache") + } + + if (!nzchar(cache)) { + tools <- asNamespace("tools") + if (is.function(tools$R_user_dir)) { + root <- tools$R_user_dir("renv", "cache") + cache <- file.path(root, "cache") + } + } + + # start completing path to cache + file.path( + cache, + renv_bootstrap_cache_version(), + renv_bootstrap_platform_prefix(), + "renv", + version, + md5, + "renv" + ) + + } + + renv_bootstrap_download_tarball <- function(version) { + + # if the user has provided the path to a tarball via + # an environment variable, then use it + tarball <- Sys.getenv("RENV_BOOTSTRAP_TARBALL", unset = NA) + if (is.na(tarball)) + return() + + # allow directories + if (dir.exists(tarball)) { + name <- sprintf("renv_%s.tar.gz", version) + tarball <- file.path(tarball, name) + } + + # bail if it doesn't exist + if (!file.exists(tarball)) { + + # let the user know we weren't able to honour their request + fmt <- "- RENV_BOOTSTRAP_TARBALL is set (%s) but does not exist." + msg <- sprintf(fmt, tarball) + warning(msg) + + # bail + return() + + } + + catf("- Using local tarball '%s'.", tarball) + tarball + + } + + renv_bootstrap_github_token <- function() { + for (envvar in c("GITHUB_TOKEN", "GITHUB_PAT", "GH_TOKEN")) { + envval <- Sys.getenv(envvar, unset = NA) + if (!is.na(envval)) + return(envval) + } + } + + renv_bootstrap_download_github <- function(version) { + + enabled <- Sys.getenv("RENV_BOOTSTRAP_FROM_GITHUB", unset = "TRUE") + if (!identical(enabled, "TRUE")) + return(FALSE) + + # prepare download options + token <- renv_bootstrap_github_token() + if (is.null(token)) + token <- "" + + if (nzchar(Sys.which("curl")) && nzchar(token)) { + fmt <- "--location --fail --header \"Authorization: token %s\"" + extra <- sprintf(fmt, token) + saved <- options("download.file.method", "download.file.extra") + options(download.file.method = "curl", download.file.extra = extra) + on.exit(do.call(base::options, saved), add = TRUE) + } else if (nzchar(Sys.which("wget")) && nzchar(token)) { + fmt <- "--header=\"Authorization: token %s\"" + extra <- sprintf(fmt, token) + saved <- options("download.file.method", "download.file.extra") + options(download.file.method = "wget", download.file.extra = extra) + on.exit(do.call(base::options, saved), add = TRUE) + } + + url <- file.path("https://api.github.com/repos/rstudio/renv/tarball", version) + name <- sprintf("renv_%s.tar.gz", version) + destfile <- file.path(tempdir(), name) + + status <- tryCatch( + renv_bootstrap_download_impl(url, destfile), + condition = identity + ) + + if (!identical(status, 0L)) + return(FALSE) + + renv_bootstrap_download_augment(destfile) + + return(destfile) + + } + + # Add Sha to DESCRIPTION. This is stop gap until #890, after which we + # can use renv::install() to fully capture metadata. + renv_bootstrap_download_augment <- function(destfile) { + sha <- renv_bootstrap_git_extract_sha1_tar(destfile) + if (is.null(sha)) { + return() + } + + # Untar + tempdir <- tempfile("renv-github-") + on.exit(unlink(tempdir, recursive = TRUE), add = TRUE) + untar(destfile, exdir = tempdir) + pkgdir <- dir(tempdir, full.names = TRUE)[[1]] + + # Modify description + desc_path <- file.path(pkgdir, "DESCRIPTION") + desc_lines <- readLines(desc_path) + remotes_fields <- c( + "RemoteType: github", + "RemoteHost: api.github.com", + "RemoteRepo: renv", + "RemoteUsername: rstudio", + "RemotePkgRef: rstudio/renv", + paste("RemoteRef: ", sha), + paste("RemoteSha: ", sha) + ) + writeLines(c(desc_lines[desc_lines != ""], remotes_fields), con = desc_path) + + # Re-tar + local({ + old <- setwd(tempdir) + on.exit(setwd(old), add = TRUE) + + tar(destfile, compression = "gzip") + }) + invisible() + } + + # Extract the commit hash from a git archive. Git archives include the SHA1 + # hash as the comment field of the tarball pax extended header + # (see https://www.kernel.org/pub/software/scm/git/docs/git-archive.html) + # For GitHub archives this should be the first header after the default one + # (512 byte) header. + renv_bootstrap_git_extract_sha1_tar <- function(bundle) { + + # open the bundle for reading + # We use gzcon for everything because (from ?gzcon) + # > Reading from a connection which does not supply a 'gzip' magic + # > header is equivalent to reading from the original connection + conn <- gzcon(file(bundle, open = "rb", raw = TRUE)) + on.exit(close(conn)) + + # The default pax header is 512 bytes long and the first pax extended header + # with the comment should be 51 bytes long + # `52 comment=` (11 chars) + 40 byte SHA1 hash + len <- 0x200 + 0x33 + res <- rawToChar(readBin(conn, "raw", n = len)[0x201:len]) + + if (grepl("^52 comment=", res)) { + sub("52 comment=", "", res) + } else { + NULL + } + } + + renv_bootstrap_install <- function(version, tarball, library) { + + # attempt to install it into project library + dir.create(library, showWarnings = FALSE, recursive = TRUE) + output <- renv_bootstrap_install_impl(library, tarball) + + # check for successful install + status <- attr(output, "status") + if (is.null(status) || identical(status, 0L)) + return(status) + + # an error occurred; report it + header <- "installation of renv failed" + lines <- paste(rep.int("=", nchar(header)), collapse = "") + text <- paste(c(header, lines, output), collapse = "\n") + stop(text) + + } + + renv_bootstrap_install_impl <- function(library, tarball) { + + # invoke using system2 so we can capture and report output + bin <- R.home("bin") + exe <- if (Sys.info()[["sysname"]] == "Windows") "R.exe" else "R" + R <- file.path(bin, exe) + + args <- c( + "--vanilla", "CMD", "INSTALL", "--no-multiarch", + "-l", shQuote(path.expand(library)), + shQuote(path.expand(tarball)) + ) + + system2(R, args, stdout = TRUE, stderr = TRUE) + + } + + renv_bootstrap_platform_prefix_default <- function() { + + # read version component + version <- Sys.getenv("RENV_PATHS_VERSION", unset = "R-%v") + + # expand placeholders + placeholders <- list( + list("%v", format(getRversion()[1, 1:2])), + list("%V", format(getRversion()[1, 1:3])) + ) + + for (placeholder in placeholders) + version <- gsub(placeholder[[1L]], placeholder[[2L]], version, fixed = TRUE) + + # include SVN revision for development versions of R + # (to avoid sharing platform-specific artefacts with released versions of R) + devel <- + identical(R.version[["status"]], "Under development (unstable)") || + identical(R.version[["nickname"]], "Unsuffered Consequences") + + if (devel) + version <- paste(version, R.version[["svn rev"]], sep = "-r") + + version + + } + + renv_bootstrap_platform_prefix <- function() { + + # construct version prefix + version <- renv_bootstrap_platform_prefix_default() + + # build list of path components + components <- c(version, R.version$platform) + + # include prefix if provided by user + prefix <- renv_bootstrap_platform_prefix_impl() + if (!is.na(prefix) && nzchar(prefix)) + components <- c(prefix, components) + + # build prefix + paste(components, collapse = "/") + + } + + renv_bootstrap_platform_prefix_impl <- function() { + + # if an explicit prefix has been supplied, use it + prefix <- Sys.getenv("RENV_PATHS_PREFIX", unset = NA) + if (!is.na(prefix)) + return(prefix) + + # if the user has requested an automatic prefix, generate it + auto <- Sys.getenv("RENV_PATHS_PREFIX_AUTO", unset = NA) + if (is.na(auto) && getRversion() >= "4.4.0") + auto <- "TRUE" + + if (auto %in% c("TRUE", "True", "true", "1")) + return(renv_bootstrap_platform_prefix_auto()) + + # empty string on failure + "" + + } + + renv_bootstrap_platform_prefix_auto <- function() { + + prefix <- tryCatch(renv_bootstrap_platform_os(), error = identity) + if (inherits(prefix, "error") || prefix %in% "unknown") { + + msg <- paste( + "failed to infer current operating system", + "please file a bug report at https://github.com/rstudio/renv/issues", + sep = "; " + ) + + warning(msg) + + } + + prefix + + } + + renv_bootstrap_platform_os <- function() { + + sysinfo <- Sys.info() + sysname <- sysinfo[["sysname"]] + + # handle Windows + macOS up front + if (sysname == "Windows") + return("windows") + else if (sysname == "Darwin") + return("macos") + + # check for os-release files + for (file in c("/etc/os-release", "/usr/lib/os-release")) + if (file.exists(file)) + return(renv_bootstrap_platform_os_via_os_release(file, sysinfo)) + + # check for redhat-release files + if (file.exists("/etc/redhat-release")) + return(renv_bootstrap_platform_os_via_redhat_release()) + + "unknown" + + } + + renv_bootstrap_platform_os_via_os_release <- function(file, sysinfo) { + + # read /etc/os-release + release <- utils::read.table( + file = file, + sep = "=", + quote = c("\"", "'"), + col.names = c("Key", "Value"), + comment.char = "#", + stringsAsFactors = FALSE + ) + + vars <- as.list(release$Value) + names(vars) <- release$Key + + # get os name + os <- tolower(sysinfo[["sysname"]]) + + # read id + id <- "unknown" + for (field in c("ID", "ID_LIKE")) { + if (field %in% names(vars) && nzchar(vars[[field]])) { + id <- vars[[field]] + break + } + } + + # read version + version <- "unknown" + for (field in c("UBUNTU_CODENAME", "VERSION_CODENAME", "VERSION_ID", "BUILD_ID")) { + if (field %in% names(vars) && nzchar(vars[[field]])) { + version <- vars[[field]] + break + } + } + + # join together + paste(c(os, id, version), collapse = "-") + + } + + renv_bootstrap_platform_os_via_redhat_release <- function() { + + # read /etc/redhat-release + contents <- readLines("/etc/redhat-release", warn = FALSE) + + # infer id + id <- if (grepl("centos", contents, ignore.case = TRUE)) + "centos" + else if (grepl("redhat", contents, ignore.case = TRUE)) + "redhat" + else + "unknown" + + # try to find a version component (very hacky) + version <- "unknown" + + parts <- strsplit(contents, "[[:space:]]")[[1L]] + for (part in parts) { + + nv <- tryCatch(numeric_version(part), error = identity) + if (inherits(nv, "error")) + next + + version <- nv[1, 1] + break + + } + + paste(c("linux", id, version), collapse = "-") + + } + + renv_bootstrap_library_root_name <- function(project) { + + # use project name as-is if requested + asis <- Sys.getenv("RENV_PATHS_LIBRARY_ROOT_ASIS", unset = "FALSE") + if (asis) + return(basename(project)) + + # otherwise, disambiguate based on project's path + id <- substring(renv_bootstrap_hash_text(project), 1L, 8L) + paste(basename(project), id, sep = "-") + + } + + renv_bootstrap_library_root <- function(project) { + + prefix <- renv_bootstrap_profile_prefix() + + path <- Sys.getenv("RENV_PATHS_LIBRARY", unset = NA) + if (!is.na(path)) + return(paste(c(path, prefix), collapse = "/")) + + path <- renv_bootstrap_library_root_impl(project) + if (!is.null(path)) { + name <- renv_bootstrap_library_root_name(project) + return(paste(c(path, prefix, name), collapse = "/")) + } + + renv_bootstrap_paths_renv("library", project = project) + + } + + renv_bootstrap_library_root_impl <- function(project) { + + root <- Sys.getenv("RENV_PATHS_LIBRARY_ROOT", unset = NA) + if (!is.na(root)) + return(root) + + type <- renv_bootstrap_project_type(project) + if (identical(type, "package")) { + userdir <- renv_bootstrap_user_dir() + return(file.path(userdir, "library")) + } + + } + + renv_bootstrap_validate_version <- function(version, description = NULL) { + + # resolve description file + # + # avoid passing lib.loc to `packageDescription()` below, since R will + # use the loaded version of the package by default anyhow. note that + # this function should only be called after 'renv' is loaded + # https://github.com/rstudio/renv/issues/1625 + description <- description %||% packageDescription("renv") + + # check whether requested version 'version' matches loaded version of renv + sha <- attr(version, "sha", exact = TRUE) + valid <- if (!is.null(sha)) + renv_bootstrap_validate_version_dev(sha, description) + else + renv_bootstrap_validate_version_release(version, description) + + if (valid) + return(TRUE) + + # the loaded version of renv doesn't match the requested version; + # give the user instructions on how to proceed + dev <- identical(description[["RemoteType"]], "github") + remote <- if (dev) + paste("rstudio/renv", description[["RemoteSha"]], sep = "@") + else + paste("renv", description[["Version"]], sep = "@") + + # display both loaded version + sha if available + friendly <- renv_bootstrap_version_friendly( + version = description[["Version"]], + sha = if (dev) description[["RemoteSha"]] + ) + + fmt <- heredoc(" + renv %1$s was loaded from project library, but this project is configured to use renv %2$s. + - Use `renv::record(\"%3$s\")` to record renv %1$s in the lockfile. + - Use `renv::restore(packages = \"renv\")` to install renv %2$s into the project library. + ") + catf(fmt, friendly, renv_bootstrap_version_friendly(version), remote) + + FALSE + + } + + renv_bootstrap_validate_version_dev <- function(version, description) { + + expected <- description[["RemoteSha"]] + if (!is.character(expected)) + return(FALSE) + + pattern <- sprintf("^\\Q%s\\E", version) + grepl(pattern, expected, perl = TRUE) + + } + + renv_bootstrap_validate_version_release <- function(version, description) { + expected <- description[["Version"]] + is.character(expected) && identical(c(expected), c(version)) + } + + renv_bootstrap_hash_text <- function(text) { + + hashfile <- tempfile("renv-hash-") + on.exit(unlink(hashfile), add = TRUE) + + writeLines(text, con = hashfile) + tools::md5sum(hashfile) + + } + + renv_bootstrap_load <- function(project, libpath, version) { + + # try to load renv from the project library + if (!requireNamespace("renv", lib.loc = libpath, quietly = TRUE)) + return(FALSE) + + # warn if the version of renv loaded does not match + renv_bootstrap_validate_version(version) + + # execute renv load hooks, if any + hooks <- getHook("renv::autoload") + for (hook in hooks) + if (is.function(hook)) + tryCatch(hook(), error = warnify) + + # load the project + renv::load(project) + + TRUE + + } + + renv_bootstrap_profile_load <- function(project) { + + # if RENV_PROFILE is already set, just use that + profile <- Sys.getenv("RENV_PROFILE", unset = NA) + if (!is.na(profile) && nzchar(profile)) + return(profile) + + # check for a profile file (nothing to do if it doesn't exist) + path <- renv_bootstrap_paths_renv("profile", profile = FALSE, project = project) + if (!file.exists(path)) + return(NULL) + + # read the profile, and set it if it exists + contents <- readLines(path, warn = FALSE) + if (length(contents) == 0L) + return(NULL) + + # set RENV_PROFILE + profile <- contents[[1L]] + if (!profile %in% c("", "default")) + Sys.setenv(RENV_PROFILE = profile) + + profile + + } + + renv_bootstrap_profile_prefix <- function() { + profile <- renv_bootstrap_profile_get() + if (!is.null(profile)) + return(file.path("profiles", profile, "renv")) + } + + renv_bootstrap_profile_get <- function() { + profile <- Sys.getenv("RENV_PROFILE", unset = "") + renv_bootstrap_profile_normalize(profile) + } + + renv_bootstrap_profile_set <- function(profile) { + profile <- renv_bootstrap_profile_normalize(profile) + if (is.null(profile)) + Sys.unsetenv("RENV_PROFILE") + else + Sys.setenv(RENV_PROFILE = profile) + } + + renv_bootstrap_profile_normalize <- function(profile) { + + if (is.null(profile) || profile %in% c("", "default")) + return(NULL) + + profile + + } + + renv_bootstrap_path_absolute <- function(path) { + + substr(path, 1L, 1L) %in% c("~", "/", "\\") || ( + substr(path, 1L, 1L) %in% c(letters, LETTERS) && + substr(path, 2L, 3L) %in% c(":/", ":\\") + ) + + } + + renv_bootstrap_paths_renv <- function(..., profile = TRUE, project = NULL) { + renv <- Sys.getenv("RENV_PATHS_RENV", unset = "renv") + root <- if (renv_bootstrap_path_absolute(renv)) NULL else project + prefix <- if (profile) renv_bootstrap_profile_prefix() + components <- c(root, renv, prefix, ...) + paste(components, collapse = "/") + } + + renv_bootstrap_project_type <- function(path) { + + descpath <- file.path(path, "DESCRIPTION") + if (!file.exists(descpath)) + return("unknown") + + desc <- tryCatch( + read.dcf(descpath, all = TRUE), + error = identity + ) + + if (inherits(desc, "error")) + return("unknown") + + type <- desc$Type + if (!is.null(type)) + return(tolower(type)) + + package <- desc$Package + if (!is.null(package)) + return("package") + + "unknown" + + } + + renv_bootstrap_user_dir <- function() { + dir <- renv_bootstrap_user_dir_impl() + path.expand(chartr("\\", "/", dir)) + } + + renv_bootstrap_user_dir_impl <- function() { + + # use local override if set + override <- getOption("renv.userdir.override") + if (!is.null(override)) + return(override) + + # use R_user_dir if available + tools <- asNamespace("tools") + if (is.function(tools$R_user_dir)) + return(tools$R_user_dir("renv", "cache")) + + # try using our own backfill for older versions of R + envvars <- c("R_USER_CACHE_DIR", "XDG_CACHE_HOME") + for (envvar in envvars) { + root <- Sys.getenv(envvar, unset = NA) + if (!is.na(root)) + return(file.path(root, "R/renv")) + } + + # use platform-specific default fallbacks + if (Sys.info()[["sysname"]] == "Windows") + file.path(Sys.getenv("LOCALAPPDATA"), "R/cache/R/renv") + else if (Sys.info()[["sysname"]] == "Darwin") + "~/Library/Caches/org.R-project.R/R/renv" + else + "~/.cache/R/renv" + + } + + renv_bootstrap_version_friendly <- function(version, shafmt = NULL, sha = NULL) { + sha <- sha %||% attr(version, "sha", exact = TRUE) + parts <- c(version, sprintf(shafmt %||% " [sha: %s]", substring(sha, 1L, 7L))) + paste(parts, collapse = "") + } + + renv_bootstrap_exec <- function(project, libpath, version) { + if (!renv_bootstrap_load(project, libpath, version)) + renv_bootstrap_run(project, libpath, version) + } + + renv_bootstrap_run <- function(project, libpath, version) { + tryCatch( + renv_bootstrap_run_impl(project, libpath, version), + error = function(e) { + msg <- paste( + "failed to bootstrap renv: the project will not be loaded.", + paste("Reason:", conditionMessage(e)), + "Use `renv::activate()` to re-initialize the project.", + sep = "\n" + ) + warning(msg, call. = FALSE) + } + ) + } + + renv_bootstrap_run_impl <- function(project, libpath, version) { + + # perform bootstrap + bootstrap(version, libpath) + + # exit early if we're just testing bootstrap + if (!is.na(Sys.getenv("RENV_BOOTSTRAP_INSTALL_ONLY", unset = NA))) + return(TRUE) + + # try again to load + if (requireNamespace("renv", lib.loc = libpath, quietly = TRUE)) { + return(renv::load(project = project)) + } + + # failed to download or load renv; warn the user + msg <- c( + "Failed to find an renv installation: the project will not be loaded.", + "Use `renv::activate()` to re-initialize the project." + ) + + warning(paste(msg, collapse = "\n"), call. = FALSE) + + } + + renv_bootstrap_cache_version <- function() { + # NOTE: users should normally not override the cache version; + # this is provided just to make testing easier + Sys.getenv("RENV_CACHE_VERSION", unset = "v5") + } + + renv_bootstrap_cache_version_previous <- function() { + version <- renv_bootstrap_cache_version() + number <- as.integer(substring(version, 2L)) + paste("v", number - 1L, sep = "") + } + + renv_json_read <- function(file = NULL, text = NULL) { + + jlerr <- NULL + + # if jsonlite is loaded, use that instead + if ("jsonlite" %in% loadedNamespaces()) { + + json <- tryCatch(renv_json_read_jsonlite(file, text), error = identity) + if (!inherits(json, "error")) + return(json) + + jlerr <- json + + } + + # otherwise, fall back to the default JSON reader + json <- tryCatch(renv_json_read_default(file, text), error = identity) + if (!inherits(json, "error")) + return(json) + + # report an error + if (!is.null(jlerr)) + stop(jlerr) + else + stop(json) + + } + + renv_json_read_jsonlite <- function(file = NULL, text = NULL) { + text <- paste(text %||% readLines(file, warn = FALSE), collapse = "\n") + jsonlite::fromJSON(txt = text, simplifyVector = FALSE) + } + + renv_json_read_patterns <- function() { + + list( + + # objects + list("{", "\t\n\tobject(\t\n\t", TRUE), + list("}", "\t\n\t)\t\n\t", TRUE), + + # arrays + list("[", "\t\n\tarray(\t\n\t", TRUE), + list("]", "\n\t\n)\n\t\n", TRUE), + + # maps + list(":", "\t\n\t=\t\n\t", TRUE), + + # newlines + list("\\u000a", "\n", FALSE) + + ) + + } + + renv_json_read_envir <- function() { + + envir <- new.env(parent = emptyenv()) + + envir[["+"]] <- `+` + envir[["-"]] <- `-` + + envir[["object"]] <- function(...) { + result <- list(...) + names(result) <- as.character(names(result)) + result + } + + envir[["array"]] <- list + + envir[["true"]] <- TRUE + envir[["false"]] <- FALSE + envir[["null"]] <- NULL + + envir + + } + + renv_json_read_remap <- function(object, patterns) { + + # repair names if necessary + if (!is.null(names(object))) { + + nms <- names(object) + for (pattern in patterns) + nms <- gsub(pattern[[2L]], pattern[[1L]], nms, fixed = TRUE) + names(object) <- nms + + } + + # repair strings if necessary + if (is.character(object)) { + for (pattern in patterns) + object <- gsub(pattern[[2L]], pattern[[1L]], object, fixed = TRUE) + } + + # recurse for other objects + if (is.recursive(object)) + for (i in seq_along(object)) + object[i] <- list(renv_json_read_remap(object[[i]], patterns)) + + # return remapped object + object + + } + + renv_json_read_default <- function(file = NULL, text = NULL) { + + # read json text + text <- paste(text %||% readLines(file, warn = FALSE), collapse = "\n") + + # convert into something the R parser will understand + patterns <- renv_json_read_patterns() + transformed <- text + for (pattern in patterns) + transformed <- gsub(pattern[[1L]], pattern[[2L]], transformed, fixed = TRUE) + + # parse it + rfile <- tempfile("renv-json-", fileext = ".R") + on.exit(unlink(rfile), add = TRUE) + writeLines(transformed, con = rfile) + json <- parse(rfile, keep.source = FALSE, srcfile = NULL)[[1L]] + + # evaluate in safe environment + result <- eval(json, envir = renv_json_read_envir()) + + # fix up strings if necessary -- do so only with reversible patterns + patterns <- Filter(function(pattern) pattern[[3L]], patterns) + renv_json_read_remap(result, patterns) + + } + + + # load the renv profile, if any + renv_bootstrap_profile_load(project) + + # construct path to library root + root <- renv_bootstrap_library_root(project) + + # construct library prefix for platform + prefix <- renv_bootstrap_platform_prefix() + + # construct full libpath + libpath <- file.path(root, prefix) + + # run bootstrap code + renv_bootstrap_exec(project, libpath, version) + + invisible() + +})