Upgrade pandas and other packages, convert to hatch

pyproject.toml

@@ -1,6 +1,6 @@
 [build-system]
-requires = ["setuptools>=64", "setuptools_scm>=8"]
-build-backend = "setuptools.build_meta"
+requires = ["hatchling>=1.27", "hatch-vcs>=0.4"]
+build-backend = "hatchling.build"
 
 [project]
 name = "rmi.dispatch"
@@ -20,44 +20,50 @@ classifiers = [
 ]
 requires-python = ">=3.12,<3.15"
 dependencies = [
-    "bottleneck >= 1.6.0,< 1.6.1",
-    "numba >= 0.65.0,< 0.66",
-    "numexpr >= 2.8, < 2.14.2",
-    "numpy >= 1.18.5,< 3",
-    "pandas >= 1.4,< 3.0",
-    "pandera >= 0.20.1, < 0.31",
-    "pyarrow>=7, <25",
+    "bottleneck>=1.6.0,<2",
+    "numba>=0.65.0,<0.66",
+    "numexpr>=2.8,<3",
+    "numpy>=1.18.5,<3",
+    "pandas>= 1.4,<4",
+    "pandera>=0.20.1,<0.31",
+    "pyarrow>=7,<25",
 ]
 
 [project.optional-dependencies]
 dev = [
-    "coverage>=5.3,<7.15",  # Lets us track what code is being tested
-    "pytest>=6.2,<9.1",  # test framework
+    "coverage>=5.3,<8",  # Lets us track what code is being tested
+    "pytest>=6.2,<10",  # test framework
     "datazip",
 ]
 doc = [
-    "doc8>=2.0.0,<2.1",
+    "doc8>=2.0.0,<3",
     "furo>=2025.12.19",
-    "rstcheck[sphinx,toml]>=5.0,<6.3",
-    "sphinx>=4,!=5.1.0,<9.1.1",
-    "sphinx-autoapi>=1.8,<3.9",
-    "sphinx-issues>=1.2,<6.1",
-    "sphinx-autodoc-typehints>1.19,<3.11.0",
-    "sphinxcontrib-mermaid>0.7,<2.1.0",
+    "rstcheck[sphinx,toml]>=5.0,<7",
+    "sphinx>=4,!=5.1.0,<10",
+    "sphinx-autoapi>=1.8,<4",
+    "sphinx-issues>=1.2,<7",
+    "sphinx-autodoc-typehints>1.19,<4",
+    "sphinxcontrib-mermaid>0.7,<3",
 ]
 qa = []
 tooling = []
 tests = []
 viz = [
-    "plotly>5.10,<6.8",
+    "plotly>5.10,<7",
     "kaleido>0.2,<2",
 ]
 
-[tool.setuptools.dynamic]
-version = {attr = "dispatch._version.__version__"}
+[tool.hatch.version]
+source = "vcs"
 
-[tool.setuptools_scm]
-version_file = "src/dispatch/_version.py"
+[tool.hatch.build.hooks.vcs]
+version-file = "src/dispatch/_version.py"
+
+[tool.hatch.build.targets.wheel]
+packages = ["src/dispatch"]
+
+[tool.hatch.build.targets.sdist]
+include = ["src/dispatch", "README.rst", "LICENSE.txt"]
 
 [tool.uv]
 constraint-dependencies = ["kaleido!=0.2.1.post1"]
@@ -176,7 +182,7 @@ pydocstyle.convention = "google"
 "tests/engine_test.py" = ["E501"]
 
 [tool.tox]
-env_list = [ "linters", "docs", "prep", "3.13", "3.14", "coverage" ]
+env_list = [ "linters", "docs", "prep", "3.13", "3.14", "3.14-pandas2", "coverage" ]
 
 [tool.tox.env.prep]
 skip_install = true
@@ -188,11 +194,16 @@ allowlist_externals = [ "bash", "ruff", "prek" ]
 runner = "uv-venv-runner"
 extras = [ "dev", "viz" ]
 commands = [
+    [ "python", "-c", 'import importlib.metadata as m; [print(f"{d.name}=={d.version}") for d in sorted(m.distributions(), key=lambda x: (x.name or "").lower())]' ],
     [ "coverage", "run", "--source={envsitepackagesdir}/dispatch", "-m", "pytest", "--doctest-modules", "{envsitepackagesdir}/dispatch", "tests" ],
 ]
 
+[tool.tox.env."3.14-pandas2"]
+description = "Run tests on Python 3.14 against the pandas <3 line to verify back-compat."
+deps = [ "pandas<3.0" ]
+
 [tool.tox.env.coverage]
-depends = [ "3.13", "3.14" ]
+depends = [ "3.13", "3.14", "3.14-pandas2" ]
 skip_install = true
 deps = "coverage"
 commands = [

src/dispatch/model.py

@@ -10,6 +10,12 @@
 import numpy as np
 import pandas as pd
 
+from dispatch import __version__
+from dispatch.constants import COLOR_MAP, MTDF, PLOT_MAP
+from dispatch.engine import dispatch_engine, dispatch_engine_auto
+from dispatch.helpers import dispatch_key, zero_profiles_outside_operating_dates
+from dispatch.metadata import LOAD_PROFILE_SCHEMA, Validator
+
 try:
     import plotly.express as px
     from plotly.graph_objects import Figure
@@ -21,6 +27,12 @@
     Figure = Any
     PLOTLY_INSTALLED = False
 
+# pandas 3.0 removed the ``dropna`` argument from ``DataFrame.stack`` because the
+# new implementation never introduces NA rows. To keep one code path that works
+# under both pandas <3 (old default stack behavior) and pandas >=3 (new default),
+# we branch on the major version.
+_PANDAS_MAJOR_VERSION = int(pd.__version__.split(".", 1)[0])
+
 __all__ = ["DispatchModel"]
 
 try:
@@ -41,12 +53,6 @@ def to_file(self, *args, **kwargs) -> None:
             raise NotImplementedError("datazip is required for this functionality")
 
 
-from dispatch import __version__
-from dispatch.constants import COLOR_MAP, MTDF, PLOT_MAP
-from dispatch.engine import dispatch_engine, dispatch_engine_auto
-from dispatch.helpers import dispatch_key, zero_profiles_outside_operating_dates
-from dispatch.metadata import LOAD_PROFILE_SCHEMA, Validator
-
 LOGGER = logging.getLogger(__name__)
 
 
@@ -991,9 +997,18 @@ def strict_grouper(
             dropna = False
         if col_name is None:
             return out
+        if _PANDAS_MAJOR_VERSION >= 3:
+            # pandas >=3 dropped the ``dropna`` kwarg and never introduces NA
+            # rows in stack. Replicate the legacy ``dropna=True`` behavior by
+            # dropping after the fact; ``dropna=False`` is already the new
+            # default so it needs no extra work.
+            stacked = out.stack(level=out.columns.names)
+            if dropna:
+                stacked = stacked.dropna()
+        else:
+            stacked = out.stack(level=out.columns.names, dropna=dropna)
         return (
-            out.stack(level=out.columns.names, dropna=dropna)
-            .reorder_levels(order=[*out.columns.names, "datetime"])
+            stacked.reorder_levels(order=[*out.columns.names, "datetime"])
             .to_frame(name=col_name)
             .sort_index()
         )

tests/helper_test.py

@@ -41,19 +41,19 @@ def zero_profiles_outside_operating_dates_slow(
     dt_idx = pd.concat(
         [profiles.index.to_series()] * profiles.shape[1],
         axis=1,
-    ).to_numpy(dtype=np.datetime64)
+    ).to_numpy(dtype="datetime64[ns]")
     return pd.DataFrame(
         (
             (
                 dt_idx
                 <= retirement_date.fillna(profiles.index.max()).to_numpy(
-                    dtype=np.datetime64
+                    dtype="datetime64[ns]"
                 )
             )
             & (
                 dt_idx
                 >= operating_date.fillna(profiles.index.min()).to_numpy(
-                    dtype=np.datetime64
+                    dtype="datetime64[ns]"
                 )
             )
         )