deps(dependabot): update camelot-py requirement from <2.0.0,>=1.0.9 to >=2.0.0,<3.0.0 in the all-dependencies group across 1 directory

[dependabot]

Updates the requirements on camelot-py to permit the latest version.
Updates camelot-py to 2.0.0

Release notes

Sourced from camelot-py's releases.

v2.0.0

[2.0.0] — 2026-06-04

The 2.0 release rolls up a substantial backend migration, the resulting performance work, an optional neural (Table Transformer) backend for borderless and scanned tables, and a handful of small but user-visible breaking changes. Heads-up if upgrading from 1.0.x — see the migration guide:

Breaking

• Dropped Python 3.9 (EOL October 2025). Minimum supported is now Python 3.10. (#740)
• flavor="lattice" default line_scale changed from 40 to 15 to match the long-standing implementation (the CLI and read_pdf docstring used to say 40 but the Lattice parser always defaulted to 15). Tables that relied on the documented-but-unimplemented 40 will need read_pdf(..., line_scale=40) explicitly. (#709)
• Table.to_excel now defaults to index=False, header=False to match Table.to_csv. Excel exports no longer carry the pandas auto-generated row index / column header by default. Opt back in with table.to_excel(path, index=True, header=True). (#711)
• TableList constructor materialises its iterable input to a list immediately, so bool() and len() work on TableList(generator()) inputs. A generator passed in will be exhausted at construction time rather than at first access. (#710)
• PDFHandler.pages is a property (was an attribute). Reads work unchanged; the value is now resolved lazily on first access. No callers in the wild set it, but if you subclassed and overrode it as an attribute, that no longer works. (#732)
• PDF backend swapped from pypdf + pdfminer.six to playa-pdf. The dependency install set is smaller, encrypted-PDF handling is more accurate, and parser hot paths shed several layers of per-page-temp-PDF dance. Pure import camelot callers should see no API change.

Added

• Optional neural flavor="ml" backend (Table Transformer / TATR). A neural model supplies the row/column/spanning-cell structure while cell text is filled from the PDF's own text layer — the model never emits cell text, so it cannot hallucinate or alter a value. Aimed at borderless tables, where the heuristic parsers plateau: on the FinTabNet borderless benchmark it roughly doubles TEDS (~0.20 → ~0.37) over network/hybrid. Heavy dependencies are optional and imported lazily — pip install "camelot-py[ml]" — so import camelot and the other flavors never load PyTorch. The box→grid post-processing and image→PDF mapping are pure (torch-free) and unit-tested. (#809)
• flavor="ml" reads scanned / image-only PDFs via optional OCR. With no text layer (ocr="auto", the default) — or always with ocr=True — cell

... (truncated)

Changelog

Sourced from camelot-py's changelog.

[2.0.0] — 2026-06-04

The 2.0 release rolls up a substantial backend migration, the resulting performance work, an optional neural (Table Transformer) backend for borderless and scanned tables, and a handful of small but user-visible breaking changes. Heads-up if upgrading from 1.0.x — see the migration guide:

Breaking

• Dropped Python 3.9 (EOL October 2025). Minimum supported is now Python 3.10. (#740)
• flavor="lattice" default line_scale changed from 40 to 15 to match the long-standing implementation (the CLI and read_pdf docstring used to say 40 but the Lattice parser always defaulted to 15). Tables that relied on the documented-but-unimplemented 40 will need read_pdf(..., line_scale=40) explicitly. (#709)
• Table.to_excel now defaults to index=False, header=False to match Table.to_csv. Excel exports no longer carry the pandas auto-generated row index / column header by default. Opt back in with table.to_excel(path, index=True, header=True). (#711)
• TableList constructor materialises its iterable input to a list immediately, so bool() and len() work on TableList(generator()) inputs. A generator passed in will be exhausted at construction time rather than at first access. (#710)
• PDFHandler.pages is a property (was an attribute). Reads work unchanged; the value is now resolved lazily on first access. No callers in the wild set it, but if you subclassed and overrode it as an attribute, that no longer works. (#732)
• PDF backend swapped from pypdf + pdfminer.six to playa-pdf. The dependency install set is smaller, encrypted-PDF handling is more accurate, and parser hot paths shed several layers of per-page-temp-PDF dance. Pure import camelot callers should see no API change.

Added

• Optional neural flavor="ml" backend (Table Transformer / TATR). A neural model supplies the row/column/spanning-cell structure while cell text is filled from the PDF's own text layer — the model never emits cell text, so it cannot hallucinate or alter a value. Aimed at borderless tables, where the heuristic parsers plateau: on the FinTabNet borderless benchmark it roughly doubles TEDS (~0.20 → ~0.37) over network/hybrid. Heavy dependencies are optional and imported lazily — pip install "camelot-py[ml]" — so import camelot and the other flavors never load PyTorch. The box→grid post-processing and image→PDF mapping are pure (torch-free) and unit-tested. (#809)
• flavor="ml" reads scanned / image-only PDFs via optional OCR. With no text layer (ocr="auto", the default) — or always with ocr=True — cell text comes from OCR of the rendered page instead of the PDF text layer;

... (truncated)

Commits

• eef30ac chore(release): prepare 2.0.0 (#816)
• 42f74e3 fix(utils): content-aware text_in_bbox dedup (#288, #625) (#814)
• 3906822 docs(comparison): verified camelot-vs-tablers head-to-head (ICDAR-2013) (#813)
• c227afd fix(release): --clobber the GitHub-release asset upload (unblocks PyPI publis...
• 40497a3 chore(release): prepare 2.0.0rc1 (version, CHANGELOG, migration guide) (#811)
• 9f71cf4 docs: parser-selection guide + reflect the ml/ocr backend (benchmark, compari...
• 15b57ed feat(ml): optional flavor='ml' Table Transformer (TATR) backend — borderless ...
• f28d479 docs: add the missing text-elements plot to the Network section (#577) (#808)
• 87bf13a fix(hybrid): default lattice half to engine='combined' (#807)
• b3c2af1 feat(hybrid): render-free vector+network hybrid (engine='vector') (#806)
• Additional commits viewable in compare view

[dependabot]

Looks like camelot-py is updatable in another way, so this is no longer needed.