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CI run for the InvisibleFix fix on top of the upstream Dependabot PR plotly#4141. Not for merge.

dependabot Bot and others added 2 commits November 10, 2026 14:23
Bumps the pip-dependencies group with 1 update: [mypy](https://github.com/python/mypy).


Updates `mypy` from 1.15.0 to 2.4.0
- [Changelog](https://github.com/python/mypy/blob/master/CHANGELOG.md)
- [Commits](python/mypy@v1.15.0...v2.4.0)

---
updated-dependencies:
- dependency-name: mypy
  dependency-version: 2.4.0
  dependency-type: direct:production
  update-type: version-update:semver-major
  dependency-group: pip-dependencies
...

Signed-off-by: dependabot[bot] <support@github.com>
mypy 2.0 turned on --local-partial-types by default, so the empty collections.OrderedDict() assigned to the module-level PAGE_REGISTRY can no longer get its type from assignments inside register_page(), and mypy reports 'Need type annotation for "PAGE_REGISTRY" [var-annotated]' whenever it checks code that imports dash.

Annotate it as collections.OrderedDict, which is the type mypy 1.15 inferred (OrderedDict[Any, Any]) and the same style dash.py uses for _mcp_callback_maps. The runtime object is unchanged.
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Thank you for your contribution to Dash! 🎉

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Dash performance benchmarks

⚠️ regressions to review

scenario metric p90 (ms) median growth baseline p90 note
⚠️ initial_render_small render_ms 150.3 102.1 1.25x 104.0 1.4x baseline (norm)
✅ callback_chain chain_ms 426.1 408.4 0.94x 499.1
✅ callback_chain graph_ms 6.0 6.0 1.0x 2.4
✅ callback_fanout fanout_ms 83.7 80.0 0.93x 92.5
✅ deep_nesting render_ms 55.6 52.6 0.83x 56.8
✅ full_children_replace replace_ms 5265.2 1929.5 17.61x 4697.1
✅ initial_render_large render_ms 585.1 572.0 0.97x 694.4
✅ patch_append_nested append_ms 122.8 91.9 2.03x 192.3
✅ patch_append_toplevel append_ms 112.8 81.6 2.33x 140.2
✅ patch_scalar_update_large update_ms 173.1 149.1 0.93x 202.9
✅ wildcard_all_resolve wildcard_ms 308.8 293.2 0.99x 313.6
✅ wildcard_all_resolve graph_ms 2.3 2.3 1.0x 1.3

growth = late-third / early-third per-op time; ~1 is flat, a large value means the per-op cost scales with accumulated state.

machine scale vs baseline: 1.06x - divided out of the baseline ratios so they compare like for like (the absolute warn/fail ceilings are left un-scaled); calibrated on initial_render_small.

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