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Normal attribute lookup makes string indexing return list methods for item names such as `count`, and reports absent `append` identifiers as present. Use `__getattr__` explicitly for identifier lookup and remove its fallback to list attributes. Ordinary attribute access still exposes list methods. Add twelve present/absent collision cases with and without prefixes. The full suite passes 1701 tests, 89 conditional skips, one existing xfail, and 64 subtests; pinned hooks, type checks, docs and packaging also pass.
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Updates IterableList name-based lookup so string indexing and membership checks resolve items by identifier rather than colliding with built-in list attributes/methods (e.g., append, sort), and adds regression tests for these edge cases.
Changes:
| File | Description |
|---|---|
| git/util.py | Adjusts IterableList lookup semantics to avoid list attribute collisions and to raise on missing identifiers. |
| test/test_util.py | Adds regression tests ensuring identifier lookup works even for names that match list methods/dunders and after deletion. |
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This PR was prepared by an OpenAI Codex agent.
IterableList string indexing currently uses normal attribute lookup. Consequently, names such as count, sort, or append return list methods rather than matching items, and an absent append is reported as present. This also affects named references and submodules, as described in #1091 (currently closed as not planned).
Route string indexing and identifier membership through the existing identifier lookup, and raise AttributeError when no matching item exists instead of falling back to list attributes. Ordinary attribute access to list methods remains available.
Twelve regression cases cover list-method names, internal/dunder names, ordinary names, and prefixed identifiers, including absence after deletion. Ten fail against pristine source; the two ordinary-name controls pass.
Validation on CPython 3.12.14 / Linux / Git 2.52.0:
The unchanged skips are platform/filesystem-specific, and the existing xfail concerns shallow submodules. One unchanged path-environment deprecation warning remains. Other operating systems and Python versions were not run locally; hosted results are reported separately.