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Martin Vogel
a8c9ace4a5
Final phase of Python LSP integration. Adds:
- docs/BENCHMARK_PYTHON.md — methodology document covering target
metrics (per-file LSP overhead < 10 ms, resolution ratio ≥ 40% on
application code, ≥ 70% with stdlib, < 5% spot-check false positive
rate), the declared accepted-failure-class ceiling (metaclass
__call__, __getattr__/__getattribute__, dynamic setattr, runtime
importlib, monkey-patching, eval/exec, descriptors beyond the
standard property/classmethod/staticmethod, dynamic type() classes),
and instructions for running scripts/benchmark-index.sh against the
largest Python repos in datadice (falkemedia: 232 files, api-hub:
188 files).
- tests/test_py_lsp_bench.c — in-process benchmark wired into
scripts/test.sh. Runs cbm_extract_file on a 65-line Python fixture
covering imports, dataclasses, classmethods, single-inheritance with
super(), typed parameters, attribute chains, and stdlib calls.
Asserts soft floor (resolved >= calls/4) and hard time budget
(< 50 ms under sanitizers). Initial run reports:
bench: 65 lines, 16 calls, 13 resolved (81%), 2.45 ms
81% beats the 40% application-code target and the 70%
application-plus-stdlib target. 2.45 ms under ASan + UBSan is well
inside the 10 ms (no-sanitizer) production budget.
This wraps the 11-phase plan documented in PYTHON_LSP_PLAN.md. Total
test count: 2874 / 0 (100% pass). Repository-level benchmarks via
scripts/benchmark-index.sh remain a manual operation against a fresh
production binary; methodology is now in place for when that runs.
