BENCHMARK_PYTHON.md updated through Round 10. The stress-test suite
went from 22 patterns (19 hard / 3 KNOWN GAP) to 43 patterns (all
hard-asserted PASS). Bench held at 100% (52/52) across the surface
expansion.
Patterns added in Round 10 cover the framework / real-world cases
that distinguish parity-with-LSP from passing-toy-fixtures:
SQLAlchemy 2.0 Mapped[T], Pydantic BaseModel, async with / async
for, Callable[..., R], next(iter), **kwargs annotation, dict-literal
dispatch tables, lambda call-site inference, recursive types,
classmethod-to-method chains, dataclass default_factory, nested
match patterns.
The original Phase 11 plan called this category "compiler-grade".
The actual line where compiler-rebuild starts is now narrower:
constraint solving for ParamSpec, code-flow narrowing across
basic blocks, custom metaclass __call__, and full descriptor
protocol. None of those are needed for what's resolved on the
bench fixture or the stress suite.
BENCHMARK_PYTHON.md ends the parity push with the in-process bench
results table (81% -> 79% -> 95% across rounds), an explicit
stopping-point list of features that would require building a
constraint solver / code-flow engine / plugin system, and an
"achievable next steps" list for future iterations that stay below
the compiler-rebuild line.
The 81% -> 79% jump going from a 65-line fixture to 136 lines is
deliberate: the smaller fixture was biased toward the resolver's
strengths. The 79% -> 95% jump comes from instance-attribute typing
(Round 4) which closed the largest single gap on real-world code
shapes.
Total: 11 LSP commits on this branch (Phases 0-11 plus Rounds 1-4),
2892 / 0 passing, 95% resolution on the parity fixture.
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.
- Delete cmd/codebase-memory-mcp/assets/ — skills and codex instructions
are embedded as C string literals in src/cli/cli.c since v0.5.0
- Move BENCHMARK.md to docs/ to reduce root clutter
- Fix setup scripts: replace stale go build with scripts/build.sh
- THIRD_PARTY.md: replace Go module dependencies with vendored C
libraries (sqlite3, mimalloc, mongoose, yyjson, xxhash, tre),
fix CGo reference to static compilation
The snippet handler now uses exact QN + suffix matching only (no fuzzy/auto-resolve).
Updated 3 tests to match: fuzzy_suggestions, fuzzy_last_segment, auto_resolve_enabled.
- Add field('path', ...) to Magma load_statement grammar rule so
parse_generic_imports() finds the import path via field lookup
instead of the broken text fallback (which only extracted 1 per file)
- Fix passImports() to resolve file-path imports (e.g. "utils.mag",
"lib/helpers.h") via fqn.ModuleQN() when raw path doesn't match
any node QN — general fix benefiting any file-path-based import
- Add TestMagmaImport_Regression and TestMagmaCall_Regression
- Update language count 59 → 63 in README, docs/index.html, marketing
- Languages: 35 -> 59
- Add Gemini CLI, VS Code, Zed to supported clients list
- Update benchmark description to match v7 methodology
- Update meta tags and comparison table
Martin Vogel