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Author	SHA1	Message	Date
Ashish	737b332129	feat(config): fold TOML array-of-tables to csv-schema via SmartCrusher (#1799) ... ## Description Adds a schema-fold tier to the structured-config compressor (introduced in #1784). TOML files containing an `[[array-of-tables]]` are parsed with the stdlib `tomllib` reference parser and bridged to SmartCrusher's lossless `csv-schema` renderer, which folds the repeated per-record keys into a single schema over the rows. On lockfiles and override-lists — where the repeated keys dominate the byte count — this is a large win. **Stacked on #1784 — review only the top commit** (`feat(config): fold TOML array-of-tables to csv-schema via SmartCrusher`). The base commit is #1784's config-compressor PR; this PR will collapse to the single new commit once #1784 merges. Faithfulness is guaranteed by construction, not by a heuristic: - `tomllib` is the reference TOML parser, so the extracted records are ground-truth. - `csv-schema` is a lossless JSON renderer (`smart_crusher.py` documents it as such), so the model reads a faithful, reformatted view of the exact parsed data. - Byte-exact recovery rides the existing CCR path — the original is persisted to the `CompressionStore` and a `Retrieve original: hash=…` marker is emitted. The fold is only emitted when that store write succeeds, so nothing is ever unrecoverable. Scope is deliberately **TOML-only**: `tomllib` is stdlib, whereas PyYAML is only a *transitive* dependency (not declared in `pyproject.toml`), and INI record-sections would need a bespoke dict-of-dicts→records transform. Those flavors can follow in a separate PR with an explicit dependency decision. ## Type of Change - [x] New feature (non-breaking change which adds functionality) ## Changes Made - `headroom/transforms/config_compressor.py`: added Tier 3 (`_schema_fold`) — TOML `[[array-of-tables]]` → `tomllib` → JSON → `SmartCrusher(csv-schema)`. New `enable_schema_fold` config flag (default on; auto-off in lossless mode since it rides `enable_ccr`). The fold competes with the reversible text tiers and is adopted only when strictly smaller. Added `_load_toml` (stdlib parser with tomli backport) and `_json_default` (TOML date/time → ISO; bail on any other non-serializable value). - Recovery reuses the existing `CompressionStore` + `Retrieve original: hash=` marker; no new CCR plumbing. - `tests/test_transforms_config_compressor.py`: 14 new tests covering the fold, big-win assertion, byte-exact CCR round-trip, lossless-mode disable, flag-off, non-TOML skip, no-array skip, small-array `passthrough` decline, store-failure fallback, savings-floor rejection, unparseable/non-serializable bails, `_load_toml`/`_json_default` units, and a datetime-valued fold. ## Testing - [x] New and existing unit tests pass locally - [x] New tests added for the new behavior ### Test Output ``` tests/test_transforms_config_compressor.py ............................. [ 59%] headroom/transforms/config_compressor.py 127 0 36 0 100% ============================== 49 passed in 0.61s ============================== ``` Must-stay-green suites (`test_lossless_mode`, `test_lossless_excluded_compaction`, `test_transforms_content_detection`, `test_compression_fidelity_regression`) — 48 passed. Router/tabular/smart_crusher regression — 73 + 82 passed. `mypy --strict` clean on the changed module. ## Real Behavior Proof - Environment: local, Python 3.11.0, macOS (darwin), `HF_HUB_OFFLINE=1` - Exact command / steps: parsed a 25-record `[[tool.mypy.overrides]]` TOML through `ConfigCompressor(ConfigCompressorConfig(enable_ccr=True)).compress()`, then retrieved the CCR hash from the `CompressionStore`. - Observed result: `strategy=config_schema_fold`, 2765 → 840 chars (30% of original); the marker hash resolved to the byte-exact original (`recovered == original` True); with `enable_ccr=False` (lossless mode) the fold did not run and no marker was emitted; a 3-record long-valued `[[package]]` array correctly declined (SmartCrusher `passthrough`). - Not tested: the live proxy end-to-end path and non-TOML flavors (YAML/INI schema folding is intentionally out of scope for this PR). ## Review Readiness - [x] I have performed a self-review - [x] This PR is ready for human review --------- Co-authored-by: Claude Fable 5 <noreply@anthropic.com>	2026-07-15 19:58:27 +00:00