mirror of
https://github.com/Hestia-Homes/Model.git
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68401c517a
Sibling migration to the sap10_calculator move — `domain.ml` now lives
at the root-level layout (`domain/sap10_ml/`) matching the pattern
already used by `domain.addresses`, `domain.tasks`, `domain.postcode`,
and `domain.sap10_calculator`.
Changes:
- `git mv packages/domain/src/domain/ml → domain/sap10_ml` (19 files;
history preserved).
- Subpackage rename: `domain.ml` → `domain.sap10_ml`. 32 references
rewritten across .py and .md files: 11 internal + 21 external
(datatypes/epc/domain/mapper.py, 14 files in domain/sap10_calculator,
2 backend tests, 2 ADRs, 1 README, 1 design doc).
- Path-string updates: `pytest.ini` testpath
`packages/domain/src/domain/ml/tests` → `domain/sap10_ml/tests` so
ML tests stay in the default auto-discovered sweep. `CONTEXT.md`
also updated.
`packages/domain/src/domain/` is now empty — the workspace `domain/`
tree has been fully migrated. Together with the `domain/__init__.py`
deletions from the sap10_calculator commit (29ac35cc), `domain` is
now a single root-level namespace package with subpackages
{addresses, sap10_calculator, sap10_ml, tasks} + the standalone
`postcode.py` module.
Verified:
- Focused sweep (backend mapper-chain + sap10_calculator worksheet
e2e + golden fixtures): 99 passed / 19 failed — identical baseline.
- Wider sweep (all sap10_calculator + sap10_ml): 1654 passed / 20
failed (same pre-existing failures).
- domain/sap10_ml/tests: 210/210 PASSED at new path.
- Pyright net-zero: heat_transmission.py 13, cert_to_inputs.py 35,
mapper.py 33, rdsap_uvalues.py 1 (all unchanged from baseline).
Note: `packages/domain/pyproject.toml` still declares
`packages = ["src/domain"]` for the hatchling wheel — that target
directory is now empty and the wheel build is effectively a no-op.
Retiring the workspace package or repointing the wheel is a follow-up.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
32 lines
1 KiB
Python
32 lines
1 KiB
Python
"""Schema dataclasses for EpcMlTransform — the cross-repo ML data contract.
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Consumed by the AutoGluon training repo (and by anything else that reads the
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transform's parquet output) to know each column's dtype, nullability, and meaning.
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"""
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from dataclasses import dataclass
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@dataclass(frozen=True)
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class ColumnSpec:
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"""Specification of a single column in the EPC ML training dataset.
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`categorical=True` signals that the column carries a categorical value (raw
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strings emitted by the transform) and should be cast to `pd.Categorical` at
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parquet write time. The schema module stays pandas-free; the cast happens at
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the I/O boundary in `services/ml_training_data/`.
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"""
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dtype: type
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nullable: bool = True
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description: str = ""
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categorical: bool = False
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@dataclass(frozen=True)
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class TransformSchema:
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"""The cross-repo ML data contract emitted by EpcMlTransform.schema()."""
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transform_version: str
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feature_columns: dict[str, ColumnSpec]
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target_columns: dict[str, ColumnSpec]
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