- Updated `Activities` class to improve garbage collection handling. - Enhanced error messaging in `ExperimentTracking` for better clarity on update failures. - Refactored `Training` class to streamline exception handling and improve type hints. - Introduced new methods in `TrainModelParams` for better handling of experiment run IDs and model metadata. - Added functionality to extract model equations in `DataManagerRepository` for linear regression models.
94 lines
3.1 KiB
Python
94 lines
3.1 KiB
Python
"""
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Test bootstrap: stub optional `sientia_do` submodules not shipped in minimal installs.
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Must run before importing `model_manager.sientia.models` (pulled in via TrainModelParams).
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Stubs Evidently submodules so `model_manager.sientia.reports` imports (via DataManagerRepository).
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"""
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from __future__ import annotations
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import sys
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from types import ModuleType
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def _make_dummy(name: str) -> type:
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return type(name, (), {})
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def _stub_evidently() -> None:
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"""Minimal Evidently API surface required to import `model_manager.sientia.reports`."""
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mp = ModuleType('evidently.metric_preset')
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mp.DataDriftPreset = _make_dummy('DataDriftPreset')
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sys.modules['evidently.metric_preset'] = mp
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metrics = ModuleType('evidently.metrics')
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_metric_names = (
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'ColumnSummaryMetric',
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'ConflictTargetMetric',
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'DatasetCorrelationsMetric',
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'DatasetSummaryMetric',
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'RegressionAbsPercentageErrorPlot',
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'RegressionDummyMetric',
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'RegressionErrorDistribution',
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'RegressionErrorPlot',
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'RegressionPerformanceMetrics',
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'RegressionPredictedVsActualPlot',
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'RegressionPredictedVsActualScatter',
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)
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for n in _metric_names:
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setattr(metrics, n, _make_dummy(n))
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sys.modules['evidently.metrics'] = metrics
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base = ModuleType('evidently.metrics.base_metric')
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def generate_column_metrics(*_a, **_k):
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return []
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base.generate_column_metrics = generate_column_metrics
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sys.modules['evidently.metrics.base_metric'] = base
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opt = ModuleType('evidently.options')
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opt.ColorOptions = _make_dummy('ColorOptions')
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sys.modules['evidently.options'] = opt
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rep = ModuleType('evidently.report')
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rep.Report = _make_dummy('Report')
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sys.modules['evidently.report'] = rep
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def pytest_configure(config) -> None: # noqa: ARG001
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"""Register stub modules so imports used by production code resolve in CI/dev venvs."""
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_stub_evidently()
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if 'sientia_do.operations.df_preprocessor' not in sys.modules:
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df_pre = ModuleType('sientia_do.operations.df_preprocessor')
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def create_features(input_data, *_a, **_k):
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return input_data
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def limit_dataset(input_data, low_lim, upp_lim, *_a, **_k):
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return input_data, low_lim, upp_lim
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def treat_nan(input_data, *_a, **_k):
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return input_data
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df_pre.create_features = create_features
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df_pre.limit_dataset = limit_dataset
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df_pre.treat_nan = treat_nan
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sys.modules['sientia_do.operations.df_preprocessor'] = df_pre
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sys.modules.setdefault('sientia_do.operations', ModuleType('sientia_do.operations'))
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if 'sientia_do.timeseries.analyzer' not in sys.modules:
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ts_an = ModuleType('sientia_do.timeseries.analyzer')
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class TimeSeriesDiscontinuityAnalyzer: # noqa: D401
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"""Stub for tests."""
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pass
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ts_an.TimeSeriesDiscontinuityAnalyzer = TimeSeriesDiscontinuityAnalyzer
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sys.modules['sientia_do.timeseries.analyzer'] = ts_an
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sys.modules.setdefault('sientia_do.timeseries', ModuleType('sientia_do.timeseries'))
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