feat: add panel and multi-model CodSpeed benchmarks - #24
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Add large-panel dataset fixture, parametrize TimeSeriesDataset.from_df benchmarks, and FoundationForecast multi-model orchestration benchmarks to measure preprocessing speedups from shared panel processing (PR #18). Co-authored-by: Cursor <cursoragent@cursor.com>
Merging this PR will not alter performance
Performance Changes
Comparing |
Annotate models as list[Forecaster] when constructing FoundationForecast. Co-authored-by: Cursor <cursoragent@cursor.com>
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Pull request overview
Adds CodSpeed benchmarks for large-panel preprocessing and multi-model orchestration.
Changes:
- Adds a 100-series × 500-point fixture.
- Parametrizes dataset benchmarks by panel size.
- Adds 3-model and 5-model orchestration benchmarks.
- Runs the new benchmarks in CodSpeed core.
File summaries
| File | Description |
|---|---|
tests/benchmarks/test_orchestration.py |
Adds multi-model dataset construction benchmarks. |
tests/benchmarks/test_core.py |
Benchmarks small and large datasets. |
tests/benchmarks/conftest.py |
Defines the large panel fixture. |
.github/workflows/codspeed.yml |
Includes orchestration benchmarks in CodSpeed core. |
Review details
- Files reviewed: 4/4 changed files
- Comments generated: 0
- Review effort level: Lite
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Summary
large_panel_dffixture (100 series × 500 points) for benchmarks where preprocessing cost is visibletest_timeseries_dataset_from_dfwithsmallandlargesizestest_foundation_forecast_multi_model(3 and 5DatasetTouchingModelinstances) to measure multi-model dataset construction overheadThese benchmarks establish baselines on
mainbefore #18 (shared panel processing) merges. After #18 lands, CodSpeed on that PR should show speedups ontest_foundation_forecast_multi_modelandtest_timeseries_dataset_from_df[large].Phase 2 (panel micro-benchmarks:
process_panel_from_df,from_panel, etc.) will be added in PR #18 once those APIs exist.Test plan
benchmarks-core)test_timeseries_dataset_from_df[large]test_foundation_forecast_multi_model[3-models]test_foundation_forecast_multi_model[5-models]Made with Cursor