Reduce time cost of tests#1116
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Cache `blobs(256, 300, 3)` and `BlobsDataset()._labels_blobs()` once per session via private session-scoped fixtures, then deepcopy into each function-scoped fixture. Cuts fixture setup from 44.8s to 35.0s (-9.8s) and total suite from 186s to 180s. All 1332 tests still pass. Benchmark CSVs committed for reference (pytest_*.csv). Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
to_circles() on labels scales linearly with pixel count. Dropping from 512×512 to 128×128 cuts test_labels_2d_to_circles from ~3.9s to ~1.0s per parametrized variant (−4.7s across the file). Updated hardcoded coordinate/radius assertions to match the new size. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Codecov Report✅ All modified and coverable lines are covered by tests. Additional details and impacted files@@ Coverage Diff @@
## main #1116 +/- ##
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- Coverage 91.93% 91.83% -0.11%
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Files 51 51
Lines 7772 7750 -22
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- Hits 7145 7117 -28
- Misses 627 633 +6
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… deepcopy Two orthogonal wins: 1. _elements.py: `get_model()` already calls `schema.validate()` internally; the explicit second validate() + get_axes_names() call in every __setitem__ was redundant. Removing it halves the DataTree (_to_dataset_view) overhead per element insertion — directly speeds up fixture setup. 2. conftest.py: introduce `_fast_deepcopy_sdata` (copy.deepcopy + manual attrs restoration for DaskDataFrame/#503 and GeoDataFrame/#286) that is ~13x faster than sd_deepcopy (7ms vs 93ms for full_sdata). Session-scope full_sdata, images, labels and the 'full' sdata parametrized fixture; each test gets a fresh 7ms copy instead of an 87ms full reconstruction. Also switch sdata_blobs from sd_deepcopy to fast_deepcopy_sdata (2ms vs 25ms). Full suite: 186s → 163s (~12% reduction, ~23s saved). Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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This PR also adjusts the tests in the CI (modified in #1114) to keep only lower-bound and upper-bound Python versions, which is the philosophy used in integration-testing. Actually since we test 3.11 and 3.14, and integration testing tests 3.12 every night, we cover also the 3.12 case, while keeping the per-commit CI leaner. |
…ion comment - get_model() now accepts validate=False to skip schema.validate() when the caller only needs to infer the element type without re-running validation - add comment to Elements.__setitem__ noting that subclass overrides call get_model() which performs the validation - drop Python 3.13 CI matrix entries (superseded by 3.14) Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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So far the tests should be running ~12% faster than in |
… elements Add skip_element_validation() context manager (backed by a ContextVar) that makes __setitem__ call get_model(validate=False) — type inference only, no schema.validate(). Use it in every code path that constructs a SpatialData from elements that originated from an existing SpatialData and were never externally mutated: bounding_box_query, polygon_query, query_by_coordinate_system, transform_to_coordinate_system, subset, and init_from_elements. test_query_spatial_data: 0.77s → 0.64s (the remaining time is the query work itself — filtering, shapely ops, raster cropping). Also inline a minimal 2-image SpatialData in test_transformations_between_coordinate_systems instead of relying on the full 8-element images fixture; the test only ever uses image2d and image2d_multiscale, so writing the other 6 to disk was pure waste. test_transformations_between_coordinate_systems: 0.61s → 0.44s. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
…dy-valid elements" This reverts commit acb25b1.
Replace per-slice O(H+W) approach (512 dask compute() calls for a 256×256 array) with a single array materialization + np.bincount O(n_pixels) pass. This speeds up get_centroids() on labels from ~1.5s to ~50ms, cutting to_circles(labels) from ~1.6s to ~53ms. Affects test_validation dataloader variants (~2.5s → ~0.2s each, saving ~9s), test_labels_2d_to_circles, and any production call to get_centroids or to_circles on label arrays. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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Reducing the time required to run tests. This complements #1113, which reduces the number of emitted warnings (@melonora observed that this was impacting the runtime).