Micro optimization -- use tuples throughout backend indexing #9009
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* add .oindex and .vindex to BackendArray * Add support for .oindex and .vindex in H5NetCDFArrayWrapper * Add support for .oindex and .vindex in NetCDF4ArrayWrapper, PydapArrayWrapper, NioArrayWrapper, and ZarrArrayWrapper * add deprecation warning * Fix deprecation warning message formatting * add tests * Update xarray/core/indexing.py Co-authored-by: Deepak Cherian <[email protected]> * Update ZarrArrayWrapper class in xarray/backends/zarr.py Co-authored-by: Deepak Cherian <[email protected]> --------- Co-authored-by: Deepak Cherian <[email protected]>
* origin/main: clean up the upstream-dev setup script (pydata#8986) Skip flaky `test_open_mfdataset_manyfiles` test (pydata#8989) Remove `.drop` warning allow (pydata#8988) Add notes on when to add ignores to warnings (pydata#8987) Docstring and documentation improvement for the Dataset class (pydata#8973)
…dexing adapters and explicitly indexed arrays (pydata#8870) * pass key tuple to indexing adapters and explicitly indexed arrays * update indexing in StackedBytesArray * Update indexing in StackedBytesArray * Add _IndexerKey type to _typing.py * Update indexing in StackedBytesArray * use tuple indexing in test_backend_array_deprecation_warning * Add support for CompatIndexedTuple in explicit indexing adapter This commit updates the `explicit_indexing_adapter` function to accept both `ExplicitIndexer` and the new `CompatIndexedTuple`. The `CompatIndexedTuple` is designed to facilitate the transition towards using raw tuples by carrying additional metadata about the indexing type (basic, vectorized, or outer). * remove unused code * type hint fixes * fix docstrings * fix tests * fix docstrings * Apply suggestions from code review Co-authored-by: Deepak Cherian <[email protected]> * update docstrings and pass tuples directly * Some test cleanup * update docstring * use `BasicIndexer` instead of `CompatIndexedTuple` * support explicit indexing with tuples * fix mypy errors * remove unused IndexerMaker * Update LazilyIndexedArray._updated_key to support explicit indexing with tuples --------- Co-authored-by: Deepak Cherian <[email protected]> Co-authored-by: Deepak Cherian <[email protected]>
* origin/main: call `np.cross` with 3D vectors only (pydata#8993) Mark `test_use_cftime_false_standard_calendar_in_range` as an expected failure (pydata#8996) Migration of datatree/ops.py -> datatree_ops.py (pydata#8976) avoid a couple of warnings in `polyfit` (pydata#8939)
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Since Python 3.X (i can't remember which) tuple concatenation like this is fast since python inspects the tuple usage and knows that it is the last reference and reuses the underlying c object. The change to LazilyIndexedArray is that `shape` is repeatidely accessed throughout the codebase (ndim, and shape are heavily used) and thus we benefit from pre-computing this at creation time.
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andersy005
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* backend-indexing: Trigger CI only if code files are modified. (pydata#9006) Enable explicit use of key tuples (instead of *Indexer objects) in indexing adapters and explicitly indexed arrays (pydata#8870) add `.oindex` and `.vindex` to `BackendArray` (pydata#8885) temporary enable CI triggers on feature branch Avoid auto creation of indexes in concat (pydata#8872) Fix benchmark CI (pydata#9013) Avoid extra read from disk when creating Pandas Index. (pydata#8893) Add a benchmark to monitor performance for large dataset indexing (pydata#9012) Zarr: Optimize `region="auto"` detection (pydata#8997) Trigger CI only if code files are modified. (pydata#9006) Fix for ruff 0.4.3 (pydata#9007) Port negative frequency fix for `pandas.date_range` to `cftime_range` (pydata#8999) Bump codecov/codecov-action from 4.3.0 to 4.3.1 in the actions group (pydata#9004) Speed up localize (pydata#8536) Simplify fast path (pydata#9001) Add argument check_dims to assert_allclose to allow transposed inputs (pydata#5733) (pydata#8991) Fix syntax error in test related to cupy (pydata#9000)
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thank you for these additions, @hmaarrfk! |
andersy005
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May 12, 2024
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xref: #9002 (comment)
Since Python 3.X (i can't remember which) tuple concatenation like this
is fast since python inspects the tuple usage and knows that it is the
last reference and reuses the underlying c object.
The change to LazilyIndexedArray is that
shapeis repeatidely accessedthroughout the codebase (
ndim, andshapeare heavily used) and thus webenefit from pre-computing this at creation time.
whats-new.rstapi.rst