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Micro optimizations to improve indexing #9002
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Original file line number | Diff line number | Diff line change |
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@@ -296,15 +296,16 @@ def slice_slice(old_slice: slice, applied_slice: slice, size: int) -> slice: | |
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def _index_indexer_1d(old_indexer, applied_indexer, size: int): | ||
assert isinstance(applied_indexer, integer_types + (slice, np.ndarray)) | ||
if isinstance(applied_indexer, slice) and applied_indexer == slice(None): | ||
# shortcut for the usual case | ||
return old_indexer | ||
if isinstance(old_indexer, slice): | ||
if isinstance(applied_indexer, slice): | ||
indexer = slice_slice(old_indexer, applied_indexer, size) | ||
elif isinstance(applied_indexer, integer_types): | ||
indexer = range(*old_indexer.indices(size))[applied_indexer] # type: ignore[assignment] | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. These kinds of There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. This one is due to the ambiguity between slice and int for these indexers. I can look into it if you want. However. It starts to touch some tuple to lists conversation that was identified as something I shouldn't adjust too much due to potential conflicts with an active in development branch. There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. The following patch would
would move the error to
While I don't disagree that:
I would rather keep this for a future change once the branch |
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else: | ||
indexer = _expand_slice(old_indexer, size)[applied_indexer] # type: ignore[assignment] | ||
indexer = _expand_slice(old_indexer, size)[applied_indexer] | ||
else: | ||
indexer = old_indexer[applied_indexer] | ||
return indexer | ||
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@@ -591,7 +592,7 @@ def __getitem__(self, key: Any): | |
class LazilyIndexedArray(ExplicitlyIndexedNDArrayMixin): | ||
"""Wrap an array to make basic and outer indexing lazy.""" | ||
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__slots__ = ("array", "key") | ||
__slots__ = ("array", "key", "_shape") | ||
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def __init__(self, array: Any, key: ExplicitIndexer | None = None): | ||
""" | ||
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@@ -614,6 +615,14 @@ def __init__(self, array: Any, key: ExplicitIndexer | None = None): | |
self.array = as_indexable(array) | ||
self.key = key | ||
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shape: _Shape = () | ||
for size, k in zip(self.array.shape, self.key.tuple): | ||
if isinstance(k, slice): | ||
shape += (len(range(*k.indices(size))),) | ||
elif isinstance(k, np.ndarray): | ||
shape += (k.size,) | ||
self._shape = shape | ||
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def _updated_key(self, new_key: ExplicitIndexer) -> BasicIndexer | OuterIndexer: | ||
iter_new_key = iter(expanded_indexer(new_key.tuple, self.ndim)) | ||
full_key = [] | ||
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@@ -630,13 +639,7 @@ def _updated_key(self, new_key: ExplicitIndexer) -> BasicIndexer | OuterIndexer: | |
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@property | ||
def shape(self) -> _Shape: | ||
shape = [] | ||
for size, k in zip(self.array.shape, self.key.tuple): | ||
if isinstance(k, slice): | ||
shape.append(len(range(*k.indices(size)))) | ||
elif isinstance(k, np.ndarray): | ||
shape.append(k.size) | ||
return tuple(shape) | ||
return self._shape | ||
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def get_duck_array(self): | ||
if isinstance(self.array, ExplicitlyIndexedNDArrayMixin): | ||
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I'm a bit wary of adding
fastpath
everywhere. It makes things a bit hard to reason about. Is this one that consequential? We do first check forisinstance(pd.Index)
insafe_cast_to_index
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Anecdotally, I remember thinking that indexes are created and copied a few too many times. I believe this was done for correctness in a big refactor, but reducing any useless copies would be a big win since we would call
_replace
less.There was a problem hiding this comment.
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this in general is my feeling after my repeated deep diving into the codebase.