Add a fast path for NameSets without wildcards #241
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When the set of ignored names doesn't use shell-style wildcards, we can use the faster `frozenset.__contains__` base implementation rather than the more expensive iteration-based fnmatch'ing approach. This is true for the default ignore list, and I expect its the more common case by far even for those who add their own ignored names. In a simple local benchmark, this results in a 2x speed improvement for that common (default) path, which I think justifies the small additional complexity.
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sigmavirus24
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Apr 2, 2025
src/pep8ext_naming.py
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| def __new__(cls, iterable: Iterable[str]): | ||
| obj = super().__new__(cls, iterable) | ||
| obj._fnmatch = any(c in r"*?[" for name in iterable for c in name) |
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Is it faster to loop over the characters in the name or the 3 characters in the raw string which doesn't strictly need to be raw?
Also would it be faster still to turn a name into a frozen set and look for the intersection of that with the frozen set of those three characters?
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It's actually fastest (by 2-3x) to check one wild character at a time, presumable because we hit a memchr or similar fast path internally:
any("*" in s or "?" in s or "[" in s for s in iterable)
sigmavirus24
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Apr 2, 2025
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When the set of ignored names doesn't use shell-style wildcards, we can use the faster
frozenset.__contains__base implementation rather than the more expensive iteration-based fnmatch'ing approach. This is true for the default ignore list, and I expect its the more common case by far even for those who add their own ignored names.In a simple local benchmark, this results in a 2x speed improvement for that common (default) path, which I think justifies the small additional complexity.