* Minor changes.
* Update Doc/faq/library.rst
Co-Authored-By: Kyle Stanley <aeros167@gmail.com>
* Apply suggestions from aeros167.
* Update Doc/faq/library.rst
Co-Authored-By: Kyle Stanley <aeros167@gmail.com>
* Apply suggestions from aeros167 + re-add a "a" that was accidentally deleted.
* Update documentation for plistlib
- Update "Mac OS X" to "Apple" since plists are used more widely than just macOS
- Re-add the UID class documentation (oops, removed in GH-15615)
* Rename PyThreadState_DeleteCurrent()
to _PyThreadState_DeleteCurrent()
* Move it to the internal C API
Co-Authored-By: Carol Willing <carolcode@willingconsulting.com>
The purpose of the `unicodedata.is_normalized` function is to answer
the question `str == unicodedata.normalized(form, str)` more
efficiently than writing just that, by using the "quick check"
optimization described in the Unicode standard in UAX #15.
However, it turns out the code doesn't implement the full algorithm
from the standard, and as a result we often miss the optimization and
end up having to compute the whole normalized string after all.
Implement the standard's algorithm. This greatly speeds up
`unicodedata.is_normalized` in many cases where our partial variant
of quick-check had been returning MAYBE and the standard algorithm
returns NO.
At a quick test on my desktop, the existing code takes about 4.4 ms/MB
(so 4.4 ns per byte) when the partial quick-check returns MAYBE and it
has to do the slow normalize-and-compare:
$ build.base/python -m timeit -s 'import unicodedata; s = "\uf900"*500000' \
-- 'unicodedata.is_normalized("NFD", s)'
50 loops, best of 5: 4.39 msec per loop
With this patch, it gets the answer instantly (58 ns) on the same 1 MB
string:
$ build.dev/python -m timeit -s 'import unicodedata; s = "\uf900"*500000' \
-- 'unicodedata.is_normalized("NFD", s)'
5000000 loops, best of 5: 58.2 nsec per loop
This restores a small optimization that the original version of this
code had for the `unicodedata.normalize` use case.
With this, that case is actually faster than in master!
$ build.base/python -m timeit -s 'import unicodedata; s = "\u0338"*500000' \
-- 'unicodedata.normalize("NFD", s)'
500 loops, best of 5: 561 usec per loop
$ build.dev/python -m timeit -s 'import unicodedata; s = "\u0338"*500000' \
-- 'unicodedata.normalize("NFD", s)'
500 loops, best of 5: 512 usec per loop
Adds a link to `dateutil.parser.isoparse` in the documentation.
It would be nice to set up intersphinx for things like this, but I think we can leave that for a separate PR.
CC: @pitrou
[bpo-37979](https://bugs.python.org/issue37979)
https://bugs.python.org/issue37979
Automerge-Triggered-By: @pitrou
- drop TargetScopeError in favour of raising SyntaxError directly
as per the updated PEP 572
- comprehension iteration variables are explicitly local, but
named expression targets in comprehensions are nonlocal or
global. Raise SyntaxError as specified in PEP 572
- named expression targets in the outermost iterable of a
comprehension have an ambiguous target scope. Avoid resolving
that question now by raising SyntaxError. PEP 572
originally required this only for cases where the bound name
conflicts with the iteration variable in the comprehension,
but CPython can't easily restrict the exception to that case
(as it doesn't know the target variable names when visiting
the outermost iterator expression)
