This PR deprecate explicit loop parameters in all public asyncio APIs
This issues is split to be easier to review.
fourth step: queue.py
https://bugs.python.org/issue36373
This PR deprecate explicit loop parameters in all public asyncio APIs
This issues is split to be easier to review.
Third step: locks.py
https://bugs.python.org/issue36373
* bpo-351428: Updates documentation to reflect AsyncMock call_count after await.
* Adds skip and fixes warning.
* Removes extra >>>.
* Adds ... in front of await mock().
The link we have points to the version from Unicode 6.0.0, dated 2010.
There have been numerous updates to it since then:
https://www.unicode.org/reports/tr44/#Modifications
Change the link to one that points to the current version. Also, use HTTPS.
* 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
Arun Persaud
Emmanuel Arias
Jeroen Demeyer
Xtreak
Nikhil
Jean-François B
Serhiy Storchaka
Lisa Roach
Greg Price
Anthony Sottile
Boris Verhovsky
Richard Sanger
Antoine
Mario Corchero
Jon Janzen
Vinay Sajip
Ashwin Vishnu
David Röthlisberger
Julien Palard
Raymond Hettinger
Joannah Nanjekye
Miro Hrončok
Andre Delfino
Roger Iyengar
Jason R. Coombs
Daniel Pope
Min ho Kim
Paul Ganssle
Rémi Lapeyre