Removed the unicodedata.ucnhash_CAPI attribute which was an internal
PyCapsule object. The related private _PyUnicode_Name_CAPI structure
was moved to the internal C API.
Rename unicodedata.ucnhash_CAPI as unicodedata._ucnhash_CAPI.
Convert the unicodedata extension module to the multiphase
initialization API (PEP 489) and convert the unicodedata.UCD static
type to a heap type.
Co-Authored-By: Mohamed Koubaa <koubaa.m@gmail.com>
* UCD_Check() uses PyModule_Check()
* Simplify the internal _PyUnicode_Name_CAPI structure:
* Remove size and state members
* Remove state and self parameters of getcode() and getname()
functions
* Remove global_module_state
The private _PyUnicode_Name_CAPI structure of the PyCapsule API
unicodedata.ucnhash_CAPI moves to the internal C API. Moreover, the
structure gets a new state member which must be passed to the
getcode() and getname() functions.
* Move Include/ucnhash.h to Include/internal/pycore_ucnhash.h
* unicodedata module is now built with Py_BUILD_CORE_MODULE.
* unicodedata: move hashAPI variable into unicodedata_module_state.
Prepare unicodedata to add a state per module: start with a global
"module" state, pass it to subfunctions which access &UCD_Type. This
change also prepares the conversion of the UCD_Type static type to a
heap type.
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
Hangul composition check boundaries are wrong for the second character
([0x1161, 0x1176) instead of [0x1161, 0x1176]) and third character ((0x11A7, 0x11C3)
instead of [0x11A7, 0x11C3]).
The new syntax is highly human readable while still preventing false
positives. The syntax also extends Python syntax to denote "self" and
positional-only parameters, allowing inspect.Signature objects to be
totally accurate for all supported builtins in Python 3.4.
annotate text signatures in docstrings, resulting in fewer false
positives. "self" parameters are also explicitly marked, allowing
inspect.Signature() to authoritatively detect (and skip) said parameters.
Issue #20326: Argument Clinic now generates separate checksums for the
input and output sections of the block, allowing external tools to verify
that the input has not changed (and thus the output is not out-of-date).
PyMethodDescr_Type, _PyMethodWrapper_Type, and PyWrapperDescr_Type)
have been modified to provide introspection information for builtins.
Also: many additional Lib, test suite, and Argument Clinic fixes.