Use PyLong_FromLong(0) and PyLong_FromLong(1) of the public C API
instead. For Python internals, _PyLong_GetZero() and _PyLong_GetOne()
of pycore_long.h can be used.
Add _PyLong_GetZero() and _PyLong_GetOne() functions and a new
internal pycore_long.h header file.
Python cannot be built without small integer singletons anymore.
* 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.
If PyDict_GetItemWithError is only used to check whether the key is in dict,
it is better to use PyDict_Contains instead.
And if it is used in combination with PyDict_SetItem, PyDict_SetDefault can
replace the combination.
These functions are considered not safe because they suppress all internal errors
and can return wrong result. PyDict_GetItemString and _PyDict_GetItemId can
also silence current exception in rare cases.
Remove no longer used _PyDict_GetItemId.
Add _PyDict_ContainsId and rename _PyDict_Contains into
_PyDict_Contains_KnownHash.
Remove complex special methods __int__, __float__, __floordiv__,
__mod__, __divmod__, __rfloordiv__, __rmod__ and __rdivmod__
which always raised a TypeError.
Enable recursion checks which were disabled when get __bases__ of
non-type objects in issubclass() and isinstance() and when intern
strings. It fixes a stack overflow when getting __bases__ leads
to infinite recursion.
Originally recursion checks was disabled for PyDict_GetItem() which
silences all errors including the one raised in case of detected
recursion and can return incorrect result. But now the code uses
PyDict_GetItemWithError() and PyDict_SetDefault() instead.
* bpo-26680: Adds support for int.is_integer() for compatibility with float.is_integer().
The int.is_integer() method always returns True.
* bpo-26680: Adds a test to ensure that False.is_integer() and True.is_integer() are always True.
* bpo-26680: Adds Real.is_integer() with a trivial implementation using conversion to int.
This default implementation is intended to reduce the workload for subclass
implementers. It is not robust in the presence of infinities or NaNs and
may have suboptimal performance for other types.
* bpo-26680: Adds Rational.is_integer which returns True if the denominator is one.
This implementation assumes the Rational is represented in it's
lowest form, as required by the class docstring.
* bpo-26680: Adds Integral.is_integer which always returns True.
* bpo-26680: Adds tests for Fraction.is_integer called as an instance method.
The tests for the Rational abstract base class use an unbound
method to sidestep the inability to directly instantiate Rational.
These tests check that everything works correct as an instance method.
* bpo-26680: Updates documentation for Real.is_integer and built-ins int and float.
The call x.is_integer() is now listed in the table of operations
which apply to all numeric types except complex, with a reference
to the full documentation for Real.is_integer(). Mention of
is_integer() has been removed from the section 'Additional Methods
on Float'.
The documentation for Real.is_integer() describes its purpose, and
mentions that it should be overridden for performance reasons, or
to handle special values like NaN.
* bpo-26680: Adds Decimal.is_integer to the Python and C implementations.
The C implementation of Decimal already implements and uses
mpd_isinteger internally, we just expose the existing function to
Python.
The Python implementation uses internal conversion to integer
using to_integral_value().
In both cases, the corresponding context methods are also
implemented.
Tests and documentation are included.
* bpo-26680: Updates the ACKS file.
* bpo-26680: NEWS entries for int, the numeric ABCs and Decimal.
Co-authored-by: Robert Smallshire <rob@sixty-north.com>
Use Py_ssize_t type rather than int, to store lengths in
unionobject.c. Fix the warning:
Objects\unionobject.c(205,1): warning C4244: 'initializing':
conversion from 'Py_ssize_t' to 'int', possible loss of data
Use Py_ssize_t type rather than int, to store lengths in
unionobject.c. Fix warnings:
Objects\unionobject.c(189,71): warning C4244: '+=':
conversion from 'Py_ssize_t' to 'int', possible loss of data
Objects\unionobject.c(182,1): warning C4244: 'initializing':
conversion from 'Py_ssize_t' to 'int', possible loss of data
Objects\unionobject.c(205,1): warning C4244: 'initializing':
conversion from 'Py_ssize_t' to 'int', possible loss of data
Objects\unionobject.c(437,1): warning C4244: 'initializing':
conversion from 'Py_ssize_t' to 'int', possible loss of data
Use _PyType_HasFeature() in the _io module and in structseq
implementation. Replace PyType_HasFeature() opaque function call with
_PyType_HasFeature() inlined function.
The new API allows to efficiently send values into native generators
and coroutines avoiding use of StopIteration exceptions to signal
returns.
ceval loop now uses this method instead of the old "private"
_PyGen_Send C API. This translates to 1.6x increased performance
of 'await' calls in micro-benchmarks.
Aside from CPython core improvements, this new API will also allow
Cython to generate more efficient code, benefiting high-performance
IO libraries like uvloop.
When allocating MemoryError classes, there is some logic to use
pre-allocated instances in a freelist only if the type that is being
allocated is not a subclass of MemoryError. Unfortunately in the
destructor this logic is not present so the freelist is altered even
with subclasses of MemoryError.
My mentee @xvxvxvxvxv noticed that iterating over array.array is
slightly faster than iterating over bytes. Looking at the source I
observed that arrayiter_next() calls `getitem(ao, it->index++)` wheras
striter_next() uses the idiom (paraphrased)
item = PyLong_FromLong(seq->ob_sval[it->it_index]);
if (item != NULL)
++it->it_next;
return item;
I'm not 100% sure but I think that the second version has fewer
opportunity for the CPU to overlap the `index++` operation with the
rest of the code (which in both cases involves a call). So here I am
optimistically incrementing the index -- if the PyLong_FromLong() call
fails, this will leave the iterator pointing at the next byte, but
honestly I doubt that anyone would seriously consider resuming use of
the iterator after that kind of failure (it would have to be a
MemoryError). And the author of arrayiter_next() made the same
consideration (or never ever gave it a thought :-).
With this, a loop like
for _ in b: pass
is now slightly *faster* than the same thing over an equivalent array,
rather than slightly *slower* (in both cases a few percent).
Yonatan Goldschmidt
Victor Stinner
Neil Schemenauer
Serhiy Storchaka
Pablo Galindo
Dong-hee Na
Ma Lin
Max Bernstein
Brandt Bucher
Yannick Jadoul
Vladimir Matveev
Mikhail Golubev
Raymond Hettinger
Stefan Pochmann
Robert Smallshire
Dennis Sweeney
Batuhan Taskaya
Maggie Moss
dxflores
Benjamin Peterson
Inada Naoki
Guido van Rossum