__oct__, and __hex__. Raise TypeError if an invalid type is
returned. Note that PyNumber_Int and PyNumber_Long can still
return ints or longs. Fixes SF bug #966618.
- weakref.ref and weakref.ReferenceType will become aliases for each
other
- weakref.ref will be a modern, new-style class with proper __new__
and __init__ methods
- weakref.WeakValueDictionary will have a lighter memory footprint,
using a new weakref.ref subclass to associate the key with the
value, allowing us to have only a single object of overhead for each
dictionary entry (currently, there are 3 objects of overhead per
entry: a weakref to the value, a weakref to the dictionary, and a
function object used as a weakref callback; the weakref to the
dictionary could be avoided without this change)
- a new macro, PyWeakref_CheckRefExact(), will be added
- PyWeakref_CheckRef() will check for subclasses of weakref.ref
This closes SF patch #983019.
The builtin eval() function now accepts any mapping for the locals argument.
Time sensitive steps guarded by PyDict_CheckExact() to keep from slowing
down the normal case. My timings so no measurable impact.
tests which nicely highly highlight weaknesses).
* Initial value is now a large prime.
* Pre-multiply by the set length to add one more basis of differentiation.
* Work a bit harder inside the loop to scatter bits from sources that
may have closely spaced hash values.
All of this is necessary to make up for keep the hash function commutative.
Fortunately, the hash value is cached so the call to frozenset_hash() will
only occur once per set.
* Non-zero initial value so that hash(frozenset()) != hash(0).
* Final permutation to differentiate nested sets.
* Add logic to make sure that -1 is not a possible hash value.
iswide() for east asian width manipulation. (Inspired by David
Goodger, Reviewed by Martin v. Loewis)
- Move _PyUnicode_TypeRecord.flags to the end of the struct so that
no padding is added for UCS-4 builds. (Suggested by Martin v. Loewis)
- Neatened the braces in PyList_New().
- Made sure "indexerr" was initialized to NULL.
- Factored if blocks in PyList_Append().
- Made sure "allocated" is initialized in list_init().
close() calls would attempt to free() the buffer already free()ed on
the first close(). [bug introduced with patch #788249]
Making sure that the buffer is free()ed in file object deallocation is
a belt-n-braces bit of insurance against a memory leak.
the newly created tuples, but tuples added in the freelist are now cleared in
tupledealloc already (which is very cheap, because we are already
Py_XDECREF'ing all elements anyway).
Python should have a standard Py_ZAP macro like ZAP in pystate.c.
This gives another 30% speedup for operations such as
map(func, d.iteritems()) or list(d.iteritems()) which can both take
advantage of length information when provided.
* Split into three separate types that share everything except the
code for iternext. Saves run time decision making and allows
each iternext function to be specialized.
* Inlined PyDict_Next(). In addition to saving a function call, this
allows a redundant test to be eliminated and further specialization
of the code for the unique needs of each iterator type.
* Created a reusable result tuple for iteritems(). Saves the malloc
time for tuples when the previous result was not kept by client code
(this is the typical use case for iteritems). If the client code
does keep the reference, then a new tuple is created.
Results in a 20% to 30% speedup depending on the size and sparsity
of the dictionary.
* Factored constant structure references out of the inner loops for
PyDict_Next(), dict_keys(), dict_values(), and dict_items().
Gave measurable speedups to each (the improvement varies depending
on the sparseness of the dictionary being measured).
* Added a freelist scheme styled after that for tuples. Saves around
80% of the calls to malloc and free. About 10% of the time, the
previous dictionary was completely empty; in those cases, the
dictionary initialization with memset() can be skipped.
scheme in situations that likely won't benefit from it. This further
improves memory utilization from Py2.3 which always over-allocates
except for PyList_New().
Situations expected to benefit from over-allocation:
list.insert(), list.pop(), list.append(), and list.extend()
Situations deemed unlikely to benefit:
list_inplace_repeat, list_ass_slice, list_ass_subscript
The most gray area was for listextend_internal() which only runs
when the argument is a list or a tuple. This could be viewed as
a one-time fixed length addition or it could be viewed as wrapping
a series of appends. I left its over-allocation turned on but
could be convinced otherwise.
worth it to in-line the call to PyIter_Next().
Saves another 15% on most list operations that acceptable a general
iterable argument (such as the list constructor).
avoids creating an intermediate tuple for iterable arguments other than
lists or tuples.
In other words, a+=b no longer requires extra memory when b is not a
list or tuple. The list and tuple cases are unchanged.
for xrange and list objects).
* list.__reversed__ now checks the length of the sequence object before
calling PyList_GET_ITEM() because the mutable could have changed length.
* all three implementations are now tranparent with respect to length and
maintain the invariant len(it) == len(list(it)) even when the underlying
sequence mutates.
* __builtin__.reversed() now frees the underlying sequence as soon
as the iterator is exhausted.
* the code paths were rearranged so that the most common paths
do not require a jump.
* Replace sprintf message with a constant message string -- this error
message ran on every invocation except straight deletions but it was
only needed when the rhs was not iterable. The message was also
out-of-date and did not reflect that iterable arguments were allowed.
* For inner loops that do not make ref count adjustments, use memmove()
for fast copying and better readability.
* For inner loops that do make ref count adjustments, speed them up by
factoring out the constant structure reference and using vitem[] instead.
* Using addition instead of substraction on array indices allows the
compiler to use a fast addressing mode. Saves about 10%.
* Using PyTuple_GET_ITEM and PyList_SET_ITEM is about 7% faster than
PySequenceFast_GET_ITEM which has to make a list check on every pass.
(Championed by Bob Ippolito.)
The update() method for mappings now accepts all the same argument forms
as the dict() constructor. This includes item lists and/or keyword
arguments.
recent gcc on Linux/x86)
[ 899109 ] 1==float('nan')
by implementing rich comparisons for floats.
Seems to make comparisons involving NaNs somewhat less surprising
when the underlying C compiler actually implements C99 semantics.
Marc-André Lemburg
Neil Schemenauer
Nicholas Bastin
Neal Norwitz
Fred Drake
Raymond Hettinger
Tim Peters
Martin v. Löwis
Anthony Baxter
Skip Montanaro
Andrew M. Kuchling
Hye-Shik Chang
Walter Dörwald
Michael W. Hudson
Thomas Heller
Andrew MacIntyre
Phillip J. Eby
Armin Rigo
Brett Cannon
Guido van Rossum