This completes the q/Q project.
longobject.c _PyLong_AsByteArray: The original code had a gross bug:
the most-significant Python digit doesn't necessarily have SHIFT
significant bits, and you really need to count how many copies of the sign
bit it has else spurious overflow errors result.
test_struct.py: This now does exhaustive std q/Q testing at, and on both
sides of, all relevant power-of-2 boundaries, both positive and negative.
NEWS: Added brief dict news while I was at it.
native mode, and only when config #defines HAVE_LONG_LONG. Standard mode
will eventually treat them as 8-byte ints across all platforms, but that
likely requires a new set of routines in longobject.c first (while
sizeof(long) >= 4 is guaranteed by C, there's nothing in C we can rely
on x-platform to hold 8 bytes of int, so we'll have to roll our own;
I'm thinking of a simple pair of conversion functions, Python long
to/from sized vector of unsigned bytes; that may be useful for GMP
conversions too; std q/Q would call them with size fixed at 8).
test_struct.py: In addition to adding some native-mode 'q' and 'Q' tests,
got rid of unused code, and repaired a non-portable assumption about
native sizeof(short) (it isn't 2 on some Cray boxes).
libstruct.tex: In addition to adding a bit of 'q'/'Q' docs (more needed
later), removed an erroneous footnote about 'I' behavior.
Armin Rigo pointed out that the way the line-# table got built didn't work
for lines generating more than 255 bytes of bytecode. Fixed as he
suggested, plus corresponding changes to pyassem.py, plus added some
long overdue docs about this subtle table to compile.c.
Bugfix candidate (line numbers may be off in tracebacks under -O).
code, less memory. Tests have uncovered no drawbacks. Christian and
Vladimir are the other two people who have burned many brain cells on the
dict code in recent years, and they like the approach too, so I'm checking
it in without further ado.
instead of multiplication to generate the probe sequence. The idea is
recorded in Python-Dev for Dec 2000, but that version is prone to rare
infinite loops.
The value is in getting *all* the bits of the hash code to participate;
and, e.g., this speeds up querying every key in a dict with keys
[i << 16 for i in range(20000)] by a factor of 500. Should be equally
valuable in any bad case where the high-order hash bits were getting
ignored.
Also wrote up some of the motivations behind Python's ever-more-subtle
hash table strategy.
*are* obsolete; three variables and the maketrans() function are not
(yet) obsolete.
Add a compensating warnings.filterwarnings() call to test_strop.py.
Add this to the NEWS.
elements when crunching a list, dict or tuple. Now takes linear time
instead -- huge speedup for even moderately large containers, and the
code is notably simpler too.
Added some basic "is the output correct?" tests to test_pprint.
The comment following used to say:
/* We use ~hash instead of hash, as degenerate hash functions, such
as for ints <sigh>, can have lots of leading zeros. It's not
really a performance risk, but better safe than sorry.
12-Dec-00 tim: so ~hash produces lots of leading ones instead --
what's the gain? */
That is, there was never a good reason for doing it. And to the contrary,
as explained on Python-Dev last December, it tended to make the *sum*
(i + incr) & mask (which is the first table index examined in case of
collison) the same "too often" across distinct hashes.
Changing to the simpler "i = hash & mask" reduced the number of string-dict
collisions (== # number of times we go around the lookup for-loop) from about
6 million to 5 million during a full run of the test suite (these are
approximate because the test suite does some random stuff from run to run).
The number of collisions in non-string dicts also decreased, but not as
dramatically.
Note that this may, for a given dict, change the order (wrt previous
releases) of entries exposed by .keys(), .values() and .items(). A number
of std tests suffered bogus failures as a result. For dicts keyed by
small ints, or (less so) by characters, the order is much more likely to be
in increasing order of key now; e.g.,
>>> d = {}
>>> for i in range(10):
... d[i] = i
...
>>> d
{0: 0, 1: 1, 2: 2, 3: 3, 4: 4, 5: 5, 6: 6, 7: 7, 8: 8, 9: 9}
>>>
Unfortunately. people may latch on to that in small examples and draw a
bogus conclusion.
test_support.py
Moved test_extcall's sortdict() into test_support, made it stronger,
and imported sortdict into other std tests that needed it.
test_unicode.py
Excluced cp875 from the "roundtrip over range(128)" test, because
cp875 doesn't have a well-defined inverse for unicode("?", "cp875").
See Python-Dev for excruciating details.
Cookie.py
Chaged various output functions to sort dicts before building
strings from them.
test_extcall
Fiddled the expected-result file. This remains sensitive to native
dict ordering, because, e.g., if there are multiple errors in a
keyword-arg dict (and test_extcall sets up many cases like that), the
specific error Python complains about first depends on native dict
ordering.
Allow module getattr and setattr to exploit string interning, via the
previously null module object tp_getattro and tp_setattro slots. Yields
a very nice speedup for things like random.random and os.path etc.
Fixed a half dozen ways in which general dict comparison could crash
Python (even cause Win98SE to reboot) in the presence of kay and/or
value comparison routines that mutate the dict during dict comparison.
Bugfix candidate.
d1 == d2 and d1 != d2 now work even if the keys and values in d1 and d2
don't support comparisons other than ==, and testing dicts for equality
is faster now (especially when inequality obtains).
NEEDS DOC CHANGES.
More AttributeErrors transmuted into TypeErrors, in test_b2.py, and,
again, this strikes me as a good thing.
This checkin completes the iterator generalization work that obviously
needed to be done. Can anyone think of others that should be changed?
NEEDS DOC CHANGES
A few more AttributeErrors turned into TypeErrors, but in test_contains
this time.
The full story for instance objects is pretty much unexplainable, because
instance_contains() tries its own flavor of iteration-based containment
testing first, and PySequence_Contains doesn't get a chance at it unless
instance_contains() blows up. A consequence is that
some_complex_number in some_instance
dies with a TypeError unless some_instance.__class__ defines __iter__ but
does not define __getitem__.
to string.join(), so that when the latter figures out in midstream that
it really needs unicode.join() instead, unicode.join() can actually get
all the sequence elements (i.e., there's no guarantee that the sequence
passed to string.join() can be iterated over *again* by unicode.join(),
so string.join() must not pass on the original sequence object anymore).
because PySequence_Fast() started working for free as soon as
PySequence_Tuple() learned how to work with iterators. For some reason
unicode.join() still doesn't work, though.
NEEDS DOC CHANGES.
This one surprised me! While I expected tuple() to be a no-brainer, turns
out it's actually dripping with consequences:
1. It will *allow* the popular PySequence_Fast() to work with any iterable
object (code for that not yet checked in, but should be trivial).
2. It caused two std tests to fail. This because some places used
PyTuple_Sequence() (the C spelling of tuple()) as an indirect way to test
whether something *is* a sequence. But tuple() code only looked for the
existence of sq->item to determine that, and e.g. an instance passed
that test whether or not it supported the other operations tuple()
needed (e.g., __len__). So some things the tests *expected* to fail
with an AttributeError now fail with a TypeError instead. This looks
like an improvement to me; e.g., test_coercion used to produce 559
TypeErrors and 2 AttributeErrors, and now they're all TypeErrors. The
error details are more informative too, because the places calling this
were *looking* for TypeErrors in order to replace the generic tuple()
"not a sequence" msg with their own more specific text, and
AttributeErrors snuck by that.
NEEDS DOC CHANGES.
Possibly contentious: The first time s.next() yields StopIteration (for
a given map argument s) is the last time map() *tries* s.next(). That
is, if other sequence args are longer, s will never again contribute
anything but None values to the result, even if trying s.next() again
could yield another result. This is the same behavior map() used to have
wrt IndexError, so it's the only way to be wholly backward-compatible.
I'm not a fan of letting StopIteration mean "try again later" anyway.
to no longer insist that len(seq) be defined.
NEEDS DOC CHANGES.
This is meant to be a model for how other functions of this ilk (max,
filter, etc) can be generalized similarly. Feel encouraged to grab your
favorite and convert it!
Note some cute consequences:
list(file) == file.readlines() == list(file.xreadlines())
list(dict) == dict.keys()
list(dict.iteritems()) = dict.items()
list(xrange(i, j, k)) == range(i, j, k)
Barry Warsaw
Tim Peters
Guido van Rossum
Martin v. Löwis
Neil Schemenauer
Marc-André Lemburg
Mark Hammond