optional, and default to `localhost' and ports 8025 and 25
respectively.
SMTPChannel.__init__(): Calculate __fqdn using socket.getfqdn()
instead of gethostby*() and friends. This allows us to run this
script even if we don't have access to dns (assuming the localhost is
configured properly).
Also, restore my precious page breaks. Hands off, oh Whitespace
Normalizer!
The profiler does not need to know anything about the exception state,
so we no longer call it when an exception is raised. We do, however,
make sure we *always* call the profiler when we exit a frame. This
ensures that timing events are more easily isolated by a profiler and
finally clauses that do a lot of work don't have their time
mis-allocated.
When an exception is propogated out of the frame, the C callback for
the profiler now receives a PyTrace_RETURN event with an arg of NULL;
the Python-level profile hook function will see a 'return' event with
an arg of None. This means that from Python it is impossible for the
profiler to determine if the frame exited with an exception or if it
returned None, but this doesn't matter for profiling. A C-based
profiler could tell the difference, but this doesn't seem important.
ceval.c:eval_frame(): Simplify the code in two places so that the
profiler is called for every exit from a frame
and not for exceptions.
sysmodule.c:profile_trampoline(): Make sure we don't expose Python
code to NULL; use None instead.
For a dynamically constructed type object, fill in the tp_doc slot with
a copy of the argument dict's "__doc__" value, provided the latter exists
and is a string.
NOTE: I don't know what to do if it's a Unicode string, so in that case
tp_doc is left NULL (which shows up as Py_None if you do Class.__doc__).
Note that tp_doc holds a char*, not a general PyObject*.
it deals correctly with some anomalous cases; according to this test
suite I've fixed it right.
The anomalous cases had to do with 'exception' events: these aren't
generated when they would be most helpful, and the profiler has to
work hard to recover the right information. The problems occur when C
code (such as hasattr(), which is used as the example here) calls back
into Python code and clears an exception raised by that Python code.
Consider this example:
def foo():
hasattr(obj, "bar")
Where obj is an instance from a class like this:
class C:
def __getattr__(self, name):
raise AttributeError
The profiler sees the following sequence of events:
call (foo)
call (__getattr__)
exception (in __getattr__)
return (from foo)
Previously, the profiler would assume the return event returned from
__getattr__. An if statement checking for this condition and raising
an exception was commented out... This version does the right thing.
test for modifying __getattr__ works, now that slot_tp_getattr_hook
zaps the slot if there's no hook. Added an XXX comment with a ref
back to slot_tp_getattr_hook.
test for getattribute==NULL was bogus because it always found
object.__getattribute__. Pick it apart using the trick we learned
from slot_sq_item, and if it's just a wrapper around
PyObject_GenericGetAttr, zap it. Also added a long XXX comment
explaining the consequences.
test dramatically:
class T(tuple): __dynamic__ = 1
t = T(range(1000))
for i in range(1000): tt = tuple(t)
The speedup was about 5x compared to the previous state of CVS (1.7
vs. 8.8, in arbitrary time units). But it's still more than twice as
slow as as the same test with __dynamic__ = 0 (0.8).
I'm not sure that I really want to go through the trouble of this kind
of speedup for every slot. Even doing it just for the most popular
slots will be a major effort (the new slot_sq_item is 40+ lines, while
the old one was one line with a powerful macro -- unfortunately the
speedup comes from expanding the macro and doing things in a way
specific to the slot signature).
An alternative that I'm currently considering is sketched in PLAN.txt:
trap setattr on type objects. But this will require keeping track of
all derived types using weak references.
Taught doctest about static methods, class methods, and property docstrings
in new-style classes. As for inspect.py/pydoc.py before it, the new stuff
needed didn't really fit into the old architecture (but was less of a
strain to force-fit here).
New-style class docstrings still aren't found, but that's the subject
of a different bug and I want to fix that right instead of hacking around
it in doctest.
pointing to a static variable to hold the object form of the string
was never used, causing endless calls to PyString_InternFromString().
One particular test (with lots of __getitem__ calls) became a third
faster with this!
Unknown whether this fixes it.
- stringobject.c, PyString_FromFormatV: don't assume that va_list is of
a type that can be copied via an initializer.
- errors.c, PyErr_Format: add a va_end() to balance the va_start().
instances).
Also added GC support to various auxiliary types: super, property,
descriptors, wrappers, dictproxy. (Only type objects have a tp_clear
field; the other types are.)
One change was necessary to the GC infrastructure. We have statically
allocated type objects that don't have a GC header (and can't easily
be given one) and heap-allocated type objects that do have a GC
header. Giving these different metatypes would be really ugly: I
tried, and I had to modify pickle.py, cPickle.c, copy.py, add a new
invent a new name for the new metatype and make it a built-in, change
affected tests... In short, a mess. So instead, we add a new type
slot tp_is_gc, which is a simple Boolean function that determines
whether a particular instance has GC headers or not. This slot is
only relevant for types that have the (new) GC flag bit set. If the
tp_is_gc slot is NULL (by far the most common case), all instances of
the type are deemed to have GC headers. This slot is called by the
PyObject_IS_GC() macro (which is only used twice, both times in
gcmodule.c).
I also changed the extern declarations for a bunch of GC-related
functions (_PyObject_GC_Del etc.): these always exist but objimpl.h
only declared them when WITH_CYCLE_GC was defined, but I needed to be
able to reference them without #ifdefs. (When WITH_CYCLE_GC is not
defined, they do the same as their non-GC counterparts anyway.)
- The test for deepcopy() in pickles() was indented wrongly, so it got
run twice (one for binary pickle mode, one for text pickle mode; but
the test doesn't depend on the pickle mode).
- In verbose mode, show which subtest (pickle/cPickle/deepcopy, text/bin).
in run_test() referenced two non-existent variables, and in
non-verbose mode, the tests didn't report the actual number, when it
differed from the expected number. Fixed this.
Also added an extra call to gc.collect() at the start of test_all().
This will be needed when I check in the changes to add GC to new-style
classes.
from Tim Hochberg. Also mucho fiddling to change the way doctest
determines whether a thing is a function, module or class. Under 2.2,
this really requires the functions in inspect.py (e.g., types.ClassType
is close to meaningless now, if not outright misleading).
try to explain the complex general scheme we actually use now, I decided
to spell out only what equality means (which is easy to explain and
intuitive), leaving the other outcomes unspecified beyond consistency.
The patch repaired internal gcc compiler errors on BeOS.
This checkin repairs them in a simpler way, by explicitly casting the
platform INFINITY to double.