Argument Clinic "converters" specify how to convert an individual
argument to the function you're defining. Although a converter could
theoretically represent any sort of conversion, most of the time they
directly represent types like "int" or "double" or "str".
Because there's such variety in argument parsing, the converters are
customizable with parameters. Many of these are common enough that
Argument Clinic suggests some standard names. Examples: "zeroes=True"
for strings and buffers means "permit internal \0 characters", and
"bitwise=True" for unsigned integers means "copy the bits over, even if
there's overflow/underflow, and even if the original is negative".
A third example is "nullable=True", which means "also accept None for
this parameter". This was originally intended for use with strings
(compare the "s" and "z" format units for PyArg_ParseTuple), however it
looks like we'll have a use for "nullable ints" in the ongoing Argument
Clinic conversion work.
Several people have said they found the name "nullable" surprising,
suggesting I use another name like "allow_none" or "noneable". I, in
turn, find their surprise surprising; "nullable" is a term long
associated with exactly this concept. It's used in C# and SQL, and the
term even has its own Wikipedia page:
http://en.wikipedia.org/wiki/Nullable_type
Most amusingly, Vala *used* to have an annotation called "(allow-none)",
but they've broken it out into two annotations, "(nullable)" and
"(optional)".
http://blogs.gnome.org/desrt/2014/05/27/allow-none-is-dead-long-live-nullab…
Before you say "the term 'nullable' will confuse end users", let me
remind you: this is not user-facing. This is a parameter for an
Argument Clinic converter, and will only ever be seen by CPython core
developers. A group which I hope is not so easily confused.
It's my contention that "nullable" is the correct name. But I've been
asked to bring up the topic for discussion, to see if a consensus forms
around this or around some other name.
Let the bike-shedding begin,
//arry/
I'm back, I've re-read the PEP, and I've re-read the long thread with "(no
subject)".
I think Georg Brandl nailed it:
"""
*I like the "sequence and dict flattening" part of the PEP, mostly because
itis consistent and should be easy to understand, but the comprehension
syntaxenhancements seem to be bad for readability and "comprehending" what
the codedoes.The call syntax part is a mixed bag on the one hand it is nice
to be consistent with the extended possibilities in literals (flattening),
but on the other hand there would be small but annoying inconsistencies
anyways (e.g. the duplicate kwarg case above).*
"""
Greg Ewing followed up explaining that the inconsistency between dict
flattening and call syntax is inherent in the pre-existing different rules
for dicts vs. keyword args: {'a':1, 'a':2} results in {'a':2}, while f(a=1,
a=2) is an error. (This form is a SyntaxError; the dynamic case f(a=1,
**{'a': 1}) is a TypeError.)
For me, allowing f(*a, *b) and f(**d, **e) and all the other combinations
for function calls proposed by the PEP is an easy +1 -- it's a
straightforward extension of the existing pattern, and anybody who knows
what f(x, *a) does will understand f(x, *a, y, *b). Guessing what f(**d,
**e) means shouldn't be hard either. Understanding the edge case for
duplicate keys with f(**d, **e) is a little harder, but the error messages
are pretty clear, and it is not a new edge case.
The sequence and dict flattening syntax proposals are also clean and
logical -- we already have *-unpacking on the receiving side, so allowing
*x in tuple expressions reads pretty naturally (and the similarity with *a
in argument lists certainly helps). From here, having [a, *x, b, *y] is
also natural, and then the extension to other displays is natural: {a, *x,
b, *y} and {a:1, **d, b:2, **e}. This, too, gets a +1 from me.
So that leaves comprehensions. IIRC, during the development of the patch we
realized that f(*x for x in xs) is sufficiently ambiguous that we decided
to disallow it -- note that f(x for x in xs) is already somewhat of a
special case because an argument can only be a "bare" generator expression
if it is the only argument. The same reasoning doesn't apply (in that form)
to list, set and dict comprehensions -- while f(x for x in xs) is identical
in meaning to f((x for x in xs)), [x for x in xs] is NOT the same as [(x
for x in xs)] (that's a list of one element, and the element is a generator
expression).
The basic premise of this part of the proposal is that if you have a few
iterables, the new proposal (without comprehensions) lets you create a list
or generator expression that iterates over all of them, essentially
flattening them:
>>> xs = [1, 2, 3]
>>> ys = ['abc', 'def']
>>> zs = [99]
>>> [*xs, *ys, *zs]
[1, 2, 3, 'abc', 'def', 99]
>>>
But now suppose you have a list of iterables:
>>> xss = [[1, 2, 3], ['abc', 'def'], [99]]
>>> [*xss[0], *xss[1], *xss[2]]
[1, 2, 3, 'abc', 'def', 99]
>>>
Wouldn't it be nice if you could write the latter using a comprehension?
>>> xss = [[1, 2, 3], ['abc', 'def'], [99]]
>>> [*xs for xs in xss]
[1, 2, 3, 'abc', 'def', 99]
>>>
This is somewhat seductive, and the following is even nicer: the *xs
position may be an expression, e.g.:
>>> xss = [[1, 2, 3], ['abc', 'def'], [99]]
>>> [*xs[:2] for xs in xss]
[1, 2, 'abc', 'def', 99]
>>>
On the other hand, I had to explore the possibilities here by experimenting
in the interpreter, and I discovered some odd edge cases (e.g. you can
parenthesize the starred expression, but that seems a syntactic accident).
All in all I am personally +0 on the comprehension part of the PEP, and I
like that it provides a way to "flatten" a sequence of sequences, but I
think very few people in the thread have supported this part. Therefore I
would like to ask Neil to update the PEP and the patch to take out the
comprehension part, so that the two "easy wins" can make it into Python 3.5
(basically, I am accepting two-thirds of the PEP :-). There is some time
yet until alpha 2.
I would also like code reviewers (Benjamin?) to start reviewing the patch
<http://bugs.python.org/issue2292>, taking into account that the
comprehension part needs to be removed.
--
--Guido van Rossum (python.org/~guido)
Hi,
The OpenBSD buildbot always fail with the same failures since many
months (ex: test_socket). Is someone interested to fix them? If no,
would it be possible to turn it off to get a better view of
regressions? Currently, they are too many red buildbots to quickly see
regressions introduced by recent commits.
http://buildbot.python.org/all/builders/x86%20OpenBSD%205.5%203.x
Victor
Hi all,
I'm not sure whether this should be python-list or here, but given it's a premature code review for http.client, I figured I'd post here first.
I'm in the process of adding support for chunked transfer encoding to http.client (issue #12319). One of the bits of functionality that I'm working on in is ironing out some of the kinks out in determining the content length of the request bodies. Given the number of data types allowed as bodies it does get a little messy, so I wanted to get some feedback here and see if anyone can shoot holes through it prior to updating the current patch. The tests are passing, but there may be use cases not accounted for in the new implementation.
https://gist.github.com/demianbrecht/f94be5a51e32bb9c81e1
The above is intended to replace _set_content_length (current state of the patch can be seen here: http://bugs.python.org/review/12319/diff/14331/Lib/http/client.py). There is a comprehensive list of data types currently supported can be found here: http://bugs.python.org/issue23740. Comments and feedback are much appreciated.
Thanks,
Demian
Hi,
The buildbot AMD64 OpenIndiana 3.x is always red since at least 6
months. Almost always, tests fail because the buildbot has not enough
memory. Well, it's fun to see how Python handles MemoryError (it's
pretty good, there is no hard crash! my work on failmalloc was maybe
useful ;-)), but it doesn't help to detect regressions.
Would it be possible to enhance this buildbot?
I copy this email to the owner of buildbot. But I also sent it to
python-dev because MemoryError is not the only error, please take care
of our buildbots!
Thanks,
Victor
its french! lol
I just wanted to see if you could, as well as making python able to have
assembly written, you should totally use blender as your main IDE it would
be so epic
and do pyjackd, and i think pyaudio will write some stuff, and like
pycoreaudio and like directpy for windows direct x
oh having blender as the main ide would just be epic
Hi,
Here is the first draft of my PEP to chain automatically exceptions at
C level in Python 3.5. Plain text version of the PEP below. HTML
version of the PEP:
https://www.python.org/dev/peps/pep-0490/
It has already an implementation, the pyerr_chain.patch file attached to
http://bugs.python.org/issue23763
The patch is very short.
We may modify more functions to hide the previous exception when the
new exception contains as much or more information. Keeping the
previous exception waste memory, make reference cycles more likely and
is useless when displaying the full exception chain.
I wrote a huge patch modifying a lot of functions to explicitly *not*
chain exceptions: pyerr_match_clear-2.patch of the issue #23763. I
wrote the patch to show where exceptions will be chained with
pyerr_chain.patch applied. But we might apply it if we want to keep
exactly the same behaviour between Python 3.4 and 3.5 for C modules
the stdlib.
pyerr_match_clear-2.patch adds also checks on the type of the previous
exception to not replace an "unexpected" exception. For example, we
can replace an expected TypeError with a ValueError (without chaining
them), but we should not raise a ValueError if we got a
KeyboardInterrupt, a MemoryError or other unexpected exceptions. But
such changes are unrelated to the PEP and may be done in a separated
issue.
The starting point of my PEP is my work on CPython done with the
pyfailmalloc module. This module injects MemoryError. I fixed a ton of
issues in the code handling errors in CPython (see the issue #18408).
I noticed that Python didn't complain when exceptions are lost. I
added many assertions to detect these mistakes. Recently, I modified
Python 3.5 to raise an exception even in release mode (issue #23571)
if a C function returns NULL without an exception set, or if a C
function returns a result with an exception set.
Victor
PEP: 490
Title: Chain exceptions at C level
Version: $Revision$
Last-Modified: $Date$
Author: Victor Stinner <victor.stinner(a)gmail.com>
Status: Draft
Type: Standards Track
Content-Type: text/x-rst
Created: 25-March-2015
Python-Version: 3.5
Abstract
========
Chain exceptions at C level, as already done at Python level.
Rationale
=========
Python 3 introduced a new killer feature: exceptions are chained by
default, PEP 3134.
Example::
try:
raise TypeError("err1")
except TypeError:
raise ValueError("err2")
Output::
Traceback (most recent call last):
File "test.py", line 2, in <module>
raise TypeError("err1")
TypeError: err1
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "test.py", line 4, in <module>
raise ValueError("err2")
ValueError: err2
Exceptions are chained by default in Python code, but not in
extensions written in C.
A new private ``_PyErr_ChainExceptions()`` function was introduced in
Python 3.4.3 and 3.5 to chain exceptions. Currently, it must be called
explicitly to chain exceptions and its usage is not trivial.
Example of ``_PyErr_ChainExceptions()`` usage from the ``zipimport``
module to chain the previous ``OSError`` to a new ``ZipImportError``
exception::
PyObject *exc, *val, *tb;
PyErr_Fetch(&exc, &val, &tb);
PyErr_Format(ZipImportError, "can't open Zip file: %R", archive);
_PyErr_ChainExceptions(exc, val, tb);
This PEP proposes to also chain exceptions automatically at C level to
stay consistent and give more information on failures to help
debugging. The previous example becomes simply::
PyErr_Format(ZipImportError, "can't open Zip file: %R", archive);
Proposal
========
Modify PyErr_*() functions to chain exceptions
----------------------------------------------
Modify C functions raising exceptions of the Python C API to
automatically chain exceptions: modify ``PyErr_SetString()``,
``PyErr_Format()``, ``PyErr_SetNone()``, etc.
Modify functions to not chain exceptions
----------------------------------------
Keeping the previous exception is not always interesting when the new
exception contains information of the previous exception or even more
information, especially when the two exceptions have the same type.
Example of an useless exception chain with ``int(str)``::
TypeError: a bytes-like object is required, not 'type'
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
TypeError: int() argument must be a string, a bytes-like object or
a number, not 'type'
The new ``TypeError`` exception contains more information than the
previous exception. The previous exception should be hidden.
The ``PyErr_Clear()`` function can be called to clear the current
exception before raising a new exception, to not chain the current
exception with a new exception.
Modify functions to chain exceptions
------------------------------------
Some functions save and then restore the current exception. If a new
exception is raised, the exception is currently displayed into
sys.stderr or ignored depending on the function. Some of these
functions should be modified to chain exceptions instead.
Examples of function ignoring the new exception(s):
* ``ptrace_enter_call()``: ignore exception
* ``subprocess_fork_exec()``: ignore exception raised by enable_gc()
* ``t_bootstrap()`` of the ``_thread`` module: ignore exception raised
by trying to display the bootstrap function to ``sys.stderr``
* ``PyDict_GetItem()``, ``_PyDict_GetItem_KnownHash()``: ignore
exception raised by looking for a key in the dictionary
* ``_PyErr_TrySetFromCause()``: ignore exception
* ``PyFrame_LocalsToFast()``: ignore exception raised by
``dict_to_map()``
* ``_PyObject_Dump()``: ignore exception. ``_PyObject_Dump()`` is used
to debug, to inspect a running process, it should not modify the
Python state.
* ``Py_ReprLeave()``: ignore exception "because there is no way to
report them"
* ``type_dealloc()``: ignore exception raised by
``remove_all_subclasses()``
* ``PyObject_ClearWeakRefs()``: ignore exception?
* ``call_exc_trace()``, ``call_trace_protected()``: ignore exception
* ``remove_importlib_frames()``: ignore exception
* ``do_mktuple()``, helper used by ``Py_BuildValue()`` for example:
ignore exception?
* ``flush_io()``: ignore exception
* ``sys_write()``, ``sys_format()``: ignore exception
* ``_PyTraceback_Add()``: ignore exception
* ``PyTraceBack_Print()``: ignore exception
Examples of function displaying the new exception to ``sys.stderr``:
* ``atexit_callfuncs()``: display exceptions with
``PyErr_Display()`` and return the latest exception, the function
calls multiple callbacks and only returns the latest exception
* ``sock_dealloc()``: log the ``ResourceWarning`` exception with
``PyErr_WriteUnraisable()``
* ``slot_tp_del()``: display exception with
``PyErr_WriteUnraisable()``
* ``_PyGen_Finalize()``: display ``gen_close()`` exception with
``PyErr_WriteUnraisable()``
* ``slot_tp_finalize()``: display exception raised by the
``__del__()`` method with ``PyErr_WriteUnraisable()``
* ``PyErr_GivenExceptionMatches()``: display exception raised by
``PyType_IsSubtype()`` with ``PyErr_WriteUnraisable()``
Backward compatibility
======================
A side effect of chaining exceptions is that exceptions store
traceback objects which store frame objects which store local
variables. Local variables are kept alive by exceptions. A common
issue is a reference cycle between local variables and exceptions: an
exception is stored in a local variable and the frame indirectly
stored in the exception. The cycle only impacts applications storing
exceptions.
The reference cycle can now be fixed with the new
``traceback.TracebackException`` object introduced in Python 3.5. It
stores informations required to format a full textual traceback without
storing local variables.
The ``asyncio`` is impacted by the reference cycle issue. This module
is also maintained outside Python standard library to release a
version for Python 3.3. ``traceback.TracebackException`` will maybe
be backported in a private ``asyncio`` module to fix reference cycle
issues.
Alternatives
============
No change
---------
A new private ``_PyErr_ChainExceptions()`` function is enough to chain
manually exceptions.
Exceptions will only be chained explicitly where it makes sense.
New helpers to chain exceptions
-------------------------------
Functions like ``PyErr_SetString()`` don't chain automatically
exceptions. To make the usage of ``_PyErr_ChainExceptions()`` easier,
new private functions are added:
* ``_PyErr_SetStringChain(exc_type, message)``
* ``_PyErr_FormatChain(exc_type, format, ...)``
* ``_PyErr_SetNoneChain(exc_type)``
* ``_PyErr_SetObjectChain(exc_type, exc_value)``
Helper functions to raise specific exceptions like
``_PyErr_SetKeyError(key)`` or ``PyErr_SetImportError(message, name,
path)`` don't chain exceptions. The generic
``_PyErr_ChainExceptions(exc_type, exc_value, exc_tb)`` should be used
to chain exceptions with these helper functions.
Appendix
========
PEPs
----
* `PEP 3134 -- Exception Chaining and Embedded Tracebacks
<https://www.python.org/dev/peps/pep-3134/>`_ (Python 3.0):
new ``__context__`` and ``__cause__`` attributes for exceptions
* `PEP 415 - Implement context suppression with exception attributes
<https://www.python.org/dev/peps/pep-0415/>`_ (Python 3.3):
``raise exc from None``
* `PEP 409 - Suppressing exception context
<https://www.python.org/dev/peps/pep-0409/>`_
(superseded by the PEP 415)
Python C API
------------
The header file ``Include/pyerror.h`` declares functions related to
exceptions.
Functions raising exceptions:
* ``PyErr_SetNone(exc_type)``
* ``PyErr_SetObject(exc_type, exc_value)``
* ``PyErr_SetString(exc_type, message)``
* ``PyErr_Format(exc, format, ...)``
Helpers to raise specific exceptions:
* ``PyErr_BadArgument()``
* ``PyErr_BadInternalCall()``
* ``PyErr_NoMemory()``
* ``PyErr_SetFromErrno(exc)``
* ``PyErr_SetFromWindowsErr(err)``
* ``PyErr_SetImportError(message, name, path)``
* ``_PyErr_SetKeyError(key)``
* ``_PyErr_TrySetFromCause(prefix_format, ...)``
Manage the current exception:
* ``PyErr_Clear()``: clear the current exception,
like ``except: pass``
* ``PyErr_Fetch(exc_type, exc_value, exc_tb)``
* ``PyErr_Restore(exc_type, exc_value, exc_tb)``
* ``PyErr_GetExcInfo(exc_type, exc_value, exc_tb)``
* ``PyErr_SetExcInfo(exc_type, exc_value, exc_tb)``
Others function to handle exceptions:
* ``PyErr_ExceptionMatches(exc)``: check to implement
``except exc: ...``
* ``PyErr_GivenExceptionMatches(exc1, exc2)``
* ``PyErr_NormalizeException(exc_type, exc_value, exc_tb)``
* ``_PyErr_ChainExceptions(exc_type, exc_value, exc_tb)``
Python Issues
-------------
Chain exceptions:
* `Issue #23763: Chain exceptions in C
<http://bugs.python.org/issue23763>`_
* `Issue #23696: zipimport: chain ImportError to OSError
<http://bugs.python.org/issue23696>`_
* `Issue #21715: Chaining exceptions at C level
<http://bugs.python.org/issue21715>`_: added
``_PyErr_ChainExceptions()``
* `Issue #18488: sqlite: finalize() method of user function may be
called with an exception set if a call to step() method failed
<http://bugs.python.org/issue18488>`_
* `Issue #23781: Add private _PyErr_ReplaceException() in 2.7
<http://bugs.python.org/issue23781>`_
* `Issue #23782: Leak in _PyTraceback_Add
<http://bugs.python.org/issue23782>`_
Changes preventing to loose exceptions:
* `Issue #23571: Raise SystemError if a function returns a result with an
exception set <http://bugs.python.org/issue23571>`_
* `Issue #18408: Fixes crashes found by pyfailmalloc
<http://bugs.python.org/issue18408>`_
Copyright
=========
This document has been placed in the public domain.
..
Local Variables:
mode: indented-text
indent-tabs-mode: nil
sentence-end-double-space: t
fill-column: 70
coding: utf-8
End:
On behalf of the Python development community and the Python 3.5 release
team, I'm thrilled to announce the availability of Python 3.5.0a3.
Python 3.5.0a3 is the third alpha release of Python 3.5, which will be
the next major release of Python. Python 3.5 is still under heavy
development, and is far from complete.
This is a preview release, and its use is not recommended for production
settings.
Two important notes for Windows users about Python 3.5.0a3:
* If you have previously installed Python 3.5.0a1, you may need to
manually uninstall it before installing Python 3.5.0a3 (issue23612).
* If installing Python 3.5.0a3 as a non-privileged user, you may need
to escalate to administrator privileges to install an update to your
C runtime libraries.
You can find Python 3.5.0a3 here:
https://www.python.org/downloads/release/python-350a3/
Happy hacking,
//arry/
Hi,
Can you please take a look at the following issue and try to reproduce it?
http://bugs.python.org/issue23771
The following tests sometimes hang on "x86 Ubuntu Shared 3.x" and
"AMD64 Debian root 3.x" buildbots:
- test_notify_all() of test_multiprocessing_spawn
- test_double_close_on_error() of test_subprocess
- other sporadic failures of test_subprocess
I'm quite sure that they are regressions, maybe related to the
implementation of the PEP 475. In the middle of all PEP 475 changes, I
changed some functions to release the GIL on I/O, it wasn't the case
before. I may be related.
Are you able to reproduce these issues? I'm unable to reproduce them
on Fedora 21. Maybe they are more likely on Debian-like operating
systems?
Victor
