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December 2016
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)
It has been a while since I posted a copy of PEP 1 to the mailing
lists and newsgroups. I've recently done some updating of a few
sections, so in the interest of gaining wider community participation
in the Python development process, I'm posting the latest revision of
PEP 1 here. A version of the PEP is always available on-line at
http://www.python.org/peps/pep-0001.html
Enjoy,
-Barry
-------------------- snip snip --------------------
PEP: 1
Title: PEP Purpose and Guidelines
Version: $Revision: 1.36 $
Last-Modified: $Date: 2002/07/29 18:34:59 $
Author: Barry A. Warsaw, Jeremy Hylton
Status: Active
Type: Informational
Created: 13-Jun-2000
Post-History: 21-Mar-2001, 29-Jul-2002
What is a PEP?
PEP stands for Python Enhancement Proposal. A PEP is a design
document providing information to the Python community, or
describing a new feature for Python. The PEP should provide a
concise technical specification of the feature and a rationale for
the feature.
We intend PEPs to be the primary mechanisms for proposing new
features, for collecting community input on an issue, and for
documenting the design decisions that have gone into Python. The
PEP author is responsible for building consensus within the
community and documenting dissenting opinions.
Because the PEPs are maintained as plain text files under CVS
control, their revision history is the historical record of the
feature proposal[1].
Kinds of PEPs
There are two kinds of PEPs. A standards track PEP describes a
new feature or implementation for Python. An informational PEP
describes a Python design issue, or provides general guidelines or
information to the Python community, but does not propose a new
feature. Informational PEPs do not necessarily represent a Python
community consensus or recommendation, so users and implementors
are free to ignore informational PEPs or follow their advice.
PEP Work Flow
The PEP editor, Barry Warsaw <peps(a)python.org>, assigns numbers
for each PEP and changes its status.
The PEP process begins with a new idea for Python. It is highly
recommended that a single PEP contain a single key proposal or new
idea. The more focussed the PEP, the more successfully it tends
to be. The PEP editor reserves the right to reject PEP proposals
if they appear too unfocussed or too broad. If in doubt, split
your PEP into several well-focussed ones.
Each PEP must have a champion -- someone who writes the PEP using
the style and format described below, shepherds the discussions in
the appropriate forums, and attempts to build community consensus
around the idea. The PEP champion (a.k.a. Author) should first
attempt to ascertain whether the idea is PEP-able. Small
enhancements or patches often don't need a PEP and can be injected
into the Python development work flow with a patch submission to
the SourceForge patch manager[2] or feature request tracker[3].
The PEP champion then emails the PEP editor <peps(a)python.org> with
a proposed title and a rough, but fleshed out, draft of the PEP.
This draft must be written in PEP style as described below.
If the PEP editor approves, he will assign the PEP a number, label
it as standards track or informational, give it status 'draft',
and create and check-in the initial draft of the PEP. The PEP
editor will not unreasonably deny a PEP. Reasons for denying PEP
status include duplication of effort, being technically unsound,
not providing proper motivation or addressing backwards
compatibility, or not in keeping with the Python philosophy. The
BDFL (Benevolent Dictator for Life, Guido van Rossum) can be
consulted during the approval phase, and is the final arbitrator
of the draft's PEP-ability.
If a pre-PEP is rejected, the author may elect to take the pre-PEP
to the comp.lang.python newsgroup (a.k.a. python-list(a)python.org
mailing list) to help flesh it out, gain feedback and consensus
from the community at large, and improve the PEP for
re-submission.
The author of the PEP is then responsible for posting the PEP to
the community forums, and marshaling community support for it. As
updates are necessary, the PEP author can check in new versions if
they have CVS commit permissions, or can email new PEP versions to
the PEP editor for committing.
Standards track PEPs consists of two parts, a design document and
a reference implementation. The PEP should be reviewed and
accepted before a reference implementation is begun, unless a
reference implementation will aid people in studying the PEP.
Standards Track PEPs must include an implementation - in the form
of code, patch, or URL to same - before it can be considered
Final.
PEP authors are responsible for collecting community feedback on a
PEP before submitting it for review. A PEP that has not been
discussed on python-list(a)python.org and/or python-dev(a)python.org
will not be accepted. However, wherever possible, long open-ended
discussions on public mailing lists should be avoided. Strategies
to keep the discussions efficient include, setting up a separate
SIG mailing list for the topic, having the PEP author accept
private comments in the early design phases, etc. PEP authors
should use their discretion here.
Once the authors have completed a PEP, they must inform the PEP
editor that it is ready for review. PEPs are reviewed by the BDFL
and his chosen consultants, who may accept or reject a PEP or send
it back to the author(s) for revision.
Once a PEP has been accepted, the reference implementation must be
completed. When the reference implementation is complete and
accepted by the BDFL, the status will be changed to `Final.'
A PEP can also be assigned status `Deferred.' The PEP author or
editor can assign the PEP this status when no progress is being
made on the PEP. Once a PEP is deferred, the PEP editor can
re-assign it to draft status.
A PEP can also be `Rejected'. Perhaps after all is said and done
it was not a good idea. It is still important to have a record of
this fact.
PEPs can also be replaced by a different PEP, rendering the
original obsolete. This is intended for Informational PEPs, where
version 2 of an API can replace version 1.
PEP work flow is as follows:
Draft -> Accepted -> Final -> Replaced
^
+----> Rejected
v
Deferred
Some informational PEPs may also have a status of `Active' if they
are never meant to be completed. E.g. PEP 1.
What belongs in a successful PEP?
Each PEP should have the following parts:
1. Preamble -- RFC822 style headers containing meta-data about the
PEP, including the PEP number, a short descriptive title
(limited to a maximum of 44 characters), the names, and
optionally the contact info for each author, etc.
2. Abstract -- a short (~200 word) description of the technical
issue being addressed.
3. Copyright/public domain -- Each PEP must either be explicitly
labelled as placed in the public domain (see this PEP as an
example) or licensed under the Open Publication License[4].
4. Specification -- The technical specification should describe
the syntax and semantics of any new language feature. The
specification should be detailed enough to allow competing,
interoperable implementations for any of the current Python
platforms (CPython, JPython, Python .NET).
5. Motivation -- The motivation is critical for PEPs that want to
change the Python language. It should clearly explain why the
existing language specification is inadequate to address the
problem that the PEP solves. PEP submissions without
sufficient motivation may be rejected outright.
6. Rationale -- The rationale fleshes out the specification by
describing what motivated the design and why particular design
decisions were made. It should describe alternate designs that
were considered and related work, e.g. how the feature is
supported in other languages.
The rationale should provide evidence of consensus within the
community and discuss important objections or concerns raised
during discussion.
7. Backwards Compatibility -- All PEPs that introduce backwards
incompatibilities must include a section describing these
incompatibilities and their severity. The PEP must explain how
the author proposes to deal with these incompatibilities. PEP
submissions without a sufficient backwards compatibility
treatise may be rejected outright.
8. Reference Implementation -- The reference implementation must
be completed before any PEP is given status 'Final,' but it
need not be completed before the PEP is accepted. It is better
to finish the specification and rationale first and reach
consensus on it before writing code.
The final implementation must include test code and
documentation appropriate for either the Python language
reference or the standard library reference.
PEP Template
PEPs are written in plain ASCII text, and should adhere to a
rigid style. There is a Python script that parses this style and
converts the plain text PEP to HTML for viewing on the web[5].
PEP 9 contains a boilerplate[7] template you can use to get
started writing your PEP.
Each PEP must begin with an RFC822 style header preamble. The
headers must appear in the following order. Headers marked with
`*' are optional and are described below. All other headers are
required.
PEP: <pep number>
Title: <pep title>
Version: <cvs version string>
Last-Modified: <cvs date string>
Author: <list of authors' real names and optionally, email addrs>
* Discussions-To: <email address>
Status: <Draft | Active | Accepted | Deferred | Final | Replaced>
Type: <Informational | Standards Track>
* Requires: <pep numbers>
Created: <date created on, in dd-mmm-yyyy format>
* Python-Version: <version number>
Post-History: <dates of postings to python-list and python-dev>
* Replaces: <pep number>
* Replaced-By: <pep number>
The Author: header lists the names and optionally, the email
addresses of all the authors/owners of the PEP. The format of the
author entry should be
address(a)dom.ain (Random J. User)
if the email address is included, and just
Random J. User
if the address is not given. If there are multiple authors, each
should be on a separate line following RFC 822 continuation line
conventions. Note that personal email addresses in PEPs will be
obscured as a defense against spam harvesters.
Standards track PEPs must have a Python-Version: header which
indicates the version of Python that the feature will be released
with. Informational PEPs do not need a Python-Version: header.
While a PEP is in private discussions (usually during the initial
Draft phase), a Discussions-To: header will indicate the mailing
list or URL where the PEP is being discussed. No Discussions-To:
header is necessary if the PEP is being discussed privately with
the author, or on the python-list or python-dev email mailing
lists. Note that email addresses in the Discussions-To: header
will not be obscured.
Created: records the date that the PEP was assigned a number,
while Post-History: is used to record the dates of when new
versions of the PEP are posted to python-list and/or python-dev.
Both headers should be in dd-mmm-yyyy format, e.g. 14-Aug-2001.
PEPs may have a Requires: header, indicating the PEP numbers that
this PEP depends on.
PEPs may also have a Replaced-By: header indicating that a PEP has
been rendered obsolete by a later document; the value is the
number of the PEP that replaces the current document. The newer
PEP must have a Replaces: header containing the number of the PEP
that it rendered obsolete.
PEP Formatting Requirements
PEP headings must begin in column zero and the initial letter of
each word must be capitalized as in book titles. Acronyms should
be in all capitals. The body of each section must be indented 4
spaces. Code samples inside body sections should be indented a
further 4 spaces, and other indentation can be used as required to
make the text readable. You must use two blank lines between the
last line of a section's body and the next section heading.
You must adhere to the Emacs convention of adding two spaces at
the end of every sentence. You should fill your paragraphs to
column 70, but under no circumstances should your lines extend
past column 79. If your code samples spill over column 79, you
should rewrite them.
Tab characters must never appear in the document at all. A PEP
should include the standard Emacs stanza included by example at
the bottom of this PEP.
A PEP must contain a Copyright section, and it is strongly
recommended to put the PEP in the public domain.
When referencing an external web page in the body of a PEP, you
should include the title of the page in the text, with a
footnote reference to the URL. Do not include the URL in the body
text of the PEP. E.g.
Refer to the Python Language web site [1] for more details.
...
[1] http://www.python.org
When referring to another PEP, include the PEP number in the body
text, such as "PEP 1". The title may optionally appear. Add a
footnote reference that includes the PEP's title and author. It
may optionally include the explicit URL on a separate line, but
only in the References section. Note that the pep2html.py script
will calculate URLs automatically, e.g.:
...
Refer to PEP 1 [7] for more information about PEP style
...
References
[7] PEP 1, PEP Purpose and Guidelines, Warsaw, Hylton
http://www.python.org/peps/pep-0001.html
If you decide to provide an explicit URL for a PEP, please use
this as the URL template:
http://www.python.org/peps/pep-xxxx.html
PEP numbers in URLs must be padded with zeros from the left, so as
to be exactly 4 characters wide, however PEP numbers in text are
never padded.
Reporting PEP Bugs, or Submitting PEP Updates
How you report a bug, or submit a PEP update depends on several
factors, such as the maturity of the PEP, the preferences of the
PEP author, and the nature of your comments. For the early draft
stages of the PEP, it's probably best to send your comments and
changes directly to the PEP author. For more mature, or finished
PEPs you may want to submit corrections to the SourceForge bug
manager[6] or better yet, the SourceForge patch manager[2] so that
your changes don't get lost. If the PEP author is a SF developer,
assign the bug/patch to him, otherwise assign it to the PEP
editor.
When in doubt about where to send your changes, please check first
with the PEP author and/or PEP editor.
PEP authors who are also SF committers, can update the PEPs
themselves by using "cvs commit" to commit their changes.
Remember to also push the formatted PEP text out to the web by
doing the following:
% python pep2html.py -i NUM
where NUM is the number of the PEP you want to push out. See
% python pep2html.py --help
for details.
Transferring PEP Ownership
It occasionally becomes necessary to transfer ownership of PEPs to
a new champion. In general, we'd like to retain the original
author as a co-author of the transferred PEP, but that's really up
to the original author. A good reason to transfer ownership is
because the original author no longer has the time or interest in
updating it or following through with the PEP process, or has
fallen off the face of the 'net (i.e. is unreachable or not
responding to email). A bad reason to transfer ownership is
because you don't agree with the direction of the PEP. We try to
build consensus around a PEP, but if that's not possible, you can
always submit a competing PEP.
If you are interested assuming ownership of a PEP, send a message
asking to take over, addressed to both the original author and the
PEP editor <peps(a)python.org>. If the original author doesn't
respond to email in a timely manner, the PEP editor will make a
unilateral decision (it's not like such decisions can be
reversed. :).
References and Footnotes
[1] This historical record is available by the normal CVS commands
for retrieving older revisions. For those without direct access
to the CVS tree, you can browse the current and past PEP revisions
via the SourceForge web site at
http://cvs.sourceforge.net/cgi-bin/cvsweb.cgi/python/nondist/peps/?cvsroot=…
[2] http://sourceforge.net/tracker/?group_id=5470&atid=305470
[3] http://sourceforge.net/tracker/?atid=355470&group_id=5470&func=browse
[4] http://www.opencontent.org/openpub/
[5] The script referred to here is pep2html.py, which lives in
the same directory in the CVS tree as the PEPs themselves.
Try "pep2html.py --help" for details.
The URL for viewing PEPs on the web is
http://www.python.org/peps/
[6] http://sourceforge.net/tracker/?group_id=5470&atid=305470
[7] PEP 9, Sample PEP Template
http://www.python.org/peps/pep-0009.html
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
End:
congrats on 3.5! Alas, windows 7 users are having problems installing it
by Laura Creighton Sept. 15, 2019 Sept. 15, 2019
Hi,
My question is simple: do we officially support Solaris and/or OpenIndiana?
Jesus Cea runs an OpenIndiana buildbot slave:
http://buildbot.python.org/all/buildslaves/cea-indiana-x86
"Open Indiana 32 bits"
The platform module of Python says "Solaris-2.11", I don't know the
exact OpenIndiana version.
A lot of unit tests fail on this buildbot with MemoryError. I guess
that it's related to Solaris which doesn't allow overcommit
(allocating more memory than available memory on the system), or more
simply because the slave has not enough memory.
There is now an issue which seems specific to OpenIndiana:
http://bugs.python.org/issue27847
It might impact Solaris as well, but the Solaris buildbot is offline
since "684 builds".
Five years ago, I reported a bug because the curses module of Python 3
doesn't build on Solaris nor OpenIndiana anymore. It seems like the
bug was not fixed, and the issue is still open:
http://bugs.python.org/issue13552
So my question is if we officially support Solaris and/or OpenIndiana.
If yes, how can we fix issues when we only have buildbot slave which
has memory errors, and no SSH access to this server?
Solaris doesn't seem to be officially supported in Python, so I
suggest to drop the OpenIndiana buildbot (which is failing since at
least 2 years) and close all Solaris issues as "WONTFIX".
Victor
Classes that doesn't define the __format__ method for custom PEP 3101
formatting inherits it from parents.
Originally the object.__format__ method was designed as [1]:
def __format__(self, format_spec):
return format(str(self), format_spec)
An instance is converted to string and resulting string is formatted
according to format specifier.
Later this design was reconsidered [2], and now object.__format__ is
equivalent to:
def __format__(self, format_spec):
assert format_spec == ''
return format(str(self), '')
Non-empty format specifier is rejected.
But why call format() on resulting string? Why not return resulting
string as is? object.__format__ could be simpler (not just
implementation, but for understanding):
def __format__(self, format_spec):
assert format_spec == ''
return str(self)
This can change the behaviour in corner case. str(self) can return not
exact string, but string subclass with overloaded __format__. But I
think we can ignore such subtle difference.
[1] https://www.python.org/dev/peps/pep-3101/
[2] http://bugs.python.org/issue7994
Hi,
The PyObject_CallFunction() function has a special case when the
format string is "O", to pass exactly one Python object:
* If the argument is a tuple, the tuple is unpacked: it behaves like func(*arg)
* Otherwise, it behaves like func(arg)
This case is not documented in the C API !
https://docs.python.org/dev/c-api/object.html#c.PyObject_CallFunction
The following C functions have the special case:
* PyObject_CallFunction(), _PyObject_CallFunction_SizeT()
* PyObject_CallMethod(), _PyObject_CallMethod_SizeT()
* _PyObject_CallMethodId(), _PyObject_CallMethodId_SizeT()
I guess that it's a side effect of the implementation: the code uses
Py_BuildValue() and then checks if the value is a tuple or not.
Py_BuildValue() is a little bit surprising:
* "i" creates an integer object
* "ii" creates a tuple
* "(i)" and "(ii)" create a tuple.
Getting a tuple or not depends on the length of the format string. It
is not obvious when you have nested tuples like "O(OO)".
Because of the special case, passing a tuple as the only argument
requires to write "((...))" instead of just "(...)".
In the past, this special behaviour caused a bug in
generator.send(arg), probably because the author of the C code
implementing generator.send() wasn't aware of the special case. See
the issue:
http://bugs.python.org/issue21209
I found code using "O" format in the new _asyncio module, and I'm
quite sure that unpacking special case is not expected. So I opened an
issue:
http://bugs.python.org/issue28920
Last days, I patched functions of PyObject_CallFunction() family to
use internally fast calls. I implemented the special case to keep
backward compatibility.
I replaced a lot of code using PyObject_CallFunction() with
PyObject_CallFunctionObjArgs() when the format string was only made of
"O", PyObject* arguments. I made this change to optimize the code, but
indirectly, it avoids also the special case for code which used
exactly "O" format. See:
http://bugs.python.org/issue28915
When I made these changes, I found some functions which rely the
unpacking feature!
* time_strptime() (change 49a7fdc0d40a)
* unpickle() of _ctypes (change ceb22b8f6d32)
I don't know well what we are supposed to do. I don't think that
changing the behaviour of PyObject_CallFunction() to remove the
special case is a good idea. It would be an obvious backward
incompatible change which can break applications.
I guess that the minimum is to document the special case?
Victor
Is there any remaining reason why weakref callbacks shouldn't be able to access the referenced object?
by Nathaniel Smith Jan. 15, 2017 Jan. 15, 2017
Hi all,
It's an old feature of the weakref API that you can define an
arbitrary callback to be invoked when the referenced object dies, and
that when this callback is invoked, it gets handed the weakref wrapper
object -- BUT, only after it's been cleared, so that the callback
can't access the originally referenced object. (I.e., this callback
will never raise: def callback(ref): assert ref() is None.)
AFAICT the original motivation for this seems was that if the weakref
callback could get at the object, then the weakref callback would
effectively be another finalizer like __del__, and finalizers and
reference cycles don't mix, so weakref callbacks can't be finalizers.
There's a long document from the 2.4 days about all the terrible
things that could happen if arbitrary code like callbacks could get
unfettered access to cyclic isolates at weakref cleanup time [1].
But that was 2.4. In the mean time, of course, PEP 442 fixed it so
that finalizers and weakrefs mix just fine. In fact, weakref callbacks
are now run *before* __del__ methods [2], so clearly it's now okay for
arbitrary code to touch the objects during that phase of the GC -- at
least in principle.
So what I'm wondering is, would anything terrible happen if we started
passing still-live weakrefs into weakref callbacks, and then clearing
them afterwards? (i.e. making step 1 of the PEP 442 cleanup order be
"run callbacks and then clear weakrefs", instead of the current "clear
weakrefs and then run callbacks"). I skimmed through the PEP 442
discussion, and AFAICT the rationale for keeping the old weakref
behavior was just that no-one could be bothered to mess with it [3].
[The motivation for my question is partly curiosity, and partly that
in the discussion about how to handle GC for async objects, it
occurred to me that it might be very nice if arbitrary classes that
needed access to the event loop during cleanup could do something like
def __init__(self, ...):
loop = asyncio.get_event_loop()
loop.gc_register(self)
# automatically called by the loop when I am GC'ed; async equivalent
of __del__
async def aclose(self):
...
Right now something *sort* of like this is possible but it requires a
much more cumbersome API, where every class would have to implement
logic to fetch a cleanup callback from the loop, store it, and then
call it from its __del__ method -- like how PEP 525 does it. Delaying
weakref clearing would make this simpler API possible.]
-n
[1] https://github.com/python/cpython/blob/master/Modules/gc_weakref.txt
[2] https://www.python.org/dev/peps/pep-0442/#id7
[3] https://mail.python.org/pipermail/python-dev/2013-May/126592.html
--
Nathaniel J. Smith -- https://vorpus.org
Hi all,
Well, we finally got that ucs2/ucs4 stuff all sorted out (yay), but I
just learned that there's another CPython build flag that also changes
the ABI: --with-fpectl
Specifically, it seems that if you build CPython with --with-fpectl,
and then use that CPython to build an extension module, and that
extension module uses PyFPE_{START,END}_PROTECT (like e.g. Cython
modules do), and you then try to import that extension module on a
CPython that *wasn't* built with --with-fpectl, then it will crash.
This bug report has more gory details:
https://github.com/numpy/numpy/issues/8415
The reverse is OK -- extensions built in a no-fpectl CPython can be
imported by both no-fpectl and yes-fpectl CPythons.
So one consequence is easy -- we need to make a note in the manylinux1
definition saying that you have to use a no-fpectl CPython build to
make manylinux1 wheels, because that's the only way to guarantee
compatibility. I just submitted a PR for this:
https://github.com/python/peps/pull/166
(Fortunately the manylinux1 docker images are already set up this way,
so in practice I think everyone is already doing this.)
But... in general this is kind of an unfortunate issue, and it's not
restricted to Linux. Should we do something? Some options:
Add another ABI flag -- e.g. cp35dmf vs. cp35dm? Though AFAICT the
offending macros are actually part of the allegedly stable ABI (!!),
so I guess this isn't really a solution. (I'm not 100% confident about
how to tell whether something is part of the stable ABI, but: Python.h
unconditionally imports pyfpe.h, and pyfpe.h doesn't have any
Py_LIMITED_API checks.)
Drop support for fpectl entirely in 3.7 on the grounds that it's not
worth the trouble? (The docs have said "don't use this" at the top
forever[1], and after clicking through every hit on github code search
for language = Python and string "turnon_sigfpe" [2], I found exactly
4 non-documentation usages [3], all of which are already broken in
no-fpectl builds.) We obviously can't do this in a point release
though, because there are lots of extant extension modules referencing
these symbols.
Or maybe make it so that even no-fpectl builds still export the
necessary symbols so that yes-fpectl extensions don't crash on import?
(This has the advantage that it can be done in a point release...)
Thoughts?
-n
[1] https://docs.python.org/2/library/fpectl.html
[2] https://github.com/search?l=Python&p=1&q=turnon_sigfpe&type=Code&utf8=%E2%9…
[3]
https://github.com/podhrmic/JSBSim/blob/36de9ac63c959cef5d7b2c56fb49c1a57fd…
https://github.com/tmbdev/iuprlab/blob/239918b5ec0f8deecbc7c2ec1283a837d11a…
https://github.com/wcs211/BEM-3D-Python/blob/874aaeffc3dac5f698f875478c3acc…
https://github.com/neobonzi/SoundPlagiarism/blob/7cff7f0145217bffb3a3cebd59…
--
Nathaniel J. Smith -- https://vorpus.org
Just a reminder: I'll be tagging 3.5.3 rc1 and 3.4.6 rc1 tomorrow, Jan 1
2017, sometime between 24 and 36 hours from now. Please work quickly if
there's anything you need to get in to either of those releases. I'm
hoping that, for once, there are literally no code changes between rc1
and final.
Best wishes for a happy new year,
//arry/
From the documentation:
https://docs.python.org/3/c-api/stable.html
In the C API documentation, API elements that are not part of the
limited API are marked as "Not part of the limited API."
But they don't.
I prepared a sample patch that adds the notes to Unicode Objects and
Codecs C API (http://bugs.python.org/issue29086). I'm going to add them
to all C API.
What are your though about formatting the note? Should it be before the
description, after the description, but before the "deprecated"
directive (as in the patch), or after the first paragraph of the
description? Should it be on the separate line or be appended at the end
of the previous paragraph, or starts the first paragraph (if before the
description)? May be introduce a special directive for it?
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