Mailman 3 March 2015 - Python-Dev

PEP 1, PEP Purpose and Guidelines
by barry＠zope.com 18 May '21

18 May '21

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:

8 14

Surely "nullable" is a reasonable name?
by Larry Hastings 25 Apr '15

25 Apr '15

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/

13 29

PEP 448 review
by Guido van Rossum 07 Apr '15

07 Apr '15

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)

7 17

OpenBSD buildbot has many failures
by Victor Stinner 02 Apr '15

02 Apr '15

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

6 8

http.client: Determining Content-Length
by Demian Brecht 01 Apr '15

01 Apr '15

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

2 1

MemoryError and other bugs on AMD64 OpenIndiana 3.x
by Victor Stinner 01 Apr '15

01 Apr '15

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

2 2

importante!!
by Alan Armour 31 Mar '15

31 Mar '15

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

3 2

RFC: PEP 490 - Chain exceptions at C level
by Victor Stinner 30 Mar '15

30 Mar '15

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:

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[RELEASED] Python 3.5.0a3 is now available
by Larry Hastings 30 Mar '15

30 Mar '15

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/

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Re: [Python-Dev] cpython: Issue #23752: When built from an existing file descriptor, io.FileIO() now only
by Serhiy Storchaka 30 Mar '15

30 Mar '15

On 30.03.15 04:22, victor.stinner wrote: > https://hg.python.org/cpython/rev/bc2a22eaa0af > changeset: 95269:bc2a22eaa0af > user: Victor Stinner <victor.stinner(a)gmail.com> > date: Mon Mar 30 03:21:06 2015 +0200 > summary: > Issue #23752: When built from an existing file descriptor, io.FileIO() now only > calls fstat() once. Before fstat() was called twice, which was not necessary. > > files: > Misc/NEWS | 26 ++++++++++++++++++++++++++ > Modules/_io/fileio.c | 24 ------------------------ > 2 files changed, 26 insertions(+), 24 deletions(-) > > > diff --git a/Misc/NEWS b/Misc/NEWS > --- a/Misc/NEWS > +++ b/Misc/NEWS > @@ -2,6 +2,32 @@ > Python News > +++++++++++ > > +What's New in Python 3.5.0 alpha 4? > +=================================== Return time machine back Victor. Current version is 3.5.0a2+.

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Python-Dev March 2015