Mailman 3 February 2018 - Python-Dev

PEP 448 review
by Guido van Rossum 29 Mar '23

29 Mar '23

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

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

congrats on 3.5! Alas, windows 7 users are having problems installing it
by Laura Creighton 15 Sep '19

15 Sep '19

webmaster has already heard from 4 people who cannot install it. I sent them to the bug tracker or to python-list but they seem not to have gone either place. Is there some guide I should be sending them to, 'how to debug installation problems'? Laura

5 6

Python startup time
by Victor Stinner 10 Oct '18

10 Oct '18

Hi, On Twitter, Raymond Hettinger wrote: "The decision making process on Python-dev is an anti-pattern, governed by anecdotal data and ambiguity over what problem is solved." https://twitter.com/raymondh/status/887069454693158912 About "anecdotal data", I would like to discuss the Python startup time. == Python 3.7 compared to 2.7 == First of all, on speed.python.org, we have: * Python 2.7: 6.4 ms with site, 3.0 ms without site (-S) * master (3.7): 14.5 ms with site, 8.4 ms without site (-S) Python 3.7 startup time is 2.3x slower with site (default mode), or 2.8x slower without site (-S command line option). (I will skip Python 3.4, 3.5 and 3.6 which are much worse than Python 3.7...) So if an user complained about Python 2.7 startup time: be prepared for a 2x - 3x more angry user when "forced" to upgrade to Python 3! == Mercurial vs Git, Python vs C, startup time == Startup time matters a lot for Mercurial since Mercurial is compared to Git. Git and Mercurial have similar features, but Git is written in C whereas Mercurial is written in Python. Quick benchmark on the speed.python.org server: * hg version: 44.6 ms +- 0.2 ms * git --version: 974 us +- 7 us Mercurial startup time is already 45.8x slower than Git whereas tested Mercurial runs on Python 2.7.12. Now try to sell Python 3 to Mercurial developers, with a startup time 2x - 3x slower... I tested Mecurial 3.7.3 and Git 2.7.4 on Ubuntu 16.04.1 using "python3 -m perf command -- ...". == CPython core developers don't care? no, they do care == Christian Heimes, Naoki INADA, Serhiy Storchaka, Yury Selivanov, me (Victor Stinner) and other core developers made multiple changes last years to reduce the number of imports at startup, optimize impotlib, etc. IHMO all these core developers are well aware of the competition of programming languages, and honesty Python startup time isn't "good". So let's compare it to other programming languages similar to Python. == PHP, Ruby, Perl == I measured the startup time of other programming languages which are similar to Python, still on the speed.python.org server using "python3 -m perf command -- ...": * perl -e ' ': 1.18 ms +- 0.01 ms * php -r ' ': 8.57 ms +- 0.05 ms * ruby -e ' ': 32.8 ms +- 0.1 ms Wow, Perl is quite good! PHP seems as good as Python 2 (but Python 3 is worse). Ruby startup time seems less optimized than other languages. Tested versions: * perl 5, version 22, subversion 1 (v5.22.1) * PHP 7.0.18-0ubuntu0.16.04.1 (cli) ( NTS ) * ruby 2.3.1p112 (2016-04-26) [x86_64-linux-gnu] == Quick Google search == I also searched for "python startup time" and "python slow startup time" on Google and found many articles. Some examples: "Reducing the Python startup time" http://www.draketo.de/book/export/html/498 => "The python startup time always nagged me (17-30ms) and I just searched again for a way to reduce it, when I found this: The Python-Launcher caches GTK imports and forks new processes to reduce the startup time of python GUI programs." https://nelsonslog.wordpress.com/2013/04/08/python-startup-time/ => "Wow, Python startup time is worse than I thought." "How to speed up python starting up and/or reduce file search while loading libraries?" https://stackoverflow.com/questions/15474160/how-to-speed-up-python-startin… => "The first time I log to the system and start one command it takes 6 seconds just to show a few line of help. If I immediately issue the same command again it takes 0.1s. After a couple of minutes it gets back to 6s. (proof of short-lived cache)" "How does one optimise the startup of a Python script/program?" https://www.quora.com/How-does-one-optimise-the-startup-of-a-Python-script-… => "I wrote a Python program that would be used very often (imagine 'cd' or 'ls') for very short runtimes, how would I make it start up as fast as possible?" "Python Interpreter Startup time" https://bytes.com/topic/python/answers/34469-pyhton-interpreter-startup-time "Python is very slow to start on Windows 7" https://stackoverflow.com/questions/29997274/python-is-very-slow-to-start-o… => "Python takes 17 times longer to load on my Windows 7 machine than Ubuntu 14.04 running on a VM" => "returns in 0.614s on Windows and 0.036s on Linux" "How to make a fast command line tool in Python" (old article Python 2.5.2) https://files.bemusement.org/talks/OSDC2008-FastPython/ => "(...) some techniques Bazaar uses to start quickly, such as lazy imports." -- So please continue efforts for make Python startup even faster to beat all other programming languages, and finally convince Mercurial to upgrade ;-) Victor

42 96

Clarifying Cygwin support in CPython
by Erik Bray 31 Jul '18

31 Jul '18

Hi folks, As some people here know I've been working off and on for a while to improve CPython's support of Cygwin. I'm motivated in part by a need to have software working on Python 3.x on Cygwin for the foreseeable future, preferably with minimal graft. (As an incidental side-effect Python's test suite--especially of system-level functionality--serves as an interesting test suite for Cygwin itself too.) This is partly what motivated PEP 539 [1], although that PEP had the advantage of benefiting other POSIX-compatible platforms as well (and in fact was fixing an aspect of CPython that made it unfriendly to supporting other platforms). As far as I can tell, the first commit to Python to add any kind of support for Cygwin was made by Guido (committing a contributed patch) back in 1999 [2]. Since then, bits and pieces have been added for Cygwin's benefit over time, with varying degrees of impact in terms of #ifdefs and the like (for the most part Cygwin does not require *much* in the way of special support, but it does have some differences from a "normal" POSIX-compliant platform, such as the possibility for case-insensitive filesystems and executables that end in .exe). I don't know whether it's ever been "officially supported" but someone with a longer memory of the project can comment on that. I'm not sure if it was discussed at all or not in the context of PEP 11. I have personally put in a fair amount of effort already in either fixing issues on Cygwin (many of these issues also impact MinGW), or more often than not fixing issues in the CPython test suite on Cygwin--these are mostly tests that are broken due to invalid assumptions about the platform (for example, that there is always a "root" user with uid=0; this is not the case on Cygwin). In other cases some tests need to be skipped or worked around due to platform-specific bugs, and Cygwin is hardly the only case of this in the test suite. I also have an experimental AppVeyor configuration for running the tests on Cygwin [3], as well as an experimental buildbot (not available on the internet, but working). These currently rely on a custom branch that includes fixes needed for the test suite to run to completion without crashing or hanging (e.g. https://bugs.python.org/issue31885). It would be nice to add this as an official buildbot, but I'm not sure if it makes sense to do that until it's "green", or at least not crashing. I have several other patches to the tests toward this goal, and am currently down to ~22 tests failing. Before I do any more work on this, however, it would be best to once and for all clarify the support for Cygwin in CPython, as it has never been "officially supported" nor unsupported--this way we can avoid having this discussion every time a patch related to Cygwin comes up. I could provide some arguments for why I believe Cygwin should supported, but before this gets too long I'd just like to float the idea of having the discussion in the first place. It's also not exactly clear to me how to meet the standards in PEP 11 for supporting a platform--in particular it's not clear when a buildbot is considered "stable", or how to achieve that without getting necessary fixes merged into the main branch in the first place. Thanks, Erik [1] https://www.python.org/dev/peps/pep-0539/ [2] https://github.com/python/cpython/commit/717d1fdf2acbef5e6b47d9b4dcf48ef182… [3] https://ci.appveyor.com/project/embray/cpython

3 6

Backward incompatible change about docstring AST
by INADA Naoki 07 Mar '18

07 Mar '18

Hi, all. There is design discussion which is deferred blocker of 3.7. https://bugs.python.org/issue32911 ## Background An year ago, I moved docstring in AST from statements list to field of module, class and functions. https://bugs.python.org/issue29463 Without this change, AST-level constant folding was complicated because "foo" can be docstring but "fo" + "o" can't be docstring. This simplified some other edge cases. For example, future import must be on top of the module, but docstring can be before it. Docstring is very special than other expressions/statement. Of course, this change was backward incompatible. Tools reading/writing docstring via AST will be broken by this change. For example, it broke PyFlakes, and PyFlakes solved it already. https://github.com/PyCQA/pyflakes/pull/273 Since AST doesn't guarantee backward compatibility, we can change AST if it's reasonable. Last week, Mark Shannon reported issue about this backward incompatibility. As he said, this change losted lineno and column of docstring from AST. https://bugs.python.org/issue32911#msg312567 ## Design discussion And as he said, there are three options: https://bugs.python.org/issue32911#msg312625 > It seems to be that there are three reasonable choices: > 1. Revert to 3.6 behaviour, with the addition of `docstring` attribute. > 2. Change the docstring attribute to an AST node, possibly by modifying the grammar. > 3. Do nothing. 1 is backward compatible about reading docstring. But when writing, it's not DRY or SSOT. There are two source of docstring. For example: `ast.Module([ast.Str("spam")], docstring="egg")` 2 is considerable. I tried to implement this idea by adding `DocString` statement AST. https://github.com/python/cpython/pull/5927/files While it seems large change, most changes are reverting the AST changes. So it's more closer to 3.6 codebase. (especially, test_ast is very close to 3.6) In this PR, `ast.Module([ast.Str("spam")])` doesn't have docstring for simplicity. So it's backward incompatible for both of reading and writing docstring too. But it keeps lineno and column of docstring in AST. 3 is most conservative because 3.7b2 was cut now and there are some tools supporting 3.7 already. I prefer 2 or 3. If we took 3, I don't want to do 2 in 3.8. One backward incompatible change is better than two. Any thoughts? -- INADA Naoki <songofacandy(a)gmail.com>

6 7

Should the dataclass frozen property apply to subclasses?
by Raymond Hettinger 28 Feb '18

28 Feb '18

When working on the docs for dataclasses, something unexpected came up. If a dataclass is specified to be frozen, that characteristic is inherited by subclasses which prevents them from assigning additional attributes: >>> @dataclass(frozen=True) class D: x: int = 10 >>> class S(D): pass >>> s = S() >>> s.cached = True Traceback (most recent call last): File "<pyshell#49>", line 1, in <module> s.cached = True File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/dataclasses.py", line 448, in _frozen_setattr raise FrozenInstanceError(f'cannot assign to field {name!r}') dataclasses.FrozenInstanceError: cannot assign to field 'cached' Other immutable classes in Python don't behave the same way: >>> class T(tuple): pass >>> t = T([10, 20, 30]) >>> t.cached = True >>> class F(frozenset): pass >>> f = F([10, 20, 30]) >>> f.cached = True >>> class B(bytes): pass >>> b = B() >>> b.cached = True Raymond

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PEP 467 (Minor API improvements for binary sequences) - any thoughts?
by Elias Zamaria 28 Feb '18

28 Feb '18

This is about some minor changes to the bytes, bytearray, and memoryview classes. Here is the PEP: https://www.python.org/dev/peps/pep-0467/ The page in the bug tracker can be seen at https://bugs.python.org/issue27923 and the pull request can be seen at https://github.com/python/cpython/pull/3237. I am waiting for this to be merged, or approved, or whatever is the next step. Someone on the bug tracker mentioned restarting the discussion on the mailing list, so that is what I'm trying to do here. Does anyone have any thoughts?

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[RELEASE] Python 3.7.0b2 is now available for testing
by Ned Deily 27 Feb '18

27 Feb '18

On behalf of the Python development community and the Python 3.7 release team, I'm happy to announce the availability of Python 3.7.0b2. b2 is the second of four planned beta releases of Python 3.7, the next major release of Python, and marks the end of the feature development phase for 3.7. You can find Python 3.7.0b2 here: https://www.python.org/downloads/release/python-370b2/ Among the new major new features in Python 3.7 are: * PEP 538, Coercing the legacy C locale to a UTF-8 based locale * PEP 539, A New C-API for Thread-Local Storage in CPython * PEP 540, UTF-8 mode * PEP 552, Deterministic pyc * PEP 553, Built-in breakpoint() * PEP 557, Data Classes * PEP 560, Core support for typing module and generic types * PEP 562, Module __getattr__ and __dir__ * PEP 563, Postponed Evaluation of Annotations * PEP 564, Time functions with nanosecond resolution * PEP 565, Show DeprecationWarning in __main__ * PEP 567, Context Variables Please see "What’s New In Python 3.7" for more information. Additional documentation for these features and for other changes will be provided during the beta phase. https://docs.python.org/3.7/whatsnew/3.7.html Beta releases are intended to give you the opportunity to test new features and bug fixes and to prepare their projects to support the new feature release. We strongly encourage you to test your projects with 3.7 during the beta phase and report issues found to https://bugs.python.org as soon as possible. While the release is feature complete entering the beta phase, it is possible that features may be modified or, in rare cases, deleted up until the start of the release candidate phase (2018-05-21). Our goal is have no ABI changes after beta 3 and no code changes after rc1. To achieve that, it will be extremely important to get as much exposure for 3.7 as possible during the beta phase. Attention macOS users: as of b1, there is a new installer variant for macOS 10.9+ that includes a built-in version of Tcl/Tk 8.6. This variant is expected to become the default version when 3.7.0 releases. Check it out! We welcome your feedback. Please keep in mind that this is a preview release and its use is not recommended for production environments. The next planned release of Python 3.7 will be 3.7.0b3, currently scheduled for 2018-03-26. More information about the release schedule can be found here: https://www.python.org/dev/peps/pep-0537/ -- Ned Deily nad(a)python.org -- []

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The `for y in [x]` idiom in comprehensions
by Serhiy Storchaka 27 Feb '18

27 Feb '18

Yet one discussion about reusing common subexpressions in comprehensions took place last week on the Python-ideas maillist (see topic "Temporary variables in comprehensions" [1]). The problem is that in comprehension like `[f(x) + g(f(x)) for x in range(10)]` the subexpression `f(x)` is evaluated twice. In normal loop you can introduce a temporary variable for `f(x)`. The OP wanted to add a special syntax for introducing temporary variables in comprehensions. This idea already was discussed multiple times in the past. There are several ways of resolving this problem with existing syntax. 1. Inner generator expression: result = [y + g(y) for y in (f(x) for x in range(10))] 2. The same, but with extracting the inner generator expression as a variable: f_samples = (f(x) for x in range(10)) result = [y+g(y) for y in f_samples] 3. Extracting the expression with repeated subexpressions as a function with local variables: def func(x): y = f(x) return y + g(y) result = [func(x) for x in range(10)] 4. Implementing the whole comprehension as a generator function: def gen(): for x in range(10): y = f(x) yield y + g(y) result = list(gen()) 5. Using a normal loop instead of a comprehension: result = [] for x in range(10): y = f(x) result.append(y + g(y)) And maybe there are other ways. Stephan Houben proposed an idiom which looks similar to new hypothetic syntax: result = [y + g(y) for x in range(10) for y in [f(x)]] `for y in [expr]` in a comprehension means just assigning expr to y. I never seen this idiom before, but it can be a good replacement for a hypothetic syntax for assignment in comprehensions. It changes the original comprehension less than other approaches, just adds yet one element in a sequence of for-s and if-s. I think that after using it more widely it will become pretty idiomatic. I have created a patch that optimizes this idiom, making it as fast as a normal assignment. [2] Yury suggested to ask Guido on the mailing list if he agrees that this language patten is worth optimizing/promoting. [1] https://mail.python.org/pipermail/python-ideas/2018-February/048971.html [2] https://bugs.python.org/issue32856

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