Mailman 3 Maio de 2015 - Python-Dev

PEP 448 review
by Guido van Rossum 29 de Março de 2023

29 de Março de 2023

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 de Maio de 2021

18 de Maio de 2021

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

Re: [Python-Dev] Status on PEP-431 Timezones
by Isaac Schwabacher 30 de Julho de 2015

30 de Julho de 2015

On 15-04-15, Akira Li <4kir4.1i(a)gmail.com> wrote: > Isaac Schwabacher <ischwabacher(a)wisc.edu> writes: > > > On 15-04-15, Akira Li <4kir4.1i(a)gmail.com> wrote: > >> Isaac Schwabacher <ischwabacher(a)wisc.edu> writes: > >> > ... > >> > > >> > I know that you can do datetime.now(tz), and you can do datetime(2013, > >> > 11, 3, 1, 30, tzinfo=zoneinfo('America/Chicago')), but not being able > >> > to add a time zone to an existing naive datetime is painful (and > >> > strptime doesn't even let you pass in a time zone). > >> > >> `.now(tz)` is correct. `datetime(..., tzinfo=tz)`) is wrong: if tz is a > >> pytz timezone then you may get a wrong tzinfo (LMT), you should use > >> `tz.localize(naive_dt, is_dst=False|True|None)` instead. > > > > The whole point of this thread is to finalize PEP 431, which fixes the > > problem for which `localize()` and `normalize()` are workarounds. When > > this is done, `datetime(..., tzinfo=tz)` will be correct. > > > > ijs > > The input time is ambiguous. Even if we assume PEP 431 is implemented in > some form, your code is still missing isdst parameter (or the > analog). PEP 431 won't fix it; it can't resolve the ambiguity by > itself. Notice is_dst paramter in the `tz.localize()` call (current > API). ...yeah, I forgot to throw that in there. It was supposed to be there all along. Nothing to see here, move along. > .now(tz) works even during end-of-DST transitions (current API) when the > local time is ambiguous. I know that. That's what I was complaining about-- I was trying to talk about how astimezone() was going to be inadequate even after the PEP was implemented because it couldn't turn naive datetimes into aware ones, and people were giving examples that started with aware datetimes generated by now(tz), which completely went around the point I was trying to make. But it looks like astimezone() is going to grow an is_dst parameter, and everything will be OK. ijs

28 142

Computed Goto dispatch for Python 2
by Parasa, Srinivas Vamsi 24 de Junho de 2015

24 de Junho de 2015

Hi All, This is Vamsi from Server Scripting Languages Optimization team at Intel Corporation. Would like to submit a request to enable the computed goto based dispatch in Python 2.x (which happens to be enabled by default in Python 3 given its performance benefits on a wide range of workloads). We talked about this patch with Guido and he encouraged us to submit a request on Python-dev (email conversation with Guido shown at the bottom of this email). Attached is the computed goto patch (along with instructions to run) for Python 2.7.10 (based on the patch submitted by Jeffrey Yasskin at http://bugs.python.org/issue4753). We built and tested this patch for Python 2.7.10 on a Linux machine (Ubuntu 14.04 LTS server, Intel Xeon - Haswell EP CPU with 18 cores, hyper-threading off, turbo off). Below is a summary of the performance we saw on the "grand unified python benchmarks" suite (available at https://hg.python.org/benchmarks/). We made 3 rigorous runs of the following benchmarks. In each rigorous run, a benchmark is run 100 times with and without the computed goto patch. Below we show the average performance boost for the 3 rigorous runs. Python 2.7.10 (original) vs Computed Goto performance Benchmark Delta (rigorous run #1) % Delta (rigorous run #2) % Delta (rigorous run #3) % Avg. Delta % iterative_count 24.48 24.36 23.78 24.2 unpack_sequence 19.06 18.47 19.48 19.0 slowspitfire 14.36 13.41 16.65 14.8 threaded_count 15.85 13.43 13.93 14.4 pystone 10.68 11.67 11.08 11.1 nbody 10.25 8.93 9.28 9.5 go 7.96 8.76 7.69 8.1 pybench 6.3 6.8 7.2 6.8 spectral_norm 5.49 9.37 4.62 6.5 float 6.09 6.2 6.96 6.4 richards 6.19 6.41 6.42 6.3 slowunpickle 6.37 8.78 3.55 6.2 json_dump_v2 1.96 12.53 3.57 6.0 call_simple 6.37 5.91 3.92 5.4 chaos 4.57 5.34 3.85 4.6 call_method_slots 2.63 3.27 7.71 4.5 telco 5.18 1.83 6.47 4.5 simple_logging 3.48 1.57 7.4 4.2 call_method 2.61 5.4 3.88 4.0 chameleon 2.03 6.26 3.2 3.8 fannkuch 3.89 3.19 4.39 3.8 silent_logging 4.33 3.07 3.39 3.6 slowpickle 5.72 -1.12 6.06 3.6 2to3 2.99 3.6 3.45 3.3 etree_iterparse 3.41 2.51 3 3.0 regex_compile 3.44 2.48 2.84 2.9 mako_v2 2.14 1.29 5.22 2.9 meteor_contest 2.01 2.2 3.88 2.7 django 6.68 -1.23 2.56 2.7 formatted_logging 1.97 5.82 -0.11 2.6 hexiom2 2.83 2.1 2.55 2.5 django_v2 1.93 2.53 2.92 2.5 etree_generate 2.38 2.13 2.51 2.3 mako -0.3 9.66 -3.11 2.1 bzr_startup 0.35 1.97 3 1.8 etree_process 1.84 1.01 1.9 1.6 spambayes 1.76 0.76 0.48 1.0 regex_v8 1.96 -0.66 1.63 1.0 html5lib 0.83 0.72 0.97 0.8 normal_startup 1.41 0.39 0.24 0.7 startup_nosite 1.2 0.41 0.42 0.7 etree_parse 0.24 0.9 0.79 0.6 json_load 1.38 0.56 -0.25 0.6 pidigits 0.45 0.33 0.28 0.4 hg_startup 0.32 2.07 -1.41 0.3 rietveld 0.05 0.91 -0.43 0.2 tornado_http 2.34 -0.92 -1.27 0.1 call_method_unknown 0.72 1.26 -1.85 0.0 raytrace -0.35 -0.75 0.94 -0.1 regex_effbot 1.97 -1.18 -2.57 -0.6 fastunpickle -1.65 0.5 -0.88 -0.7 nqueens -2.24 -1.53 -0.81 -1.5 fastpickle -0.74 1.98 -6.26 -1.7 Thanks, Vamsi ------------------------------------------------------------------------------------------------------------------------------------------------------------ From: gvanrossum(a)gmail.com<mailto:gvanrossum@gmail.com> [mailto:gvanrossum@gmail.com] On Behalf Of Guido van Rossum Sent: Tuesday, May 19, 2015 1:59 PM To: Cohn, Robert S Cc: R. David Murray (r.david.murray(a)murrayandwalker.com<mailto:r.david.murray@murrayandwalker.com>) Subject: Re: meeting at PyCon Hi Robert and David, I just skimmed that thread. There were a lot of noises about backporting it to 2.7 but the final message on the topic, by Antoine, claimed it was too late for 2.7. However, that was before we had announced the EOL extension of 2.7 till 2020, and perhaps we were also in denial about 3.x uptake vs. 2.x. So I think it's definitively worth bringing this up. I would start with a post on python-dev linking to the source code for your patch, and adding a message to the original tracker issue too (without reopening it though -- just so the people who were on the bug will be pinged about it). Because of backwards compatibility with previous 2.7.x releases, it's very important that the patch not break anything -- in particular this means you can't add opcodes or change their specification. You will also undoubtedly be asked to test this on a variety of platforms 32-bit and 64-bit that people care about. But I'm sure you're expecting all that. :-) You might also check with Benjamin Peterson, who is the 2.7 release manager. I think he just announced 2.7.10, so it's too late for that, but I assume we'll keep doing 2.7.x releases until 2020. Good luck, --Guido PS. I am assuming you are contributing this under a PSF-accepted license, e.g. Apache 2.0, otherwise it's an automatic nogo. On Tue, May 19, 2015 at 9:33 AM, Cohn, Robert S <robert.s.cohn(a)intel.com<mailto:robert.s.cohn@intel.com>> wrote: Hi Guido, When we met for lunch at pycon, I asked if performance related patches would be ok for python 2.x. My understanding is that you thought it was possible if it did not create a maintainability problem. We have an example now, a 2.7 patch for computed goto based on the implementation in python 3 http://bugs.python.org/issue4753 It increases performance by up to 10% across a wide range of workloads. As I mentioned at lunch, we hired David Murray's company, and he is guiding intel through the development process for cpython. David and I thought it would be good to run this by you before raising the issue on python-dev. Do you have a specific concern about this patch or a more general concern about performance patches to 2.7? Thanks. Robert --------

45 118

Obtaining stack-frames from co-routine objects
by Ben Leslie 14 de Junho de 2015

14 de Junho de 2015

Hi all, Apologies in advance; I'm not a regular, and this may have been handled already (but I couldn't find it when searching). I've been using the new async/await functionality (congrats again to Yury on getting that through!), and I'd like to get a stack trace between the place at which blocking occurs and the outer co-routine. For example, consider this code: """ async def a(): await b() async def b(): await switch() @types.coroutine def switch(): yield coro_a = a() coro_a.send(None) """ At this point I'd really like to be able to somehow get a stack trace similar to: test.py:2 test.py:4 test.py:9 Using the gi_frame attribute of coro_a, I can get the line number of the outer frame (e.g.: line 2), but from there there is no way to descend the stack to reach the actual yield point. I thought that perhaps the switch() co-routine could yield the frame object returned from inspect.currentframe(), however once that function yields that frame object has f_back changed to None. A hypothetical approach would be to work the way down form the outer-frame, but that requires getting access to the co-routine object that the outer-frame is currently await-ing. Some hypothetical code could be: """ def show(coro): print("{}:{}".format(coro.gi_frame.f_code.co_filename, coro.gi_frame.f_lineno)) if dis.opname[coro.gi_code.co_code[coro.gi_frame.f_lasti + 1]] == 'YIELD_FROM': show(coro.gi_frame.f_stack[0]) """ This relies on the fact that an await-ing co-routine will be executing a YIELD_FROM instruction. The above code uses a completely hypothetical 'f_stack' property of frame objects to pull the co-routine object which a co-routine is currently await-ing from the stack. I've implemented a proof-of-concept f_stack property in the frameobject.c just to test out the above code, and it seems to work. With all that, some questions: 1) Does anyone else see value in trying to get the stack-trace down to the actual yield point? 2) Is there a different way of doing it that doesn't require changes to Python internals? 3) Assuming no to #2 is there a better way of getting the information compared to the pretty hacking byte-code/stack inspection? Thanks, Ben

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Tracker reviews look like spam
by Terry Reedy 10 de Junho de 2015

10 de Junho de 2015

Gmail dumps patch review email in my junk box. The problem seems to be the spoofed From: header. Received: from psf.upfronthosting.co.za ([2a01:4f8:131:2480::3]) by mx.google.com with ESMTP id m1si26039166wjy.52.2015.05.12.00.20.38 for <tjreedy(a)udel.edu>; Tue, 12 May 2015 00:20:38 -0700 (PDT) Received-SPF: softfail (google.com: domain of transitioning storchaka(a)gmail.com does not designate 2a01:4f8:131:2480::3 as permitted sender) client-ip=2a01:4f8:131:2480::3; Tracker reviews are the only false positives in my junk list. Otherwise, I might stop reviewing. Verizon does not even deliver mail that fails its junk test, so I would not be surprised if there are people who simply do not get emailed reviews. Tracker posts are sent from Person Name <report(a)bugs.python.org> Perhaps reviews could come 'from' Person Name <review(a)bugs.python.org> Even direct tracker posts just get a neutral score. Received-SPF: neutral (google.com: 2a01:4f8:131:2480::3 is neither permitted nor denied by best guess record for domain of roundup-admin(a)psf.upfronthosting.co.za) client-ip=2a01:4f8:131:2480::3; SPF is Sender Policy Framework https://en.wikipedia.org/wiki/Sender_Policy_Framework Checkins mail, for instance, gets an SPF 'pass' because python.org designates mail.python.org as a permitted sender. -- Terry Jan Reedy

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Unable to build regex module against Python 3.5 32-bit
by MRAB 5 de Junho de 2015

5 de Junho de 2015

As the subject says, I've been unable to build the regex module against Python 3.5b1 for 32-bit. MingGW says: skipping incompatible .../libpython35.a when searching for -lpython35 It builds without a problem against Python 3.5 for 64-bit. Any ideas? Should I just wait until beta 2?

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RM for 3.6?
by Serhiy Storchaka 2 de Junho de 2015

2 de Junho de 2015

Isn't it a time to assign release manager for 3.6-3.7?

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Python 3 migration status update across some key subcommunities (was Re: 2.7 is here until 2020, please don't call it a waste.)
by Nick Coghlan 1 de Junho de 2015

1 de Junho de 2015

On 31 May 2015 at 19:07, Ludovic Gasc <gmludo(a)gmail.com> wrote: > About Python 3 migration, I think that one of our best control stick is > newcomers, and by extension, Python trainers/teachers. > If newcomers learn first Python 3, when they will start to work > professionally, they should help to rationalize the Python 3 migration > inside existing dev teams, especially because they don't have an interest > conflict based on the fact that they haven't written plenty of code with > Python 2. > 2020 is around the corner, 5 years shouldn't be enough to change the > community mind, I don't know. The education community started switching a while back - if you watch Carrie-Anne Philbin's PyCon UK 2014 keynote, one of her requests for the broader Python community was for everyone else to just catch up already in order to reduce student's confusion (she phrased it more politely than that, though). Educators need to tweak examples and exercises to account for a version switch, but that's substantially easier than migrating hundreds of thousands or even millions of lines of production code. And yes, if you learn Python 3 first, subsequently encountering Python 2's quirks and cruft is likely to encourage folks that know both versions of the language to start advocating for a version upgrade :) After accounting for the "Wow, the existing Python 2 install base is even larger than we realised" factour, the migration is actually in a pretty good place overall these days. The "enterprise" crowd really are likely to be the only ones that might need the full remaining 5 years of migration time (and they may potentially have even more time, if they're relying on a commercial redistributor). Web frameworks have allowed Python 3 development for a while now, and with Django switching their tutorial to Python 3 by default, Django downloads via pip show one of the highest proportions of Python 3 adoption on PyPI. www.python.org itself is now a production Python 3 Django web service, and the next generation of pypi.python.org will be a Pyramid application that's also running on Python 3. The dedicated async/await syntax in 3.5 represents a decent carrot to encourage migration for anyone currently using yield (or yield from) based coroutines, since the distinct syntax not only allows for easier local reasoning about whether something is an iterator or a coroutine, it also provides a much improved user experience for asynchronous iterators and context managers (including finally handling the "asynchronous database transaction as a context manager" case, which previous versions of Python couldn't really do at all). The matrix multiplication operator is similarly a major improvement for the science and data analysis part of the Python community. In terms of reducing *barriers* to adoption, after inviting them to speak at the 2014 language summit, we spent a fair bit of time with the Twisted and Mercurial folks over the past year or so working through "What's still missing from Python 3 for your use cases?", as Python 3.4 was still missing some features for binary data manipulation where we'd been a bit too ruthless in pruning back the binary side of things when deciding what counted as text-only features, and what was applicable to binary data as well. So 3.5 brings back binary interpolation, adds a hex() method to bytes, and adds binary data support directly to a couple of standard library modules (tempfile, difflib). If I understand the situation correctly, the work Guido et al have been doing on PEP 484 and type hinting standardisation is also aimed at reducing barriers to Python 3 adoption, by making it possible to develop better migration tools that are more semantically aware than the existing syntax focused tools. The type hinting actually acts as a carrot as well, since it's a feature that mainly shows its value when attempting to scale a *team* to larger sizes (as it lets you delegate more of the code review process to an automated tool, letting the human reviewers spend more time focusing on higher level semantic concerns). Finally, both Debian/Ubuntu and Fedora are well advanced in their efforts to replace Python 2 with Python 3 in their respective default images (but keeping Py2 available in their package repos). That work is close to finished now (myself, Slavek Kabrda, Barry Warsaw, and Matthias Klose had some good opportunities to discuss that at PyCon), although there are still some significant rough edges to figure out (such as coming up with a coherent cross-platform story for what we're going to do with the Python symlink), as well as a few more key projects to either migrate entirely, or at least finish porting to the source compatible subset of Python 2 & 3 (e.g. Samba). Cheers, Nick. -- Nick Coghlan | ncoghlan(a)gmail.com | Brisbane, Australia

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Can someone configure the buildbots to build the 3.5 branch?
by Larry Hastings 1 de Junho de 2015

1 de Junho de 2015

The buildbots currently live in a state of denial about the 3.5 branch. Could someone whisper tenderly in their collective shell-like ears so that they start building 3.5, in addition to 3.4 and trunk? Thank you, //arry/

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