Mailman 3 October 2016 - 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

OpenIndiana and Solaris support
by Victor Stinner 27 Mar '17

27 Mar '17

Hi, My question is simple: do we officially support Solaris and/or OpenIndiana? Jesus Cea runs an OpenIndiana buildbot slave: http://buildbot.python.org/all/buildslaves/cea-indiana-x86 "Open Indiana 32 bits" The platform module of Python says "Solaris-2.11", I don't know the exact OpenIndiana version. A lot of unit tests fail on this buildbot with MemoryError. I guess that it's related to Solaris which doesn't allow overcommit (allocating more memory than available memory on the system), or more simply because the slave has not enough memory. There is now an issue which seems specific to OpenIndiana: http://bugs.python.org/issue27847 It might impact Solaris as well, but the Solaris buildbot is offline since "684 builds". Five years ago, I reported a bug because the curses module of Python 3 doesn't build on Solaris nor OpenIndiana anymore. It seems like the bug was not fixed, and the issue is still open: http://bugs.python.org/issue13552 So my question is if we officially support Solaris and/or OpenIndiana. If yes, how can we fix issues when we only have buildbot slave which has memory errors, and no SSH access to this server? Solaris doesn't seem to be officially supported in Python, so I suggest to drop the OpenIndiana buildbot (which is failing since at least 2 years) and close all Solaris issues as "WONTFIX". Victor

6 12

Default formatting
by Serhiy Storchaka 22 Jan '17

22 Jan '17

Classes that doesn't define the __format__ method for custom PEP 3101 formatting inherits it from parents. Originally the object.__format__ method was designed as [1]: def __format__(self, format_spec): return format(str(self), format_spec) An instance is converted to string and resulting string is formatted according to format specifier. Later this design was reconsidered [2], and now object.__format__ is equivalent to: def __format__(self, format_spec): assert format_spec == '' return format(str(self), '') Non-empty format specifier is rejected. But why call format() on resulting string? Why not return resulting string as is? object.__format__ could be simpler (not just implementation, but for understanding): def __format__(self, format_spec): assert format_spec == '' return str(self) This can change the behaviour in corner case. str(self) can return not exact string, but string subclass with overloaded __format__. But I think we can ignore such subtle difference. [1] https://www.python.org/dev/peps/pep-3101/ [2] http://bugs.python.org/issue7994

4 6

Is there any remaining reason why weakref callbacks shouldn't be able to access the referenced object?
by Nathaniel Smith 15 Jan '17

15 Jan '17

Hi all, It's an old feature of the weakref API that you can define an arbitrary callback to be invoked when the referenced object dies, and that when this callback is invoked, it gets handed the weakref wrapper object -- BUT, only after it's been cleared, so that the callback can't access the originally referenced object. (I.e., this callback will never raise: def callback(ref): assert ref() is None.) AFAICT the original motivation for this seems was that if the weakref callback could get at the object, then the weakref callback would effectively be another finalizer like __del__, and finalizers and reference cycles don't mix, so weakref callbacks can't be finalizers. There's a long document from the 2.4 days about all the terrible things that could happen if arbitrary code like callbacks could get unfettered access to cyclic isolates at weakref cleanup time [1]. But that was 2.4. In the mean time, of course, PEP 442 fixed it so that finalizers and weakrefs mix just fine. In fact, weakref callbacks are now run *before* __del__ methods [2], so clearly it's now okay for arbitrary code to touch the objects during that phase of the GC -- at least in principle. So what I'm wondering is, would anything terrible happen if we started passing still-live weakrefs into weakref callbacks, and then clearing them afterwards? (i.e. making step 1 of the PEP 442 cleanup order be "run callbacks and then clear weakrefs", instead of the current "clear weakrefs and then run callbacks"). I skimmed through the PEP 442 discussion, and AFAICT the rationale for keeping the old weakref behavior was just that no-one could be bothered to mess with it [3]. [The motivation for my question is partly curiosity, and partly that in the discussion about how to handle GC for async objects, it occurred to me that it might be very nice if arbitrary classes that needed access to the event loop during cleanup could do something like def __init__(self, ...): loop = asyncio.get_event_loop() loop.gc_register(self) # automatically called by the loop when I am GC'ed; async equivalent of __del__ async def aclose(self): ... Right now something *sort* of like this is possible but it requires a much more cumbersome API, where every class would have to implement logic to fetch a cleanup callback from the loop, store it, and then call it from its __del__ method -- like how PEP 525 does it. Delaying weakref clearing would make this simpler API possible.] -n [1] https://github.com/python/cpython/blob/master/Modules/gc_weakref.txt [2] https://www.python.org/dev/peps/pep-0442/#id7 [3] https://mail.python.org/pipermail/python-dev/2013-May/126592.html -- Nathaniel J. Smith -- https://vorpus.org

3 5

Benchmarking Python and micro-optimizations
by Victor Stinner 01 Nov '16

01 Nov '16

Hi, Last months, I worked a lot on benchmarks. I ran benchmarks, analyzed results in depth (up to the hardware and kernel drivers!), I wrote new tools and enhanced existing tools. * I wrote a new perf module which runs benchmarks in a reliable way and contains a LOT of features: collect metadata, JSON file format, commands to compare, render an histogram, etc. * I rewrote the Python benchmark suite: the old benchmarks Mercurial repository moved to a new performance GitHub project which uses my perf module and contains more benchmarks. * I also made minor enhancements to timeit in Python 3.7 -- some dev don't want major changes to not "break the backward compatibility". For timeit, I suggest to use my perf tool which includes a reliable timeit command and has much more features like --duplicate (repeat the statements to reduce the cost of the outer loop) and --compare-to (compare two versions of Python), but also all builtin perf features (JSON output, statistics, histogram, etc.). I added benchmarks from PyPy and Pyston benchmark suites to performance: performance 0.3.1 contains 51 benchmark scripts which run a total of 121 benchmarks. Example of tested Python modules: * SQLAlchemy * Dulwich (full Git implementation in Python) * Mercurial (currently only the startup time) * html5lib * pyaes (AES crypto cipher in pure Python) * sympy * Tornado (HTTP client and server) * Django (sadly, only the template engine right now, Pyston contains HTTP benchmarks) * pathlib * spambayes More benchmarks will be added later. It would be nice to add benchmarks on numpy for example, numpy is important for a large part of our community. All these (new or updated) tools can now be used to take smarter decisions on optimizations. Please don't push any optimization anymore without providing reliable benchmark results! My first major action was to close the latest attempt to micro-optimize int+int in Python/ceval.c, http://bugs.python.org/issue21955 : I closed the issue as rejected, because there is no significant speedup on benchmarks other than two (tiny) microbenchmarks. To make sure that no one looses its time on trying to micro-optimize int+int, I even added a comment to Python/ceval.c :-) https://hg.python.org/cpython/rev/61fcb12a9873 "Please don't try to micro-optimize int+int" The perf and performance are now well tested: Travis CI runs tests on the new commits and pull requests, and the "tox" command can be used locally to test different Python versions, pep8, doc, ... in a single command. Next steps: * Run performance 0.3.1 on speed.python.org: the benchmark runner is currently stopped (and still uses the old benchmarks project). The website part may be updated to allow to download full JSON files which includes *all* information (all timings, metadata and more). * I plan to run performance on CPython 2.7, CPython 3.7, PyPy and PyPy 3. Maybe also CPython 3.5 and CPython 3.6 if they don't take too much resources. * Later, we can consider adding more implementations of Python: Jython, IronPython, MicroPython, Pyston, Pyjion, etc. All benchmarks should be run on the same hardware to be comparable. * Later, we might also allow other projects to upload their own benchmark results, but we should find a solution to groups benchmark results per benchmark runner (ex: at least by the hostname, perf JSON contains the hostname) to not compare two results from two different hardware * We should continue to add more benchmarks to the performance benchmark suite, especially benchmarks more representative of real applications (we have enough microbenchmarks!) Links: * perf: http://perf.readthedocs.io/ * performance: https://github.com/python/performance * Python Speed mailing list: https://mail.python.org/mailman/listinfo/speed * https://speed.python.org/ (currently outdated, and don't use performance yet) See https://pypi.python.org/pypi/performance which contains even more links to Python benchmarks (PyPy, Pyston, Numba, Pythran, etc.) Victor

9 9

2.6 branch in Mercurial?
by Skip Montanaro 01 Nov '16

01 Nov '16

I need to do a little 2.6 spelunking. I don't see a 2.6 branch in the output of "hg branches". Is "hg clone v2.6.9" the proper incantation to get the latest version (or perhaps "v2.6")? Thx, Skip

3 4

Re: [Python-Dev] [Python-ideas] Show more info when `python -vV`
by INADA Naoki 30 Oct '16

30 Oct '16

(Added python-dev in CC list, because there are enough +1 already). On Mon, Oct 17, 2016 at 3:06 PM, Chris Angelico <rosuav(a)gmail.com> wrote: > On Mon, Oct 17, 2016 at 5:02 PM, INADA Naoki <songofacandy(a)gmail.com> wrote: >> $ ./python.exe -V >> Python 3.6.0b2+ >> >> $ ./python.exe -VV >> Python 3.6.0b2+ (3.6:0b29adb5c804+, Oct 17 2016, 15:00:12) >> [GCC 4.2.1 Compatible Apple LLVM 8.0.0 (clang-800.0.38)] > > LGTM. > > What's the view on backporting this to 2.7.x? We're still a good few > years away from its death, and it'd be helpful if recent 2.7s could > give this info too. > > ChrisA I want to add it at least Python 3.6. Because one reason I want to propose this is I can't see exact Python version (commit id) for "nightly" or "3.6-dev" on Travis-CI test. But Python 3.6 is beta stage already. If we apply rule strictly, it should be added only in default branch (Python 3.7). So, what version can I add this? a. Only Python 3.7+ b. (beta) Python 3.6+ c. (maintenance) Python 2.7 and Python 3.5+ -- INADA Naoki <songofacandy(a)gmail.com>

5 5

Reminder: 3.6.0b3 snapshot 2016-10-31 12:00 UTC
by Ned Deily 28 Oct '16

28 Oct '16

The third, and next-to-last, beta snapshot planned for the 3.6 release cycle is coming up in a few days. With fewer than 7 weeks remaining until the 3.6.0 release, it is very important that we all focus on stability and correctness. Please try to make sure that all remaining non-doc issues associated with new features are addressed in b3. Any remaining 3.6 feature-related issues still open after b3 should be marked in the issue tracker as "release blocker" and *must* be addressed one way or another by b4, 11-21. All other non-critical bug fixes should also be checked in by b4. Only release critical and doc fixes will be allowed once we exit the beta phase. Please plan accordingly. Please contact me if you have any questions about the 3.6.0 schedule or about whether a change is appropriate at this point in the 3.6.0 cycle. To recap, the remaining milestones for 3.6.0: 2016-10-31, 1200 UTC: 3.6.0 beta 3 (feature fixes, bug fixes, doc fixes) 2016-11-21: 3.6.0 beta 4 (important bug fixes and doc fixes) 2016-12-05 3.6.0 release candidate 1 (3.6.0 code freeze, release critical bug fixes, doc fixes) 2016-12-16 3.6.0 release (3.6.0rc1 plus any necessary emergency fixes) Thank you all again for your efforts so far on 3.6! --Ned https://www.python.org/dev/peps/pep-0494/ -- Ned Deily nad(a)python.org -- []

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Python-Dev October 2016