Python-Dev September 2014

python-dev@python.org

86 participants
37 discussions

by barry＠zope.com

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 months, 1 week

Surely "nullable" is a reasonable name?

by Larry Hastings

Argument Clinic "converters" specify how to convert an individual argument to the function you're defining. Although a converter could theoretically represent any sort of conversion, most of the time they directly represent types like "int" or "double" or "str". Because there's such variety in argument parsing, the converters are customizable with parameters. Many of these are common enough that Argument Clinic suggests some standard names. Examples: "zeroes=True" for strings and buffers means "permit internal \0 characters", and "bitwise=True" for unsigned integers means "copy the bits over, even if there's overflow/underflow, and even if the original is negative". A third example is "nullable=True", which means "also accept None for this parameter". This was originally intended for use with strings (compare the "s" and "z" format units for PyArg_ParseTuple), however it looks like we'll have a use for "nullable ints" in the ongoing Argument Clinic conversion work. Several people have said they found the name "nullable" surprising, suggesting I use another name like "allow_none" or "noneable". I, in turn, find their surprise surprising; "nullable" is a term long associated with exactly this concept. It's used in C# and SQL, and the term even has its own Wikipedia page: http://en.wikipedia.org/wiki/Nullable_type Most amusingly, Vala *used* to have an annotation called "(allow-none)", but they've broken it out into two annotations, "(nullable)" and "(optional)". http://blogs.gnome.org/desrt/2014/05/27/allow-none-is-dead-long-live-nullab… Before you say "the term 'nullable' will confuse end users", let me remind you: this is not user-facing. This is a parameter for an Argument Clinic converter, and will only ever be seen by CPython core developers. A group which I hope is not so easily confused. It's my contention that "nullable" is the correct name. But I've been asked to bring up the topic for discussion, to see if a consensus forms around this or around some other name. Let the bike-shedding begin, //arry/

6 years, 9 months

Update to PEP 11 to clarify garnering platform support

by Brett Cannon

Here is some proposed wording. Since it is more of a clarification of what it takes to garner support -- which is just a new section -- rather than a complete rewrite I'm including just the diff to make it easier to read the changes. *diff -r 49d18bb47ebc pep-0011.txt* *--- a/pep-0011.txt Wed May 14 11:18:22 2014 -0400* *+++ b/pep-0011.txt Fri May 16 13:48:30 2014 -0400* @@ -2,22 +2,21 @@ Title: Removing support for little used platforms Version: $Revision$ Last-Modified: $Date$ -Author: martin(a)v.loewis.de (Martin von Löwis) +Author: Martin von Löwis <martin(a)v.loewis.de>, + Brett Cannon <brett(a)python.org> Status: Active Type: Process Content-Type: text/x-rst Created: 07-Jul-2002 Post-History: 18-Aug-2007 + 16-May-2014 Abstract -------- -This PEP documents operating systems (platforms) which are not -supported in Python anymore. For some of these systems, -supporting code might be still part of Python, but will be removed -in a future release - unless somebody steps forward as a volunteer -to maintain this code. +This PEP documents how an operating system (platform) garners +support in Python as well as documenting past support. Rationale @@ -37,16 +36,53 @@ change to the Python source code will work on all supported platforms. -To reduce this risk, this PEP proposes a procedure to remove code -for platforms with no Python users. +To reduce this risk, this PEP specifies what is required for a +platform to be considered supported by Python as well as providing a +procedure to remove code for platforms with little or no Python +users. +Supporting platforms +-------------------- + +Gaining official platform support requires two things. First, a core +developer needs to volunteer to maintain platform-specific code. This +core developer can either already be a member of the Python +development team or be given contributor rights on the basis of +maintaining platform support (it is at the discretion of the Python +development team to decide if a person is ready to have such rights +even if it is just for supporting a specific platform). + +Second, a stable buildbot must be provided [2]_. This guarantees that +platform support will not be accidentally broken by a Python core +developer who does not have personal access to the platform. For a +buildbot to be considered stable it requires that the machine be +reliably up and functioning (but it is up to the Python core +developers to decide whether to promote a buildbot to being +considered stable). + +This policy does not disqualify supporting other platforms +indirectly. Patches which are not platform-specific but still done to +add platform support will be considered for inclusion. For example, +if platform-independent changes were necessary in the configure +script which was motivated to support a specific platform that would +be accepted. Patches which add platform-specific code such as the +name of a specific platform to the configure script will generally +not be accepted without the platform having official support. + +CPU architecture and compiler support are viewed in a similar manner +as platforms. For example, to consider the ARM architecture supported +a buildbot running on ARM would be required along with support from +the Python development team. In general it is not required to have +a CPU architecture run under every possible platform in order to be +considered supported. Unsupporting platforms ---------------------- -If a certain platform that currently has special code in it is -deemed to be without Python users, a note must be posted in this -PEP that this platform is no longer actively supported. This +If a certain platform that currently has special code in Python is +deemed to be without Python users or lacks proper support from the +Python development team and/or a buildbot, a note must be posted in +this PEP that this platform is no longer actively supported. This note must include: - the name of the system @@ -69,8 +105,8 @@ forward and offer maintenance. -Resupporting platforms ----------------------- +Re-supporting platforms +----------------------- If a user of a platform wants to see this platform supported again, he may volunteer to maintain the platform support. Such an @@ -101,7 +137,7 @@ release is made. Developers of extension modules will generally need to use the same Visual Studio release; they are concerned both with the availability of the versions they need to use, and with keeping -the zoo of versions small. The Python source tree will keep +the zoo of versions small. The Python source tree will keep unmaintained build files for older Visual Studio releases, for which patches will be accepted. Such build files will be removed from the source tree 3 years after the extended support for the compiler has @@ -223,6 +259,7 @@ ---------- .. [1] http://support.microsoft.com/lifecycle/ +.. [2] http://buildbot.python.org/3.x.stable/ Copyright ---------

6 years, 11 months

More compact dictionaries with faster iteration

by Raymond Hettinger

The current memory layout for dictionaries is unnecessarily inefficient. It has a sparse table of 24-byte entries containing the hash value, key pointer, and value pointer. Instead, the 24-byte entries should be stored in a dense table referenced by a sparse table of indices. For example, the dictionary: d = {'timmy': 'red', 'barry': 'green', 'guido': 'blue'} is currently stored as: entries = [['--', '--', '--'], [-8522787127447073495, 'barry', 'green'], ['--', '--', '--'], ['--', '--', '--'], ['--', '--', '--'], [-9092791511155847987, 'timmy', 'red'], ['--', '--', '--'], [-6480567542315338377, 'guido', 'blue']] Instead, the data should be organized as follows: indices = [None, 1, None, None, None, 0, None, 2] entries = [[-9092791511155847987, 'timmy', 'red'], [-8522787127447073495, 'barry', 'green'], [-6480567542315338377, 'guido', 'blue']] Only the data layout needs to change. The hash table algorithms would stay the same. All of the current optimizations would be kept, including key-sharing dicts and custom lookup functions for string-only dicts. There is no change to the hash functions, the table search order, or collision statistics. The memory savings are significant (from 30% to 95% compression depending on the how full the table is). Small dicts (size 0, 1, or 2) get the most benefit. For a sparse table of size t with n entries, the sizes are: curr_size = 24 * t new_size = 24 * n + sizeof(index) * t In the above timmy/barry/guido example, the current size is 192 bytes (eight 24-byte entries) and the new size is 80 bytes (three 24-byte entries plus eight 1-byte indices). That gives 58% compression. Note, the sizeof(index) can be as small as a single byte for small dicts, two bytes for bigger dicts and up to sizeof(Py_ssize_t) for huge dict. In addition to space savings, the new memory layout makes iteration faster. Currently, keys(), values, and items() loop over the sparse table, skipping-over free slots in the hash table. Now, keys/values/items can loop directly over the dense table, using fewer memory accesses. Another benefit is that resizing is faster and touches fewer pieces of memory. Currently, every hash/key/value entry is moved or copied during a resize. In the new layout, only the indices are updated. For the most part, the hash/key/value entries never move (except for an occasional swap to fill a hole left by a deletion). With the reduced memory footprint, we can also expect better cache utilization. For those wanting to experiment with the design, there is a pure Python proof-of-concept here: http://code.activestate.com/recipes/578375 YMMV: Keep in mind that the above size statics assume a build with 64-bit Py_ssize_t and 64-bit pointers. The space savings percentages are a bit different on other builds. Also, note that in many applications, the size of the data dominates the size of the container (i.e. the weight of a bucket of water is mostly the water, not the bucket). Raymond

7 years

Semi-official read-only Github mirror of the CPython Mercurial repository

by Eli Bendersky

Hi all, https://github.com/python/cpython is now live as a semi-official, *read only* Github mirror of the CPython Mercurial repository. Let me know if you have any problems/concerns. I still haven't decided how often to update it (considering either just N times a day, or maybe use a Hg hook for batching). Suggestions are welcome. The methodology I used to create it is via hg-fast-export. I also tried to pack and gc the git repo as much as possible before the initial Github push - it went down from almost ~2GB to ~200MB (so this is the size of a fresh clone right now). Eli P.S. thanks Jesse for the keys to https://github.com/python

7 years, 3 months

PEP476: Enabling certificate validation by default

by Alex Gaynor

Hi all, I've just updated the PEP to reflect the API suggestions from Nick, and the fact that the necessary changes to urllib were landed. I think this is ready for pronouncement, Guido? Cheers, Alex

7 years, 3 months

Sad status of Python 3.x buildbots

by Victor Stinner

Hi, I'm using Python buildbots to ensure that my changes don't fail on some platform. It's important for changes close to the operation system. The problem is that many buildbots are ill. Before, only a few buildbots had sporadic failures. Now most buildbots are always fail (are red). Here is an incomplete list of failures seen on buildbots. Before I opened an issue for each bug, but usually nobody takes care of them. So today I'm trying the mailing list. How can we fix all these issues to have more "green" buildbots? Can anyone help on this task? AMD64 OpenIndiana 3.x: a lot of tests fail with OSError(12, "Not enough space") or MemoryError. It's probably on issue on the host. AMD64 Snow Leop 3.x: many tests are not reliable (stable) on this platform. For example, test_logging.test_race() sometimes fail with PermissionError(1, "Operation not permitted: '/tmp/test_logging-3-bjulw8iz.log'"). Another example, test_asyncio.test_stdin_broken_pipe() sometimes fail with an assertion error because BrokenPipeError was not raised. Do we still support this old version of Mac OS X? Released in 2009, it is 5 years old. Is upgrading to Maverick (10.9) free and possible on old Mac computers? I don't have access to this old OS. x86 RHEL 6 3.x: TestReadline.test_init() fails, issue #19884. I don't have to this platform, I don't know how to fix it. x86 Windows Server 2003 [SB] 3.x: test_build_ext() of test_distutils hangs during 1 hang before being killed, it hangs something in the C compiler. x86 Windows7 3.x: test_nntplib fails with OSError("cannot read from timed out object"). x86 XP-4 3.x: test_distutils fails because Visual Studio linker (link.exe) fails with the error 1181 (cannot open input file). test_capi.test_forced_io_encoding() fails with an assertion error because sys.__stdin__ is None. AMD64 Solaris 11 [SB] 3.x: sometimes, tests fail with MemoryError. test_uuid.test_uuid4() fails with an assertion error. ctypes has issue with the sign of integer numbers (bug in libffi?). ARMv7 3.x: "Read-only file system", Mercurial fails... x86 FreeBSD 7.2 3.x: test_io.test_interrupted_write_text() hangs. x86 FreeBSD 6.4 3.x: test_urllib2net.test_urlwithfrag() fails with urllib.error.URLError: <urlopen error unknown url type: https>. test_tcl has many issues. test_multiprocessing_spawn fails whereas the test should be skipped. x86 OpenBSD 5.5 3.x: many failing tests. x86 OpenIndiana 3.x: MemoryError. TestReadline.test_init() also fails. x86 Tiger 3.x: test_nntplib fails with OSError("cannot read from timed out object". I skipped "SPARC Solaris 10 OpenCSW 3.x" and "PPC64 AIX 3.x" in my list, I'm not really interested by these platforms. Victor

7 years, 3 months

Microsoft Visual C++ Compiler for Python 2.7

by Steve Dower

Hi all, (This is advance notice since people on this list will be interested. Official announcements are coming when setuptools makes their next release.) Microsoft has released a compiler package targeting Python 2.7 (i.e. VC9). We've produced this package to help library developers build wheels for Windows, but also to help users unblock themselves when they need to build C extensions themselves. The Microsoft Visual C++ Compiler for Python 2.7 is available from: http://aka.ms/vcpython27 This package contains all the tools and headers required to build C extension modules for Python 2.7 32-bit and 64-bit (note that some extension modules require 3rd party dependencies such as OpenSSL or libxml2 that are not included). Other versions of Python built with Visual C++ 2008 are also supported. You can install the package without requiring administrative privileges and, with the latest version of setuptools (when it releases), use tools such as pip, wheel, or a setup.py file to produce binaries on Windows. Unfortunately, this package isn't necessarily going to help with building CPython 2.7 itself, as the build process is complicated and Visual Studio 2008 is practically required. However, as most people aren't building CPython on Windows, this isn't a huge issue. This compiler package should be sufficient for most extension modules. I should also point out that VC9 is no longer supported by Microsoft. This means there won't be any improvements or bug fixes coming, and there's no official support offered. Feel free to contact me directly <steve.dower(a)microsoft.com> if there are issues with the package. Cheers, Steve

7 years, 3 months

PEP 394 - Clarification of what "python" command should invoke

by Bohuslav Kabrda

Hi, as Fedora is getting closer to having python3 as a default, I'm being more and more asked by Fedora users/contributors what'll "/usr/bin/python" invoke when we achieve this (Fedora 22 hopefully). So I was rereading PEP 394 and I think I need a small clarification regarding two points in the PEP: - "for the time being, all distributions should ensure that python refers to the same target as python2." - "Similarly, the more general python command should be installed whenever any version of Python is installed and should invoke the same version of Python as either python2 or python3." The important word in the second point is, I think, *whenever*. Trying to apply these two points to Fedora 22 situation, I can think of several approaches: - /usr/bin/python will always point to python3 (seems to go against the first mentioned PEP recommendation) - /usr/bin/python will always point to python2 (seems to go against the second mentioned PEP recommendation, there is no /usr/bin/python if python2 is not installed) - /usr/bin/python will point to python3 if python2 is not installed, else it will point to python2 (inconsistent; also the user doesn't know he's running and what libraries he'll be able to import - the system can have different sets of python2-* and python3-* extension modules installed) - there will be no /usr/bin/python (goes against PEP and seems just wrong) I'd really appreciate upstream guidance and perhaps a PEP clarification for distributions that ship both python2 and python3, but can live without python2 (and are not Arch :)). Thanks a lot! -- Regards, Slavek Kabrda

7 years, 3 months

Re: [Python-Dev] 3.5 release schedule PEP

by Mike Miller

On 09/24/2014 10:00 PM, Nick Coghlan <ncoghlan(a)gmail.com> wrote: > Subject: Re: [Python-Dev] 3.5 release schedule PEP > > On 24 Sep 2014 15:15, "Tim Golden" <mail(a)timgolden.me.uk> wrote: > > > > On 23/09/2014 18:05, Steve Dower wrote: > >> I'm also considering/experimenting with installing into "Program > >> Files" by default, but I suspect that isn't going to work out yet. > > > > I'd like to see that go forward: I think it's increasingly difficult to > justify Python's position at c:\pythonxx. But it does run the risk of > > breaking All The Things. > > It might be better to offer that as a supported option in 3.5, and then make it > the default in 3.6. > > That will offer a couple of years to work out the issues, rather than a few months. Hi all, ProgramFiles was the default in Python 1.X. It has been a supported option for just shy of 15 years on 2.X... most if not all the bugs (setuptools) were fixed a decade ago, and right now thousands, if not millions of people are running it under Program Files right now. I can vouch for several thousand because a company I work for distributes Python and pip there for its customers all around the world w/o issue. I've never once encountered a bug due to install to ProgramFiles, or heard of anyone who has, and have been using Python for everything since the year 2000. If any rare bugs happen to surface, they can likely be fixed or replaced with a line of code, or worked around by installing elsewhere. The potential existence of such bugs isn't enough reason to stay stuck in 1990 while leaving users vulnerable to tampering attacks for another few years. -Mike

7 years, 4 months

2022

2021

2020

2019

2018

2017

2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

1999

Python-Dev September 2014