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PEP 5 – Guidelines for Language Evolution Author: Paul Prescod <paul at prescod.net> Status: Superseded Type: Process Created: 26-Oct-2000 Post-History: Superseded-By: 387 Table of Contents Abstract Implementation Details Scope Steps For Introducing Backwards-Incompatible Features Abstract In the natural evolution of programming languages it is sometimes necessary to make changes that modify the behavior of older programs. This PEP proposes a policy for implementing these changes in a manner respectful of the installed base of Python users. Implementation Details Implementation of this PEP requires the addition of a formal warning and deprecation facility that will be described in another proposal. Scope These guidelines apply to future versions of Python that introduce backward-incompatible behavior. Backward incompatible behavior is a major deviation in Python interpretation from an earlier behavior described in the standard Python documentation. Removal of a feature also constitutes a change of behavior. This PEP does not replace or preclude other compatibility strategies such as dynamic loading of backwards-compatible parsers. On the other hand, if execution of “old code” requires a special switch or pragma then that is indeed a change of behavior from the point of view of the user and that change should be implemented according to these guidelines. In general, common sense must prevail in the implementation of these guidelines. For instance changing “sys.copyright” does not constitute a backwards-incompatible change of behavior! Steps For Introducing Backwards-Incompatible Features Propose backwards-incompatible behavior in a PEP. The PEP must include a section on backwards compatibility that describes in detail a plan to complete the remainder of these steps. Once the PEP is accepted as a productive direction, implement an alternate way to accomplish the task previously provided by the feature that is being removed or changed. For instance if the addition operator were scheduled for removal, a new version of Python could implement an “add()” built-in function. Formally deprecate the obsolete construct in the Python documentation. Add an optional warning mode to the parser that will inform users when the deprecated construct is used. In other words, all programs that will behave differently in the future must trigger warnings in this mode. Compile-time warnings are preferable to runtime warnings. The warning messages should steer people from the deprecated construct to the alternative construct. There must be at least a one-year transition period between the release of the transitional version of Python and the release of the backwards incompatible version. Users will have at least a year to test their programs and migrate them from use of the deprecated construct to the alternative one.

Superseded

PEP 5 – Guidelines for Language Evolution

Process

In the natural evolution of programming languages it is sometimes necessary to make changes that modify the behavior of older programs. This PEP proposes a policy for implementing these changes in a manner respectful of the installed base of Python users.

PEP 6 – Bug Fix Releases Author: Aahz <aahz at pythoncraft.com>, Anthony Baxter <anthony at interlink.com.au> Status: Superseded Type: Process Created: 15-Mar-2001 Post-History: 15-Mar-2001, 18-Apr-2001, 19-Aug-2004 Table of Contents Abstract Motivation Prohibitions Not-Quite-Prohibitions Applicability of Prohibitions Helping the Bug Fix Releases Happen Version Numbers Procedure Patch Czar History History References Copyright Note This PEP is obsolete. The current release policy is documented in the devguide. See also PEP 101 for mechanics of the release process. Abstract Python has historically had only a single fork of development, with releases having the combined purpose of adding new features and delivering bug fixes (these kinds of releases will be referred to as “major releases”). This PEP describes how to fork off maintenance, or bug fix, releases of old versions for the primary purpose of fixing bugs. This PEP is not, repeat NOT, a guarantee of the existence of bug fix releases; it only specifies a procedure to be followed if bug fix releases are desired by enough of the Python community willing to do the work. Motivation With the move to SourceForge, Python development has accelerated. There is a sentiment among part of the community that there was too much acceleration, and many people are uncomfortable with upgrading to new versions to get bug fixes when so many features have been added, sometimes late in the development cycle. One solution for this issue is to maintain the previous major release, providing bug fixes until the next major release. This should make Python more attractive for enterprise development, where Python may need to be installed on hundreds or thousands of machines. Prohibitions Bug fix releases are required to adhere to the following restrictions: There must be zero syntax changes. All .pyc and .pyo files must work (no regeneration needed) with all bugfix releases forked off from a major release. There must be zero pickle changes. There must be no incompatible C API changes. All extensions must continue to work without recompiling in all bugfix releases in the same fork as a major release. Breaking any of these prohibitions requires a BDFL proclamation (and a prominent warning in the release notes). Not-Quite-Prohibitions Where possible, bug fix releases should also: Have no new features. The purpose of a bug fix release is to fix bugs, not add the latest and greatest whizzo feature from the HEAD of the CVS root. Be a painless upgrade. Users should feel confident that an upgrade from 2.x.y to 2.x.(y+1) will not break their running systems. This means that, unless it is necessary to fix a bug, the standard library should not change behavior, or worse yet, APIs. Applicability of Prohibitions The above prohibitions and not-quite-prohibitions apply both for a final release to a bugfix release (for instance, 2.4 to 2.4.1) and for one bugfix release to the next in a series (for instance 2.4.1 to 2.4.2). Following the prohibitions listed in this PEP should help keep the community happy that a bug fix release is a painless and safe upgrade. Helping the Bug Fix Releases Happen Here’s a few pointers on helping the bug fix release process along. Backport bug fixes. If you fix a bug, and it seems appropriate, port it to the CVS branch for the current bug fix release. If you’re unwilling or unable to backport it yourself, make a note in the commit message, with words like ‘Bugfix candidate’ or ‘Backport candidate’. If you’re not sure, ask. Ask the person managing the current bug fix releases if they think a particular fix is appropriate. If there’s a particular bug you’d particularly like fixed in a bug fix release, jump up and down and try to get it done. Do not wait until 48 hours before a bug fix release is due, and then start asking for bug fixes to be included. Version Numbers Starting with Python 2.0, all major releases are required to have a version number of the form X.Y; bugfix releases will always be of the form X.Y.Z. The current major release under development is referred to as release N; the just-released major version is referred to as N-1. In CVS, the bug fix releases happen on a branch. For release 2.x, the branch is named ‘release2x-maint’. For example, the branch for the 2.3 maintenance releases is release23-maint Procedure The process for managing bugfix releases is modeled in part on the Tcl system [1]. The Patch Czar is the counterpart to the BDFL for bugfix releases. However, the BDFL and designated appointees retain veto power over individual patches. A Patch Czar might only be looking after a single branch of development - it’s quite possible that a different person might be maintaining the 2.3.x and the 2.4.x releases. As individual patches get contributed to the current trunk of CVS, each patch committer is requested to consider whether the patch is a bug fix suitable for inclusion in a bugfix release. If the patch is considered suitable, the committer can either commit the release to the maintenance branch, or else mark the patch in the commit message. In addition, anyone from the Python community is free to suggest patches for inclusion. Patches may be submitted specifically for bugfix releases; they should follow the guidelines in PEP 3. In general, though, it’s probably better that a bug in a specific release also be fixed on the HEAD as well as the branch. The Patch Czar decides when there are a sufficient number of patches to warrant a release. The release gets packaged up, including a Windows installer, and made public. If any new bugs are found, they must be fixed immediately and a new bugfix release publicized (with an incremented version number). For the 2.3.x cycle, the Patch Czar (Anthony) has been trying for a release approximately every six months, but this should not be considered binding in any way on any future releases. Bug fix releases are expected to occur at an interval of roughly six months. This is only a guideline, however - obviously, if a major bug is found, a bugfix release may be appropriate sooner. In general, only the N-1 release will be under active maintenance at any time. That is, during Python 2.4’s development, Python 2.3 gets bugfix releases. If, however, someone qualified wishes to continue the work to maintain an older release, they should be encouraged. Patch Czar History Anthony Baxter is the Patch Czar for 2.3.1 through 2.3.4. Barry Warsaw is the Patch Czar for 2.2.3. Guido van Rossum is the Patch Czar for 2.2.2. Michael Hudson is the Patch Czar for 2.2.1. Anthony Baxter is the Patch Czar for 2.1.2 and 2.1.3. Thomas Wouters is the Patch Czar for 2.1.1. Moshe Zadka is the Patch Czar for 2.0.1. History This PEP started life as a proposal on comp.lang.python. The original version suggested a single patch for the N-1 release to be released concurrently with the N release. The original version also argued for sticking with a strict bug fix policy. Following feedback from the BDFL and others, the draft PEP was written containing an expanded bugfix release cycle that permitted any previous major release to obtain patches and also relaxed the strict bug fix requirement (mainly due to the example of PEP 235, which could be argued as either a bug fix or a feature). Discussion then mostly moved to python-dev, where BDFL finally issued a proclamation basing the Python bugfix release process on Tcl’s, which essentially returned to the original proposal in terms of being only the N-1 release and only bug fixes, but allowing multiple bugfix releases until release N is published. Anthony Baxter then took this PEP and revised it, based on lessons from the 2.3 release cycle. References [1] http://www.tcl.tk/cgi-bin/tct/tip/28.html Copyright This document has been placed in the public domain.

Superseded

PEP 6 – Bug Fix Releases

Process

Python has historically had only a single fork of development, with releases having the combined purpose of adding new features and delivering bug fixes (these kinds of releases will be referred to as “major releases”). This PEP describes how to fork off maintenance, or bug fix, releases of old versions for the primary purpose of fixing bugs.

PEP 10 – Voting Guidelines Author: Barry Warsaw <barry at python.org> Status: Active Type: Process Created: 07-Mar-2002 Post-History: 07-Mar-2002 Table of Contents Abstract Rationale Voting Scores References Copyright Abstract This PEP outlines the python-dev voting guidelines. These guidelines serve to provide feedback or gauge the “wind direction” on a particular proposal, idea, or feature. They don’t have a binding force. Rationale When a new idea, feature, patch, etc. is floated in the Python community, either through a PEP or on the mailing lists (most likely on python-dev [1]), it is sometimes helpful to gauge the community’s general sentiment. Sometimes people just want to register their opinion of an idea. Sometimes the BDFL wants to take a straw poll. Whatever the reason, these guidelines have been adopted so as to provide a common language for developers. While opinions are (sometimes) useful, but they are never binding. Opinions that are accompanied by rationales are always valued higher than bare scores (this is especially true with -1 votes). Voting Scores The scoring guidelines are loosely derived from the Apache voting procedure [2], with of course our own spin on things. There are 4 possible vote scores: +1 I like it +0 I don’t care, but go ahead -0 I don’t care, so why bother? -1 I hate it You may occasionally see wild flashes of enthusiasm (either for or against) with vote scores like +2, +1000, or -1000. These aren’t really valued much beyond the above scores, but it’s nice to see people get excited about such geeky stuff. References [1] Python Developer’s Guide, (http://www.python.org/dev/) [2] Apache Project Guidelines and Voting Rules (http://httpd.apache.org/dev/guidelines.html) Copyright This document has been placed in the public domain.

Active

PEP 10 – Voting Guidelines

Process

This PEP outlines the python-dev voting guidelines. These guidelines serve to provide feedback or gauge the “wind direction” on a particular proposal, idea, or feature. They don’t have a binding force.

PEP 11 – CPython platform support Author: Martin von Löwis <martin at v.loewis.de>, Brett Cannon <brett at python.org> Status: Active Type: Process Created: 07-Jul-2002 Post-History: 18-Aug-2007, 14-May-2014, 20-Feb-2015, 10-Mar-2022 Table of Contents Abstract Rationale Support tiers Tier 1 Tier 2 Tier 3 All other platforms Notes Microsoft Windows Legacy C Locale Unsupporting platforms No-longer-supported platforms Discussions Copyright Abstract This PEP documents how an operating system (platform) becomes supported in CPython, what platforms are currently supported, and documents past support. Rationale Over time, the CPython source code has collected various pieces of platform-specific code, which, at some point in time, was considered necessary to use CPython on a specific platform. Without access to this platform, it is not possible to determine whether this code is still needed. As a result, this code may either break during CPython’s evolution, or it may become unnecessary as the platforms evolve as well. Allowing these fragments to grow poses the risk of unmaintainability: without having experts for a large number of platforms, it is not possible to determine whether a certain change to the CPython source code will work on all supported platforms. To reduce this risk, this PEP specifies what is required for a platform to be considered supported by CPython as well as providing a procedure to remove code for platforms with few or no CPython users. This PEP also lists what platforms are supported by the CPython interpreter. This lets people know what platforms are directly supported by the CPython development team. Support tiers Platform support is broken down into tiers. Each tier comes with different requirements which lead to different promises being made about support. To be promoted to a tier, steering council support is required and is expected to be driven by team consensus. Demotion to a lower tier occurs when the requirements of the current tier are no longer met for a platform for an extended period of time based on the judgment of the release manager or steering council. For platforms which no longer meet the requirements of any tier by b1 of a new feature release, an announcement will be made to warn the community of the pending removal of support for the platform (e.g. in the b1 announcement). If the platform is not brought into line for at least one of the tiers by the first release candidate, it will be listed as unsupported in this PEP. Tier 1 STATUS CI failures block releases. Changes which would break the main branch are not allowed to be merged; any breakage should be fixed or reverted immediately. All core developers are responsible to keep main, and thus these platforms, working. Failures on these platforms block a release. Target Triple Notes i686-pc-windows-msvc x86_64-pc-windows-msvc x86_64-apple-darwin BSD libc, clang x86_64-unknown-linux-gnu glibc, gcc Tier 2 STATUS Must have a reliable buildbot. At least two core developers are signed up to support the platform. Changes which break any of these platforms are to be fixed or reverted within 24 hours. Failures on these platforms block a release. Target Triple Notes Contacts aarch64-apple-darwin clang Ned Deily, Ronald Oussoren, Dong-hee Na aarch64-unknown-linux-gnu glibc, gccglibc, clang Petr Viktorin, Victor StinnerVictor Stinner, Gregory P. Smith wasm32-unknown-wasi WASI SDK, Wasmtime Brett Cannon, Eric Snow x86_64-unknown-linux-gnu glibc, clang Victor Stinner, Gregory P. Smith Tier 3 STATUS Must have a reliable buildbot. At least one core developer is signed up to support the platform. No response SLA to failures. Failures on these platforms do not block a release. Target Triple Notes Contacts aarch64-pc-windows-msvc Steve Dower armv7l-unknown-linux-gnueabihf Raspberry Pi OS, glibc, gcc Gregory P. Smith powerpc64le-unknown-linux-gnu glibc, clangglibc, gcc Victor StinnerVictor Stinner s390x-unknown-linux-gnu glibc, gcc Victor Stinner x86_64-unknown-freebsd BSD libc, clang Victor Stinner All other platforms Support for a platform may be partial within the code base, such as from active development around platform support or accidentally. Code changes to platforms not listed in the above tiers may be rejected or removed from the code base without a deprecation process if they cause a maintenance burden or obstruct general improvements. Platforms not listed here may be supported by the wider Python community in some way. If your desired platform is not listed above, please perform a search online to see if someone is already providing support in some form. Notes Microsoft Windows Windows versions prior to Windows 10 follow Microsoft’s Fixed Lifecycle Policy, with a mainstream support phase for 5 years after release, where the product is generally commercially available, and an additional 5 year extended support phase, where paid support is still available and certain bug fixes are released. Extended Security Updates (ESU) is a paid program available to high-volume enterprise customers as a “last resort” option to receive certain security updates after extended support ends. ESU is considered a distinct phase that follows the expiration of extended support. Windows 10 and later follow Microsoft’s Modern Lifecycle Policy, which varies per-product, per-version, per-edition and per-channel. Generally, feature updates (1709, 22H2) occur every 6-12 months and are supported for 18-36 months; Server and IoT editions, and LTSC channel releases are supported for 5-10 years, and the latest feature release of a major version (Windows 10, Windows 11) generally receives new updates for at least 10 years following release. Microsoft’s Windows Lifecycle FAQ has more specific and up-to-date guidance. CPython’s Windows support currently follows Microsoft’s lifecycles. A new feature release X.Y.0 will support all Windows versions whose extended support phase has not yet expired. Subsequent bug fix releases will support the same Windows versions as the original feature release, even if no longer supported by Microsoft. New versions of Windows released while CPython is in maintenance mode may be supported at the discretion of the core team and release manager. As of 2024, our current interpretation of Microsoft’s lifecycles is that Windows for IoT and embedded systems is out of scope for new CPython releases, as the intent of those is to avoid feature updates. Windows Server will usually be the oldest version still receiving free security fixes, and that will determine the earliest supported client release with equivalent API version (which will usually be past its end-of-life). Each feature release is built by a specific version of Microsoft Visual Studio. That version should have mainstream support when the 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 CPython 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 ended (but continue to remain available in revision control). Legacy C Locale Starting with CPython 3.7.0, *nix platforms are expected to provide at least one of C.UTF-8 (full locale), C.utf8 (full locale) or UTF-8 (LC_CTYPE-only locale) as an alternative to the legacy C locale. Any Unicode-related integration problems that occur only in the legacy C locale and cannot be reproduced in an appropriately configured non-ASCII locale will be closed as “won’t fix”. Unsupporting platforms If a platform drops out of tiered support, a note must be posted in this PEP that the platform is no longer actively supported. This note must include: The name of the system, The first release number that does not support this platform anymore, and The first release where the historical support code is actively removed. In some cases, it is not possible to identify the specific list of systems for which some code is used (e.g. when autoconf tests for absence of some feature which is considered present on all supported systems). In this case, the name will give the precise condition (usually a preprocessor symbol) that will become unsupported. At the same time, the CPython build must be changed to produce a warning if somebody tries to install CPython on this platform. On platforms using autoconf, configure should also be made emit a warning about the unsupported platform. This gives potential users of the platform a chance to step forward and offer maintenance. We do not treat a platform that loses Tier 3 support any worse than a platform that was never supported. No-longer-supported platforms Name: MS-DOS, MS-Windows 3.x Unsupported in: Python 2.0 Code removed in: Python 2.1 Name: SunOS 4 Unsupported in: Python 2.3 Code removed in: Python 2.4 Name: DYNIX Unsupported in: Python 2.3 Code removed in: Python 2.4 Name: dgux Unsupported in: Python 2.3 Code removed in: Python 2.4 Name: Minix Unsupported in: Python 2.3 Code removed in: Python 2.4 Name: Irix 4 and –with-sgi-dl Unsupported in: Python 2.3 Code removed in: Python 2.4 Name: Linux 1 Unsupported in: Python 2.3 Code removed in: Python 2.4 Name: Systems defining __d6_pthread_create (configure.in) Unsupported in: Python 2.3 Code removed in: Python 2.4 Name: Systems defining PY_PTHREAD_D4, PY_PTHREAD_D6, or PY_PTHREAD_D7 in thread_pthread.h Unsupported in: Python 2.3 Code removed in: Python 2.4 Name: Systems using –with-dl-dld Unsupported in: Python 2.3 Code removed in: Python 2.4 Name: Systems using –without-universal-newlines, Unsupported in: Python 2.3 Code removed in: Python 2.4 Name: MacOS 9 Unsupported in: Python 2.4 Code removed in: Python 2.4 Name: Systems using –with-wctype-functions Unsupported in: Python 2.6 Code removed in: Python 2.6 Name: Win9x, WinME, NT4 Unsupported in: Python 2.6 (warning in 2.5 installer) Code removed in: Python 2.6 Name: AtheOS Unsupported in: Python 2.6 (with “AtheOS” changed to “Syllable”) Build broken in: Python 2.7 (edit configure to re-enable) Code removed in: Python 3.0 Details: http://www.syllable.org/discussion.php?id=2320 Name: BeOS Unsupported in: Python 2.6 (warning in configure) Build broken in: Python 2.7 (edit configure to re-enable) Code removed in: Python 3.0 Name: Systems using Mach C Threads Unsupported in: Python 3.2 Code removed in: Python 3.3 Name: SunOS lightweight processes (LWP) Unsupported in: Python 3.2 Code removed in: Python 3.3 Name: Systems using –with-pth (GNU pth threads) Unsupported in: Python 3.2 Code removed in: Python 3.3 Name: Systems using Irix threads Unsupported in: Python 3.2 Code removed in: Python 3.3 Name: OSF* systems (issue 8606) Unsupported in: Python 3.2 Code removed in: Python 3.3 Name: OS/2 (issue 16135) Unsupported in: Python 3.3 Code removed in: Python 3.4 Name: VMS (issue 16136) Unsupported in: Python 3.3 Code removed in: Python 3.4 Name: Windows 2000 Unsupported in: Python 3.3 Code removed in: Python 3.4 Name: Windows systems where COMSPEC points to command.com Unsupported in: Python 3.3 Code removed in: Python 3.4 Name: RISC OS Unsupported in: Python 3.0 (some code actually removed) Code removed in: Python 3.4 Name: IRIX Unsupported in: Python 3.7 Code removed in: Python 3.7 Name: Systems without multithreading support Unsupported in: Python 3.7 Code removed in: Python 3.7 Name: wasm32-unknown-emscripten Unsupported in: Python 3.13 Code removed in: Unknown Discussions April 2022: Consider adding a Tier 3 to tiered platform support (Victor Stinner) March 2022: Proposed tiered platform support (Brett Cannon) February 2015: Update to PEP 11 to clarify garnering platform support (Brett Cannon) May 2014: Where is our official policy of what platforms we do support? (Brett Cannon) August 2007: PEP 11 update - Call for port maintainers to step forward (Skip Montanaro) Copyright This document is placed in the public domain or under the CC0-1.0-Universal license, whichever is more permissive.

Active

PEP 11 – CPython platform support

Process

This PEP documents how an operating system (platform) becomes supported in CPython, what platforms are currently supported, and documents past support.

PEP 12 – Sample reStructuredText PEP Template Author: David Goodger <goodger at python.org>, Barry Warsaw <barry at python.org>, Brett Cannon <brett at python.org> Status: Active Type: Process Created: 05-Aug-2002 Post-History: 30-Aug-2002 Table of Contents Abstract Rationale How to Use This Template ReStructuredText PEP Formatting Requirements General Section Headings Paragraphs Inline Markup Block Quotes Literal Blocks Lists Tables Hyperlinks Internal and PEP/RFC Links Footnotes Images Comments Escaping Mechanism Canonical Documentation and Intersphinx Habits to Avoid Suggested Sections Resources Copyright Note For those who have written a PEP before, there is a template (which is included as a file in the PEPs repository). Abstract This PEP provides a boilerplate or sample template for creating your own reStructuredText PEPs. In conjunction with the content guidelines in PEP 1, this should make it easy for you to conform your own PEPs to the format outlined below. Note: if you are reading this PEP via the web, you should first grab the text (reStructuredText) source of this PEP in order to complete the steps below. DO NOT USE THE HTML FILE AS YOUR TEMPLATE! The source for this (or any) PEP can be found in the PEPs repository, as well as via a link at the bottom of each PEP. Rationale If you intend to submit a PEP, you MUST use this template, in conjunction with the format guidelines below, to ensure that your PEP submission won’t get automatically rejected because of form. ReStructuredText provides PEP authors with useful functionality and expressivity, while maintaining easy readability in the source text. The processed HTML form makes the functionality accessible to readers: live hyperlinks, styled text, tables, images, and automatic tables of contents, among other advantages. How to Use This Template To use this template you must first decide whether your PEP is going to be an Informational or Standards Track PEP. Most PEPs are Standards Track because they propose a new feature for the Python language or standard library. When in doubt, read PEP 1 for details, or open a tracker issue on the PEPs repo to ask for assistance. Once you’ve decided which type of PEP yours is going to be, follow the directions below. Make a copy of this file (the .rst file, not the HTML!) and perform the following edits. Name the new file pep-NNNN.rst, using the next available number (not used by a published or in-PR PEP). Replace the “PEP: 12” header with “PEP: NNNN”, matching the file name. Note that the file name should be padded with zeros (eg pep-0012.rst), but the header should not (PEP: 12). Change the Title header to the title of your PEP. Change the Author header to include your name, and optionally your email address. Be sure to follow the format carefully: your name must appear first, and it must not be contained in parentheses. Your email address may appear second (or it can be omitted) and if it appears, it must appear in angle brackets. It is okay to obfuscate your email address. If none of the authors are Python core developers, include a Sponsor header with the name of the core developer sponsoring your PEP. Add the direct URL of the PEP’s canonical discussion thread (on e.g. Python-Dev, Discourse, etc) under the Discussions-To header. If the thread will be created after the PEP is submitted as an official draft, it is okay to just list the venue name initially, but remember to update the PEP with the URL as soon as the PEP is successfully merged to the PEPs repository and you create the corresponding discussion thread. See PEP 1 for more details. Change the Status header to “Draft”. For Standards Track PEPs, change the Type header to “Standards Track”. For Informational PEPs, change the Type header to “Informational”. For Standards Track PEPs, if your feature depends on the acceptance of some other currently in-development PEP, add a Requires header right after the Type header. The value should be the PEP number of the PEP yours depends on. Don’t add this header if your dependent feature is described in a Final PEP. Change the Created header to today’s date. Be sure to follow the format carefully: it must be in dd-mmm-yyyy format, where the mmm is the 3 English letter month abbreviation, i.e. one of Jan, Feb, Mar, Apr, May, Jun, Jul, Aug, Sep, Oct, Nov, Dec. For Standards Track PEPs, after the Created header, add a Python-Version header and set the value to the next planned version of Python, i.e. the one your new feature will hopefully make its first appearance in. Do not use an alpha or beta release designation here. Thus, if the last version of Python was 2.2 alpha 1 and you’re hoping to get your new feature into Python 2.2, set the header to:Python-Version: 2.2 Add a Topic header if the PEP belongs under one shown at the Topic Index. Most PEPs don’t. Leave Post-History alone for now; you’ll add dates and corresponding links to this header each time you post your PEP to the designated discussion forum (and update the Discussions-To header with said link, as above). For each thread, use the date (in the dd-mmm-yyy format) as the linked text, and insert the URLs inline as anonymous reST hyperlinks, with commas in between each posting.If you posted threads for your PEP on August 14, 2001 and September 3, 2001, the Post-History header would look like, e.g.: Post-History: `14-Aug-2001 <https://www.example.com/thread_1>`__, `03-Sept-2001 <https://www.example.com/thread_2>`__ You should add the new dates/links here as soon as you post a new discussion thread. Add a Replaces header if your PEP obsoletes an earlier PEP. The value of this header is the number of the PEP that your new PEP is replacing. Only add this header if the older PEP is in “final” form, i.e. is either Accepted, Final, or Rejected. You aren’t replacing an older open PEP if you’re submitting a competing idea. Now write your Abstract, Rationale, and other content for your PEP, replacing all this gobbledygook with your own text. Be sure to adhere to the format guidelines below, specifically on the prohibition of tab characters and the indentation requirements. See “Suggested Sections” below for a template of sections to include. Update your Footnotes section, listing any footnotes and non-inline link targets referenced by the text. Run ./build.py to ensure the PEP is rendered without errors, and check that the output in build/pep-NNNN.html looks as you intend. Create a pull request against the PEPs repository. For reference, here are all of the possible header fields (everything in brackets should either be replaced or have the field removed if it has a leading * marking it as optional and it does not apply to your PEP): PEP: [NNN] Title: [...] Author: [Full Name <email at example.com>] Sponsor: *[Full Name <email at example.com>] PEP-Delegate: Discussions-To: [URL] Status: Draft Type: [Standards Track | Informational | Process] Topic: *[Governance | Packaging | Release | Typing] Requires: *[NNN] Created: [DD-MMM-YYYY] Python-Version: *[M.N] Post-History: [`DD-MMM-YYYY <URL>`__] Replaces: *[NNN] Superseded-By: *[NNN] Resolution: ReStructuredText PEP Formatting Requirements The following is a PEP-specific summary of reStructuredText syntax. For the sake of simplicity and brevity, much detail is omitted. For more detail, see Resources below. Literal blocks (in which no markup processing is done) are used for examples throughout, to illustrate the plaintext markup. General Lines should usually not extend past column 79, excepting URLs and similar circumstances. Tab characters must never appear in the document at all. Section Headings 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. Section titles must be adorned with an underline, a single repeated punctuation character, which begins in column zero and must extend at least as far as the right edge of the title text (4 characters minimum). First-level section titles are underlined with “=” (equals signs), second-level section titles with “-” (hyphens), and third-level section titles with “’” (single quotes or apostrophes). For example: First-Level Title ================= Second-Level Title ------------------ Third-Level Title ''''''''''''''''' If there are more than three levels of sections in your PEP, you may insert overline/underline-adorned titles for the first and second levels as follows: ============================ First-Level Title (optional) ============================ ----------------------------- Second-Level Title (optional) ----------------------------- Third-Level Title ================= Fourth-Level Title ------------------ Fifth-Level Title ''''''''''''''''' You shouldn’t have more than five levels of sections in your PEP. If you do, you should consider rewriting it. You must use two blank lines between the last line of a section’s body and the next section heading. If a subsection heading immediately follows a section heading, a single blank line in-between is sufficient. The body of each section is not normally indented, although some constructs do use indentation, as described below. Blank lines are used to separate constructs. Paragraphs Paragraphs are left-aligned text blocks separated by blank lines. Paragraphs are not indented unless they are part of an indented construct (such as a block quote or a list item). Inline Markup Portions of text within paragraphs and other text blocks may be styled. For example: Text may be marked as *emphasized* (single asterisk markup, typically shown in italics) or **strongly emphasized** (double asterisks, typically boldface). ``Inline literals`` (using double backquotes) are typically rendered in a monospaced typeface. No further markup recognition is done within the double backquotes, so they're safe for any kind of code snippets. Block Quotes Block quotes consist of indented body elements. For example: This is a paragraph. This is a block quote. A block quote may contain many paragraphs. Block quotes are used to quote extended passages from other sources. Block quotes may be nested inside other body elements. Use 4 spaces per indent level. Literal Blocks Literal blocks are used for code samples and other preformatted text. To indicate a literal block, preface the indented text block with “::” (two colons), or use the .. code-block:: directive. Indent the text block by 4 spaces; the literal block continues until the end of the indentation. For example: This is a typical paragraph. A literal block follows. :: for a in [5, 4, 3, 2, 1]: # this is program code, shown as-is print(a) print("it's...") “::” is also recognized at the end of any paragraph; if not immediately preceded by whitespace, one colon will remain visible in the final output: This is an example:: Literal block By default, literal blocks will be syntax-highlighted as Python code. For specific blocks that contain code or data in other languages/formats, use the .. code-block:: language directive, substituting the “short name” of the appropriate Pygments lexer (or text to disable highlighting) for language. For example: .. code-block:: rst An example of the ``rst`` lexer (i.e. *reStructuredText*). For PEPs that predominantly contain literal blocks of a specific language, use the .. highlight:: language directive with the appropriate language at the top of the PEP body (below the headers and above the Abstract). All literal blocks will then be treated as that language, unless specified otherwise in the specific .. code-block. For example: .. highlight:: c Abstract ======== Here's some C code:: printf("Hello, World!\n"); Lists Bullet list items begin with one of “-”, “*”, or “+” (hyphen, asterisk, or plus sign), followed by whitespace and the list item body. List item bodies must be left-aligned and indented relative to the bullet; the text immediately after the bullet determines the indentation. For example: This paragraph is followed by a list. * This is the first bullet list item. The blank line above the first list item is required; blank lines between list items (such as below this paragraph) are optional. * This is the first paragraph in the second item in the list. This is the second paragraph in the second item in the list. The blank line above this paragraph is required. The left edge of this paragraph lines up with the paragraph above, both indented relative to the bullet. - This is a sublist. The bullet lines up with the left edge of the text blocks above. A sublist is a new list so requires a blank line above and below. * This is the third item of the main list. This paragraph is not part of the list. Enumerated (numbered) list items are similar, but use an enumerator instead of a bullet. Enumerators are numbers (1, 2, 3, …), letters (A, B, C, …; uppercase or lowercase), or Roman numerals (i, ii, iii, iv, …; uppercase or lowercase), formatted with a period suffix (“1.”, “2.”), parentheses (“(1)”, “(2)”), or a right-parenthesis suffix (“1)”, “2)”). For example: 1. As with bullet list items, the left edge of paragraphs must align. 2. Each list item may contain multiple paragraphs, sublists, etc. This is the second paragraph of the second list item. a) Enumerated lists may be nested. b) Blank lines may be omitted between list items. Definition lists are written like this: what Definition lists associate a term with a definition. how The term is a one-line phrase, and the definition is one or more paragraphs or body elements, indented relative to the term. Tables Simple tables are easy and compact: ===== ===== ======= A B A and B ===== ===== ======= False False False True False False False True False True True True ===== ===== ======= There must be at least two columns in a table (to differentiate from section titles). Column spans use underlines of hyphens (“Inputs” spans the first two columns): ===== ===== ====== Inputs Output ------------ ------ A B A or B ===== ===== ====== False False False True False True False True True True True True ===== ===== ====== Text in a first-column cell starts a new row. No text in the first column indicates a continuation line; the rest of the cells may consist of multiple lines. For example: ===== ========================= col 1 col 2 ===== ========================= 1 Second column of row 1. 2 Second column of row 2. Second line of paragraph. 3 - Second column of row 3. - Second item in bullet list (row 3, column 2). ===== ========================= Hyperlinks When referencing an external web page in the body of a PEP, you should include the title of the page or a suitable description in the text, with either an inline hyperlink or a separate explicit target with the URL. Do not include bare URLs in the body text of the PEP, and use HTTPS links wherever available. Hyperlink references use backquotes and a trailing underscore to mark up the reference text; backquotes are optional if the reference text is a single word. For example, to reference a hyperlink target named Python website, you would write: In this paragraph, we refer to the `Python website`_. If you intend to only reference a link once, and want to define it inline with the text, insert the link into angle brackets (<>) after the text you want to link, but before the closing backtick, with a space between the text and the opening backtick. You should also use a double-underscore after the closing backtick instead of a single one, which makes it an anonymous reference to avoid conflicting with other target names. For example: Visit the `website <https://www.python.org/>`__ for more. If you want to use one link multiple places with different linked text, or want to ensure you don’t have to update your link target names when changing the linked text, include the target name within angle brackets following the text to link, with an underscore after the target name but before the closing angle bracket (or the link will not work). For example: For further examples, see the `documentation <pydocs_>`_. An explicit target provides the URL. Put targets in the Footnotes section at the end of the PEP, or immediately after the paragraph with the reference. Hyperlink targets begin with two periods and a space (the “explicit markup start”), followed by a leading underscore, the reference text, a colon, and the URL. .. _Python web site: https://www.python.org/ .. _pydocs: https://docs.python.org/ The reference text and the target text must match (although the match is case-insensitive and ignores differences in whitespace). Note that the underscore trails the reference text but precedes the target text. If you think of the underscore as a right-pointing arrow, it points away from the reference and toward the target. Internal and PEP/RFC Links The same mechanism as hyperlinks can be used for internal references. Every unique section title implicitly defines an internal hyperlink target. We can make a link to the Abstract section like this: Here is a hyperlink reference to the `Abstract`_ section. The backquotes are optional since the reference text is a single word; we can also just write: Abstract_. To refer to PEPs or RFCs, always use the :pep: and :rfc: roles, never hardcoded URLs. For example: See :pep:`1` for more information on how to write a PEP, and :pep:`the Hyperlink section of PEP 12 <12#hyperlinks>` for how to link. This renders as: See PEP 1 for more information on how to write a PEP, and the Hyperlink section of PEP 12 for how to link. PEP numbers in the text are never padded, and there is a space (not a dash) between “PEP” or “RFC” and the number; the above roles will take care of that for you. Footnotes Footnote references consist of a left square bracket, a label, a right square bracket, and a trailing underscore. Instead of a number, use a label of the form “#word”, where “word” is a mnemonic consisting of alphanumerics plus internal hyphens, underscores, and periods (no whitespace or other characters are allowed). For example: Refer to The TeXbook [#TeXbook]_ for more information. which renders as Refer to The TeXbook [1] for more information. Whitespace must precede the footnote reference. Leave a space between the footnote reference and the preceding word. Use footnotes for additional notes, explanations and caveats, as well as for references to books and other sources not readily available online. Native reST hyperlink targets or inline hyperlinks in the text should be used in preference to footnotes for including URLs to online resources. Footnotes begin with “.. “ (the explicit markup start), followed by the footnote marker (no underscores), followed by the footnote body. For example: .. [#TeXbook] Donald Knuth's *The TeXbook*, pages 195 and 196. which renders as [1] Donald Knuth’s The TeXbook, pages 195 and 196. Footnotes and footnote references will be numbered automatically, and the numbers will always match. Images If your PEP contains a diagram or other graphic, you may include it in the processed output using the image directive: .. image:: diagram.png Any browser-friendly graphics format is possible; PNG should be preferred for graphics, JPEG for photos and GIF for animations. Currently, SVG must be avoided due to compatibility issues with the PEP build system. For accessibility and readers of the source text, you should include a description of the image and any key information contained within using the :alt: option to the image directive: .. image:: dataflow.png :alt: Data flows from the input module, through the "black box" module, and finally into (and through) the output module. Comments A comment is an indented block of arbitrary text immediately following an explicit markup start: two periods and whitespace. Leave the “..” on a line by itself to ensure that the comment is not misinterpreted as another explicit markup construct. Comments are not visible in the processed document. For example: .. This section should be updated in the final PEP. Ensure the date is accurate. Escaping Mechanism reStructuredText uses backslashes (”\”) to override the special meaning given to markup characters and get the literal characters themselves. To get a literal backslash, use an escaped backslash (”\\”). There are two contexts in which backslashes have no special meaning: literal blocks and inline literals (see Inline Markup above). In these contexts, no markup recognition is done, and a single backslash represents a literal backslash, without having to double up. If you find that you need to use a backslash in your text, consider using inline literals or a literal block instead. Canonical Documentation and Intersphinx As PEP 1 describes, PEPs are considered historical documents once marked Final, and their canonical documentation/specification should be moved elsewhere. To indicate this, use the canonical-doc directive or an appropriate subclass: canonical-pypa-spec for packaging standards canonical-typing-spec for typing standards Furthermore, you can use Intersphinx references to other Sphinx sites, currently the Python documentation and packaging.python.org, to easily cross-reference pages, sections and Python/C objects. This works with both the “canonical” directives and anywhere in your PEP. Add the directive between the headers and the first section of the PEP (typically the Abstract) and pass as an argument an Intersphinx reference of the canonical doc/spec (or if the target is not on a Sphinx site, a reST hyperlink). For example, to create a banner pointing to the sqlite3 docs, you would write the following: .. canonical-doc:: :mod:`python:sqlite3` which would generate the banner: Important This PEP is a historical document. The up-to-date, canonical documentation can now be found at sqlite3. × See PEP 1 for how to propose changes. Or for a PyPA spec, such as the Core metadata specifications, you would use: .. canonical-pypa-spec:: :ref:`packaging:core-metadata` which renders as: Attention This PEP is a historical document. The up-to-date, canonical spec, Core metadata specifications, is maintained on the PyPA specs page. × See the PyPA specification update process for how to propose changes. The argument accepts arbitrary reST, so you can include multiple linked docs/specs and name them whatever you like, and you can also include directive content that will be inserted into the text. The following advanced example: .. canonical-doc:: the :ref:`python:sqlite3-connection-objects` and :exc:`python:~sqlite3.DataError` docs Also, see the :ref:`Data Persistence docs <persistence>` for other examples. would render as: Important This PEP is a historical document. The up-to-date, canonical documentation can now be found at the Connection objects and sqlite3.DataError docs. × Also, see the Data Persistence docs for other examples. See PEP 1 for how to propose changes. Habits to Avoid Many programmers who are familiar with TeX often write quotation marks like this: `single-quoted' or ``double-quoted'' Backquotes are significant in reStructuredText, so this practice should be avoided. For ordinary text, use ordinary ‘single-quotes’ or “double-quotes”. For inline literal text (see Inline Markup above), use double-backquotes: ``literal text: in here, anything goes!`` Suggested Sections Various sections are found to be common across PEPs and are outlined in PEP 1. Those sections are provided here for convenience. PEP: <REQUIRED: pep number> Title: <REQUIRED: pep title> Author: <REQUIRED: list of authors' real names and optionally, email addrs> Sponsor: <real name of sponsor> PEP-Delegate: <PEP delegate's real name> Discussions-To: <REQUIRED: URL of current canonical discussion thread> Status: <REQUIRED: Draft | Active | Accepted | Provisional | Deferred | Rejected | Withdrawn | Final | Superseded> Type: <REQUIRED: Standards Track | Informational | Process> Topic: <Governance | Packaging | Release | Typing> Requires: <pep numbers> Created: <date created on, in dd-mmm-yyyy format> Python-Version: <version number> Post-History: <REQUIRED: dates, in dd-mmm-yyyy format, and corresponding links to PEP discussion threads> Replaces: <pep number> Superseded-By: <pep number> Resolution: <url> Abstract ======== [A short (~200 word) description of the technical issue being addressed.] Motivation ========== [Clearly explain why the existing language specification is inadequate to address the problem that the PEP solves.] Rationale ========= [Describe why particular design decisions were made.] Specification ============= [Describe the syntax and semantics of any new language feature.] Backwards Compatibility ======================= [Describe potential impact and severity on pre-existing code.] Security Implications ===================== [How could a malicious user take advantage of this new feature?] How to Teach This ================= [How to teach users, new and experienced, how to apply the PEP to their work.] Reference Implementation ======================== [Link to any existing implementation and details about its state, e.g. proof-of-concept.] Rejected Ideas ============== [Why certain ideas that were brought while discussing this PEP were not ultimately pursued.] Open Issues =========== [Any points that are still being decided/discussed.] Footnotes ========= [A collection of footnotes cited in the PEP, and a place to list non-inline hyperlink targets.] Copyright ========= This document is placed in the public domain or under the CC0-1.0-Universal license, whichever is more permissive. Resources Many other constructs and variations are possible, both those supported by basic Docutils and the extensions added by Sphinx. A number of resources are available to learn more about them: Sphinx ReStructuredText Primer, a gentle but fairly detailed introduction. reStructuredText Markup Specification, the authoritative, comprehensive documentation of the basic reST syntax, directives, roles and more. Sphinx Roles and Sphinx Directives, the extended constructs added by the Sphinx documentation system used to render the PEPs to HTML. If you have questions or require assistance with writing a PEP that the above resources don’t address, ping @python/pep-editors on GitHub, open an issue on the PEPs repository or reach out to a PEP editor directly. Copyright This document is placed in the public domain or under the CC0-1.0-Universal license, whichever is more permissive.

Active

PEP 12 – Sample reStructuredText PEP Template

Process

This PEP provides a boilerplate or sample template for creating your own reStructuredText PEPs. In conjunction with the content guidelines in PEP 1, this should make it easy for you to conform your own PEPs to the format outlined below.

PEP 13 – Python Language Governance Author: The Python core team and community Status: Active Type: Process Topic: Governance Created: 16-Dec-2018 Table of Contents Abstract Current steering council Specification The steering council Composition Mandate Powers Electing the council Term Vacancies Conflicts of interest Ejecting core team members Vote of no confidence The core team Role Prerogatives Membership Changing this document History Creation of this document History of council elections History of amendments Acknowledgements Copyright Abstract This PEP defines the formal governance process for Python, and records how this has changed over time. Currently, governance is based around a steering council. The council has broad authority, which they seek to exercise as rarely as possible. Current steering council The 2024 term steering council consists of: Barry Warsaw Emily Morehouse Gregory P. Smith Pablo Galindo Salgado Thomas Wouters Per the results of the vote tracked in PEP 8105. The core team consists of those listed in the private https://github.com/python/voters/ repository which is publicly shared via https://devguide.python.org/developers/. Specification The steering council Composition The steering council is a 5-person committee. Mandate The steering council shall work to: Maintain the quality and stability of the Python language and CPython interpreter, Make contributing as accessible, inclusive, and sustainable as possible, Formalize and maintain the relationship between the core team and the PSF, Establish appropriate decision-making processes for PEPs, Seek consensus among contributors and the core team before acting in a formal capacity, Act as a “court of final appeal” for decisions where all other methods have failed. Powers The council has broad authority to make decisions about the project. For example, they can: Accept or reject PEPs Enforce or update the project’s code of conduct Work with the PSF to manage any project assets Delegate parts of their authority to other subcommittees or processes However, they cannot modify this PEP, or affect the membership of the core team, except via the mechanisms specified in this PEP. The council should look for ways to use these powers as little as possible. Instead of voting, it’s better to seek consensus. Instead of ruling on individual PEPs, it’s better to define a standard process for PEP decision making (for example, by accepting one of the other 801x series of PEPs). It’s better to establish a Code of Conduct committee than to rule on individual cases. And so on. To use its powers, the council votes. Every council member must either vote or explicitly abstain. Members with conflicts of interest on a particular vote must abstain. Passing requires a strict majority of non-abstaining council members. Whenever possible, the council’s deliberations and votes shall be held in public. Electing the council A council election consists of two phases: Phase 1: Candidates advertise their interest in serving. Candidates must be nominated by a core team member. Self-nominations are allowed. Phase 2: Each core team member can vote for zero or more of the candidates. Voting is performed anonymously. Candidates are ranked by the total number of votes they receive. If a tie occurs, it may be resolved by mutual agreement among the candidates, or else the winner will be chosen at random. Each phase lasts one to two weeks, at the outgoing council’s discretion. For the initial election, both phases will last two weeks. The election process is managed by a returns officer nominated by the outgoing steering council. For the initial election, the returns officer will be nominated by the PSF Executive Director. The council should ideally reflect the diversity of Python contributors and users, and core team members are encouraged to vote accordingly. Term A new council is elected after each feature release. Each council’s term runs from when their election results are finalized until the next council’s term starts. There are no term limits. Vacancies Council members may resign their position at any time. Whenever there is a vacancy during the regular council term, the council may vote to appoint a replacement to serve out the rest of the term. If a council member drops out of touch and cannot be contacted for a month or longer, then the rest of the council may vote to replace them. Conflicts of interest While we trust council members to act in the best interests of Python rather than themselves or their employers, the mere appearance of any one company dominating Python development could itself be harmful and erode trust. In order to avoid any appearance of conflict of interest, at most 2 members of the council can work for any single employer. In a council election, if 3 of the top 5 vote-getters work for the same employer, then whichever of them ranked lowest is disqualified and the 6th-ranking candidate moves up into 5th place; this is repeated until a valid council is formed. During a council term, if changing circumstances cause this rule to be broken (for instance, due to a council member changing employment), then one or more council members must resign to remedy the issue, and the resulting vacancies can then be filled as normal. Ejecting core team members In exceptional circumstances, it may be necessary to remove someone from the core team against their will. (For example: egregious and ongoing code of conduct violations.) This can be accomplished by a steering council vote, but unlike other steering council votes, this requires at least a two-thirds majority. With 5 members voting, this means that a 3:2 vote is insufficient; 4:1 in favor is the minimum required for such a vote to succeed. In addition, this is the one power of the steering council which cannot be delegated, and this power cannot be used while a vote of no confidence is in process. If the ejected core team member is also on the steering council, then they are removed from the steering council as well. Vote of no confidence In exceptional circumstances, the core team may remove a sitting council member, or the entire council, via a vote of no confidence. A no-confidence vote is triggered when a core team member calls for one publicly on an appropriate project communication channel, and another core team member seconds the proposal. The vote lasts for two weeks. Core team members vote for or against. If at least two thirds of voters express a lack of confidence, then the vote succeeds. There are two forms of no-confidence votes: those targeting a single member, and those targeting the council as a whole. The initial call for a no-confidence vote must specify which type is intended. If a single-member vote succeeds, then that member is removed from the council and the resulting vacancy can be handled in the usual way. If a whole-council vote succeeds, the council is dissolved and a new council election is triggered immediately. The core team Role The core team is the group of trusted volunteers who manage Python. They assume many roles required to achieve the project’s goals, especially those that require a high level of trust. They make the decisions that shape the future of the project. Core team members are expected to act as role models for the community and custodians of the project, on behalf of the community and all those who rely on Python. They will intervene, where necessary, in online discussions or at official Python events on the rare occasions that a situation arises that requires intervention. They have authority over the Python Project infrastructure, including the Python Project website itself, the Python GitHub organization and repositories, the bug tracker, the mailing lists, IRC channels, etc. Prerogatives Core team members may participate in formal votes, typically to nominate new team members and to elect the steering council. Membership Python core team members demonstrate: a good grasp of the philosophy of the Python Project a solid track record of being constructive and helpful significant contributions to the project’s goals, in any form willingness to dedicate some time to improving Python As the project matures, contributions go beyond code. Here’s an incomplete list of areas where contributions may be considered for joining the core team, in no particular order: Working on community management and outreach Providing support on the mailing lists and on IRC Triaging tickets Writing patches (code, docs, or tests) Reviewing patches (code, docs, or tests) Participating in design decisions Providing expertise in a particular domain (security, i18n, etc.) Managing the continuous integration infrastructure Managing the servers (website, tracker, documentation, etc.) Maintaining related projects (alternative interpreters, core infrastructure like packaging, etc.) Creating visual designs Core team membership acknowledges sustained and valuable efforts that align well with the philosophy and the goals of the Python project. It is granted by receiving at least two-thirds positive votes in a core team vote that is open for one week and is not vetoed by the steering council. Core team members are always looking for promising contributors, teaching them how the project is managed, and submitting their names to the core team’s vote when they’re ready. There’s no time limit on core team membership. However, in order to provide the general public with a reasonable idea of how many people maintain Python, core team members who have stopped contributing are encouraged to declare themselves as “inactive”. Those who haven’t made any non-trivial contribution in two years may be asked to move themselves to this category, and moved there if they don’t respond. To record and honor their contributions, inactive team members will continue to be listed alongside active core team members; and, if they later resume contributing, they can switch back to active status at will. While someone is in inactive status, though, they lose their active privileges like voting or nominating for the steering council, and commit access. The initial active core team members will consist of everyone currently listed in the “Python core” team on GitHub (access granted for core members only), and the initial inactive members will consist of everyone else who has been a committer in the past. Changing this document Changes to this document require at least a two-thirds majority of votes cast in a core team vote which should be open for two weeks. History Creation of this document The Python project was started by Guido van Rossum, who served as its Benevolent Dictator for Life (BDFL) from inception until July 2018, when he stepped down. After discussion, a number of proposals were put forward for a new governance model, and the core devs voted to choose between them. The overall process is described in PEP 8000 and PEP 8001, a review of other projects was performed in PEP 8002, and the proposals themselves were written up as the 801x series of PEPs. Eventually the proposal in PEP 8016 was selected as the new governance model, and was used to create the initial version of this PEP. The 8000-series PEPs are preserved for historical reference (and in particular, PEP 8016 contains additional rationale and links to contemporary discussions), but this PEP is now the official reference, and will evolve following the rules described herein. History of council elections January 2019: PEP 8100 December 2019: PEP 8101 December 2020: PEP 8102 December 2021: PEP 8103 December 2022: PEP 8104 December 2023: PEP 8105 History of amendments 2019-04-17: Added the vote length for core devs and changes to this document. Acknowledgements This PEP began as PEP 8016, which was written by Nathaniel J. Smith and Donald Stufft, based on a Django governance document written by Aymeric Augustin, and incorporated feedback and assistance from numerous others. Copyright This document has been placed in the public domain.

Active

PEP 13 – Python Language Governance

Process

This PEP defines the formal governance process for Python, and records how this has changed over time. Currently, governance is based around a steering council. The council has broad authority, which they seek to exercise as rarely as possible.

PEP 20 – The Zen of Python Author: Tim Peters <tim.peters at gmail.com> Status: Active Type: Informational Created: 19-Aug-2004 Post-History: 22-Aug-2004 Table of Contents Abstract The Zen of Python Easter Egg References Copyright Abstract Long time Pythoneer Tim Peters succinctly channels the BDFL’s guiding principles for Python’s design into 20 aphorisms, only 19 of which have been written down. The Zen of Python Beautiful is better than ugly. Explicit is better than implicit. Simple is better than complex. Complex is better than complicated. Flat is better than nested. Sparse is better than dense. Readability counts. Special cases aren't special enough to break the rules. Although practicality beats purity. Errors should never pass silently. Unless explicitly silenced. In the face of ambiguity, refuse the temptation to guess. There should be one-- and preferably only one --obvious way to do it. Although that way may not be obvious at first unless you're Dutch. Now is better than never. Although never is often better than *right* now. If the implementation is hard to explain, it's a bad idea. If the implementation is easy to explain, it may be a good idea. Namespaces are one honking great idea -- let's do more of those! Easter Egg >>> import this References Originally posted to comp.lang.python/[email protected] under a thread called “The Way of Python” Copyright This document has been placed in the public domain.

Active

PEP 20 – The Zen of Python

Informational

Long time Pythoneer Tim Peters succinctly channels the BDFL’s guiding principles for Python’s design into 20 aphorisms, only 19 of which have been written down.

PEP 101 – Doing Python Releases 101 Author: Barry Warsaw <barry at python.org>, Guido van Rossum <guido at python.org> Status: Active Type: Informational Created: 22-Aug-2001 Post-History: Replaces: 102 Table of Contents Abstract Things You’ll Need Types of Releases How To Make A Release What Next? Moving to End-of-life Windows Notes Copyright Abstract Making a Python release is a thrilling and crazy process. You’ve heard the expression “herding cats”? Imagine trying to also saddle those purring little creatures up, and ride them into town, with some of their buddies firmly attached to your bare back, anchored by newly sharpened claws. At least they’re cute, you remind yourself. Actually, no, that’s a slight exaggeration 😉 The Python release process has steadily improved over the years and now, with the help of our amazing community, is really not too difficult. This PEP attempts to collect, in one place, all the steps needed to make a Python release. Most of the steps are now automated or guided by automation, so manually following this list is no longer necessary. Things You’ll Need As a release manager there are a lot of resources you’ll need to access. Here’s a hopefully-complete list. A GPG key.Python releases are digitally signed with GPG; you’ll need a key, which hopefully will be on the “web of trust” with at least one of the other release managers. A bunch of software: A checkout of the python/release-tools repo. It contains a requirements.txt file that you need to install dependencies from first. Afterwards, you can fire up scripts in the repo, covered later in this PEP. blurb, the Misc/NEWS management tool. You can pip install it. A fairly complete installation of a recent TeX distribution, such as texlive. You need that for building the PDF docs. Access to servers where you will upload files: downloads.nyc1.psf.io, the server that hosts download files; and docs.nyc1.psf.io, the server that hosts the documentation. Administrator access to https://github.com/python/cpython. An administrator account on www.python.org, including an “API key”. Write access to the PEP repository.If you’re reading this, you probably already have this–the first task of any release manager is to draft the release schedule. But in case you just signed up… sucker! I mean, uh, congratulations! Posting access to http://blog.python.org, a Blogger-hosted weblog. The RSS feed from this blog is used for the ‘Python News’ section on www.python.org. A subscription to the super secret release manager mailing list, which may or may not be called python-cabal. Bug Barry about this. A @python.org email address that you will use to sign your releases with. Ask postmaster@ for an address; you can either get a full account, or a redirecting alias + SMTP credentials to send email from this address that looks legit to major email providers. Types of Releases There are several types of releases you will need to make. These include: alpha begin beta, also known as beta 1, also known as new branch beta 2+ release candidate 1 release candidate 2+ final new branch begin bugfix mode begin security-only mode end-of-life Some of these release types actually involve more than one release branch. In particular, a new branch is that point in the release cycle when a new feature release cycle begins. Under the current organization of the cpython git repository, the main branch is always the target for new features. At some point in the release cycle of the next feature release, a new branch release is made which creates a new separate branch for stabilization and later maintenance of the current in-progress feature release (3.n.0) and the main branch is modified to build a new version (which will eventually be released as 3.n+1.0). While the new branch release step could occur at one of several points in the release cycle, current practice is for it to occur at feature code cutoff for the release which is scheduled for the first beta release. In the descriptions that follow, steps specific to release types are labeled accordingly, for now, new branch and final. How To Make A Release Here are the steps taken to make a Python release. Some steps are more fuzzy than others because there’s little that can be automated (e.g. writing the NEWS entries). Where a step is usually performed by An Expert, the role of that expert is given. Otherwise, assume the step is done by the Release Manager (RM), the designated person performing the release. The roles and their current experts are: RM = Release Manager Thomas Wouters <[email protected]> (NL) Pablo Galindo Salgado <[email protected]> (UK) Łukasz Langa <[email protected]> (PL) WE = Windows - Steve Dower <[email protected]> ME = Mac - Ned Deily <[email protected]> (US) DE = Docs - Julien Palard <[email protected]> (Central Europe) Note It is highly recommended that the RM contact the Experts the day before the release. Because the world is round and everyone lives in different timezones, the RM must ensure that the release tag is created in enough time for the Experts to cut binary releases. You should not make the release public (by updating the website and sending announcements) before all experts have updated their bits. In rare cases where the expert for Windows or Mac is MIA, you may add a message “(Platform) binaries will be provided shortly” and proceed. As much as possible, the release steps are automated and guided by the release script, which is available in a separate repository: https://github.com/python/release-tools We use the following conventions in the examples below. Where a release number is given, it is of the form 3.X.YaN, e.g. 3.13.0a3 for Python 3.13.0 alpha 3, where “a” == alpha, “b” == beta, “rc” == release candidate. Release tags are named v3.X.YaN. The branch name for minor release maintenance branches is 3.X. This helps by performing several automatic editing steps, and guides you to perform some manual editing steps. Log into Discord and join the Python Core Devs server. Ask Thomas or Łukasz for an invite.You probably need to coordinate with other people around the world. This communication channel is where we’ve arranged to meet. Check to see if there are any showstopper bugs.Go to https://github.com/python/cpython/issues and look for any open bugs that can block this release. You’re looking at two relevant labels: release-blockerStops the release dead in its tracks. You may not make any release with any open release blocker bugs. deferred-blockerDoesn’t block this release, but it will block a future release. You may not make a final or candidate release with any open deferred blocker bugs. Review the release blockers and either resolve them, bump them down to deferred, or stop the release and ask for community assistance. If you’re making a final or candidate release, do the same with any open deferred. Check the stable buildbots.Go to https://buildbot.python.org/all/#/release_status Look at the buildbots for the release you’re making. Ignore any that are offline (or inform the community so they can be restarted). If what remains are (mostly) green buildbots, you’re good to go. If you have non-offline red buildbots, you may want to hold up the release until they are fixed. Review the problems and use your judgement, taking into account whether you are making an alpha, beta, or final release. Make a release clone.On a fork of the cpython repository on GitHub, create a release branch within it (called the “release clone” from now on). You can use the same GitHub fork you use for cpython development. Using the standard setup recommended in the Python Developer’s Guide, your fork would be referred to as origin and the standard cpython repo as upstream. You will use the branch on your fork to do the release engineering work, including tagging the release, and you will use it to share with the other experts for making the binaries. For a final or release candidate 2+ release, if you are going to cherry-pick a subset of changes for the next rc or final from all those merged since the last rc, you should create a release engineering branch starting from the most recent release candidate tag, i.e. v3.8.0rc1. You will then cherry-pick changes from the standard release branch as necessary into the release engineering branch and then proceed as usual. If you are going to take all of the changes since the previous rc, you can proceed as normal. Make sure the current branch of your release clone is the branch you want to release from. (git status) Run blurb release <version> specifying the version number (e.g. blurb release 3.4.7rc1). This merges all the recent news blurbs into a single file marked with this release’s version number. Regenerate Lib/pydoc-topics.py.While still in the Doc directory, run make pydoc-topics. Then copy build/pydoc-topics/topics.py to ../Lib/pydoc_data/topics.py. Commit your changes to pydoc_topics.py (and any fixes you made in the docs). Consider running autoconf using the currently accepted standard version in case configure or other autoconf-generated files were last committed with a newer or older version and may contain spurious or harmful differences. Currently, autoconf 2.71 is our de facto standard. if there are differences, commit them. Make sure the SOURCE_URI in Doc/tools/extensions/pyspecific.py points to the right branch in the git repository (main or 3.X). For a new branch release, change the branch in the file from main to the new release branch you are about to create (3.X). Bump version numbers via the release script:$ .../release-tools/release.py --bump 3.X.YaN Reminder: X, Y, and N should be integers. a should be one of “a”, “b”, or “rc” (e.g. “3.4.3rc1”). For final releases omit the aN (“3.4.3”). For the first release of a new version Y should be 0 (“3.6.0”). This automates updating various release numbers, but you will have to modify a few files manually. If your $EDITOR environment variable is set up correctly, release.py will pop up editor windows with the files you need to edit. Review the blurb-generated Misc/NEWS file and edit as necessary. Make sure all changes have been committed. (release.py --bump doesn’t check in its changes for you.) Check the years on the copyright notice. If the last release was some time last year, add the current year to the copyright notice in several places: README LICENSE (make sure to change on trunk and the branch) Python/getcopyright.c Doc/copyright.rst Doc/license.rst PC/python_ver_rc.h sets up the DLL version resource for Windows (displayed when you right-click on the DLL and select Properties). This isn’t a C include file, it’s a Windows “resource file” include file. For a final major release, edit the first paragraph of Doc/whatsnew/3.X.rst to include the actual release date; e.g. “Python 2.5 was released on August 1, 2003.” There’s no need to edit this for alpha or beta releases. Do a “git status” in this directory.You should not see any files. I.e. you better not have any uncommitted changes in your working directory. Tag the release for 3.X.YaN:$ .../release-tools/release.py --tag 3.X.YaN This executes a git tag command with the -s option so that the release tag in the repo is signed with your gpg key. When prompted choose the private key you use for signing release tarballs etc. For begin security-only mode and end-of-life releases, review the two files and update the versions accordingly in all active branches. Time to build the source tarball. Use the release script to create the source gzip and xz tarballs, documentation tar and zip files, and gpg signature files:$ .../release-tools/release.py --export 3.X.YaN This can take a while for final releases, and it will leave all the tarballs and signatures in a subdirectory called 3.X.YaN/src, and the built docs in 3.X.YaN/docs (for final releases). Note that the script will sign your release with Sigstore. Please use your @python.org email address for this. See here for more information: https://www.python.org/download/sigstore/. Now you want to perform the very important step of checking the tarball you just created, to make sure a completely clean, virgin build passes the regression test. Here are the best steps to take:$ cd /tmp $ tar xvf /path/to/your/release/clone/<version>//Python-3.2rc2.tgz $ cd Python-3.2rc2 $ ls (Do things look reasonable?) $ ls Lib (Are there stray .pyc files?) $ ./configure (Loads of configure output) $ make test (Do all the expected tests pass?) If you’re feeling lucky and have some time to kill, or if you are making a release candidate or final release, run the full test suite: $ make testall If the tests pass, then you can feel good that the tarball is fine. If some of the tests fail, or anything else about the freshly unpacked directory looks weird, you better stop now and figure out what the problem is. Push your commits to the remote release branch in your GitHub fork.:# Do a dry run first. $ git push --dry-run --tags origin # Make sure you are pushing to your GitHub fork, *not* to the main # python/cpython repo! $ git push --tags origin Notify the experts that they can start building binaries. Warning STOP: at this point you must receive the “green light” from other experts in order to create the release. There are things you can do while you wait though, so keep reading until you hit the next STOP. The WE generates and publishes the Windows files using the Azure Pipelines build scripts in .azure-pipelines/windows-release/, currently set up at https://dev.azure.com/Python/cpython/_build?definitionId=21.The build process runs in multiple stages, with each stage’s output being available as a downloadable artifact. The stages are: Compile all variants of binaries (32-bit, 64-bit, debug/release), including running profile-guided optimization. Compile the HTML Help file containing the Python documentation Codesign all the binaries with the PSF’s certificate Create packages for python.org, nuget.org, the embeddable distro and the Windows Store Perform basic verification of the installers Upload packages to python.org and nuget.org, purge download caches and run a test download. After the uploads are complete, the WE copies the generated hashes from the build logs and emails them to the RM. The Windows Store packages are uploaded manually to https://partner.microsoft.com/dashboard/home by the WE. The ME builds Mac installer packages and uploads them to downloads.nyc1.psf.io together with gpg signature files. scp or rsync all the files built by release.py --export to your home directory on downloads.nyc1.psf.io.While you’re waiting for the files to finish uploading, you can continue on with the remaining tasks. You can also ask folks on #python-dev and/or python-committers to download the files as they finish uploading so that they can test them on their platforms as well. Now you need to go to downloads.nyc1.psf.io and move all the files in place over there. Our policy is that every Python version gets its own directory, but each directory contains all releases of that version. On downloads.nyc1.psf.io, cd /srv/www.python.org/ftp/python/3.X.Y creating it if necessary. Make sure it is owned by group ‘downloads’ and group-writable. Move the release .tgz, and .tar.xz files into place, as well as the .asc GPG signature files. The Win/Mac binaries are usually put there by the experts themselves.Make sure they are world readable. They should also be group writable, and group-owned by downloads. Use gpg --verify to make sure they got uploaded intact. If this is a final or rc release: Move the doc zips and tarballs to /srv/www.python.org/ftp/python/doc/3.X.Y[rcA], creating the directory if necessary, and adapt the “current” symlink in .../doc to point to that directory. Note though that if you’re releasing a maintenance release for an older version, don’t change the current link. If this is a final or rc release (even a maintenance release), also unpack the HTML docs to /srv/docs.python.org/release/3.X.Y[rcA] on docs.nyc1.psf.io. Make sure the files are in group docs and are group-writeable. Let the DE check if the docs are built and work all right. Note both the documentation and downloads are behind a caching CDN. If you change archives after downloading them through the website, you’ll need to purge the stale data in the CDN like this:$ curl -X PURGE https://www.python.org/ftp/python/3.12.0/Python-3.12.0.tar.xz You should always purge the cache of the directory listing as people use that to browse the release files: $ curl -X PURGE https://www.python.org/ftp/python/3.12.0/ For the extra paranoid, do a completely clean test of the release. This includes downloading the tarball from www.python.org.Make sure the md5 checksums match. Then unpack the tarball, and do a clean make test.: $ make distclean $ ./configure $ make test To ensure that the regression test suite passes. If not, you screwed up somewhere! Warning STOP and confirm: Have you gotten the green light from the WE? Have you gotten the green light from the ME? Have you gotten the green light from the DE? If green, it’s time to merge the release engineering branch back into the main repo. In order to push your changes to GitHub, you’ll have to temporarily disable branch protection for administrators. Go to the Settings | Branches page:https://github.com/python/cpython/settings/branches/ “Edit” the settings for the branch you’re releasing on. This will load the settings page for that branch. Uncheck the “Include administrators” box and press the “Save changes” button at the bottom. Merge your release clone into the main development repo:# Pristine copy of the upstream repo branch $ git clone [email protected]:python/cpython.git merge $ cd merge # Checkout the correct branch: # 1. For feature pre-releases up to and including a # **new branch** release, i.e. alphas and first beta # do a checkout of the main branch $ git checkout main # 2. Else, for all other releases, checkout the # appropriate release branch. $ git checkout 3.X # Fetch the newly created and signed tag from your clone repo $ git fetch --tags [email protected]:your-github-id/cpython.git v3.X.YaN # Merge the temporary release engineering branch back into $ git merge --no-squash v3.X.YaN $ git commit -m 'Merge release engineering branch' If this is a new branch release, i.e. first beta, now create the new release branch:$ git checkout -b 3.X Do any steps needed to setup the new release branch, including: In README.rst, change all references from main to the new branch, in particular, GitHub repo URLs. For all releases, do the guided post-release steps with the release script.:$ .../release-tools/release.py --done 3.X.YaN For a final or release candidate 2+ release, you may need to do some post-merge cleanup. Check the top-level README.rst and include/patchlevel.h files to ensure they now reflect the desired post-release values for on-going development. The patchlevel should be the release tag with a +. Also, if you cherry-picked changes from the standard release branch into the release engineering branch for this release, you will now need to manual remove each blurb entry from the Misc/NEWS.d/next directory that was cherry-picked into the release you are working on since that blurb entry is now captured in the merged x.y.z.rst file for the new release. Otherwise, the blurb entry will appear twice in the changelog.html file, once under Python next and again under x.y.z. Review and commit these changes:$ git commit -m 'Post release updates' If this is a new branch release (e.g. the first beta), update the main branch to start development for the following feature release. When finished, the main branch will now build Python X.Y+1. First, set main up to be the next release, i.e.X.Y+1.a0:$ git checkout main $ .../release-tools/release.py --bump 3.9.0a0 Edit all version references in README.rst Move any historical “what’s new” entries from Misc/NEWS to Misc/HISTORY. Edit Doc/tutorial/interpreter.rst (2 references to ‘[Pp]ython3x’, one to ‘Python 3.x’, also make the date in the banner consistent). Edit Doc/tutorial/stdlib.rst and Doc/tutorial/stdlib2.rst, which have each one reference to ‘[Pp]ython3x’. Add a new whatsnew/3.x.rst file (with the comment near the top and the toplevel sections copied from the previous file) and add it to the toctree in whatsnew/index.rst. But beware that the initial whatsnew/3.x.rst checkin from previous releases may be incorrect due to the initial midstream change to blurb that propagates from release to release! Help break the cycle: if necessary make the following change:- For full details, see the :source:`Misc/NEWS` file. + For full details, see the :ref:`changelog <changelog>`. Update the version number in configure.ac and re-run autoconf. Make sure the SOURCE_URI in Doc/tools/extensions/pyspecific.py points to main. Update the version numbers for the Windows builds in PC/ and PCbuild/, which have references to python38. NOTE, check with Steve Dower about this step, it is probably obsolete.:$ find PC/ PCbuild/ -type f | xargs sed -i 's/python38/python39/g' $ git mv -f PC/os2emx/python38.def PC/os2emx/python39.def $ git mv -f PC/python38stub.def PC/python39stub.def $ git mv -f PC/python38gen.py PC/python39gen.py Commit these changes to the main branch:$ git status $ git add ... $ git commit -m 'Bump to 3.9.0a0' Do another git status in this directory.You should not see any files. I.e. you better not have any uncommitted changes in your working directory. Commit and push to the main repo.:# Do a dry run first. # For feature pre-releases prior to a **new branch** release, # i.e. a feature alpha release: $ git push --dry-run --tags [email protected]:python/cpython.git main # If it looks OK, take the plunge. There's no going back! $ git push --tags [email protected]:python/cpython.git main # For a **new branch** release, i.e. first beta: $ git push --dry-run --tags [email protected]:python/cpython.git 3.X $ git push --dry-run --tags [email protected]:python/cpython.git main # If it looks OK, take the plunge. There's no going back! $ git push --tags [email protected]:python/cpython.git 3.X $ git push --tags [email protected]:python/cpython.git main # For all other releases: $ git push --dry-run --tags [email protected]:python/cpython.git 3.X # If it looks OK, take the plunge. There's no going back! $ git push --tags [email protected]:python/cpython.git 3.X If this is a new branch release, add a Branch protection rule for the newly created branch (3.X). Look at the values for the previous release branch (3.X-1) and use them as a template. https://github.com/python/cpython/settings/branches/Also, add a needs backport to 3.X label to the GitHub repo. https://github.com/python/cpython/labels You can now re-enable enforcement of branch settings against administrators on GitHub. Go back to the Settings | Branch page:https://github.com/python/cpython/settings/branches/ “Edit” the settings for the branch you’re releasing on. Re-check the “Include administrators” box and press the “Save changes” button at the bottom. Now it’s time to twiddle the web site. Almost none of this is automated, sorry. To do these steps, you must have the permission to edit the website. If you don’t have that, ask someone on [email protected] for the proper permissions. (Or ask Ewa, who coordinated the effort for the new website with RevSys.) Log in to https://www.python.org/admin . Create a new “release” for the release. Currently “Releases” are sorted under “Downloads”.The easiest thing is probably to copy fields from an existing Python release “page”, editing as you go. You can use Markdown or ReStructured Text to describe your release. The former is less verbose, while the latter has nifty integration for things like referencing PEPs. Leave the “Release page” field on the form empty. “Save” the release. Populate the release with the downloadable files.Your friend and mine, Georg Brandl, made a lovely tool called “add-to-pydotorg.py”. You can find it in the “release” tree (next to “release.py”). You run the tool on downloads.nyc1.psf.io, like this: $ AUTH_INFO=<username>:<python.org-api-key> python add-to-pydotorg.py <version> This walks the correct download directory for <version>, looks for files marked with <version>, and populates the “Release Files” for the correct “release” on the web site with these files. Note that clears the “Release Files” for the relevant version each time it’s run. You may run it from any directory you like, and you can run it as many times as you like if the files happen to change. Keep a copy in your home directory on dl-files and keep it fresh. If new types of files are added to the release, someone will need to update add-to-pydotorg.py so it recognizes these new files. (It’s best to update add-to-pydotorg.py when file types are removed, too.) The script will also sign any remaining files that were not signed with Sigstore until this point. Again, if this happens, do use your @python.org address for this process. More info: https://www.python.org/download/sigstore/ In case the CDN already cached a version of the Downloads page without the files present, you can invalidate the cache using:$ curl -X PURGE https://www.python.org/downloads/release/python-XXX/ If this is a final release: Add the new version to the Python Documentation by Version page https://www.python.org/doc/versions/ and remove the current version from any ‘in development’ section. For 3.X.Y, edit all the previous X.Y releases’ page(s) to point to the new release. This includes the content field of the Downloads -> Releases entry for the release:Note: Python 3.x.(y-1) has been superseded by `Python 3.x.y </downloads/release/python-3xy/>`_. And, for those releases having separate release page entries (phasing these out?), update those pages as well, e.g. download/releases/3.x.y: Note: Python 3.x.(y-1) has been superseded by `Python 3.x.y </download/releases/3.x.y/>`_. Update the “Current Pre-release Testing Versions web page”.There’s a page that lists all the currently-in-testing versions of Python: https://www.python.org/download/pre-releases/ Every time you make a release, one way or another you’ll have to update this page: If you’re releasing a version before 3.x.0, you should add it to this page, removing the previous pre-release of version 3.x as needed. If you’re releasing 3.x.0 final, you need to remove the pre-release version from this page. This is in the “Pages” category on the Django-based website, and finding it through that UI is kind of a chore. However! If you’re already logged in to the admin interface (which, at this point, you should be), Django will helpfully add a convenient “Edit this page” link to the top of the page itself. So you can simply follow the link above, click on the “Edit this page” link, and make your changes as needed. How convenient! If appropriate, update the “Python Documentation by Version” page: https://www.python.org/doc/versions/ This lists all releases of Python by version number and links to their static (not built daily) online documentation. There’s a list at the bottom of in-development versions, which is where all alphas/betas/RCs should go. And yes you should be able to click on the link above then press the shiny, exciting “Edit this page” button. Write the announcement on https://discuss.python.org/. This is the fuzzy bit because not much can be automated. You can use an earlier announcement as a template, but edit it for content! Once the announcement is up on Discourse, send an equivalent to the following mailing lists:[email protected] [email protected] [email protected] Also post the announcement to The Python Insider blog. To add a new entry, go to your Blogger home page, here. Update any release PEPs (e.g. 719) with the release dates. Update the labels on https://github.com/python/cpython/issues: Flip all the deferred-blocker issues back to release-blocker for the next release. Add version 3.X+1 as when version 3.X enters alpha. Change non-doc feature requests to version 3.X+1 when version 3.X enters beta. Update issues from versions that your release makes unsupported to the next supported version. Review open issues, as this might find lurking showstopper bugs, besides reminding people to fix the easy ones they forgot about. You can delete the remote release clone branch from your repo clone. If this is a new branch release, you will need to ensure various pieces of the development infrastructure are updated for the new branch. These include: Update the issue tracker for the new branch: add the new version to the versions list. Update the devguide to reflect the new branches and versions. Create a PR to update the supported releases table on the downloads page. (See https://github.com/python/pythondotorg/issues/1302) Ensure buildbots are defined for the new branch (contact Łukasz or Zach Ware). Ensure the various GitHub bots are updated, as needed, for the new branch, in particular, make sure backporting to the new branch works (contact core-workflow team) https://github.com/python/core-workflow/issues Review the most recent commit history for the main and new release branches to identify and backport any merges that might have been made to the main branch during the release engineering phase and that should be in the release branch. Verify that CI is working for new PRs for the main and new release branches and that the release branch is properly protected (no direct pushes, etc). Verify that the on-line docs are building properly (this may take up to 24 hours for a complete build on the web site). What Next? Verify! Pretend you’re a user: download the files from python.org, and make Python from it. This step is too easy to overlook, and on several occasions we’ve had useless release files. Once a general server problem caused mysterious corruption of all files; once the source tarball got built incorrectly; more than once the file upload process on SF truncated files; and so on. Rejoice. Drink. Be Merry. Write a PEP like this one. Or be like unto Guido and take A Vacation. You’ve just made a Python release! Moving to End-of-life Under current policy, a release branch normally reaches end-of-life status 5 years after its initial release. The policy is discussed in more detail in the Python Developer’s Guide. When end-of-life is reached, there are a number of tasks that need to be performed either directly by you as release manager or by ensuring someone else does them. Some of those tasks include: Optionally making a final release to publish any remaining unreleased changes. Freeze the state of the release branch by creating a tag of its current HEAD and then deleting the branch from the cpython repo. The current HEAD should be at or beyond the final security release for the branch:git fetch upstream git tag --sign -m 'Final head of the former 3.3 branch' 3.3 upstream/3.3 git push upstream refs/tags/3.3 If all looks good, delete the branch. This may require the assistance of someone with repo administrator privileges:git push upstream --delete 3.3 # or perform from GitHub Settings page Remove the release from the list of “Active Python Releases” on the Downloads page. To do this, log in to the admin page for python.org, navigate to Boxes, and edit the downloads-active-releases entry. Simply strip out the relevant paragraph of HTML for your release. (You’ll probably have to do the curl -X PURGE trick to purge the cache if you want to confirm you made the change correctly.) Add retired notice to each release page on python.org for the retired branch. For example: https://www.python.org/downloads/release/python-337/https://www.python.org/downloads/release/python-336/ In the developer’s guide, add the branch to the recent end-of-life branches list (https://devguide.python.org/devcycle/#end-of-life-branches) and update or remove references to the branch elsewhere in the devguide. Retire the release from the issue tracker. Tasks include: remove version label from list of versions remove the “needs backport to” label for the retired version review and dispose of open issues marked for this branch Announce the branch retirement in the usual places: discuss.python.org mailing lists (python-dev, python-list, python-announcements) Python Dev blog Enjoy your retirement and bask in the glow of a job well done! Windows Notes Windows has a MSI installer, various flavors of Windows have “special limitations”, and the Windows installer also packs precompiled “foreign” binaries (Tcl/Tk, expat, etc). The installer is tested as part of the Azure Pipeline. In the past, those steps were performed manually. We’re keeping this for posterity. Concurrent with uploading the installer, the WE installs Python from it twice: once into the default directory suggested by the installer, and later into a directory with embedded spaces in its name. For each installation, the WE runs the full regression suite from a DOS box, and both with and without -0. For maintenance release, the WE also tests whether upgrade installations succeed. The WE also tries every shortcut created under Start -> Menu -> the Python group. When trying IDLE this way, you need to verify that Help -> Python Documentation works. When trying pydoc this way (the “Module Docs” Start menu entry), make sure the “Start Browser” button works, and make sure you can search for a random module (like “random” <wink>) and then that the “go to selected” button works. It’s amazing how much can go wrong here – and even more amazing how often last-second checkins break one of these things. If you’re “the Windows geek”, keep in mind that you’re likely the only person routinely testing on Windows, and that Windows is simply a mess. Repeat the testing for each target architecture. Try both an Admin and a plain User (not Power User) account. Copyright This document has been placed in the public domain.

Active

PEP 101 – Doing Python Releases 101

Informational

Making a Python release is a thrilling and crazy process. You’ve heard the expression “herding cats”? Imagine trying to also saddle those purring little creatures up, and ride them into town, with some of their buddies firmly attached to your bare back, anchored by newly sharpened claws. At least they’re cute, you remind yourself.

PEP 102 – Doing Python Micro Releases Author: Anthony Baxter <anthony at interlink.com.au>, Barry Warsaw <barry at python.org>, Guido van Rossum <guido at python.org> Status: Superseded Type: Informational Created: 09-Jan-2002 Post-History: Superseded-By: 101 Table of Contents Replacement Note Abstract How to Make A Release What Next? Final Release Notes Windows Notes Copyright Replacement Note Although the size of the to-do list in this PEP is much less scary than that in PEP 101, it turns out not to be enough justification for the duplication of information, and with it, the danger of one of the copies to become out of date. Therefore, this PEP is not maintained anymore, and micro releases are fully covered by PEP 101. Abstract Making a Python release is an arduous process that takes a minimum of half a day’s work even for an experienced releaser. Until recently, most – if not all – of that burden was borne by Guido himself. But several recent releases have been performed by other folks, so this PEP attempts to collect, in one place, all the steps needed to make a Python bugfix release. The major Python release process is covered in PEP 101 - this PEP is just PEP 101, trimmed down to only include the bits that are relevant for micro releases, a.k.a. patch, or bug fix releases. It is organized as a recipe and you can actually print this out and check items off as you complete them. How to Make A Release Here are the steps taken to make a Python release. Some steps are more fuzzy than others because there’s little that can be automated (e.g. writing the NEWS entries). Where a step is usually performed by An Expert, the name of that expert is given. Otherwise, assume the step is done by the Release Manager (RM), the designated person performing the release. Almost every place the RM is mentioned below, this step can also be done by the BDFL of course! XXX: We should include a dependency graph to illustrate the steps that can be taken in parallel, or those that depend on other steps. We use the following conventions in the examples below. Where a release number is given, it is of the form X.Y.MaA, e.g. 2.1.2c1 for Python 2.1.2 release candidate 1, where “a” == alpha, “b” == beta, “c” == release candidate. Final releases are tagged with “releaseXYZ” in CVS. The micro releases are made from the maintenance branch of the major release, e.g. Python 2.1.2 is made from the release21-maint branch. Send an email to [email protected] indicating the release is about to start. Put a freeze on check ins into the maintenance branch. At this point, nobody except the RM should make any commits to the branch (or his duly assigned agents, i.e. Guido the BDFL, Fred Drake for documentation, or Thomas Heller for Windows). If the RM screwed up and some desperate last minute change to the branch is necessary, it can mean extra work for Fred and Thomas. So try to avoid this! On the branch, change Include/patchlevel.h in two places, to reflect the new version number you’ve just created. You’ll want to change the PY_VERSION macro, and one or several of the version subpart macros just above PY_VERSION, as appropriate. Change the “%define version” line of Misc/RPM/python-2.3.spec to the same string as PY_VERSION was changed to above. E.g:%define version 2.3.1 You also probably want to reset the %define release line to ‘1pydotorg’ if it’s not already that. If you’re changing the version number for Python (e.g. from Python 2.1.1 to Python 2.1.2), you also need to update the README file, which has a big banner at the top proclaiming its identity. Don’t do this if you’re just releasing a new alpha or beta release, but /do/ do this if you’re release a new micro, minor or major release. The LICENSE file also needs to be changed, due to several references to the release number. As for the README file, changing these are necessary for a new micro, minor or major release.The LICENSE file contains a table that describes the legal heritage of Python; you should add an entry for the X.Y.Z release you are now making. You should update this table in the LICENSE file on the CVS trunk too. When the year changes, copyright legends need to be updated in many places, including the README and LICENSE files. For the Windows build, additional files have to be updated.PCbuild/BUILDno.txt contains the Windows build number, see the instructions in this file how to change it. Saving the project file PCbuild/pythoncore.dsp results in a change to PCbuild/pythoncore.dsp as well. PCbuild/python20.wse sets up the Windows installer version resource (displayed when you right-click on the installer .exe and select Properties), and also contains the Python version number. (Before version 2.3.2, it was required to manually edit PC/python_nt.rc, this step is now automated by the build process.) After starting the process, the most important thing to do next is to update the Misc/NEWS file. Thomas will need this in order to do the Windows release and he likes to stay up late. This step can be pretty tedious, so it’s best to get to it immediately after making the branch, or even before you’ve made the branch. The sooner the better (but again, watch for new checkins up until the release is made!)Add high level items new to this release. E.g. if we’re releasing 2.2a3, there must be a section at the top of the file explaining “What’s new in Python 2.2a3”. It will be followed by a section entitled “What’s new in Python 2.2a2”. Note that you /hope/ that as developers add new features to the trunk, they’ve updated the NEWS file accordingly. You can’t be positive, so double check. If you’re a Unix weenie, it helps to verify with Thomas about changes on Windows, and Jack Jansen about changes on the Mac. This command should help you (but substitute the correct -r tag!): % cvs log -rr22a1: | python Tools/scripts/logmerge.py > /tmp/news.txt IOW, you’re printing out all the cvs log entries from the previous release until now. You can then troll through the news.txt file looking for interesting things to add to NEWS. Check your NEWS changes into the maintenance branch. It’s easy to forget to update the release date in this file! Check in any changes to IDLE’s NEWS.txt. Update the header in Lib/idlelib/NEWS.txt to reflect its release version and date. Update the IDLE version in Lib/idlelib/idlever.py to match. Once the release process has started, the documentation needs to be built and posted on python.org according to the instructions in PEP 101.Note that Fred is responsible both for merging doc changes from the trunk to the branch AND for merging any branch changes from the branch to the trunk during the cleaning up phase. Basically, if it’s in Doc/ Fred will take care of it. Thomas compiles everything with MSVC 6.0 SP5, and moves the python23.chm file into the src/chm directory. The installer executable is then generated with Wise Installation System.The installer includes the MSVC 6.0 runtime in the files MSVCRT.DLL and MSVCIRT.DLL. It leads to disaster if these files are taken from the system directory of the machine where the installer is built, instead it must be absolutely made sure that these files come from the VCREDIST.EXE redistributable package contained in the MSVC SP5 CD. VCREDIST.EXE must be unpacked with winzip, and the Wise Installation System prompts for the directory. After building the installer, it should be opened with winzip, and the MS dlls extracted again and check for the same version number as those unpacked from VCREDIST.EXE. Thomas uploads this file to the starship. He then sends the RM a notice which includes the location and MD5 checksum of the Windows executable. Note that Thomas’s creation of the Windows executable may generate a few more commits on the branch. Thomas will be responsible for merging Windows-specific changes from trunk to branch, and from branch to trunk. Sean performs his Red Hat magic, generating a set of RPMs. He uploads these files to python.org. He then sends the RM a notice which includes the location and MD5 checksum of the RPMs. It’s Build Time!Now, you’re ready to build the source tarball. First cd to your working directory for the branch. E.g. % cd …/python-22a3 Do a “cvs update” in this directory. Do NOT include the -A flag!You should not see any “M” files, but you may see several “P” and/or “U” files. I.e. you better not have any uncommitted changes in your working directory, but you may pick up some of Fred’s or Thomas’s last minute changes. Now tag the branch using a symbolic name like “rXYMaZ”, e.g. r212% cvs tag r212 Be sure to tag only the python/dist/src subdirectory of the Python CVS tree! Change to a neutral directory, i.e. one in which you can do a fresh, virgin, cvs export of the branch. You will be creating a new directory at this location, to be named “Python-X.Y.M”. Do a CVS export of the tagged branch.% cd ~ % cvs -d cvs.sf.net:/cvsroot/python export -rr212 \ -d Python-2.1.2 python/dist/src Generate the tarball. Note that we’re not using the ‘z’ option on the tar command because 1) that’s only supported by GNU tar as far as we know, and 2) we’re going to max out the compression level, which isn’t a supported option. We generate both tar.gz tar.bz2 formats, as the latter is about 1/6th smaller.% tar -cf - Python-2.1.2 | gzip -9 > Python-2.1.2.tgz % tar -cf - Python-2.1.2 | bzip2 -9 > Python-2.1.2.tar.bz2 Calculate the MD5 checksum of the tgz and tar.bz2 files you just created% md5sum Python-2.1.2.tgz Note that if you don’t have the md5sum program, there is a Python replacement in the Tools/scripts/md5sum.py file. Create GPG keys for each of the files.% gpg -ba Python-2.1.2.tgz % gpg -ba Python-2.1.2.tar.bz2 % gpg -ba Python-2.1.2.exe Now you want to perform the very important step of checking the tarball you just created, to make sure a completely clean, virgin build passes the regression test. Here are the best steps to take:% cd /tmp % tar zxvf ~/Python-2.1.2.tgz % cd Python-2.1.2 % ls (Do things look reasonable?) % ./configure (Loads of configure output) % make test (Do all the expected tests pass?) If the tests pass, then you can feel good that the tarball is fine. If some of the tests fail, or anything else about the freshly unpacked directory looks weird, you better stop now and figure out what the problem is. You need to upload the tgz and the exe file to creosote.python.org. This step can take a long time depending on your network bandwidth. scp both files from your own machine to creosote. While you’re waiting, you can start twiddling the web pages to include the announcement. In the top of the python.org web site CVS tree, create a subdirectory for the X.Y.Z release. You can actually copy an earlier patch release’s subdirectory, but be sure to delete the X.Y.Z/CVS directory and “cvs add X.Y.Z”, for example:% cd .../pydotorg % cp -r 2.2.2 2.2.3 % rm -rf 2.2.3/CVS % cvs add 2.2.3 % cd 2.2.3 Edit the files for content: usually you can globally replace X.Ya(Z-1) with X.YaZ. However, you’ll need to think about the “What’s New?” section. Copy the Misc/NEWS file to NEWS.txt in the X.Y.Z directory for python.org; this contains the “full scoop” of changes to Python since the previous release for this version of Python. Copy the .asc GPG signatures you created earlier here as well. Also, update the MD5 checksums. Preview the web page by doing a “make” or “make install” (as long as you’ve created a new directory for this release!) Similarly, edit the ../index.ht file, i.e. the python.org home page. In the Big Blue Announcement Block, move the paragraph for the new version up to the top and boldify the phrase “Python X.YaZ is out”. Edit for content, and preview locally, but do NOT do a “make install” yet! Now we’re waiting for the scp to creosote to finish. Da de da, da de dum, hmm, hmm, dum de dum. Once that’s done you need to go to creosote.python.org and move all the files in place over there. Our policy is that every Python version gets its own directory, but each directory may contain several releases. We keep all old releases, moving them into a “prev” subdirectory when we have a new release.So, there’s a directory called “2.2” which contains Python-2.2a2.exe and Python-2.2a2.tgz, along with a “prev” subdirectory containing Python-2.2a1.exe and Python-2.2a1.tgz. So… On creosote, cd to ~ftp/pub/python/X.Y creating it if necessary. Move the previous release files to a directory called “prev” creating the directory if necessary (make sure the directory has g+ws bits on). If this is the first alpha release of a new Python version, skip this step. Move the .tgz file and the .exe file to this directory. Make sure they are world readable. They should also be group writable, and group-owned by webmaster. md5sum the files and make sure they got uploaded intact. the X.Y/bugs.ht file if necessary. It is best to get BDFL input for this step. Go up to the parent directory (i.e. the root of the web page hierarchy) and do a “make install” there. You’re release is now live! Now it’s time to write the announcement for the mailing lists. This is the fuzzy bit because not much can be automated. You can use one of Guido’s earlier announcements as a template, but please edit it for content!Once the announcement is ready, send it to the following addresses: [email protected] [email protected] [email protected] Send a SourceForge News Item about the release. From the project’s “menu bar”, select the “News” link; once in News, select the “Submit” link. Type a suitable subject (e.g. “Python 2.2c1 released” :-) in the Subject box, add some text to the Details box (at the very least including the release URL at www.python.org and the fact that you’re happy with the release) and click the SUBMIT button.Feel free to remove any old news items. Now it’s time to do some cleanup. These steps are very important! Edit the file Include/patchlevel.h so that the PY_VERSION string says something like “X.YaZ+”. Note the trailing ‘+’ indicating that the trunk is going to be moving forward with development. E.g. the line should look like:#define PY_VERSION "2.1.2+" Make sure that the other PY_ version macros contain the correct values. Commit this change. For the extra paranoid, do a completely clean test of the release. This includes downloading the tarball from www.python.org. Make sure the md5 checksums match. Then unpack the tarball, and do a clean make test.% make distclean % ./configure % make test To ensure that the regression test suite passes. If not, you screwed up somewhere! Step 5 … Verify! This can be interleaved with Step 4. Pretend you’re a user: download the files from python.org, and make Python from it. This step is too easy to overlook, and on several occasions we’ve had useless release files. Once a general server problem caused mysterious corruption of all files; once the source tarball got built incorrectly; more than once the file upload process on SF truncated files; and so on. What Next? Rejoice. Drink. Be Merry. Write a PEP like this one. Or be like unto Guido and take A Vacation. You’ve just made a Python release! Actually, there is one more step. You should turn over ownership of the branch to Jack Jansen. All this means is that now he will be responsible for making commits to the branch. He’s going to use this to build the MacOS versions. He may send you information about the Mac release that should be merged into the informational pages on www.python.org. When he’s done, he’ll tag the branch something like “rX.YaZ-mac”. He’ll also be responsible for merging any Mac-related changes back into the trunk. Final Release Notes The Final release of any major release, e.g. Python 2.2 final, has special requirements, specifically because it will be one of the longest lived releases (i.e. betas don’t last more than a couple of weeks, but final releases can last for years!). For this reason we want to have a higher coordination between the three major releases: Windows, Mac, and source. The Windows and source releases benefit from the close proximity of the respective release-bots. But the Mac-bot, Jack Jansen, is 6 hours away. So we add this extra step to the release process for a final release: Hold up the final release until Jack approves, or until we lose patience <wink>. The python.org site also needs some tweaking when a new bugfix release is issued. The documentation should be installed at doc/<version>/. Add a link from doc/<previous-minor-release>/index.ht to the documentation for the new version. All older doc/<old-release>/index.ht files should be updated to point to the documentation for the new version. /robots.txt should be modified to prevent the old version’s documentation from being crawled by search engines. Windows Notes Windows has a GUI installer, various flavors of Windows have “special limitations”, and the Windows installer also packs precompiled “foreign” binaries (Tcl/Tk, expat, etc). So Windows testing is tiresome but very necessary. Concurrent with uploading the installer, Thomas installs Python from it twice: once into the default directory suggested by the installer, and later into a directory with embedded spaces in its name. For each installation, he runs the full regression suite from a DOS box, and both with and without -0. He also tries every shortcut created under Start -> Menu -> the Python group. When trying IDLE this way, you need to verify that Help -> Python Documentation works. When trying pydoc this way (the “Module Docs” Start menu entry), make sure the “Start Browser” button works, and make sure you can search for a random module (Thomas uses “random” <wink>) and then that the “go to selected” button works. It’s amazing how much can go wrong here – and even more amazing how often last-second checkins break one of these things. If you’re “the Windows geek”, keep in mind that you’re likely the only person routinely testing on Windows, and that Windows is simply a mess. Repeat all of the above on at least one flavor of Win9x, and one of NT/2000/XP. On NT/2000/XP, try both an Admin and a plain User (not Power User) account. WRT Step 5 above (verify the release media), since by the time release files are ready to download Thomas has generally run many Windows tests on the installer he uploaded, he usually doesn’t do anything for Step 5 except a full byte-comparison (“fc /b” if using a Windows shell) of the downloaded file against the file he uploaded. Copyright This document has been placed in the public domain.

Superseded

PEP 102 – Doing Python Micro Releases

Informational

Making a Python release is an arduous process that takes a minimum of half a day’s work even for an experienced releaser. Until recently, most – if not all – of that burden was borne by Guido himself. But several recent releases have been performed by other folks, so this PEP attempts to collect, in one place, all the steps needed to make a Python bugfix release.

PEP 103 – Collecting information about git Author: Oleg Broytman <phd at phdru.name> Status: Withdrawn Type: Informational Created: 01-Jun-2015 Post-History: 12-Sep-2015 Table of Contents Withdrawal Abstract Documentation Documentation for starters Advanced documentation Offline documentation Quick start Download and installation Initial configuration Examples in this PEP Branches and branches Remote repositories and remote branches Updating local and remote-tracking branches Fetch and pull Push Tags Private information Commit editing and caveats Undo git checkout: restore file’s content git reset: remove (non-pushed) commits Unstaging git reflog: reference log git revert: revert a commit One thing that cannot be undone Merge or rebase? Null-merges Branching models Advanced configuration Line endings Useful assets Advanced topics Staging area Root ReReRe Database maintenance Tips and tricks Command-line options and arguments bash/zsh completion bash/zsh prompt SSH connection sharing git on server From Mercurial to git Git and GitHub Copyright Withdrawal This PEP was withdrawn as it’s too generic and doesn’t really deals with Python development. It is no longer updated. The content was moved to Python Wiki. Make further updates in the wiki. Abstract This Informational PEP collects information about git. There is, of course, a lot of documentation for git, so the PEP concentrates on more complex (and more related to Python development) issues, scenarios and examples. The plan is to extend the PEP in the future collecting information about equivalence of Mercurial and git scenarios to help migrating Python development from Mercurial to git. The author of the PEP doesn’t currently plan to write a Process PEP on migration Python development from Mercurial to git. Documentation Git is accompanied with a lot of documentation, both online and offline. Documentation for starters Git Tutorial: part 1, part 2. Git User’s manual. Everyday GIT With 20 Commands Or So. Git workflows. Advanced documentation Git Magic, with a number of translations. Pro Git. The Book about git. Buy it at Amazon or download in PDF, mobi, or ePub form. It has translations to many different languages. Download Russian translation from GArik. Git Wiki. Git Buch (German). Offline documentation Git has builtin help: run git help $TOPIC. For example, run git help git or git help help. Quick start Download and installation Unix users: download and install using your package manager. Microsoft Windows: download git-for-windows. MacOS X: use git installed with XCode or download from MacPorts or git-osx-installer or install git with Homebrew: brew install git. git-cola (repository) is a Git GUI written in Python and GPL licensed. Linux, Windows, MacOS X. TortoiseGit is a Windows Shell Interface to Git based on TortoiseSVN; open source. Initial configuration This simple code is often appears in documentation, but it is important so let repeat it here. Git stores author and committer names/emails in every commit, so configure your real name and preferred email: $ git config --global user.name "User Name" $ git config --global user.email [email protected] Examples in this PEP Examples of git commands in this PEP use the following approach. It is supposed that you, the user, works with a local repository named python that has an upstream remote repo named origin. Your local repo has two branches v1 and master. For most examples the currently checked out branch is master. That is, it’s assumed you have done something like that: $ git clone https://git.python.org/python.git $ cd python $ git branch v1 origin/v1 The first command clones remote repository into local directory python, creates a new local branch master, sets remotes/origin/master as its upstream remote-tracking branch and checks it out into the working directory. The last command creates a new local branch v1 and sets remotes/origin/v1 as its upstream remote-tracking branch. The same result can be achieved with commands: $ git clone -b v1 https://git.python.org/python.git $ cd python $ git checkout --track origin/master The last command creates a new local branch master, sets remotes/origin/master as its upstream remote-tracking branch and checks it out into the working directory. Branches and branches Git terminology can be a bit misleading. Take, for example, the term “branch”. In git it has two meanings. A branch is a directed line of commits (possibly with merges). And a branch is a label or a pointer assigned to a line of commits. It is important to distinguish when you talk about commits and when about their labels. Lines of commits are by itself unnamed and are usually only lengthening and merging. Labels, on the other hand, can be created, moved, renamed and deleted freely. Remote repositories and remote branches Remote-tracking branches are branches (pointers to commits) in your local repository. They are there for git (and for you) to remember what branches and commits have been pulled from and pushed to what remote repos (you can pull from and push to many remotes). Remote-tracking branches live under remotes/$REMOTE namespaces, e.g. remotes/origin/master. To see the status of remote-tracking branches run: $ git branch -rv To see local and remote-tracking branches (and tags) pointing to commits: $ git log --decorate You never do your own development on remote-tracking branches. You create a local branch that has a remote branch as upstream and do development on that local branch. On push git pushes commits to the remote repo and updates remote-tracking branches, on pull git fetches commits from the remote repo, updates remote-tracking branches and fast-forwards, merges or rebases local branches. When you do an initial clone like this: $ git clone -b v1 https://git.python.org/python.git git clones remote repository https://git.python.org/python.git to directory python, creates a remote named origin, creates remote-tracking branches, creates a local branch v1, configure it to track upstream remotes/origin/v1 branch and checks out v1 into the working directory. Some commands, like git status --branch and git branch --verbose, report the difference between local and remote branches. Please remember they only do comparison with remote-tracking branches in your local repository, and the state of those remote-tracking branches can be outdated. To update remote-tracking branches you either fetch and merge (or rebase) commits from the remote repository or update remote-tracking branches without updating local branches. Updating local and remote-tracking branches To update remote-tracking branches without updating local branches run git remote update [$REMOTE...]. For example: $ git remote update $ git remote update origin Fetch and pull There is a major difference between $ git fetch $REMOTE $BRANCH and $ git fetch $REMOTE $BRANCH:$BRANCH The first command fetches commits from the named $BRANCH in the $REMOTE repository that are not in your repository, updates remote-tracking branch and leaves the id (the hash) of the head commit in file .git/FETCH_HEAD. The second command fetches commits from the named $BRANCH in the $REMOTE repository that are not in your repository and updates both the local branch $BRANCH and its upstream remote-tracking branch. But it refuses to update branches in case of non-fast-forward. And it refuses to update the current branch (currently checked out branch, where HEAD is pointing to). The first command is used internally by git pull. $ git pull $REMOTE $BRANCH is equivalent to $ git fetch $REMOTE $BRANCH $ git merge FETCH_HEAD Certainly, $BRANCH in that case should be your current branch. If you want to merge a different branch into your current branch first update that non-current branch and then merge: $ git fetch origin v1:v1 # Update v1 $ git pull --rebase origin master # Update the current branch master # using rebase instead of merge $ git merge v1 If you have not yet pushed commits on v1, though, the scenario has to become a bit more complex. Git refuses to update non-fast-forwardable branch, and you don’t want to do force-pull because that would remove your non-pushed commits and you would need to recover. So you want to rebase v1 but you cannot rebase non-current branch. Hence, checkout v1 and rebase it before merging: $ git checkout v1 $ git pull --rebase origin v1 $ git checkout master $ git pull --rebase origin master $ git merge v1 It is possible to configure git to make it fetch/pull a few branches or all branches at once, so you can simply run $ git pull origin or even $ git pull Default remote repository for fetching/pulling is origin. Default set of references to fetch is calculated using matching algorithm: git fetches all branches having the same name on both ends. Push Pushing is a bit simpler. There is only one command push. When you run $ git push origin v1 master git pushes local v1 to remote v1 and local master to remote master. The same as: $ git push origin v1:v1 master:master Git pushes commits to the remote repo and updates remote-tracking branches. Git refuses to push commits that aren’t fast-forwardable. You can force-push anyway, but please remember - you can force-push to your own repositories but don’t force-push to public or shared repos. If you find git refuses to push commits that aren’t fast-forwardable, better fetch and merge commits from the remote repo (or rebase your commits on top of the fetched commits), then push. Only force-push if you know what you do and why you do it. See the section Commit editing and caveats below. It is possible to configure git to make it push a few branches or all branches at once, so you can simply run $ git push origin or even $ git push Default remote repository for pushing is origin. Default set of references to push in git before 2.0 is calculated using matching algorithm: git pushes all branches having the same name on both ends. Default set of references to push in git 2.0+ is calculated using simple algorithm: git pushes the current branch back to its @{upstream}. To configure git before 2.0 to the new behaviour run: $ git config push.default simple To configure git 2.0+ to the old behaviour run: $ git config push.default matching Git doesn’t allow to push a branch if it’s the current branch in the remote non-bare repository: git refuses to update remote working directory. You really should push only to bare repositories. For non-bare repositories git prefers pull-based workflow. When you want to deploy code on a remote host and can only use push (because your workstation is behind a firewall and you cannot pull from it) you do that in two steps using two repositories: you push from the workstation to a bare repo on the remote host, ssh to the remote host and pull from the bare repo to a non-bare deployment repo. That changed in git 2.3, but see the blog post for caveats; in 2.4 the push-to-deploy feature was further improved. Tags Git automatically fetches tags that point to commits being fetched during fetch/pull. To fetch all tags (and commits they point to) run git fetch --tags origin. To fetch some specific tags fetch them explicitly: $ git fetch origin tag $TAG1 tag $TAG2... For example: $ git fetch origin tag 1.4.2 $ git fetch origin v1:v1 tag 2.1.7 Git doesn’t automatically pushes tags. That allows you to have private tags. To push tags list them explicitly: $ git push origin tag 1.4.2 $ git push origin v1 master tag 2.1.7 Or push all tags at once: $ git push --tags origin Don’t move tags with git tag -f or remove tags with git tag -d after they have been published. Private information When cloning/fetching/pulling/pushing git copies only database objects (commits, trees, files and tags) and symbolic references (branches and lightweight tags). Everything else is private to the repository and never cloned, updated or pushed. It’s your config, your hooks, your private exclude file. If you want to distribute hooks, copy them to the working tree, add, commit, push and instruct the team to update and install the hooks manually. Commit editing and caveats A warning not to edit published (pushed) commits also appears in documentation but it’s repeated here anyway as it’s very important. It is possible to recover from a forced push but it’s PITA for the entire team. Please avoid it. To see what commits have not been published yet compare the head of the branch with its upstream remote-tracking branch: $ git log origin/master.. # from origin/master to HEAD (of master) $ git log origin/v1..v1 # from origin/v1 to the head of v1 For every branch that has an upstream remote-tracking branch git maintains an alias @{upstream} (short version @{u}), so the commands above can be given as: $ git log @{u}.. $ git log v1@{u}..v1 To see the status of all branches: $ git branch -avv To compare the status of local branches with a remote repo: $ git remote show origin Read how to recover from upstream rebase. It is in git help rebase. On the other hand, don’t be too afraid about commit editing. You can safely edit, reorder, remove, combine and split commits that haven’t been pushed yet. You can even push commits to your own (backup) repo, edit them later and force-push edited commits to replace what have already been pushed. Not a problem until commits are in a public or shared repository. Undo Whatever you do, don’t panic. Almost anything in git can be undone. git checkout: restore file’s content git checkout, for example, can be used to restore the content of file(s) to that one of a commit. Like this: git checkout HEAD~ README The commands restores the contents of README file to the last but one commit in the current branch. By default the commit ID is simply HEAD; i.e. git checkout README restores README to the latest commit. (Do not use git checkout to view a content of a file in a commit, use git cat-file -p; e.g. git cat-file -p HEAD~:path/to/README). git reset: remove (non-pushed) commits git reset moves the head of the current branch. The head can be moved to point to any commit but it’s often used to remove a commit or a few (preferably, non-pushed ones) from the top of the branch - that is, to move the branch backward in order to undo a few (non-pushed) commits. git reset has three modes of operation - soft, hard and mixed. Default is mixed. ProGit explains the difference very clearly. Bare repositories don’t have indices or working trees so in a bare repo only soft reset is possible. Unstaging Mixed mode reset with a path or paths can be used to unstage changes - that is, to remove from index changes added with git add for committing. See The Book for details about unstaging and other undo tricks. git reflog: reference log Removing commits with git reset or moving the head of a branch sounds dangerous and it is. But there is a way to undo: another reset back to the original commit. Git doesn’t remove commits immediately; unreferenced commits (in git terminology they are called “dangling commits”) stay in the database for some time (default is two weeks) so you can reset back to it or create a new branch pointing to the original commit. For every move of a branch’s head - with git commit, git checkout, git fetch, git pull, git rebase, git reset and so on - git stores a reference log (reflog for short). For every move git stores where the head was. Command git reflog can be used to view (and manipulate) the log. In addition to the moves of the head of every branch git stores the moves of the HEAD - a symbolic reference that (usually) names the current branch. HEAD is changed with git checkout $BRANCH. By default git reflog shows the moves of the HEAD, i.e. the command is equivalent to git reflog HEAD. To show the moves of the head of a branch use the command git reflog $BRANCH. So to undo a git reset lookup the original commit in git reflog, verify it with git show or git log and run git reset $COMMIT_ID. Git stores the move of the branch’s head in reflog, so you can undo that undo later again. In a more complex situation you’d want to move some commits along with resetting the head of the branch. Cherry-pick them to the new branch. For example, if you want to reset the branch master back to the original commit but preserve two commits created in the current branch do something like: $ git branch save-master # create a new branch saving master $ git reflog # find the original place of master $ git reset $COMMIT_ID $ git cherry-pick save-master~ save-master $ git branch -D save-master # remove temporary branch git revert: revert a commit git revert reverts a commit or commits, that is, it creates a new commit or commits that revert(s) the effects of the given commits. It’s the only way to undo published commits (git commit --amend, git rebase and git reset change the branch in non-fast-forwardable ways so they should only be used for non-pushed commits.) There is a problem with reverting a merge commit. git revert can undo the code created by the merge commit but it cannot undo the fact of merge. See the discussion How to revert a faulty merge. One thing that cannot be undone Whatever you undo, there is one thing that cannot be undone - overwritten uncommitted changes. Uncommitted changes don’t belong to git so git cannot help preserving them. Most of the time git warns you when you’re going to execute a command that overwrites uncommitted changes. Git doesn’t allow you to switch branches with git checkout. It stops you when you’re going to rebase with non-clean working tree. It refuses to pull new commits over non-committed files. But there are commands that do exactly that - overwrite files in the working tree. Commands like git checkout $PATHs or git reset --hard silently overwrite files including your uncommitted changes. With that in mind you can understand the stance “commit early, commit often”. Commit as often as possible. Commit on every save in your editor or IDE. You can edit your commits before pushing - edit commit messages, change commits, reorder, combine, split, remove. But save your changes in git database, either commit changes or at least stash them with git stash. Merge or rebase? Internet is full of heated discussions on the topic: “merge or rebase?” Most of them are meaningless. When a DVCS is being used in a big team with a big and complex project with many branches there is simply no way to avoid merges. So the question’s diminished to “whether to use rebase, and if yes - when to use rebase?” Considering that it is very much recommended not to rebase published commits the question’s diminished even further: “whether to use rebase on non-pushed commits?” That small question is for the team to decide. To preserve the beauty of linear history it’s recommended to use rebase when pulling, i.e. do git pull --rebase or even configure automatic setup of rebase for every new branch: $ git config branch.autosetuprebase always and configure rebase for existing branches: $ git config branch.$NAME.rebase true For example: $ git config branch.v1.rebase true $ git config branch.master.rebase true After that git pull origin master becomes equivalent to git pull --rebase origin master. It is recommended to create new commits in a separate feature or topic branch while using rebase to update the mainline branch. When the topic branch is ready merge it into mainline. To avoid a tedious task of resolving large number of conflicts at once you can merge the topic branch to the mainline from time to time and switch back to the topic branch to continue working on it. The entire workflow would be something like: $ git checkout -b issue-42 # create a new issue branch and switch to it ...edit/test/commit... $ git checkout master $ git pull --rebase origin master # update master from the upstream $ git merge issue-42 $ git branch -d issue-42 # delete the topic branch $ git push origin master When the topic branch is deleted only the label is removed, commits are stayed in the database, they are now merged into master: o--o--o--o--o--M--< master - the mainline branch \ / --*--*--* - the topic branch, now unnamed The topic branch is deleted to avoid cluttering branch namespace with small topic branches. Information on what issue was fixed or what feature was implemented should be in the commit messages. But even that small amount of rebasing could be too big in case of long-lived merged branches. Imagine you’re doing work in both v1 and master branches, regularly merging v1 into master. After some time you will have a lot of merge and non-merge commits in master. Then you want to push your finished work to a shared repository and find someone has pushed a few commits to v1. Now you have a choice of two equally bad alternatives: either you fetch and rebase v1 and then have to recreate all you work in master (reset master to the origin, merge v1 and cherry-pick all non-merge commits from the old master); or merge the new v1 and loose the beauty of linear history. Null-merges Git has a builtin merge strategy for what Python core developers call “null-merge”: $ git merge -s ours v1 # null-merge v1 into master Branching models Git doesn’t assume any particular development model regarding branching and merging. Some projects prefer to graduate patches from the oldest branch to the newest, some prefer to cherry-pick commits backwards, some use squashing (combining a number of commits into one). Anything is possible. There are a few examples to start with. git help workflows describes how the very git authors develop git. ProGit book has a few chapters devoted to branch management in different projects: Git Branching - Branching Workflows and Distributed Git - Contributing to a Project. There is also a well-known article A successful Git branching model by Vincent Driessen. It recommends a set of very detailed rules on creating and managing mainline, topic and bugfix branches. To support the model the author implemented git flow extension. Advanced configuration Line endings Git has builtin mechanisms to handle line endings between platforms with different end-of-line styles. To allow git to do CRLF conversion assign text attribute to files using .gitattributes. For files that have to have specific line endings assign eol attribute. For binary files the attribute is, naturally, binary. For example: $ cat .gitattributes *.py text *.txt text *.png binary /readme.txt eol=CRLF To check what attributes git uses for files use git check-attr command. For example: $ git check-attr -a -- \*.py Useful assets GitAlias (repository) is a big collection of aliases. A careful selection of aliases for frequently used commands could save you a lot of keystrokes! GitIgnore and https://github.com/github/gitignore are collections of .gitignore files for all kinds of IDEs and programming languages. Python included! pre-commit (repositories) is a framework for managing and maintaining multi-language pre-commit hooks. The framework is written in Python and has a lot of plugins for many programming languages. Advanced topics Staging area Staging area aka index aka cache is a distinguishing feature of git. Staging area is where git collects patches before committing them. Separation between collecting patches and commit phases provides a very useful feature of git: you can review collected patches before commit and even edit them - remove some hunks, add new hunks and review again. To add files to the index use git add. Collecting patches before committing means you need to do that for every change, not only to add new (untracked) files. To simplify committing in case you just want to commit everything without reviewing run git commit --all (or just -a) - the command adds every changed tracked file to the index and then commit. To commit a file or files regardless of patches collected in the index run git commit [--only|-o] -- $FILE.... To add hunks of patches to the index use git add --patch (or just -p). To remove collected files from the index use git reset HEAD -- $FILE... To add/inspect/remove collected hunks use git add --interactive (-i). To see the diff between the index and the last commit (i.e., collected patches) use git diff --cached. To see the diff between the working tree and the index (i.e., uncollected patches) use just git diff. To see the diff between the working tree and the last commit (i.e., both collected and uncollected patches) run git diff HEAD. See WhatIsTheIndex and IndexCommandQuickref in Git Wiki. Root Git switches to the root (top-level directory of the project where .git subdirectory exists) before running any command. Git remembers though the directory that was current before the switch. Some programs take into account the current directory. E.g., git status shows file paths of changed and unknown files relative to the current directory; git grep searches below the current directory; git apply applies only those hunks from the patch that touch files below the current directory. But most commands run from the root and ignore the current directory. Imagine, for example, that you have two work trees, one for the branch v1 and the other for master. If you want to merge v1 from a subdirectory inside the second work tree you must write commands as if you’re in the top-level dir. Let take two work trees, project-v1 and project, for example: $ cd project/subdirectory $ git fetch ../project-v1 v1:v1 $ git merge v1 Please note the path in git fetch ../project-v1 v1:v1 is ../project-v1 and not ../../project-v1 despite the fact that we run the commands from a subdirectory, not from the root. ReReRe Rerere is a mechanism that helps to resolve repeated merge conflicts. The most frequent source of recurring merge conflicts are topic branches that are merged into mainline and then the merge commits are removed; that’s often performed to test the topic branches and train rerere; merge commits are removed to have clean linear history and finish the topic branch with only one last merge commit. Rerere works by remembering the states of tree before and after a successful commit. That way rerere can automatically resolve conflicts if they appear in the same files. Rerere can be used manually with git rerere command but most often it’s used automatically. Enable rerere with these commands in a working tree: $ git config rerere.enabled true $ git config rerere.autoupdate true You don’t need to turn rerere on globally - you don’t want rerere in bare repositories or single-branch repositories; you only need rerere in repos where you often perform merges and resolve merge conflicts. See Rerere in The Book. Database maintenance Git object database and other files/directories under .git require periodic maintenance and cleanup. For example, commit editing left unreferenced objects (dangling objects, in git terminology) and these objects should be pruned to avoid collecting cruft in the DB. The command git gc is used for maintenance. Git automatically runs git gc --auto as a part of some commands to do quick maintenance. Users are recommended to run git gc --aggressive from time to time; git help gc recommends to run it every few hundred changesets; for more intensive projects it should be something like once a week and less frequently (biweekly or monthly) for lesser active projects. git gc --aggressive not only removes dangling objects, it also repacks object database into indexed and better optimized pack(s); it also packs symbolic references (branches and tags). Another way to do it is to run git repack. There is a well-known message from Linus Torvalds regarding “stupidity” of git gc --aggressive. The message can safely be ignored now. It is old and outdated, git gc --aggressive became much better since that time. For those who still prefer git repack over git gc --aggressive the recommended parameters are git repack -a -d -f --depth=20 --window=250. See this detailed experiment for explanation of the effects of these parameters. From time to time run git fsck [--strict] to verify integrity of the database. git fsck may produce a list of dangling objects; that’s not an error, just a reminder to perform regular maintenance. Tips and tricks Command-line options and arguments git help cli recommends not to combine short options/flags. Most of the times combining works: git commit -av works perfectly, but there are situations when it doesn’t. E.g., git log -p -5 cannot be combined as git log -p5. Some options have arguments, some even have default arguments. In that case the argument for such option must be spelled in a sticky way: -Oarg, never -O arg because for an option that has a default argument the latter means “use default value for option -O and pass arg further to the option parser”. For example, git grep has an option -O that passes a list of names of the found files to a program; default program for -O is a pager (usually less), but you can use your editor: $ git grep -Ovim # but not -O vim BTW, if git is instructed to use less as the pager (i.e., if pager is not configured in git at all it uses less by default, or if it gets less from GIT_PAGER or PAGER environment variables, or if it was configured with git config [--global] core.pager less, or less is used in the command git grep -Oless) git grep passes +/$pattern option to less which is quite convenient. Unfortunately, git grep doesn’t pass the pattern if the pager is not exactly less, even if it’s less with parameters (something like git config [--global] core.pager less -FRSXgimq); fortunately, git grep -Oless always passes the pattern. bash/zsh completion It’s a bit hard to type git rebase --interactive --preserve-merges HEAD~5 manually even for those who are happy to use command-line, and this is where shell completion is of great help. Bash/zsh come with programmable completion, often automatically installed and enabled, so if you have bash/zsh and git installed, chances are you are already done - just go and use it at the command-line. If you don’t have necessary bits installed, install and enable bash_completion package. If you want to upgrade your git completion to the latest and greatest download necessary file from git contrib. Git-for-windows comes with git-bash for which bash completion is installed and enabled. bash/zsh prompt For command-line lovers shell prompt can carry a lot of useful information. To include git information in the prompt use git-prompt.sh. Read the detailed instructions in the file. Search the Net for “git prompt” to find other prompt variants. SSH connection sharing SSH connection sharing is a feature of OpenSSH and perhaps derivatives like PuTTY. SSH connection sharing is a way to decrease ssh client startup time by establishing one connection and reusing it for all subsequent clients connecting to the same server. SSH connection sharing can be used to speedup a lot of short ssh sessions like scp, sftp, rsync and of course git over ssh. If you regularly fetch/pull/push from/to remote repositories accessible over ssh then using ssh connection sharing is recommended. To turn on ssh connection sharing add something like this to your ~/.ssh/config: Host * ControlMaster auto ControlPath ~/.ssh/mux-%r@%h:%p ControlPersist 600 See OpenSSH wikibook and search for more information. SSH connection sharing can be used at GitHub, GitLab and SourceForge repositories, but please be advised that BitBucket doesn’t allow it and forcibly closes master connection after a short inactivity period so you will see errors like this from ssh: “Connection to bitbucket.org closed by remote host.” git on server The simplest way to publish a repository or a group of repositories is git daemon. The daemon provides anonymous access, by default it is read-only. The repositories are accessible by git protocol (git:// URLs). Write access can be enabled but the protocol lacks any authentication means, so it should be enabled only within a trusted LAN. See git help daemon for details. Git over ssh provides authentication and repo-level authorisation as repositories can be made user- or group-writeable (see parameter core.sharedRepository in git help config). If that’s too permissive or too restrictive for some project’s needs there is a wrapper gitolite that can be configured to allow access with great granularity; gitolite is written in Perl and has a lot of documentation. Web interface to browse repositories can be created using gitweb or cgit. Both are CGI scripts (written in Perl and C). In addition to web interface both provide read-only dumb http access for git (http(s):// URLs). Klaus is a small and simple WSGI web server that implements both web interface and git smart HTTP transport; supports Python 2 and Python 3, performs syntax highlighting. There are also more advanced web-based development environments that include ability to manage users, groups and projects; private, group-accessible and public repositories; they often include issue trackers, wiki pages, pull requests and other tools for development and communication. Among these environments are Kallithea and pagure, both are written in Python; pagure was written by Fedora developers and is being used to develop some Fedora projects. GitPrep is yet another GitHub clone, written in Perl. Gogs is written in Go. GitBucket is written in Scala. And last but not least, GitLab. It’s perhaps the most advanced web-based development environment for git. Written in Ruby, community edition is free and open source (MIT license). From Mercurial to git There are many tools to convert Mercurial repositories to git. The most famous are, probably, hg-git and fast-export (many years ago it was known under the name hg2git). But a better tool, perhaps the best, is git-remote-hg. It provides transparent bidirectional (pull and push) access to Mercurial repositories from git. Its author wrote a comparison of alternatives that seems to be mostly objective. To use git-remote-hg, install or clone it, add to your PATH (or copy script git-remote-hg to a directory that’s already in PATH) and prepend hg:: to Mercurial URLs. For example: $ git clone https://github.com/felipec/git-remote-hg.git $ PATH=$PATH:"`pwd`"/git-remote-hg $ git clone hg::https://hg.python.org/peps/ PEPs To work with the repository just use regular git commands including git fetch/pull/push. To start converting your Mercurial habits to git see the page Mercurial for Git users at Mercurial wiki. At the second half of the page there is a table that lists corresponding Mercurial and git commands. Should work perfectly in both directions. Python Developer’s Guide also has a chapter Mercurial for git developers that documents a few differences between git and hg. Git and GitHub gitsome - Git/GitHub command line interface (CLI). Written in Python, work on MacOS, Unix, Windows. Git/GitHub CLI with autocomplete, includes many GitHub integrated commands that work with all shells, builtin xonsh with Python REPL to run Python commands alongside shell commands, command history, customizable highlighting, thoroughly documented. Copyright This document has been placed in the public domain.

Withdrawn

PEP 103 – Collecting information about git

Informational

This Informational PEP collects information about git. There is, of course, a lot of documentation for git, so the PEP concentrates on more complex (and more related to Python development) issues, scenarios and examples.

PEP 207 – Rich Comparisons Author: Guido van Rossum <guido at python.org>, David Ascher <DavidA at ActiveState.com> Status: Final Type: Standards Track Created: 25-Jul-2000 Python-Version: 2.1 Post-History: Table of Contents Abstract Motivation Previous Work Concerns Proposed Resolutions Implementation Proposal C API Changes to the interpreter Classes Copyright Appendix Abstract Motivation Current State of Affairs Proposed Mechanism Chained Comparisons Problem Solution Abstract This PEP proposes several new features for comparisons: Allow separately overloading of <, >, <=, >=, ==, !=, both in classes and in C extensions. Allow any of those overloaded operators to return something else besides a Boolean result. Motivation The main motivation comes from NumPy, whose users agree that A<B should return an array of elementwise comparison outcomes; they currently have to spell this as less(A,B) because A<B can only return a Boolean result or raise an exception. An additional motivation is that frequently, types don’t have a natural ordering, but still need to be compared for equality. Currently such a type must implement comparison and thus define an arbitrary ordering, just so that equality can be tested. Also, for some object types an equality test can be implemented much more efficiently than an ordering test; for example, lists and dictionaries that differ in length are unequal, but the ordering requires inspecting some (potentially all) items. Previous Work Rich Comparisons have been proposed before; in particular by David Ascher, after experience with Numerical Python: http://starship.python.net/crew/da/proposals/richcmp.html It is also included below as an Appendix. Most of the material in this PEP is derived from David’s proposal. Concerns Backwards compatibility, both at the Python level (classes using __cmp__ need not be changed) and at the C level (extensions defining tp_comparea need not be changed, code using PyObject_Compare() must work even if the compared objects use the new rich comparison scheme). When A<B returns a matrix of elementwise comparisons, an easy mistake to make is to use this expression in a Boolean context. Without special precautions, it would always be true. This use should raise an exception instead. If a class overrides x==y but nothing else, should x!=y be computed as not(x==y), or fail? What about the similar relationship between < and >=, or between > and <=? Similarly, should we allow x<y to be calculated from y>x? And x<=y from not(x>y)? And x==y from y==x, or x!=y from y!=x? When comparison operators return elementwise comparisons, what to do about shortcut operators like A<B<C, A<B and C<D, A<B or C<D? What to do about min() and max(), the ‘in’ and ‘not in’ operators, list.sort(), dictionary key comparison, and other uses of comparisons by built-in operations? Proposed Resolutions Full backwards compatibility can be achieved as follows. When an object defines tp_compare() but not tp_richcompare(), and a rich comparison is requested, the outcome of tp_compare() is used in the obvious way. E.g. if “<” is requested, an exception if tp_compare() raises an exception, the outcome is 1 if tp_compare() is negative, and 0 if it is zero or positive. Etc.Full forward compatibility can be achieved as follows. When a classic comparison is requested on an object that implements tp_richcompare(), up to three comparisons are used: first == is tried, and if it returns true, 0 is returned; next, < is tried and if it returns true, -1 is returned; next, > is tried and if it returns true, +1 is returned. If any operator tried returns a non-Boolean value (see below), the exception raised by conversion to Boolean is passed through. If none of the operators tried returns true, the classic comparison fallbacks are tried next. (I thought long and hard about the order in which the three comparisons should be tried. At one point I had a convincing argument for doing it in this order, based on the behavior of comparisons for cyclical data structures. But since that code has changed again, I’m not so sure that it makes a difference any more.) Any type that returns a collection of Booleans instead of a single boolean should define nb_nonzero() to raise an exception. Such a type is considered a non-Boolean. The == and != operators are not assumed to be each other’s complement (e.g. IEEE 754 floating point numbers do not satisfy this). It is up to the type to implement this if desired. Similar for < and >=, or > and <=; there are lots of examples where these assumptions aren’t true (e.g. tabnanny). The reflexivity rules are assumed by Python. Thus, the interpreter may swap y>x with x<y, y>=x with x<=y, and may swap the arguments of x==y and x!=y. (Note: Python currently assumes that x==x is always true and x!=x is never true; this should not be assumed.) In the current proposal, when A<B returns an array of elementwise comparisons, this outcome is considered non-Boolean, and its interpretation as Boolean by the shortcut operators raises an exception. David Ascher’s proposal tries to deal with this; I don’t think this is worth the additional complexity in the code generator. Instead of A<B<C, you can write (A<B)&(B<C). The min() and list.sort() operations will only use the < operator; max() will only use the > operator. The ‘in’ and ‘not in’ operators and dictionary lookup will only use the == operator. Implementation Proposal This closely follows David Ascher’s proposal. C API New functions:PyObject *PyObject_RichCompare(PyObject *, PyObject *, int) This performs the requested rich comparison, returning a Python object or raising an exception. The 3rd argument must be one of Py_LT, Py_LE, Py_EQ, Py_NE, Py_GT or Py_GE. int PyObject_RichCompareBool(PyObject *, PyObject *, int) This performs the requested rich comparison, returning a Boolean: -1 for exception, 0 for false, 1 for true. The 3rd argument must be one of Py_LT, Py_LE, Py_EQ, Py_NE, Py_GT or Py_GE. Note that when PyObject_RichCompare() returns a non-Boolean object, PyObject_RichCompareBool() will raise an exception. New typedef:typedef PyObject *(*richcmpfunc) (PyObject *, PyObject *, int); New slot in type object, replacing spare tp_xxx7:richcmpfunc tp_richcompare; This should be a function with the same signature as PyObject_RichCompare(), and performing the same comparison. At least one of the arguments is of the type whose tp_richcompare slot is being used, but the other may have a different type. If the function cannot compare the particular combination of objects, it should return a new reference to Py_NotImplemented. PyObject_Compare() is changed to try rich comparisons if they are defined (but only if classic comparisons aren’t defined). Changes to the interpreter Whenever PyObject_Compare() is called with the intent of getting the outcome of a particular comparison (e.g. in list.sort(), and of course for the comparison operators in ceval.c), the code is changed to call PyObject_RichCompare() or PyObject_RichCompareBool() instead; if the C code needs to know the outcome of the comparison, PyObject_IsTrue() is called on the result (which may raise an exception). Most built-in types that currently define a comparison will be modified to define a rich comparison instead. (This is optional; I’ve converted lists, tuples, complex numbers, and arrays so far, and am not sure whether I will convert others.) Classes Classes can define new special methods __lt__, __le__, __eq__, __ne__, __gt__, __ge__ to override the corresponding operators. (I.e., <, <=, ==, !=, >, >=. You gotta love the Fortran heritage.) If a class defines __cmp__ as well, it is only used when __lt__ etc. have been tried and return NotImplemented. Copyright This document has been placed in the public domain. Appendix Here is most of David Ascher’s original proposal (version 0.2.1, dated Wed Jul 22 16:49:28 1998; I’ve left the Contents, History and Patches sections out). It addresses almost all concerns above. Abstract A new mechanism allowing comparisons of Python objects to return values other than -1, 0, or 1 (or raise exceptions) is proposed. This mechanism is entirely backwards compatible, and can be controlled at the level of the C PyObject type or of the Python class definition. There are three cooperating parts to the proposed mechanism: the use of the last slot in the type object structure to store a pointer to a rich comparison function the addition of special methods for classes the addition of an optional argument to the builtin cmp() function. Motivation The current comparison protocol for Python objects assumes that any two Python objects can be compared (as of Python 1.5, object comparisons can raise exceptions), and that the return value for any comparison should be -1, 0 or 1. -1 indicates that the first argument to the comparison function is less than the right one, +1 indicating the contrapositive, and 0 indicating that the two objects are equal. While this mechanism allows the establishment of an order relationship (e.g. for use by the sort() method of list objects), it has proven to be limited in the context of Numeric Python (NumPy). Specifically, NumPy allows the creation of multidimensional arrays, which support most of the numeric operators. Thus: x = array((1,2,3,4)) y = array((2,2,4,4)) are two NumPy arrays. While they can be added elementwise,: z = x + y # z == array((3,4,7,8)) they cannot be compared in the current framework - the released version of NumPy compares the pointers, (thus yielding junk information) which was the only solution before the recent addition of the ability (in 1.5) to raise exceptions in comparison functions. Even with the ability to raise exceptions, the current protocol makes array comparisons useless. To deal with this fact, NumPy includes several functions which perform the comparisons: less(), less_equal(), greater(), greater_equal(), equal(), not_equal(). These functions return arrays with the same shape as their arguments (modulo broadcasting), filled with 0’s and 1’s depending on whether the comparison is true or not for each element pair. Thus, for example, using the arrays x and y defined above: less(x,y) would be an array containing the numbers (1,0,0,0). The current proposal is to modify the Python object interface to allow the NumPy package to make it so that x < y returns the same thing as less(x,y). The exact return value is up to the NumPy package – what this proposal really asks for is changing the Python core so that extension objects have the ability to return something other than -1, 0, 1, should their authors choose to do so. Current State of Affairs The current protocol is, at the C level, that each object type defines a tp_compare slot, which is a pointer to a function which takes two PyObject* references and returns -1, 0, or 1. This function is called by the PyObject_Compare() function defined in the C API. PyObject_Compare() is also called by the builtin function cmp() which takes two arguments. Proposed Mechanism Changes to the C structure for type objectsThe last available slot in the PyTypeObject, reserved up to now for future expansion, is used to optionally store a pointer to a new comparison function, of type richcmpfunc defined by: typedef PyObject *(*richcmpfunc) Py_PROTO((PyObject *, PyObject *, int)); This function takes three arguments. The first two are the objects to be compared, and the third is an integer corresponding to an opcode (one of LT, LE, EQ, NE, GT, GE). If this slot is left NULL, then rich comparison for that object type is not supported (except for class instances whose class provide the special methods described below). The above opcodes need to be added to the published Python/C API (probably under the names Py_LT, Py_LE, etc.) Additions of special methods for classesClasses wishing to support the rich comparison mechanisms must add one or more of the following new special methods: def __lt__(self, other): ... def __le__(self, other): ... def __gt__(self, other): ... def __ge__(self, other): ... def __eq__(self, other): ... def __ne__(self, other): ... Each of these is called when the class instance is the on the left-hand-side of the corresponding operators (<, <=, >, >=, ==, and != or <>). The argument other is set to the object on the right side of the operator. The return value of these methods is up to the class implementor (after all, that’s the entire point of the proposal). If the object on the left side of the operator does not define an appropriate rich comparison operator (either at the C level or with one of the special methods, then the comparison is reversed, and the right hand operator is called with the opposite operator, and the two objects are swapped. This assumes that a < b and b > a are equivalent, as are a <= b and b >= a, and that == and != are commutative (e.g. a == b if and only if b == a). For example, if obj1 is an object which supports the rich comparison protocol and x and y are objects which do not support the rich comparison protocol, then obj1 < x will call the __lt__ method of obj1 with x as the second argument. x < obj1 will call obj1’s __gt__ method with x as a second argument, and x < y will just use the existing (non-rich) comparison mechanism. The above mechanism is such that classes can get away with not implementing either __lt__ and __le__ or __gt__ and __ge__. Further smarts could have been added to the comparison mechanism, but this limited set of allowed “swaps” was chosen because it doesn’t require the infrastructure to do any processing (negation) of return values. The choice of six special methods was made over a single (e.g. __richcmp__) method to allow the dispatching on the opcode to be performed at the level of the C implementation rather than the user-defined method. Addition of an optional argument to the builtin cmp()The builtin cmp() is still used for simple comparisons. For rich comparisons, it is called with a third argument, one of “<”, “<=”, “>”, “>=”, “==”, “!=”, “<>” (the last two have the same meaning). When called with one of these strings as the third argument, cmp() can return any Python object. Otherwise, it can only return -1, 0 or 1 as before. Chained Comparisons Problem It would be nice to allow objects for which the comparison returns something other than -1, 0, or 1 to be used in chained comparisons, such as: x < y < z Currently, this is interpreted by Python as: temp1 = x < y if temp1: return y < z else: return temp1 Note that this requires testing the truth value of the result of comparisons, with potential “shortcutting” of the right-side comparison testings. In other words, the truth-value of the result of the result of the comparison determines the result of a chained operation. This is problematic in the case of arrays, since if x, y and z are three arrays, then the user expects: x < y < z to be an array of 0’s and 1’s where 1’s are in the locations corresponding to the elements of y which are between the corresponding elements in x and z. In other words, the right-hand side must be evaluated regardless of the result of x < y, which is incompatible with the mechanism currently in use by the parser. Solution Guido mentioned that one possible way out would be to change the code generated by chained comparisons to allow arrays to be chained-compared intelligently. What follows is a mixture of his idea and my suggestions. The code generated for x < y < z would be equivalent to: temp1 = x < y if temp1: temp2 = y < z return boolean_combine(temp1, temp2) else: return temp1 where boolean_combine is a new function which does something like the following: def boolean_combine(a, b): if hasattr(a, '__boolean_and__') or \ hasattr(b, '__boolean_and__'): try: return a.__boolean_and__(b) except: return b.__boolean_and__(a) else: # standard behavior if a: return b else: return 0 where the __boolean_and__ special method is implemented for C-level types by another value of the third argument to the richcmp function. This method would perform a boolean comparison of the arrays (currently implemented in the umath module as the logical_and ufunc). Thus, objects returned by rich comparisons should always test true, but should define another special method which creates boolean combinations of them and their argument. This solution has the advantage of allowing chained comparisons to work for arrays, but the disadvantage that it requires comparison arrays to always return true (in an ideal world, I’d have them always raise an exception on truth testing, since the meaning of testing “if a>b:” is massively ambiguous. The inlining already present which deals with integer comparisons would still apply, resulting in no performance cost for the most common cases.

Final

PEP 207 – Rich Comparisons

Standards Track

This PEP proposes several new features for comparisons:

PEP 208 – Reworking the Coercion Model Author: Neil Schemenauer <nas at arctrix.com>, Marc-André Lemburg <mal at lemburg.com> Status: Final Type: Standards Track Created: 04-Dec-2000 Python-Version: 2.1 Post-History: Table of Contents Abstract Rationale Specification Reference Implementation Credits Copyright References Abstract Many Python types implement numeric operations. When the arguments of a numeric operation are of different types, the interpreter tries to coerce the arguments into a common type. The numeric operation is then performed using this common type. This PEP proposes a new type flag to indicate that arguments to a type’s numeric operations should not be coerced. Operations that do not support the supplied types indicate it by returning a new singleton object. Types which do not set the type flag are handled in a backwards compatible manner. Allowing operations handle different types is often simpler, more flexible, and faster than having the interpreter do coercion. Rationale When implementing numeric or other related operations, it is often desirable to provide not only operations between operands of one type only, e.g. integer + integer, but to generalize the idea behind the operation to other type combinations as well, e.g. integer + float. A common approach to this mixed type situation is to provide a method of “lifting” the operands to a common type (coercion) and then use that type’s operand method as execution mechanism. Yet, this strategy has a few drawbacks: the “lifting” process creates at least one new (temporary) operand object, since the coercion method is not being told about the operation that is to follow, it is not possible to implement operation specific coercion of types, there is no elegant way to solve situations were a common type is not at hand, and the coercion method will always have to be called prior to the operation’s method itself. A fix for this situation is obviously needed, since these drawbacks make implementations of types needing these features very cumbersome, if not impossible. As an example, have a look at the DateTime and DateTimeDelta [1] types, the first being absolute, the second relative. You can always add a relative value to an absolute one, giving a new absolute value. Yet, there is no common type which the existing coercion mechanism could use to implement that operation. Currently, PyInstance types are treated specially by the interpreter in that their numeric methods are passed arguments of different types. Removing this special case simplifies the interpreter and allows other types to implement numeric methods that behave like instance types. This is especially useful for extension types like ExtensionClass. Specification Instead of using a central coercion method, the process of handling different operand types is simply left to the operation. If the operation finds that it cannot handle the given operand type combination, it may return a special singleton as indicator. Note that “numbers” (anything that implements the number protocol, or part of it) written in Python already use the first part of this strategy - it is the C level API that we focus on here. To maintain nearly 100% backward compatibility we have to be very careful to make numbers that don’t know anything about the new strategy (old style numbers) work just as well as those that expect the new scheme (new style numbers). Furthermore, binary compatibility is a must, meaning that the interpreter may only access and use new style operations if the number indicates the availability of these. A new style number is considered by the interpreter as such if and only if it sets the type flag Py_TPFLAGS_CHECKTYPES. The main difference between an old style number and a new style one is that the numeric slot functions can no longer assume to be passed arguments of identical type. New style slots must check all arguments for proper type and implement the necessary conversions themselves. This may seem to cause more work on the behalf of the type implementor, but is in fact no more difficult than writing the same kind of routines for an old style coercion slot. If a new style slot finds that it cannot handle the passed argument type combination, it may return a new reference of the special singleton Py_NotImplemented to the caller. This will cause the caller to try the other operands operation slots until it finds a slot that does implement the operation for the specific type combination. If none of the possible slots succeed, it raises a TypeError. To make the implementation easy to understand (the whole topic is esoteric enough), a new layer in the handling of numeric operations is introduced. This layer takes care of all the different cases that need to be taken into account when dealing with all the possible combinations of old and new style numbers. It is implemented by the two static functions binary_op() and ternary_op(), which are both internal functions that only the functions in Objects/abstract.c have access to. The numeric API (PyNumber_*) is easy to adapt to this new layer. As a side-effect all numeric slots can be NULL-checked (this has to be done anyway, so the added feature comes at no extra cost). The scheme used by the layer to execute a binary operation is as follows: v w Action taken new new v.op(v,w), w.op(v,w) new old v.op(v,w), coerce(v,w), v.op(v,w) old new w.op(v,w), coerce(v,w), v.op(v,w) old old coerce(v,w), v.op(v,w) The indicated action sequence is executed from left to right until either the operation succeeds and a valid result (!= Py_NotImplemented) is returned or an exception is raised. Exceptions are returned to the calling function as-is. If a slot returns Py_NotImplemented, the next item in the sequence is executed. Note that coerce(v,w) will use the old style nb_coerce slot methods via a call to PyNumber_Coerce(). Ternary operations have a few more cases to handle: v w z Action taken new new new v.op(v,w,z), w.op(v,w,z), z.op(v,w,z) new old new v.op(v,w,z), z.op(v,w,z), coerce(v,w,z), v.op(v,w,z) old new new w.op(v,w,z), z.op(v,w,z), coerce(v,w,z), v.op(v,w,z) old old new z.op(v,w,z), coerce(v,w,z), v.op(v,w,z) new new old v.op(v,w,z), w.op(v,w,z), coerce(v,w,z), v.op(v,w,z) new old old v.op(v,w,z), coerce(v,w,z), v.op(v,w,z) old new old w.op(v,w,z), coerce(v,w,z), v.op(v,w,z) old old old coerce(v,w,z), v.op(v,w,z) The same notes as above, except that coerce(v,w,z) actually does: if z != Py_None: coerce(v,w), coerce(v,z), coerce(w,z) else: # treat z as absent variable coerce(v,w) The current implementation uses this scheme already (there’s only one ternary slot: nb_pow(a,b,c)). Note that the numeric protocol is also used for some other related tasks, e.g. sequence concatenation. These can also benefit from the new mechanism by implementing right-hand operations for type combinations that would otherwise fail to work. As an example, take string concatenation: currently you can only do string + string. With the new mechanism, a new string-like type could implement new_type + string and string + new_type, even though strings don’t know anything about new_type. Since comparisons also rely on coercion (every time you compare an integer to a float, the integer is first converted to float and then compared…), a new slot to handle numeric comparisons is needed: PyObject *nb_cmp(PyObject *v, PyObject *w) This slot should compare the two objects and return an integer object stating the result. Currently, this result integer may only be -1, 0, 1. If the slot cannot handle the type combination, it may return a reference to Py_NotImplemented. [XXX Note that this slot is still in flux since it should take into account rich comparisons (i.e. PEP 207).] Numeric comparisons are handled by a new numeric protocol API: PyObject *PyNumber_Compare(PyObject *v, PyObject *w) This function compare the two objects as “numbers” and return an integer object stating the result. Currently, this result integer may only be -1, 0, 1. In case the operation cannot be handled by the given objects, a TypeError is raised. The PyObject_Compare() API needs to adjusted accordingly to make use of this new API. Other changes include adapting some of the built-in functions (e.g. cmp()) to use this API as well. Also, PyNumber_CoerceEx() will need to check for new style numbers before calling the nb_coerce slot. New style numbers don’t provide a coercion slot and thus cannot be explicitly coerced. Reference Implementation A preliminary patch for the CVS version of Python is available through the Source Forge patch manager [2]. Credits This PEP and the patch are heavily based on work done by Marc-André Lemburg [3]. Copyright This document has been placed in the public domain. References [1] http://www.lemburg.com/files/python/mxDateTime.html [2] http://sourceforge.net/patch/?func=detailpatch&patch_id=102652&group_id=5470 [3] http://www.lemburg.com/files/python/CoercionProposal.html

Final

PEP 208 – Reworking the Coercion Model

Standards Track

Many Python types implement numeric operations. When the arguments of a numeric operation are of different types, the interpreter tries to coerce the arguments into a common type. The numeric operation is then performed using this common type. This PEP proposes a new type flag to indicate that arguments to a type’s numeric operations should not be coerced. Operations that do not support the supplied types indicate it by returning a new singleton object. Types which do not set the type flag are handled in a backwards compatible manner. Allowing operations handle different types is often simpler, more flexible, and faster than having the interpreter do coercion.