It has been a while since I posted a copy of PEP 1 to the mailing
lists and newsgroups. I've recently done some updating of a few
sections, so in the interest of gaining wider community participation
in the Python development process, I'm posting the latest revision of
PEP 1 here. A version of the PEP is always available on-line at
-------------------- snip snip --------------------
Title: PEP Purpose and Guidelines
Version: $Revision: 1.36 $
Last-Modified: $Date: 2002/07/29 18:34:59 $
Author: Barry A. Warsaw, Jeremy Hylton
Post-History: 21-Mar-2001, 29-Jul-2002
What is a PEP?
PEP stands for Python Enhancement Proposal. A PEP is a design
document providing information to the Python community, or
describing a new feature for Python. The PEP should provide a
concise technical specification of the feature and a rationale for
We intend PEPs to be the primary mechanisms for proposing new
features, for collecting community input on an issue, and for
documenting the design decisions that have gone into Python. The
PEP author is responsible for building consensus within the
community and documenting dissenting opinions.
Because the PEPs are maintained as plain text files under CVS
control, their revision history is the historical record of the
Kinds of PEPs
There are two kinds of PEPs. A standards track PEP describes a
new feature or implementation for Python. An informational PEP
describes a Python design issue, or provides general guidelines or
information to the Python community, but does not propose a new
feature. Informational PEPs do not necessarily represent a Python
community consensus or recommendation, so users and implementors
are free to ignore informational PEPs or follow their advice.
PEP Work Flow
The PEP editor, Barry Warsaw <peps(a)python.org>, assigns numbers
for each PEP and changes its status.
The PEP process begins with a new idea for Python. It is highly
recommended that a single PEP contain a single key proposal or new
idea. The more focussed the PEP, the more successfully it tends
to be. The PEP editor reserves the right to reject PEP proposals
if they appear too unfocussed or too broad. If in doubt, split
your PEP into several well-focussed ones.
Each PEP must have a champion -- someone who writes the PEP using
the style and format described below, shepherds the discussions in
the appropriate forums, and attempts to build community consensus
around the idea. The PEP champion (a.k.a. Author) should first
attempt to ascertain whether the idea is PEP-able. Small
enhancements or patches often don't need a PEP and can be injected
into the Python development work flow with a patch submission to
the SourceForge patch manager or feature request tracker.
The PEP champion then emails the PEP editor <peps(a)python.org> with
a proposed title and a rough, but fleshed out, draft of the PEP.
This draft must be written in PEP style as described below.
If the PEP editor approves, he will assign the PEP a number, label
it as standards track or informational, give it status 'draft',
and create and check-in the initial draft of the PEP. The PEP
editor will not unreasonably deny a PEP. Reasons for denying PEP
status include duplication of effort, being technically unsound,
not providing proper motivation or addressing backwards
compatibility, or not in keeping with the Python philosophy. The
BDFL (Benevolent Dictator for Life, Guido van Rossum) can be
consulted during the approval phase, and is the final arbitrator
of the draft's PEP-ability.
If a pre-PEP is rejected, the author may elect to take the pre-PEP
to the comp.lang.python newsgroup (a.k.a. python-list(a)python.org
mailing list) to help flesh it out, gain feedback and consensus
from the community at large, and improve the PEP for
The author of the PEP is then responsible for posting the PEP to
the community forums, and marshaling community support for it. As
updates are necessary, the PEP author can check in new versions if
they have CVS commit permissions, or can email new PEP versions to
the PEP editor for committing.
Standards track PEPs consists of two parts, a design document and
a reference implementation. The PEP should be reviewed and
accepted before a reference implementation is begun, unless a
reference implementation will aid people in studying the PEP.
Standards Track PEPs must include an implementation - in the form
of code, patch, or URL to same - before it can be considered
PEP authors are responsible for collecting community feedback on a
PEP before submitting it for review. A PEP that has not been
discussed on python-list(a)python.org and/or python-dev(a)python.org
will not be accepted. However, wherever possible, long open-ended
discussions on public mailing lists should be avoided. Strategies
to keep the discussions efficient include, setting up a separate
SIG mailing list for the topic, having the PEP author accept
private comments in the early design phases, etc. PEP authors
should use their discretion here.
Once the authors have completed a PEP, they must inform the PEP
editor that it is ready for review. PEPs are reviewed by the BDFL
and his chosen consultants, who may accept or reject a PEP or send
it back to the author(s) for revision.
Once a PEP has been accepted, the reference implementation must be
completed. When the reference implementation is complete and
accepted by the BDFL, the status will be changed to `Final.'
A PEP can also be assigned status `Deferred.' The PEP author or
editor can assign the PEP this status when no progress is being
made on the PEP. Once a PEP is deferred, the PEP editor can
re-assign it to draft status.
A PEP can also be `Rejected'. Perhaps after all is said and done
it was not a good idea. It is still important to have a record of
PEPs can also be replaced by a different PEP, rendering the
original obsolete. This is intended for Informational PEPs, where
version 2 of an API can replace version 1.
PEP work flow is as follows:
Draft -> Accepted -> Final -> Replaced
Some informational PEPs may also have a status of `Active' if they
are never meant to be completed. E.g. PEP 1.
What belongs in a successful PEP?
Each PEP should have the following parts:
1. Preamble -- RFC822 style headers containing meta-data about the
PEP, including the PEP number, a short descriptive title
(limited to a maximum of 44 characters), the names, and
optionally the contact info for each author, etc.
2. Abstract -- a short (~200 word) description of the technical
issue being addressed.
3. Copyright/public domain -- Each PEP must either be explicitly
labelled as placed in the public domain (see this PEP as an
example) or licensed under the Open Publication License.
4. Specification -- The technical specification should describe
the syntax and semantics of any new language feature. The
specification should be detailed enough to allow competing,
interoperable implementations for any of the current Python
platforms (CPython, JPython, Python .NET).
5. Motivation -- The motivation is critical for PEPs that want to
change the Python language. It should clearly explain why the
existing language specification is inadequate to address the
problem that the PEP solves. PEP submissions without
sufficient motivation may be rejected outright.
6. Rationale -- The rationale fleshes out the specification by
describing what motivated the design and why particular design
decisions were made. It should describe alternate designs that
were considered and related work, e.g. how the feature is
supported in other languages.
The rationale should provide evidence of consensus within the
community and discuss important objections or concerns raised
7. Backwards Compatibility -- All PEPs that introduce backwards
incompatibilities must include a section describing these
incompatibilities and their severity. The PEP must explain how
the author proposes to deal with these incompatibilities. PEP
submissions without a sufficient backwards compatibility
treatise may be rejected outright.
8. Reference Implementation -- The reference implementation must
be completed before any PEP is given status 'Final,' but it
need not be completed before the PEP is accepted. It is better
to finish the specification and rationale first and reach
consensus on it before writing code.
The final implementation must include test code and
documentation appropriate for either the Python language
reference or the standard library reference.
PEPs are written in plain ASCII text, and should adhere to a
rigid style. There is a Python script that parses this style and
converts the plain text PEP to HTML for viewing on the web.
PEP 9 contains a boilerplate template you can use to get
started writing your PEP.
Each PEP must begin with an RFC822 style header preamble. The
headers must appear in the following order. Headers marked with
`*' are optional and are described below. All other headers are
PEP: <pep number>
Title: <pep title>
Version: <cvs version string>
Last-Modified: <cvs date string>
Author: <list of authors' real names and optionally, email addrs>
* Discussions-To: <email address>
Status: <Draft | Active | Accepted | Deferred | Final | Replaced>
Type: <Informational | Standards Track>
* Requires: <pep numbers>
Created: <date created on, in dd-mmm-yyyy format>
* Python-Version: <version number>
Post-History: <dates of postings to python-list and python-dev>
* Replaces: <pep number>
* Replaced-By: <pep number>
The Author: header lists the names and optionally, the email
addresses of all the authors/owners of the PEP. The format of the
author entry should be
address(a)dom.ain (Random J. User)
if the email address is included, and just
Random J. User
if the address is not given. If there are multiple authors, each
should be on a separate line following RFC 822 continuation line
conventions. Note that personal email addresses in PEPs will be
obscured as a defense against spam harvesters.
Standards track PEPs must have a Python-Version: header which
indicates the version of Python that the feature will be released
with. Informational PEPs do not need a Python-Version: header.
While a PEP is in private discussions (usually during the initial
Draft phase), a Discussions-To: header will indicate the mailing
list or URL where the PEP is being discussed. No Discussions-To:
header is necessary if the PEP is being discussed privately with
the author, or on the python-list or python-dev email mailing
lists. Note that email addresses in the Discussions-To: header
will not be obscured.
Created: records the date that the PEP was assigned a number,
while Post-History: is used to record the dates of when new
versions of the PEP are posted to python-list and/or python-dev.
Both headers should be in dd-mmm-yyyy format, e.g. 14-Aug-2001.
PEPs may have a Requires: header, indicating the PEP numbers that
this PEP depends on.
PEPs may also have a Replaced-By: header indicating that a PEP has
been rendered obsolete by a later document; the value is the
number of the PEP that replaces the current document. The newer
PEP must have a Replaces: header containing the number of the PEP
that it rendered obsolete.
PEP Formatting Requirements
PEP headings must begin in column zero and the initial letter of
each word must be capitalized as in book titles. Acronyms should
be in all capitals. The body of each section must be indented 4
spaces. Code samples inside body sections should be indented a
further 4 spaces, and other indentation can be used as required to
make the text readable. You must use two blank lines between the
last line of a section's body and the next section heading.
You must adhere to the Emacs convention of adding two spaces at
the end of every sentence. You should fill your paragraphs to
column 70, but under no circumstances should your lines extend
past column 79. If your code samples spill over column 79, you
should rewrite them.
Tab characters must never appear in the document at all. A PEP
should include the standard Emacs stanza included by example at
the bottom of this PEP.
A PEP must contain a Copyright section, and it is strongly
recommended to put the PEP in the public domain.
When referencing an external web page in the body of a PEP, you
should include the title of the page in the text, with a
footnote reference to the URL. Do not include the URL in the body
text of the PEP. E.g.
Refer to the Python Language web site  for more details.
When referring to another PEP, include the PEP number in the body
text, such as "PEP 1". The title may optionally appear. Add a
footnote reference that includes the PEP's title and author. It
may optionally include the explicit URL on a separate line, but
only in the References section. Note that the pep2html.py script
will calculate URLs automatically, e.g.:
Refer to PEP 1  for more information about PEP style
 PEP 1, PEP Purpose and Guidelines, Warsaw, Hylton
If you decide to provide an explicit URL for a PEP, please use
this as the URL template:
PEP numbers in URLs must be padded with zeros from the left, so as
to be exactly 4 characters wide, however PEP numbers in text are
Reporting PEP Bugs, or Submitting PEP Updates
How you report a bug, or submit a PEP update depends on several
factors, such as the maturity of the PEP, the preferences of the
PEP author, and the nature of your comments. For the early draft
stages of the PEP, it's probably best to send your comments and
changes directly to the PEP author. For more mature, or finished
PEPs you may want to submit corrections to the SourceForge bug
manager or better yet, the SourceForge patch manager so that
your changes don't get lost. If the PEP author is a SF developer,
assign the bug/patch to him, otherwise assign it to the PEP
When in doubt about where to send your changes, please check first
with the PEP author and/or PEP editor.
PEP authors who are also SF committers, can update the PEPs
themselves by using "cvs commit" to commit their changes.
Remember to also push the formatted PEP text out to the web by
doing the following:
% python pep2html.py -i NUM
where NUM is the number of the PEP you want to push out. See
% python pep2html.py --help
Transferring PEP Ownership
It occasionally becomes necessary to transfer ownership of PEPs to
a new champion. In general, we'd like to retain the original
author as a co-author of the transferred PEP, but that's really up
to the original author. A good reason to transfer ownership is
because the original author no longer has the time or interest in
updating it or following through with the PEP process, or has
fallen off the face of the 'net (i.e. is unreachable or not
responding to email). A bad reason to transfer ownership is
because you don't agree with the direction of the PEP. We try to
build consensus around a PEP, but if that's not possible, you can
always submit a competing PEP.
If you are interested assuming ownership of a PEP, send a message
asking to take over, addressed to both the original author and the
PEP editor <peps(a)python.org>. If the original author doesn't
respond to email in a timely manner, the PEP editor will make a
unilateral decision (it's not like such decisions can be
References and Footnotes
 This historical record is available by the normal CVS commands
for retrieving older revisions. For those without direct access
to the CVS tree, you can browse the current and past PEP revisions
via the SourceForge web site at
 The script referred to here is pep2html.py, which lives in
the same directory in the CVS tree as the PEPs themselves.
Try "pep2html.py --help" for details.
The URL for viewing PEPs on the web is
 PEP 9, Sample PEP Template
This document has been placed in the public domain.
webmaster has already heard from 4 people who cannot install it.
I sent them to the bug tracker or to python-list but they seem
not to have gone either place. Is there some guide I should be
sending them to, 'how to debug installation problems'?
My question is simple: do we officially support Solaris and/or OpenIndiana?
Jesus Cea runs an OpenIndiana buildbot slave:
"Open Indiana 32 bits"
The platform module of Python says "Solaris-2.11", I don't know the
exact OpenIndiana version.
A lot of unit tests fail on this buildbot with MemoryError. I guess
that it's related to Solaris which doesn't allow overcommit
(allocating more memory than available memory on the system), or more
simply because the slave has not enough memory.
There is now an issue which seems specific to OpenIndiana:
It might impact Solaris as well, but the Solaris buildbot is offline
since "684 builds".
Five years ago, I reported a bug because the curses module of Python 3
doesn't build on Solaris nor OpenIndiana anymore. It seems like the
bug was not fixed, and the issue is still open:
So my question is if we officially support Solaris and/or OpenIndiana.
If yes, how can we fix issues when we only have buildbot slave which
has memory errors, and no SSH access to this server?
Solaris doesn't seem to be officially supported in Python, so I
suggest to drop the OpenIndiana buildbot (which is failing since at
least 2 years) and close all Solaris issues as "WONTFIX".
Classes that doesn't define the __format__ method for custom PEP 3101
formatting inherits it from parents.
Originally the object.__format__ method was designed as :
def __format__(self, format_spec):
return format(str(self), format_spec)
An instance is converted to string and resulting string is formatted
according to format specifier.
Later this design was reconsidered , and now object.__format__ is
def __format__(self, format_spec):
assert format_spec == ''
return format(str(self), '')
Non-empty format specifier is rejected.
But why call format() on resulting string? Why not return resulting
string as is? object.__format__ could be simpler (not just
implementation, but for understanding):
def __format__(self, format_spec):
assert format_spec == ''
This can change the behaviour in corner case. str(self) can return not
exact string, but string subclass with overloaded __format__. But I
think we can ignore such subtle difference.
It's an old feature of the weakref API that you can define an
arbitrary callback to be invoked when the referenced object dies, and
that when this callback is invoked, it gets handed the weakref wrapper
object -- BUT, only after it's been cleared, so that the callback
can't access the originally referenced object. (I.e., this callback
will never raise: def callback(ref): assert ref() is None.)
AFAICT the original motivation for this seems was that if the weakref
callback could get at the object, then the weakref callback would
effectively be another finalizer like __del__, and finalizers and
reference cycles don't mix, so weakref callbacks can't be finalizers.
There's a long document from the 2.4 days about all the terrible
things that could happen if arbitrary code like callbacks could get
unfettered access to cyclic isolates at weakref cleanup time .
But that was 2.4. In the mean time, of course, PEP 442 fixed it so
that finalizers and weakrefs mix just fine. In fact, weakref callbacks
are now run *before* __del__ methods , so clearly it's now okay for
arbitrary code to touch the objects during that phase of the GC -- at
least in principle.
So what I'm wondering is, would anything terrible happen if we started
passing still-live weakrefs into weakref callbacks, and then clearing
them afterwards? (i.e. making step 1 of the PEP 442 cleanup order be
"run callbacks and then clear weakrefs", instead of the current "clear
weakrefs and then run callbacks"). I skimmed through the PEP 442
discussion, and AFAICT the rationale for keeping the old weakref
behavior was just that no-one could be bothered to mess with it .
[The motivation for my question is partly curiosity, and partly that
in the discussion about how to handle GC for async objects, it
occurred to me that it might be very nice if arbitrary classes that
needed access to the event loop during cleanup could do something like
def __init__(self, ...):
loop = asyncio.get_event_loop()
# automatically called by the loop when I am GC'ed; async equivalent
async def aclose(self):
Right now something *sort* of like this is possible but it requires a
much more cumbersome API, where every class would have to implement
logic to fetch a cleanup callback from the loop, store it, and then
call it from its __del__ method -- like how PEP 525 does it. Delaying
weakref clearing would make this simpler API possible.]
Nathaniel J. Smith -- https://vorpus.org
Last months, I worked a lot on benchmarks. I ran benchmarks, analyzed
results in depth (up to the hardware and kernel drivers!), I wrote new
tools and enhanced existing tools.
* I wrote a new perf module which runs benchmarks in a reliable way
and contains a LOT of features: collect metadata, JSON file format,
commands to compare, render an histogram, etc.
* I rewrote the Python benchmark suite: the old benchmarks Mercurial
repository moved to a new performance GitHub project which uses my
perf module and contains more benchmarks.
* I also made minor enhancements to timeit in Python 3.7 -- some dev
don't want major changes to not "break the backward compatibility".
For timeit, I suggest to use my perf tool which includes a reliable
timeit command and has much more features like --duplicate (repeat the
statements to reduce the cost of the outer loop) and --compare-to
(compare two versions of Python), but also all builtin perf features
(JSON output, statistics, histogram, etc.).
I added benchmarks from PyPy and Pyston benchmark suites to
performance: performance 0.3.1 contains 51 benchmark scripts which run
a total of 121 benchmarks. Example of tested Python modules:
* Dulwich (full Git implementation in Python)
* Mercurial (currently only the startup time)
* pyaes (AES crypto cipher in pure Python)
* Tornado (HTTP client and server)
* Django (sadly, only the template engine right now, Pyston contains
More benchmarks will be added later. It would be nice to add
benchmarks on numpy for example, numpy is important for a large part
of our community.
All these (new or updated) tools can now be used to take smarter
decisions on optimizations. Please don't push any optimization anymore
without providing reliable benchmark results!
My first major action was to close the latest attempt to
micro-optimize int+int in Python/ceval.c,
http://bugs.python.org/issue21955 : I closed the issue as rejected,
because there is no significant speedup on benchmarks other than two
(tiny) microbenchmarks. To make sure that no one looses its time on
trying to micro-optimize int+int, I even added a comment to
"Please don't try to micro-optimize int+int"
The perf and performance are now well tested: Travis CI runs tests on
the new commits and pull requests, and the "tox" command can be used
locally to test different Python versions, pep8, doc, ... in a single
* Run performance 0.3.1 on speed.python.org: the benchmark runner is
currently stopped (and still uses the old benchmarks project). The
website part may be updated to allow to download full JSON files which
includes *all* information (all timings, metadata and more).
* I plan to run performance on CPython 2.7, CPython 3.7, PyPy and PyPy
3. Maybe also CPython 3.5 and CPython 3.6 if they don't take too much
* Later, we can consider adding more implementations of Python:
Jython, IronPython, MicroPython, Pyston, Pyjion, etc. All benchmarks
should be run on the same hardware to be comparable.
* Later, we might also allow other projects to upload their own
benchmark results, but we should find a solution to groups benchmark
results per benchmark runner (ex: at least by the hostname, perf JSON
contains the hostname) to not compare two results from two different
* We should continue to add more benchmarks to the performance
benchmark suite, especially benchmarks more representative of real
applications (we have enough microbenchmarks!)
* perf: http://perf.readthedocs.io/
* performance: https://github.com/python/performance
* Python Speed mailing list: https://mail.python.org/mailman/listinfo/speed
* https://speed.python.org/ (currently outdated, and don't use performance yet)
See https://pypi.python.org/pypi/performance which contains even more
links to Python benchmarks (PyPy, Pyston, Numba, Pythran, etc.)
(Added python-dev in CC list, because there are enough +1 already).
On Mon, Oct 17, 2016 at 3:06 PM, Chris Angelico <rosuav(a)gmail.com> wrote:
> On Mon, Oct 17, 2016 at 5:02 PM, INADA Naoki <songofacandy(a)gmail.com> wrote:
>> $ ./python.exe -V
>> Python 3.6.0b2+
>> $ ./python.exe -VV
>> Python 3.6.0b2+ (3.6:0b29adb5c804+, Oct 17 2016, 15:00:12)
>> [GCC 4.2.1 Compatible Apple LLVM 8.0.0 (clang-800.0.38)]
> What's the view on backporting this to 2.7.x? We're still a good few
> years away from its death, and it'd be helpful if recent 2.7s could
> give this info too.
I want to add it at least Python 3.6. Because one reason I want to
propose this is
I can't see exact Python version (commit id) for "nightly" or
"3.6-dev" on Travis-CI test.
But Python 3.6 is beta stage already. If we apply rule strictly, it
should be added
only in default branch (Python 3.7).
So, what version can I add this?
a. Only Python 3.7+
b. (beta) Python 3.6+
c. (maintenance) Python 2.7 and Python 3.5+
INADA Naoki <songofacandy(a)gmail.com>
The third, and next-to-last, beta snapshot planned for the 3.6 release cycle is coming up in a few days. With fewer than 7 weeks remaining until the 3.6.0 release, it is very important that we all focus on stability and correctness. Please try to make sure that all remaining non-doc issues associated with new features are addressed in b3. Any remaining 3.6 feature-related issues still open after b3 should be marked in the issue tracker as "release blocker" and *must* be addressed one way or another by b4, 11-21. All other non-critical bug fixes should also be checked in by b4. Only release critical and doc fixes will be allowed once we exit the beta phase. Please plan accordingly.
Please contact me if you have any questions about the 3.6.0 schedule or about whether a change is appropriate at this point in the 3.6.0 cycle.
To recap, the remaining milestones for 3.6.0:
2016-10-31, 1200 UTC: 3.6.0 beta 3 (feature fixes, bug fixes, doc fixes)
2016-11-21: 3.6.0 beta 4 (important bug fixes and doc fixes)
2016-12-05 3.6.0 release candidate 1 (3.6.0 code freeze, release critical bug fixes, doc fixes)
2016-12-16 3.6.0 release (3.6.0rc1 plus any necessary emergency fixes)
Thank you all again for your efforts so far on 3.6!
nad(a)python.org -- 
The docs for this class state:
"Future instances are created by Executor.submit() and should not be
created directly except for testing."
We have a need for a thread-safe future type in our extension but this
statement makes us hesitate to use it. We don't need the executor
We can write our own future class easily enough, we're just wondering what
the justification was for the limitations mentioned in the docs.