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.
In Python 2.5 `0or` was accepted by the Python parser. It became an
error in 2.6 because "0o" became recognizing as an incomplete octal
number. `1or` still is accepted.
On other hand, `1if 2else 3` is accepted despites the fact that "2e" can
be recognized as an incomplete floating point number. In this case the
tokenizer pushes "e" back and returns "2".
Shouldn't it do the same with "0o"? It is possible to make `0or` be
parseable again. Python implementation is able to tokenize this example:
$ echo '0or' | ./python -m tokenize
1,0-1,1: NUMBER '0'
1,1-1,3: NAME 'or'
1,3-1,4: OP '['
1,4-1,5: OP ']'
1,5-1,6: NEWLINE '\n'
2,0-2,0: ENDMARKER ''
On other hand, all these examples look weird. There is an assymmetry:
`1or 2` is a valid syntax, but `1 or2` is not. It is hard to recognize
visually the boundary between a number and the following identifier or
keyword, especially if numbers can contain letters ("b", "e", "j", "o",
"x") and underscores, and identifiers can contain digits. On both sides
of the boundary can be letters, digits, and underscores.
I propose to change the Python syntax by adding a requirement that there
should be a whitespace or delimiter between a numeric literal and the
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'?
If one goes to httWhps://www.python.org/downloads
<https://www.python.org/downloads> from a Windows browser, the default
download URL is for the 32-bit installer instead of the 64-bit one.
I wonder why is this still the case?
Shouldn't we encourage new Windows users (who may not even know the
distinction between the two architectures) to use the 64-bit version of
Python, since most likely they can?
If this is not the correct forum for this, please let me know where I can
direct my question/feature request, thanks.
Happy New Year everyone!
I would like to start a thread here for wider feedback on my proposal to
change the return type of the addition operation between a datetime
subclass and a timedelta. Currently, adding a timedelta to a subclass of
datetime /always/ returns a datetime rather than an instance of the
I have an open PR implementing this, PR #10902
<https://github.com/python/cpython/pull/10902>, but I know it's a major
change so I did not want to move forward without more discussion. I
first brought this up on datetime-SIG
, and we decided to move the discussion over here because the people
most likely to object to the change would be on this list and not on
In addition to the datetime-SIG thread, you may find a detailed
rationale for the change in bpo-35364
<https://bugs.python.org/issue35364#msg331065> , and a rationale for
why we would want to (and arguably already /do/) support subclassing
datetime in bpo-32417 <https://bugs.python.org/issue32417#msg331353> .
A short version of the strongest rationale for changing how this works
is that it is causing inconsistencies in how subclassing is handled in
alternate constructors of datetime. For a given subclass of datetime
(which I will call DateTimeSub), nearly all alternate constructors
already support subclasses correctly - DateTimeSub.fromtimestamp(x) will
return a DateTimeSub, for example. However, because DateTimeSub +
timedelta returns datetime, any alternate constructor implemented in
terms of timedelta additions will leak that implementation detail by
returning a datetime object instead of the subclass. The biggest problem
is that datetime.fromutc is defined in terms of timedelta addition, so
DateTimeSub.now() returns a DateTimeSub object, but
DateTimeSub.now(timezone.utc) returns a datetime object! This is one of
the most annoying things to work around when building a datetime
subclass, and I don't know of any situation where someone /wants/ their
subclass to be lost on addition with a timedelta.
From my understanding, this has been discussed before and the original
objection was that this implementation assumes that the datetime
subclass has a constructor with the same (or a sufficiently similar)
signature as datetime. This may be a legitimate gripe, but unfortunately
that ship has sailed long ago. All of datetime's alternate constructors
make this assumption. Any subclass that does not meet this requirement
must have worked around it long ago (or they don't care about alternate
Thanks for your attention, I look forward to your replies.
Now that regular dicts are ordered and compact, it makes more sense for the _asdict() method to create a regular dict (as it did in its early days) rather than an OrderedDict. The regular dict is much smaller, much faster, and has a much cleaner looking repr. It would also help namedtuple() stay in sync with dataclasses which already take advantage of the ordering feature of regular dicts.
The question is how to be go about making the change in a way gives the most benefit to users as soon as possible and that creates the least disruption.
Option 1) Add a deprecation notice to 3.8, make no code change in 3.8, and then update the code in 3.9. This has several issues: a) it doesn't provide an executable DeprecationWarning in 3.8, b) it isn't really a deprecation, and c) it defers the benefits of the change for another release.
Option 2) Add a deprecation notice to 3.8, add a DeprecationWarning to the _asdict() method, and make the actual improvement in 3.9. The main issue here is that it will create a lot of noise for normal uses of the _asdict() method which are otherwise unaffected by the change. The typical use cases for _asdict() are to create keyword arguments and to pass named tuple data into functions or methods that expect regular dictionaries. Those use cases would benefit from seeing the change made sooner and would suffer in the interim from their code slowing down for warnings that aren't useful.
Option 3). Add a deprecation notice to 3.8 and have the _asdict() method create a subclass of OrderedDict that issues warnings only for the methods and attributes that will change (move_to_end, popitem, __eq__, __dict__, __weakref__). This is less noisy but it adds a lot of machinery just to make a notification of a minor change. Also, it fails to warn that the data type will change. And it may create more confusion than options 1 and 4 which are simpler.
Option 4) Just make the change directly in 3.8, s/OrderedDict/dict/, and be done will it. This gives users the benefits right away and doesn't annoy them with warnings that they likely don't care about. There is some precedent for this. To make namedtuple class creation faster, the *verbose* option was dropped without any deprecation period. It looks like no one missed that feature at all, but they did get the immediate benefit of faster import times. In the case of using regular dicts in named tuples, people will get immediate and significant space savings as well as a speed benefit.
My recommendation is Option 4 as being less disruptive and more beneficial than the other options. In the unlikely event that anyone is currently depending on the reordering methods for the output of _asdict(), the remediation is trivially simple: nt._asdict() -> OrderedDict(nt.as_dict()).
What do you all think?
---------- Forwarded message ---------
From: Steve Holden <steve(a)holdenweb.com>
Date: Thu, Jan 31, 2019 at 11:05 AM
Subject: Re: [Python-Dev] How about updating OrderedDict in csv and
configparser to regular dict?
To: INADA Naoki <songofacandy(a)gmail.com>
And I see that such a patch is now merged. Thanks, Raymond!
https://bugs.python.org/issue15248 is about situations like the following:
Traceback (most recent call last):
File "<pyshell#4>", line 2, in <module>
TypeError: 'tuple' object is not callable
The original poster requested that the error message be augmented with
something like "(missing preceding comma?)"
Ezio Melotti suggested a FAQ entry like
(I think such entries below in a separate doc and will try to post on
python-ideas when I have a prototype.)
Serhiy Storchaka suggested a compiler SyntaxWarning and uploaded a
proof-of-concept diff that handled the above and many similar cases. The
diff is based on the idea that while we can only positively identify
'callables' at runtime, we *can* negatively identify many non-callables
when compiling. Ditto for subscriptables and indexables.
Serhiy concluded with
"This patch was inspired by usability improvements in GCC 8.
I haven't created a pull request because I have doubts about that this
should be in the compiler rather of a third-party linter. But if several
other core developers will support this idea I'll continue working in
I was impressed with how clear and readable the patch is and consider it
a plausible enhancement. I would like other core developers to comment.
Terry Jan Reedy
csv.DictReader uses OrderedDict by default, from Python 3.6.
But it doesn't make sense anymore, like namedtuple._asdict().
How about changing default dict type back to regular dict.
Python is widely used for handling learge data. So I think
changing default dict type to OrderedDict was performance
and memory usage regression in 3.6.
Additionally, configparser uses OrderedDict by default from Python 3.6 too.
I am not sure about `parser['section1'] == parser['section2']` is not used yet.
But we broke it once in 3.6 by changing dict to OrderedDict. Are there any
issue report caused by this backward incompatibility?
And I think performance and memory efficiency is not so important for
configparser, unlike csv.
* +1 about changing csv.DictReader's default dict type
* +0.5 about changing configparser's default dict type.
How do you think?
INADA Naoki <songofacandy(a)gmail.com>