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.
I've received some enthusiastic emails from someone who wants to
revive restricted mode. He started out with a bunch of patches to the
CPython runtime using ctypes, which he attached to an App Engine bug:
Based on his code (the file secure.py is all you need, included in
secure.tar.gz) it seems he believes the only security leaks are
__subclasses__, gi_frame and gi_code. (I have since convinced him that
if we add "restricted" guards to these attributes, he doesn't need the
functions added to sys.)
I don't recall the exploits that Samuele once posted that caused the
death of rexec.py -- does anyone recall, or have a pointer to the
--Guido van Rossum (home page: http://www.python.org/~guido/)
Alright, I will re-submit with the contents pasted. I never use double
backquotes as I think them rather ugly; that is the work of an editor
or some automated program in the chain. Plus, it also messed up my
line formatting and now I have lines with one word on them... Anyway,
the contents of PEP 3145:
Title: Asynchronous I/O For subprocess.Popen
Author: (James) Eric Pruitt, Charles R. McCreary, Josiah Carlson
Type: Standards Track
In its present form, the subprocess.Popen implementation is prone to
dead-locking and blocking of the parent Python script while waiting on data
from the child process.
A search for "python asynchronous subprocess" will turn up numerous
accounts of people wanting to execute a child process and communicate with
it from time to time reading only the data that is available instead of
blocking to wait for the program to produce data   . The current
behavior of the subprocess module is that when a user sends or receives
data via the stdin, stderr and stdout file objects, dead locks are common
and documented  . While communicate can be used to alleviate some of
the buffering issues, it will still cause the parent process to block while
attempting to read data when none is available to be read from the child
There is a documented need for asynchronous, non-blocking functionality in
subprocess.Popen    . Inclusion of the code would improve the
utility of the Python standard library that can be used on Unix based and
Windows builds of Python. Practically every I/O object in Python has a
file-like wrapper of some sort. Sockets already act as such and for
strings there is StringIO. Popen can be made to act like a file by simply
using the methods attached the the subprocess.Popen.stderr, stdout and
stdin file-like objects. But when using the read and write methods of
those options, you do not have the benefit of asynchronous I/O. In the
proposed solution the wrapper wraps the asynchronous methods to mimic a
I have been maintaining a Google Code repository that contains all of my
changes including tests and documentation  as well as blog detailing
the problems I have come across in the development process .
I have been working on implementing non-blocking asynchronous I/O in the
subprocess.Popen module as well as a wrapper class for subprocess.Popen
that makes it so that an executed process can take the place of a file by
duplicating all of the methods and attributes that file objects have.
There are two base functions that have been added to the subprocess.Popen
class: Popen.send and Popen._recv, each with two separate implementations,
one for Windows and one for Unix based systems. The Windows
implementation uses ctypes to access the functions needed to control pipes
in the kernel 32 DLL in an asynchronous manner. On Unix based systems,
the Python interface for file control serves the same purpose. The
different implementations of Popen.send and Popen._recv have identical
arguments to make code that uses these functions work across multiple
When calling the Popen._recv function, it requires the pipe name be
passed as an argument so there exists the Popen.recv function that passes
selects stdout as the pipe for Popen._recv by default. Popen.recv_err
selects stderr as the pipe by default. "Popen.recv" and "Popen.recv_err"
are much easier to read and understand than "Popen._recv('stdout' ..." and
"Popen._recv('stderr' ..." respectively.
Since the Popen._recv function does not wait on data to be produced
before returning a value, it may return empty bytes. Popen.asyncread
handles this issue by returning all data read over a given time
The ProcessIOWrapper class uses the asyncread and asyncwrite functions to
allow a process to act like a file so that there are no blocking issues
that can arise from using the stdout and stdin file objects produced from
a subprocess.Popen call.
 [ python-Feature Requests-1191964 ] asynchronous Subprocess
 Daily Life in an Ivory Basement : /feb-07/problems-with-subprocess
 How can I run an external command asynchronously from Python? - Stack
 18.1. subprocess - Subprocess management - Python v2.6.2 documentation
 18.1. subprocess - Subprocess management - Python v2.6.2 documentation
 Issue 1191964: asynchronous Subprocess - Python tracker
 Module to allow Asynchronous subprocess use on Windows and Posix
platforms - ActiveState Code
 subprocess.rst - subprocdev - Project Hosting on Google Code
 subprocdev - Project Hosting on Google Code
 Python Subprocess Dev
This P.E.P. is licensed under the Open Publication License;
On Tue, Sep 8, 2009 at 22:56, Benjamin Peterson <benjamin(a)python.org> wrote:
> 2009/9/7 Eric Pruitt <eric.pruitt(a)gmail.com>:
>> Hello all,
>> I have been working on adding asynchronous I/O to the Python
>> subprocess module as part of my Google Summer of Code project. Now
>> that I have finished documenting and pruning the code, I present PEP
>> 3145 for its inclusion into the Python core code. Any and all feedback
>> on the PEP (http://www.python.org/dev/peps/pep-3145/) is appreciated.
> Hi Eric,
> One of the reasons you're not getting many response is that you've not
> pasted the contents of the PEP in this message. That makes it really
> easy for people to comment on various sections.
> BTW, it seems like you were trying to use reST formatting with the
> text PEP layout. Double backquotes only mean something in reST.
In reviewing a fix for the metaclass calculation in __build_class__
, I realised that PEP 3115 poses a potential problem for the common
practice of using "type(name, bases, ns)" for dynamic class creation.
Specifically, if one of the base classes has a metaclass with a
significant __prepare__() method, then the current idiom will do the
wrong thing (and most likely fail as a result), since "ns" will
probably be an ordinary dictionary instead of whatever __prepare__()
would have returned.
Initially I was going to suggest making __build_class__ part of the
language definition rather than a CPython implementation detail, but
then I realised that various CPython specific elements in its
signature made that a bad idea.
Instead, I'm thinking along the lines of an
"operator.prepare(metaclass, bases)" function that does the metaclass
calculation dance, invoking __prepare__() and returning the result if
it exists, otherwise returning an ordinary dict. Under the hood we
would refactor this so that operator.prepare and __build_class__ were
using a shared implementation of the functionality at the C level - it
may even be advisable to expose that implementation via the C API as
The correct idiom for dynamic type creation in a PEP 3115 world would then be:
from operator import prepare
cls = type(name, bases, prepare(type, bases))
Nick Coghlan | ncoghlan(a)gmail.com | Brisbane, Australia
while there is at least some interest in incorporating my
optimizations, response has still been low. I figure that the changes
are probably too much for a single big incorporation step. On a recent
flight, I thought about cutting it down to make it more easily
digestible. The basic idea is to remove the optimized interpreter
dispatch loop and advanced instruction format and use the existing
ones. Currently (rev. ca8a0dfb2176), opcode.h uses 109 of potentially
available 255 instructions using the current instruction format.
Hence, up to 149 instruction opcodes could be given to optimized
instruction derivatives. Consequently, a possible change would require
a) opcode.h to add new instruction opcodes,
b) ceval.c to include the new instruction opcodes in PyEval_EvalFrameEx,
c) abstract.c, object.c (possible other files) to add the
quickening/rewriting function calls.
If this is more interesting, I could start evaluating which
instruction opcodes should be allocated to which derivatives to get
the biggest benefit. This is a lot easier to implement (because I can
re-use the existing instruction implementations) and can easily be
made to be conditionally compile-able, similar to the computed-gotos
option. Since the changes are minimal it is also simpler to understand
and deal with for everybody else, too. On the "downside", however, not
all optimizations are possible and/or make sense in the given limit of
instructions (no data-object inlining and no reference-count
How does that sound?
Have a nice day,
Currently if you work in console and define a function and then
immediately call it - it will fail with SyntaxError.
For example, copy paste this completely valid Python script into console:
There is an issue for that that was just closed by Eric. However, I'd
like to know if there are people here that agree that if you paste a
valid Python script into console - it should work without changes.
> branch: 2.7
> user: Jason R. Coombs <jaraco(a)jaraco.com>
> date: Thu Nov 17 18:03:24 2011 -0500
> PDB now will properly escape backslashes in the names of modules it executes. Fixes #7750
> diff --git a/Lib/test/test_pdb.py b/Lib/test/test_pdb.py
> +class Tester7750(unittest.TestCase):
I think we have an unwritten rule that test class and method names
should tell something about what they test. (We do have things like
TestWeirdBugs and test_12345, but I don’t think it’s a useful pattern to
follow :) Not a big deal anyway.
> + # if the filename has something that resolves to a python
> + # escape character (such as \t), it will fail
> + test_fn = '.\\test7750.py'
> + msg = "issue7750 only applies when os.sep is a backslash"
> + @unittest.skipUnless(os.path.sep == '\\', msg)
> + def test_issue7750(self):
> + with open(self.test_fn, 'w') as f:
> + f.write('print("hello world")')
> + cmd = [sys.executable, '-m', 'pdb', self.test_fn,]
> + proc = subprocess.Popen(cmd,
> + stdout=subprocess.PIPE,
> + stdin=subprocess.PIPE,
> + stderr=subprocess.STDOUT,
> + )
> + stdout, stderr = proc.communicate('quit\n')
> + self.assertNotIn('IOError', stdout, "pdb munged the filename")
Why not check for assertIn(filename, stdout)? (In other words, check
for intended behavior rather than implementation of the erstwhile bug.)
BTW, I’ve just tested that giving a message argument to assertNotIn (the
third argument), unittest still displays the other arguments to allow
for easier debugging. I didn’t know that, it’s cool!
> + def tearDown(self):
> + if os.path.isfile(self.test_fn):
> + os.remove(self.test_fn)
In my own tests, I’ve become fond of using “self.addCleanup(os.remove,
filename)”: It’s shorter that a tearDown and is right there on the line
that follows or precedes the file creation.
> if __name__ == '__main__':
> + unittest.main()
This looks strange.
Given GCC's announcement that Intel's STM will be an extension for C
and C++ in GCC 4.7, what does this mean for Python, and the GIL?
I've seen efforts made to make STM available as a context, and for use
in user code. I've also read about the "old attempts way back" that
attempted to use finer grain locking. The understandably failed due to
the heavy costs involved in both the locking mechanisms used, and the
overhead of a reference counting garbage collection system.
However given advances in locking and garbage collection in the last
decade, what attempts have been made recently to try these new ideas
out? In particular, how unlikely is it that all the thread safe
primitives, global contexts, and reference counting functions be made
__transaction_atomic, and magical parallelism performance boosts
I'm aware that C89, platforms without STM/GCC, and single threaded
performance are concerns. Please ignore these for the sake of
discussion about possibilities.
I apologize in advance for the length of this mail.
When a script or a module is executed by invoking python with proper
arguments, sys.path is extended. When a path to script is given, the
directory containing the script is prepended. When '-m' or '-c' is used,
$CWD is prepended. This is documented in
http://docs.python.org/dev/using/cmdline.html, so far ok.
sys.path and $PYTHONPATH is like $PATH -- if you can convince someone to
put a directory under your control in any of them, you can execute code
as this someone. Therefore, sys.path is dangerous and important.
Unfortunately, sys.path manipulations are only described very briefly,
and without any commentary, in the on-line documentation. python(1)
manpage doesn't even mention them.
The problem: each of the commands below is insecure:
python /tmp/script.py (when script.py is safe by itself)
('/tmp' is added to sys.path, so an attacker can override any
module imported in /tmp/script.py by writing to /tmp/module.py)
cd /tmp && python -mtimeit -s 'import numpy' 'numpy.test()'
(UNIX users are accustomed to being able to safely execute
programs in any directory, e.g. ls, or gcc, or something.
Here '' is added to sys.path, so it is not secure to run
python is other-user-writable directories.)
cd /tmp/ && python -c 'import numpy; print(numpy.version.version)'
(The same as above, '' is added to sys.path.)
cd /tmp && python
(The same as above).
IMHO, if this (long-lived) behaviour is necessary, it should at least be
prominently documented. Also in the manpage.
Before adding a directory to sys.path as described above, Python
actually runs os.path.realpath over it. This means that if the path to a
script given on the commandline is actually a symlink, the directory
containing the real file will be executed. This behaviour is not really
documented (the documentation only says "the directory containing that
file is added to the start of sys.path"), but since the integrity of
sys.path is so important, it should be, IMHO.
Using realpath instead of the (expected) path specified by the user
breaks imports of non-pure-python (mixed .py and .so) modules from
modules executed as scripts on Debian. This is because Debian installs
architecture-independent python files in /usr/share/pyshared, and
symlinks those files into /usr/lib/pymodules/pythonX.Y/. The
architecture-dependent .so and python-version-dependent .pyc files are
installed in /usr/lib/pymodules/pythonX.Y/. When a script, e.g.
/usr/lib/pymodules/pythonX.Y/script.py, is executed, the directory
/usr/share/pyshared is prepended to sys.path. If the script tries to
import a module which has architecture-dependent parts (e.g. numpy) it
first sees the incomplete module in /usr/share/pyshared and fails.
This happens for example in parallel python
(http://bugs.debian.org/cgi-bin/bugreport.cgi?bug=620551) and recently
when packaging CellProfiler for Debian.
Again, if this is on purpose, it should be documented.
PEP 395 (Qualified Names for Modules)
PEP 395 proposes another sys.path manipulation. When running a script,
the directory tree will be walked upwards as long as there are
__init__.py files, and then the first directory without will be added.
This is of course a fine idea, but it makes a scenario, which was
previously safe, insecure. More precisely, when executing a script in a
directory in a parent directory-writable-by-other-users, the parent
directory will be added to sys.path.
So the (safe) operation of downloading an archive with a package,
unzipping it in /tmp, changing into the created directory, checking that
the script doesn't do anything bad, and running a script is now insecure
if there is __init__.py in the archive root.
I guess that it would be useful to have an option to turn off those