It has been a while since I posted a copy of PEP 1 to the mailing
lists and newsgroups. I've recently done some updating of a few
sections, so in the interest of gaining wider community participation
in the Python development process, I'm posting the latest revision of
PEP 1 here. A version of the PEP is always available on-line at
http://www.python.org/peps/pep-0001.html
Enjoy,
-Barry
-------------------- snip snip --------------------
PEP: 1
Title: PEP Purpose and Guidelines
Version: $Revision: 1.36 $
Last-Modified: $Date: 2002/07/29 18:34:59 $
Author: Barry A. Warsaw, Jeremy Hylton
Status: Active
Type: Informational
Created: 13-Jun-2000
Post-History: 21-Mar-2001, 29-Jul-2002
What is a PEP?
PEP stands for Python Enhancement Proposal. A PEP is a design
document providing information to the Python community, or
describing a new feature for Python. The PEP should provide a
concise technical specification of the feature and a rationale for
the feature.
We intend PEPs to be the primary mechanisms for proposing new
features, for collecting community input on an issue, and for
documenting the design decisions that have gone into Python. The
PEP author is responsible for building consensus within the
community and documenting dissenting opinions.
Because the PEPs are maintained as plain text files under CVS
control, their revision history is the historical record of the
feature proposal[1].
Kinds of PEPs
There are two kinds of PEPs. A standards track PEP describes a
new feature or implementation for Python. An informational PEP
describes a Python design issue, or provides general guidelines or
information to the Python community, but does not propose a new
feature. Informational PEPs do not necessarily represent a Python
community consensus or recommendation, so users and implementors
are free to ignore informational PEPs or follow their advice.
PEP Work Flow
The PEP editor, Barry Warsaw <peps(a)python.org>, assigns numbers
for each PEP and changes its status.
The PEP process begins with a new idea for Python. It is highly
recommended that a single PEP contain a single key proposal or new
idea. The more focussed the PEP, the more successfully it tends
to be. The PEP editor reserves the right to reject PEP proposals
if they appear too unfocussed or too broad. If in doubt, split
your PEP into several well-focussed ones.
Each PEP must have a champion -- someone who writes the PEP using
the style and format described below, shepherds the discussions in
the appropriate forums, and attempts to build community consensus
around the idea. The PEP champion (a.k.a. Author) should first
attempt to ascertain whether the idea is PEP-able. Small
enhancements or patches often don't need a PEP and can be injected
into the Python development work flow with a patch submission to
the SourceForge patch manager[2] or feature request tracker[3].
The PEP champion then emails the PEP editor <peps(a)python.org> with
a proposed title and a rough, but fleshed out, draft of the PEP.
This draft must be written in PEP style as described below.
If the PEP editor approves, he will assign the PEP a number, label
it as standards track or informational, give it status 'draft',
and create and check-in the initial draft of the PEP. The PEP
editor will not unreasonably deny a PEP. Reasons for denying PEP
status include duplication of effort, being technically unsound,
not providing proper motivation or addressing backwards
compatibility, or not in keeping with the Python philosophy. The
BDFL (Benevolent Dictator for Life, Guido van Rossum) can be
consulted during the approval phase, and is the final arbitrator
of the draft's PEP-ability.
If a pre-PEP is rejected, the author may elect to take the pre-PEP
to the comp.lang.python newsgroup (a.k.a. python-list(a)python.org
mailing list) to help flesh it out, gain feedback and consensus
from the community at large, and improve the PEP for
re-submission.
The author of the PEP is then responsible for posting the PEP to
the community forums, and marshaling community support for it. As
updates are necessary, the PEP author can check in new versions if
they have CVS commit permissions, or can email new PEP versions to
the PEP editor for committing.
Standards track PEPs consists of two parts, a design document and
a reference implementation. The PEP should be reviewed and
accepted before a reference implementation is begun, unless a
reference implementation will aid people in studying the PEP.
Standards Track PEPs must include an implementation - in the form
of code, patch, or URL to same - before it can be considered
Final.
PEP authors are responsible for collecting community feedback on a
PEP before submitting it for review. A PEP that has not been
discussed on python-list(a)python.org and/or python-dev(a)python.org
will not be accepted. However, wherever possible, long open-ended
discussions on public mailing lists should be avoided. Strategies
to keep the discussions efficient include, setting up a separate
SIG mailing list for the topic, having the PEP author accept
private comments in the early design phases, etc. PEP authors
should use their discretion here.
Once the authors have completed a PEP, they must inform the PEP
editor that it is ready for review. PEPs are reviewed by the BDFL
and his chosen consultants, who may accept or reject a PEP or send
it back to the author(s) for revision.
Once a PEP has been accepted, the reference implementation must be
completed. When the reference implementation is complete and
accepted by the BDFL, the status will be changed to `Final.'
A PEP can also be assigned status `Deferred.' The PEP author or
editor can assign the PEP this status when no progress is being
made on the PEP. Once a PEP is deferred, the PEP editor can
re-assign it to draft status.
A PEP can also be `Rejected'. Perhaps after all is said and done
it was not a good idea. It is still important to have a record of
this fact.
PEPs can also be replaced by a different PEP, rendering the
original obsolete. This is intended for Informational PEPs, where
version 2 of an API can replace version 1.
PEP work flow is as follows:
Draft -> Accepted -> Final -> Replaced
^
+----> Rejected
v
Deferred
Some informational PEPs may also have a status of `Active' if they
are never meant to be completed. E.g. PEP 1.
What belongs in a successful PEP?
Each PEP should have the following parts:
1. Preamble -- RFC822 style headers containing meta-data about the
PEP, including the PEP number, a short descriptive title
(limited to a maximum of 44 characters), the names, and
optionally the contact info for each author, etc.
2. Abstract -- a short (~200 word) description of the technical
issue being addressed.
3. Copyright/public domain -- Each PEP must either be explicitly
labelled as placed in the public domain (see this PEP as an
example) or licensed under the Open Publication License[4].
4. Specification -- The technical specification should describe
the syntax and semantics of any new language feature. The
specification should be detailed enough to allow competing,
interoperable implementations for any of the current Python
platforms (CPython, JPython, Python .NET).
5. Motivation -- The motivation is critical for PEPs that want to
change the Python language. It should clearly explain why the
existing language specification is inadequate to address the
problem that the PEP solves. PEP submissions without
sufficient motivation may be rejected outright.
6. Rationale -- The rationale fleshes out the specification by
describing what motivated the design and why particular design
decisions were made. It should describe alternate designs that
were considered and related work, e.g. how the feature is
supported in other languages.
The rationale should provide evidence of consensus within the
community and discuss important objections or concerns raised
during discussion.
7. Backwards Compatibility -- All PEPs that introduce backwards
incompatibilities must include a section describing these
incompatibilities and their severity. The PEP must explain how
the author proposes to deal with these incompatibilities. PEP
submissions without a sufficient backwards compatibility
treatise may be rejected outright.
8. Reference Implementation -- The reference implementation must
be completed before any PEP is given status 'Final,' but it
need not be completed before the PEP is accepted. It is better
to finish the specification and rationale first and reach
consensus on it before writing code.
The final implementation must include test code and
documentation appropriate for either the Python language
reference or the standard library reference.
PEP Template
PEPs are written in plain ASCII text, and should adhere to a
rigid style. There is a Python script that parses this style and
converts the plain text PEP to HTML for viewing on the web[5].
PEP 9 contains a boilerplate[7] template you can use to get
started writing your PEP.
Each PEP must begin with an RFC822 style header preamble. The
headers must appear in the following order. Headers marked with
`*' are optional and are described below. All other headers are
required.
PEP: <pep number>
Title: <pep title>
Version: <cvs version string>
Last-Modified: <cvs date string>
Author: <list of authors' real names and optionally, email addrs>
* Discussions-To: <email address>
Status: <Draft | Active | Accepted | Deferred | Final | Replaced>
Type: <Informational | Standards Track>
* Requires: <pep numbers>
Created: <date created on, in dd-mmm-yyyy format>
* Python-Version: <version number>
Post-History: <dates of postings to python-list and python-dev>
* Replaces: <pep number>
* Replaced-By: <pep number>
The Author: header lists the names and optionally, the email
addresses of all the authors/owners of the PEP. The format of the
author entry should be
address(a)dom.ain (Random J. User)
if the email address is included, and just
Random J. User
if the address is not given. If there are multiple authors, each
should be on a separate line following RFC 822 continuation line
conventions. Note that personal email addresses in PEPs will be
obscured as a defense against spam harvesters.
Standards track PEPs must have a Python-Version: header which
indicates the version of Python that the feature will be released
with. Informational PEPs do not need a Python-Version: header.
While a PEP is in private discussions (usually during the initial
Draft phase), a Discussions-To: header will indicate the mailing
list or URL where the PEP is being discussed. No Discussions-To:
header is necessary if the PEP is being discussed privately with
the author, or on the python-list or python-dev email mailing
lists. Note that email addresses in the Discussions-To: header
will not be obscured.
Created: records the date that the PEP was assigned a number,
while Post-History: is used to record the dates of when new
versions of the PEP are posted to python-list and/or python-dev.
Both headers should be in dd-mmm-yyyy format, e.g. 14-Aug-2001.
PEPs may have a Requires: header, indicating the PEP numbers that
this PEP depends on.
PEPs may also have a Replaced-By: header indicating that a PEP has
been rendered obsolete by a later document; the value is the
number of the PEP that replaces the current document. The newer
PEP must have a Replaces: header containing the number of the PEP
that it rendered obsolete.
PEP Formatting Requirements
PEP headings must begin in column zero and the initial letter of
each word must be capitalized as in book titles. Acronyms should
be in all capitals. The body of each section must be indented 4
spaces. Code samples inside body sections should be indented a
further 4 spaces, and other indentation can be used as required to
make the text readable. You must use two blank lines between the
last line of a section's body and the next section heading.
You must adhere to the Emacs convention of adding two spaces at
the end of every sentence. You should fill your paragraphs to
column 70, but under no circumstances should your lines extend
past column 79. If your code samples spill over column 79, you
should rewrite them.
Tab characters must never appear in the document at all. A PEP
should include the standard Emacs stanza included by example at
the bottom of this PEP.
A PEP must contain a Copyright section, and it is strongly
recommended to put the PEP in the public domain.
When referencing an external web page in the body of a PEP, you
should include the title of the page in the text, with a
footnote reference to the URL. Do not include the URL in the body
text of the PEP. E.g.
Refer to the Python Language web site [1] for more details.
...
[1] http://www.python.org
When referring to another PEP, include the PEP number in the body
text, such as "PEP 1". The title may optionally appear. Add a
footnote reference that includes the PEP's title and author. It
may optionally include the explicit URL on a separate line, but
only in the References section. Note that the pep2html.py script
will calculate URLs automatically, e.g.:
...
Refer to PEP 1 [7] for more information about PEP style
...
References
[7] PEP 1, PEP Purpose and Guidelines, Warsaw, Hylton
http://www.python.org/peps/pep-0001.html
If you decide to provide an explicit URL for a PEP, please use
this as the URL template:
http://www.python.org/peps/pep-xxxx.html
PEP numbers in URLs must be padded with zeros from the left, so as
to be exactly 4 characters wide, however PEP numbers in text are
never padded.
Reporting PEP Bugs, or Submitting PEP Updates
How you report a bug, or submit a PEP update depends on several
factors, such as the maturity of the PEP, the preferences of the
PEP author, and the nature of your comments. For the early draft
stages of the PEP, it's probably best to send your comments and
changes directly to the PEP author. For more mature, or finished
PEPs you may want to submit corrections to the SourceForge bug
manager[6] or better yet, the SourceForge patch manager[2] so that
your changes don't get lost. If the PEP author is a SF developer,
assign the bug/patch to him, otherwise assign it to the PEP
editor.
When in doubt about where to send your changes, please check first
with the PEP author and/or PEP editor.
PEP authors who are also SF committers, can update the PEPs
themselves by using "cvs commit" to commit their changes.
Remember to also push the formatted PEP text out to the web by
doing the following:
% python pep2html.py -i NUM
where NUM is the number of the PEP you want to push out. See
% python pep2html.py --help
for details.
Transferring PEP Ownership
It occasionally becomes necessary to transfer ownership of PEPs to
a new champion. In general, we'd like to retain the original
author as a co-author of the transferred PEP, but that's really up
to the original author. A good reason to transfer ownership is
because the original author no longer has the time or interest in
updating it or following through with the PEP process, or has
fallen off the face of the 'net (i.e. is unreachable or not
responding to email). A bad reason to transfer ownership is
because you don't agree with the direction of the PEP. We try to
build consensus around a PEP, but if that's not possible, you can
always submit a competing PEP.
If you are interested assuming ownership of a PEP, send a message
asking to take over, addressed to both the original author and the
PEP editor <peps(a)python.org>. If the original author doesn't
respond to email in a timely manner, the PEP editor will make a
unilateral decision (it's not like such decisions can be
reversed. :).
References and Footnotes
[1] This historical record is available by the normal CVS commands
for retrieving older revisions. For those without direct access
to the CVS tree, you can browse the current and past PEP revisions
via the SourceForge web site at
http://cvs.sourceforge.net/cgi-bin/cvsweb.cgi/python/nondist/peps/?cvsroot=…
[2] http://sourceforge.net/tracker/?group_id=5470&atid=305470
[3] http://sourceforge.net/tracker/?atid=355470&group_id=5470&func=browse
[4] http://www.opencontent.org/openpub/
[5] The script referred to here is pep2html.py, which lives in
the same directory in the CVS tree as the PEPs themselves.
Try "pep2html.py --help" for details.
The URL for viewing PEPs on the web is
http://www.python.org/peps/
[6] http://sourceforge.net/tracker/?group_id=5470&atid=305470
[7] PEP 9, Sample PEP Template
http://www.python.org/peps/pep-0009.html
Copyright
This document has been placed in the public domain.
Local Variables:
mode: indented-text
indent-tabs-mode: nil
sentence-end-double-space: t
fill-column: 70
End:
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:
http://code.google.com/p/googleappengine/issues/detail?id=671
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
threads?
--
--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:
PEP: 3145
Title: Asynchronous I/O For subprocess.Popen
Author: (James) Eric Pruitt, Charles R. McCreary, Josiah Carlson
Type: Standards Track
Content-Type: text/plain
Created: 04-Aug-2009
Python-Version: 3.2
Abstract:
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.
Motivation:
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 [1] [2] [3]. 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 [4] [5]. 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
process.
Rationale:
There is a documented need for asynchronous, non-blocking functionality in
subprocess.Popen [6] [7] [2] [3]. 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
file object.
Reference Implementation:
I have been maintaining a Google Code repository that contains all of my
changes including tests and documentation [9] as well as blog detailing
the problems I have come across in the development process [10].
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
platforms.
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
interval.
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.
References:
[1] [ python-Feature Requests-1191964 ] asynchronous Subprocess
http://mail.python.org/pipermail/python-bugs-list/2006-December/
036524.html
[2] Daily Life in an Ivory Basement : /feb-07/problems-with-subprocess
http://ivory.idyll.org/blog/feb-07/problems-with-subprocess
[3] How can I run an external command asynchronously from Python? - Stack
Overflow
http://stackoverflow.com/questions/636561/how-can-i-run-an-external-
command-asynchronously-from-python
[4] 18.1. subprocess - Subprocess management - Python v2.6.2 documentation
http://docs.python.org/library/subprocess.html#subprocess.Popen.wait
[5] 18.1. subprocess - Subprocess management - Python v2.6.2 documentation
http://docs.python.org/library/subprocess.html#subprocess.Popen.kill
[6] Issue 1191964: asynchronous Subprocess - Python tracker
http://bugs.python.org/issue1191964
[7] Module to allow Asynchronous subprocess use on Windows and Posix
platforms - ActiveState Code
http://code.activestate.com/recipes/440554/
[8] subprocess.rst - subprocdev - Project Hosting on Google Code
http://code.google.com/p/subprocdev/source/browse/doc/subprocess.rst?spec=s…
[9] subprocdev - Project Hosting on Google Code
http://code.google.com/p/subprocdev
[10] Python Subprocess Dev
http://subdev.blogspot.com/
Copyright:
This P.E.P. is licensed under the Open Publication License;
http://www.opencontent.org/openpub/.
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.
>
>
> --
> Regards,
> Benjamin
>
Which I noticed since it's cited in the BeOpen license we still refer
to in LICENSE. Since pythonlabs.com itself is still up, it probably
isn't much work to make the logos.html URI work again, but I don't know
who maintains that page.
cheer,
Georg
--
Thus spake the Lord: Thou shalt indent with four spaces. No more, no less.
Four shall be the number of spaces thou shalt indent, and the number of thy
indenting shall be four. Eight shalt thou not indent, nor either indent thou
two, excepting that thou then proceed to four. Tabs are right out.
Hello everyone.
I see several problems with the two hex-conversion function pairs that
Python offers:
1. binascii.hexlify and binascii.unhexlify
2. bytes.fromhex and bytes.hex
Problem #1:
bytes.hex is not implemented, although it was specified in PEP 358.
This means there is no symmetrical function to accompany bytes.fromhex.
Problem #2:
Both pairs perform the same function, although The Zen Of Python suggests
that
"There should be one-- and preferably only one --obvious way to do it."
I do not understand why PEP 358 specified the bytes function pair although
it mentioned the binascii pair...
Problem #3:
bytes.fromhex may receive spaces in the input string, although
binascii.unhexlify may not.
I see no good reason for these two functions to have different features.
Problem #4:
binascii.unhexlify may receive both input types: strings or bytes, whereas
bytes.fromhex raises an exception when given a bytes parameter.
Again there is no reason for these functions to be different.
Problem #5:
binascii.hexlify returns a bytes type - although ideally, converting to hex
should
always return string types and converting from hex should always return
bytes.
IMO there is no meaning of bytes as an output of hexlify, since the output
is a
representation of other bytes.
This is also the suggested behavior of bytes.hex in PEP 358
Problems #4 and #5 call for a decision about the input and output of the
functions being discussed:
Option A : Strict input and output
unhexlify (and bytes.fromhex) may only receives string and may only return
bytes
hexlify (and bytes.hex) may only receives bytes and may only return strings
Option B : Robust input and strict output
unhexlify (and bytes.fromhex) may receive bytes and strings and may only
return bytes
hexlify (and bytes.hex) may receive bytes or strings and may only return
strings
Of course we may also consider a third option, which will allow the return
type of
all functions to be robust (perhaps specified in a keyword argument), but as
I wrote in
the description of problem #5, I see no sense in that.
Note that PEP 3137 describes: "... the more strict definitions of encoding
and decoding in
Python 3000: encoding always takes a Unicode string and returns a bytes
sequence, and decoding
always takes a bytes sequence and returns a Unicode string." - suggesting
option A.
To repeat problems #4 and #5, the current behavior does not match any
option:
* The return type of binascii.hexlify should be string, and this is not the
current behavior.
As for the input:
* Option A is not the current behavior because binascii.unhexlify may
receive both input types.
* Option B is not the current behavior because bytes.fromhex does not allow
bytes as input.
To fix these issues, three changes should be applied:
1. Deprecate bytes.fromhex. This fixes the following problems:
#4 (go with option B and remove the function that does not allow bytes
input)
#2 (the binascii functions will be the only way to "do it")
#1 (bytes.hex should not be implemented)
2. In order to keep the functionality that bytes.fromhex has over unhexlify,
the latter function should be able to handle spaces in its input (fix #3)
3. binascii.hexlify should return string as its return type (fix #5)
Hello,
This is a follow-up of the Pycon summit + sprints on packaging.
This is what we have planned to do:
1. refactor distutils in a new standalone version called distutils2
[this is done already and we are actively working in the code]
2. completely revert distutils in Lib/ and Doc/ so the code + doc is
the same than the current 2.6.x branch
3. leave the new sysconfig module, that is used by the Makefile and
the site module
The rest of the work will happen in distutils2 and we will try to
release a version asap for Python 2.x and 3.x (2.4 to 3.2), and the
goal
is to put it back in the stdlib in Python 3.3
Distutils in Python will be feature-frozen and I will only do bug
fixes there. All feature requests will be redirected to Distutils2.
I think the easiest way to manage this for me and for the feedback of
the community is to add in bugs.python.org a "Distutils2" component,
so I can
start to reorganize the issues in there and reassign new issues to
Distutils2 when it applies.
Regards
Tarek
--
Tarek Ziadé | http://ziade.org
On Feb 03, 2010, at 12:42 PM, Brett Cannon wrote:
>So what happens when only bytecode is present?
We discussed this at Pycon and agreed that we will not support source-less
deployments by default. The source file must exist or it will be an
ImportError.
This does not mean source-less deployments are not possible though. To
support this use case, you'd have to write a custom import hook. We may write
one as part of the PEP 3147 implementation. Contributions are of course
welcome!
-Barry
Hi All,
Recently some discussion began in the issue 3132 thread (
http://bugs.python.org/issue3132) regarding
implementation of the new struct string syntax for PEP 3118. Mark Dickinson
suggested that I bring the discussion on over to Python Dev. Below is a
summary
of the questions\comments from the thread.
Unpacking a long-double
===================
1. Should this return a Decimal object or a ctypes 'long double'?
2. Using ctypes 'long double' is easier to implement, but precision is
lost when needing to do arithmetic, since the value for cytpes 'long
double'
is converted to a Python float.
3. Using Decimal keeps the desired precision, but the implementation would
be non-trivial and architecture specific (unless we just picked a
fixed number of bytes regardless of the architecture).
4. What representation should be used for standard size and alignment?
IEEE 754 extended double precision?
Pointers
======
1. What is a specific pointer? For example, is '&d' is a pointer to a
double?
2. How would unpacking a pointer to a Python Object work out? Given an
address how would the appropriate object to be unpacked be determined?
3. Can pointers be nested, e.g. '&&d' ?
4. For the 'X{}' format (pointer to a function), is this supposed to mean a
Python function or a C function?
String Syntax
==========
The syntax seems to have transcended verbal description. I think we
need to put forth a grammar. There are also some questions regarding
nesting
levels and mixing specifiers that could perhaps be answered more clearly by
having a grammar:
1. What nesting level can structures have? Arbitrary?
2. The new array syntax claims "multi-dimensional array of whatever
follows".
Truly whatever? Arrays of structures? Arrays of pointers?
3. How do array specifiers and pointer specifiers mix? For example,
would '(2, 2)&d' be a two-by-two array of pointers to doubles?
What about '&(2, 2)d'? Is this a pointer to an two-by-two array of
doubles?
An example grammar is contained in a diff against the PEP attached to this
mail. NOTE: I am *not* actually submitting a patch against the PEP. This
was just the clearest way to present the example grammar.
Use Cases
========
1. What are the real world use cases for these struct string extensions?
These should be fleshed out and documented.
-- Meador
Hello,
On November 2006 and September 2007 Fredrik proposed to update "xml.etree" in
Python 2.6 with the upcoming version 1.3.
Now we are three years later, and the version shipped with 2.7alpha3 is 1.2.6.
http://bugs.python.org/issue1602189#msg54944http://bugs.python.org/issue1143
This would not be an issue, without the numerous bug reports accumulating on
bugs.python.org. Most of these reports are waiting for the 1.3 release.
Three months ago I worked on some of these issues, and after fixing them
separately, I proposed a patch which merges the latest 1.3 snapshot (released in
2007) within the standard library. The aim is to provide a bug-free version of
ElementTree/cElementTree in the standard library.
For this purpose, I grew the test suite from 300 lines to 1800 lines, using both
the tests from upstream and the tests proposed by Neil Muller on issue #6232. To
ensure consistency, now the test_suite for the C implementation is the same as
the Python implementation.
http://bugs.python.org/issue6472
We are still interested with the upcoming release of ElementTree, but we should
adopt a pragmatic approach: the xml.etree.ElementTree needs to be fixed for all
Python users, even if 1.3 is not ready before 2.7beta. This is the only purpose
of the patch.
The patch sticks as much as possible to the upstream library. Initially I kept
all the new features of the 1.3 branch in the patch.
It should ease the integration of 1.3 final when it is released.
With the last comment from Fredrik, I think to be more conservative: I plan to
split out the experimental C API from the package. It is not required for the
bug-fix release, and there's some risk of incompatibility with the final design
of the API, which is still secret.
As a side-effect, the patch will add some features and methods from the 1.3
branch (some of them where requested in the bug tracker):
- ET.fromstringlist(), ET.tostringlist()
- Element.extend(), Element.iter(), Element.itertext()
- new selector engine
- extended slicing
However the highlighted features of this patch are:
- to fix many bugs which were postponed because of 1.3 release
- to ensure consistency between C and Python implementations (with tests)
- to provide a better test coverage
The patch is uploaded on Rietveld for review.
The 3.x version of the patch will be updated after 2.x is merged in trunk.
The patch covers documentation, too.
http://codereview.appspot.com/207048/show
It's time to comment and review.
The proposed plan is to merge the patch in trunk before 2.7 alpha4.
Best regards,
--
Florent Xicluna
Hi,
pysandbox is a new Python sandbox project under development. By default,
untrusted code executed in the sandbox cannot modify the environment (write a
file, use print or import a module). But you can configure the sandbox to
choose exactly which features are allowed or not, eg. import sys module and
read the file /etc/issue.
Website: http://github.com/haypo/pysandbox/
Download the repository using git:
git clone git://github.com/haypo/pysandbox.git
or
git clone http://github.com/haypo/pysandbox.git
Or download the .zip or .tar.gz tarball using the "Download source" button on
the website.
I think that the project reached the "testable" stage. I launch a new
challenge: try to escape from the sandbox. I'm unable to write strict rules.
The goal is to access objects outside the sandbox. Eg. write into a file,
import a module which is not in the whitelist, modify an object outside the
sandbox, etc.
To test the sandbox, you have 3 choices:
- interpreter.py: interactive interpreter executed in the sandbox, use:
--verbose to display the whole sandbox configuration,
--features=help to enable help() function,
--features=regex to enable regex,
--help to display the help.
- execfile.py <your_script.py>: execute your script in the sandbox.
It has also --features option: use --features=stdout to be able
to use the print instruction :-)
- use directly the Sandbox class: use methods call(), execute()
or createCallback()
Don't use "with sandbox: ..." because there is known but with local frame
variables. I think that I will later drop this syntax because of this bug.
Except of debug_sandbox, I consider that all features are safe and so you can
enable all features :-)
There is no prize, it's just for fun! But I will add the name of hackers
founding the best exploits.
pysandbox is not ready for production, it's under heavy development. Anyway I
*hope* that you will quickly find bugs!
--
Use tests.py to found some examples of how you can escape a sandbox. pysandbox
is protected against all methods described in tests.py ;-)
See the README file to get more information about how pysandbox is implemented
and get a list of other Python sandboxes.
pysandbox is currently specific to CPython, and it uses some ugly hacks to
patch CPython in memory. In the worst case it will crash the pysandbox Python
process, that's all. I tested it under Linux with Python 2.5 and 2.6. The
portage to Python3 is not done yet (is someone motivated to write a
patch? :-)).
--
Victor Stinner
http://www.haypocalc.com/
