Mailman 3 July 2006 - Python-Dev

PEP 1, PEP Purpose and Guidelines
by barry＠zope.com May 18, 2021

May 18, 2021

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:

8 14

pthreads, fork, import, and execvp
by Rotem Yaari Sept. 16, 2009

Sept. 16, 2009

Hello everyone! We have been encountering several deadlocks in a threaded Python application which calls subprocess.Popen (i.e. fork()) in some of its threads. This has occurred on Python 2.4.1 on a 2.4.27 Linux kernel. Preliminary analysis of the hang shows that the child process blocks upon entering the execvp function, in which the import_lock is acquired due to the following line: def _ execvpe(file, args, env=None): from errno import ENOENT, ENOTDIR ... It is known that when forking from a pthreaded application, acquisition attempts on locks which were already locked by other threads while fork() was called will deadlock. Due to these oddities we were wondering if it would be better to extract the above import line from the execvpe call, to prevent lock acquisition attempts in such cases. Another workaround could be re-assigning a new lock to import_lock (such a thing is done with the global interpreter lock) at PyOS_AfterFork or pthread_atfork. We'd appreciate any opinions you might have on the subject. Thanks in advance, Yair and Rotem

12 29

Re: subprocess and EINTR errnos
by Peter Astrand July 6, 2009

July 6, 2009

On Wed, 10 Nov 2004, John P Speno wrote: Hi, sorry for the delayed response. > While using subprocess (aka popen5), I came across one potential gotcha. I've had > exceptions ending like this: > > File "test.py", line 5, in test > cmd = popen5.Popen(args, stdout=PIPE) > File "popen5.py", line 577, in __init__ > data = os.read(errpipe_read, 1048576) # Exceptions limited to 1 MB > OSError: [Errno 4] Interrupted system call > > (on Solaris 9) > > Would it make sense for subprocess to use a more robust read() function > which can handle these cases, i.e. when the parent's read on the pipe > to the child's stderr is interrupted by a system call, and returns EINTR? > I imagine it could catch EINTR and EAGAIN and retry the failed read(). I assume you are using signals in your application? The os.read above is not the only system call that can fail with EINTR. subprocess.py is full of other system calls that can fail, and I suspect that many other Python modules are as well. I've made a patch (attached) to subprocess.py (and test_subprocess.py) that should guard against EINTR, but I haven't committed it yet. It's quite large. Are Python modules supposed to handle EINTR? Why not let the C code handle this? Or, perhaps the signal module should provide a sigaction function, so that users can use SA_RESTART. Index: subprocess.py =================================================================== RCS file: /cvsroot/python/python/dist/src/Lib/subprocess.py,v retrieving revision 1.8 diff -u -r1.8 subprocess.py --- subprocess.py 7 Nov 2004 14:30:34 -0000 1.8 +++ subprocess.py 17 Nov 2004 19:42:30 -0000 @@ -888,6 +888,50 @@ pass + def _read_no_intr(self, fd, buffersize): + """Like os.read, but retries on EINTR""" + while True: + try: + return os.read(fd, buffersize) + except OSError, e: + if e.errno == errno.EINTR: + continue + else: + raise + + + def _read_all(self, fd, buffersize): + """Like os.read, but retries on EINTR, and reads until EOF""" + all = "" + while True: + data = self._read_no_intr(fd, buffersize) + all += data + if data == "": + return all + + + def _write_no_intr(self, fd, s): + """Like os.write, but retries on EINTR""" + while True: + try: + return os.write(fd, s) + except OSError, e: + if e.errno == errno.EINTR: + continue + else: + raise + + def _waitpid_no_intr(self, pid, options): + """Like os.waitpid, but retries on EINTR""" + while True: + try: + return os.waitpid(pid, options) + except OSError, e: + if e.errno == errno.EINTR: + continue + else: + raise + def _execute_child(self, args, executable, preexec_fn, close_fds, cwd, env, universal_newlines, startupinfo, creationflags, shell, @@ -963,7 +1007,7 @@ exc_value, tb) exc_value.child_traceback = ''.join(exc_lines) - os.write(errpipe_write, pickle.dumps(exc_value)) + self._write_no_intr(errpipe_write, pickle.dumps(exc_value)) # This exitcode won't be reported to applications, so it # really doesn't matter what we return. @@ -979,7 +1023,7 @@ os.close(errwrite) # Wait for exec to fail or succeed; possibly raising exception - data = os.read(errpipe_read, 1048576) # Exceptions limited to 1 MB + data = self._read_all(errpipe_read, 1048576) # Exceptions limited to 1 MB os.close(errpipe_read) if data != "": child_exception = pickle.loads(data) @@ -1003,7 +1047,7 @@ attribute.""" if self.returncode == None: try: - pid, sts = os.waitpid(self.pid, os.WNOHANG) + pid, sts = self._waitpid_no_intr(self.pid, os.WNOHANG) if pid == self.pid: self._handle_exitstatus(sts) except os.error: @@ -1015,7 +1059,7 @@ """Wait for child process to terminate. Returns returncode attribute.""" if self.returncode == None: - pid, sts = os.waitpid(self.pid, 0) + pid, sts = self._waitpid_no_intr(self.pid, 0) self._handle_exitstatus(sts) return self.returncode @@ -1049,27 +1093,33 @@ stderr = [] while read_set or write_set: - rlist, wlist, xlist = select.select(read_set, write_set, []) + try: + rlist, wlist, xlist = select.select(read_set, write_set, []) + except select.error, e: + if e[0] == errno.EINTR: + continue + else: + raise if self.stdin in wlist: # When select has indicated that the file is writable, # we can write up to PIPE_BUF bytes without risk # blocking. POSIX defines PIPE_BUF >= 512 - bytes_written = os.write(self.stdin.fileno(), input[:512]) + bytes_written = self._write_no_intr(self.stdin.fileno(), input[:512]) input = input[bytes_written:] if not input: self.stdin.close() write_set.remove(self.stdin) if self.stdout in rlist: - data = os.read(self.stdout.fileno(), 1024) + data = self._read_no_intr(self.stdout.fileno(), 1024) if data == "": self.stdout.close() read_set.remove(self.stdout) stdout.append(data) if self.stderr in rlist: - data = os.read(self.stderr.fileno(), 1024) + data = self._read_no_intr(self.stderr.fileno(), 1024) if data == "": self.stderr.close() read_set.remove(self.stderr) Index: test/test_subprocess.py =================================================================== RCS file: /cvsroot/python/python/dist/src/Lib/test/test_subprocess.py,v retrieving revision 1.14 diff -u -r1.14 test_subprocess.py --- test/test_subprocess.py 12 Nov 2004 15:51:48 -0000 1.14 +++ test/test_subprocess.py 17 Nov 2004 19:42:30 -0000 @@ -7,6 +7,7 @@ import tempfile import time import re +import errno mswindows = (sys.platform == "win32") @@ -35,6 +36,16 @@ fname = tempfile.mktemp() return os.open(fname, os.O_RDWR|os.O_CREAT), fname + def read_no_intr(self, obj): + while True: + try: + return obj.read() + except IOError, e: + if e.errno == errno.EINTR: + continue + else: + raise + # # Generic tests # @@ -123,7 +134,7 @@ p = subprocess.Popen([sys.executable, "-c", 'import sys; sys.stdout.write("orange")'], stdout=subprocess.PIPE) - self.assertEqual(p.stdout.read(), "orange") + self.assertEqual(self.read_no_intr(p.stdout), "orange") def test_stdout_filedes(self): # stdout is set to open file descriptor @@ -151,7 +162,7 @@ p = subprocess.Popen([sys.executable, "-c", 'import sys; sys.stderr.write("strawberry")'], stderr=subprocess.PIPE) - self.assertEqual(remove_stderr_debug_decorations(p.stderr.read()), + self.assertEqual(remove_stderr_debug_decorations(self.read_no_intr(p.stderr)), "strawberry") def test_stderr_filedes(self): @@ -186,7 +197,7 @@ 'sys.stderr.write("orange")'], stdout=subprocess.PIPE, stderr=subprocess.STDOUT) - output = p.stdout.read() + output = self.read_no_intr(p.stdout) stripped = remove_stderr_debug_decorations(output) self.assertEqual(stripped, "appleorange") @@ -220,7 +231,7 @@ stdout=subprocess.PIPE, cwd=tmpdir) normcase = os.path.normcase - self.assertEqual(normcase(p.stdout.read()), normcase(tmpdir)) + self.assertEqual(normcase(self.read_no_intr(p.stdout)), normcase(tmpdir)) def test_env(self): newenv = os.environ.copy() @@ -230,7 +241,7 @@ 'sys.stdout.write(os.getenv("FRUIT"))'], stdout=subprocess.PIPE, env=newenv) - self.assertEqual(p.stdout.read(), "orange") + self.assertEqual(self.read_no_intr(p.stdout), "orange") def test_communicate(self): p = subprocess.Popen([sys.executable, "-c", @@ -305,7 +316,8 @@ 'sys.stdout.write("\\nline6");'], stdout=subprocess.PIPE, universal_newlines=1) - stdout = p.stdout.read() + + stdout = self.read_no_intr(p.stdout) if hasattr(open, 'newlines'): # Interpreter with universal newline support self.assertEqual(stdout, @@ -343,7 +355,7 @@ def test_no_leaking(self): # Make sure we leak no resources - max_handles = 1026 # too much for most UNIX systems + max_handles = 10 # too much for most UNIX systems if mswindows: max_handles = 65 # a full test is too slow on Windows for i in range(max_handles): @@ -424,7 +436,7 @@ 'sys.stdout.write(os.getenv("FRUIT"))'], stdout=subprocess.PIPE, preexec_fn=lambda: os.putenv("FRUIT", "apple")) - self.assertEqual(p.stdout.read(), "apple") + self.assertEqual(self.read_no_intr(p.stdout), "apple") def test_args_string(self): # args is a string @@ -457,7 +469,7 @@ p = subprocess.Popen(["echo $FRUIT"], shell=1, stdout=subprocess.PIPE, env=newenv) - self.assertEqual(p.stdout.read().strip(), "apple") + self.assertEqual(self.read_no_intr(p.stdout).strip(), "apple") def test_shell_string(self): # Run command through the shell (string) @@ -466,7 +478,7 @@ p = subprocess.Popen("echo $FRUIT", shell=1, stdout=subprocess.PIPE, env=newenv) - self.assertEqual(p.stdout.read().strip(), "apple") + self.assertEqual(self.read_no_intr(p.stdout).strip(), "apple") def test_call_string(self): # call() function with string argument on UNIX @@ -525,7 +537,7 @@ p = subprocess.Popen(["set"], shell=1, stdout=subprocess.PIPE, env=newenv) - self.assertNotEqual(p.stdout.read().find("physalis"), -1) + self.assertNotEqual(self.read_no_intr(p.stdout).find("physalis"), -1) def test_shell_string(self): # Run command through the shell (string) @@ -534,7 +546,7 @@ p = subprocess.Popen("set", shell=1, stdout=subprocess.PIPE, env=newenv) - self.assertNotEqual(p.stdout.read().find("physalis"), -1) + self.assertNotEqual(self.read_no_intr(p.stdout).find("physalis"), -1) def test_call_string(self): # call() function with string argument on Windows /Peter Åstrand <astrand(a)lysator.liu.se>

5 5

Re: [Python-Dev] [Python-checkins] r45510 - python/trunk/Lib/pkgutil.py python/trunk/Lib/pydoc.py
by M.-A. Lemburg March 21, 2008

March 21, 2008

Phillip.eby wrote: > Author: phillip.eby > Date: Tue Apr 18 02:59:55 2006 > New Revision: 45510 > > Modified: > python/trunk/Lib/pkgutil.py > python/trunk/Lib/pydoc.py > Log: > Second phase of refactoring for runpy, pkgutil, pydoc, and setuptools > to share common PEP 302 support code, as described here: > > http://mail.python.org/pipermail/python-dev/2006-April/063724.html Shouldn't this new module be named "pkglib" to be in line with the naming scheme used for all the other utility modules, e.g. httplib, imaplib, poplib, etc. ? > pydoc now supports PEP 302 importers, by way of utility functions in > pkgutil, such as 'walk_packages()'. It will properly document > modules that are in zip files, and is backward compatible to Python > 2.3 (setuptools installs for Python <2.5 will bundle it so pydoc > doesn't break when used with eggs.) Are you saying that the installation of setuptools in Python 2.3 and 2.4 will then overwrite the standard pydoc included with those versions ? I think that's the wrong way to go if not made an explicit option in the installation process or a separate installation altogether. I bothered by the fact that installing setuptools actually changes the standard Python installation by either overriding stdlib modules or monkey-patching them at setuptools import time. > What has not changed is that pydoc command line options do not support > zip paths or other importer paths, and the webserver index does not > support sys.meta_path. Those are probably okay as limitations. > > Tasks remaining: write docs and Misc/NEWS for pkgutil/pydoc changes, > and update setuptools to use pkgutil wherever possible, then add it > to the stdlib. Add setuptools to the stdlib ? I'm still missing the PEP for this along with the needed discussion touching among other things, the change of the distutils standard "python setup.py install" to install an egg instead of a site package. -- Marc-Andre Lemburg eGenix.com Professional Python Services directly from the Source (#1, Apr 18 2006) >>> Python/Zope Consulting and Support ... http://www.egenix.com/ >>> mxODBC.Zope.Database.Adapter ... http://zope.egenix.com/ >>> mxODBC, mxDateTime, mxTextTools ... http://python.egenix.com/ ________________________________________________________________________ ::: Try mxODBC.Zope.DA for Windows,Linux,Solaris,FreeBSD for free ! ::::

14 51

Making builtins more efficient
by Steven Elliott April 14, 2007

April 14, 2007

I'm interested in how builtins could be more efficient. I've read over some of the PEPs having to do with making global variables more efficient (search for "global"): http://www.python.org/doc/essays/pepparade.html But I think the problem can be simplified by focusing strictly on builtins. One of my assumptions is that only a small fractions of modules override the default builtins with something like: import mybuiltins __builtins__ = mybuiltins As you probably know each access of a builtin requires two hash table lookups. First, the builtin is not found in the list of globals. It is then found in the list of builtins. Why not have a means of referencing the default builtins with some sort of index the way the LOAD_FAST op code currently works? In other words, by default each module gets the default set of builtins indexed (where the index indexes into an array) in a certain order. The version stored in the pyc file would be bumped each time the set of default builtins is changed. I don't have very strong feelings whether things like True = (1 == 1) would be a syntax error, but assigning to a builtin could just do the equivalent of STORE_FAST. I also don't have very strong feelings about whether the array of default builtins would be shared between modules. To simulate the current behavior where attempting to assign to builtin actually alters that module's global hashtable a separate array of builtins could be used for each module. As to assigning to __builtins__ (like I mentioned at the beginning of this post) perhaps it could assign to the builtin array for those items that have a name that matches a default builtin (such as "True" or "len"). Those items that don't match a default builtin would just create global variables. Perhaps what I'm suggesting isn't feasible for reasons that have already been discussed. But it seems like it should be possible to make "while True" as efficient as "while 1". -- ----------------------------------------------------------------------- | Steven Elliott | selliott4(a)austin.rr.com | -----------------------------------------------------------------------

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GeneratorExit inheriting from Exception
by Nick Coghlan Feb. 28, 2007

Feb. 28, 2007

Should GeneratorExit inherit from Exception or BaseException? Currently, a generator that catches Exception and continues on to yield another value can't be closed properly (you get a runtime error pointing out that the generator ignored GeneratorExit). The only decent reference I could find to it in the old PEP 348/352 discussions is Guido writing [1]: > when GeneratorExit or StopIteration > reach the outer level of an app, it's a bug like all the others that > bare 'except:' WANTS to catch. (at that point in the conversation, I believe bare except was considered the equivalent of "except Exception:") While I agree with what Guido says about GeneratorExit being a bug if it reaches the outer level of an app, it seems like a bit of a trap that a correctly written generator can't write "except Exception:" without preceding it with an "except GeneratorExit:" that reraises the exception. Isn't that exactly the idiom we're trying to get rid of for SystemExit and KeyboardInterrupt? Regards, Nick. [1] http://mail.python.org/pipermail/python-dev/2005-August/055173.html -- Nick Coghlan | ncoghlan(a)gmail.com | Brisbane, Australia --------------------------------------------------------------- http://www.boredomandlaziness.org

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Plea to distribute debugging lib
by David Abrahams Oct. 14, 2006

Oct. 14, 2006

For years, Boost.Python has been doing some hacks to work around the fact that a Windows Python distro doesn't include the debug build of the library. http://www.boost.org/libs/python/doc/building.html#variants explains. We wanted to make it reasonably convenient for Windows developers (and our distributed testers) to work with a debug build of the Boost.Python library and of their own code. Having to download the Python source and build the debug DLL was deemed unacceptable. Well, those hacks have run out of road. VC++8 now detects that some of its headers have been #included with _DEBUG and some without, and it will refuse to build anything when it does. We have several new hacks to work around that detection, and I think we _might_ be able to get away with them for one more release. But it's really time to do it right. MS is recommending that we (Boost) start distributing a debug build of the Python DLL with Boost, but Boost really seems like the wrong place to host such a thing. Is there any way Python.org can make a debug build more accessible? Thanks, Dave -- Dave Abrahams Boost Consulting www.boost-consulting.com

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Community buildbots (was Re: User's complaints)
by glyph＠divmod.com Sept. 10, 2006

Sept. 10, 2006

On Wed, 12 Jul 2006 10:30:17 +1000, Michael Ellerman <michael(a)ellerman.id.au> wrote: >Well here's one I stumbled across the other day. I don't know if it's >legit, but it's still bad PR: > >http://www.gbch.net/gjb/blog/software/discuss/python-sucks.html Having been exhorted (or maybe I mean "excoriated") by your friendly release manager earlier this week to post my comments and criticisms about Python here rather than vent in random IRC chatter, I feel morally compelled to comment. I see some responses to that post which indicate that the specific bug will be fixed, and that's good, but there is definitely a pattern he's talking about here, not just one issue. I think there is a general pattern of small, difficult to detect breakages in Python. Twisted (and the various other Divmod projects that I maintain) are thoroughly unit-tested, but there are still significant issues in each Python release that require changes. Unlike the jerk who posted that "python sucks" rant, I'm not leaving Python because one function changed in a major release; I do expect to have to maintain my projects myself, and major releases are "major" for a reason. I only wish that upgrading all my other dependencies were as easy as upgrading Python! I do see that the developers are working with some caution to avoid breaking code, and attempting to consider the cost of each change. However, although I've seen lots of discussions of what "average" code might break when exposed to new versions of Python, these discussions tend to be entirely hypothetical. Do the core Python developers typically run the test suites of major Python applications when considering major changes, such as Zope, Plone, TurboGears, and of course Twisted? Not that breakages would be considered unacceptable -- some gain is surely worth the cost -- but to establish some empirical level of burden on the community? I would like to propose, although I certainly don't have time to implement, a program by which Python-using projects could contribute buildslaves which would run their projects' tests with the latest Python trunk. This would provide two useful incentives: Python code would gain a reputation as generally well-tested (since there is a direct incentive to write tests for your project: get notified when core python changes might break it), and the core developers would have instant feedback when a "small" change breaks more code than it was expected to. I can see that certain Python developers expect that some of this work is the responsibility of the user community, and to some extent that's true, but at least half of the work needs to be done _before_ the changes are made. If some Python change breaks half of Twisted, I would like to know about it in time to complain about the implementation, rather than flailing around once the Python feature-freeze has set in and hoping that it's nothing too serious. For example, did anyone here know that the new-style exceptions stuff in 2.5 caused hundreds of unit-test failures in Twisted? I am glad the change was made, and one of our users did catch it, so the process isn't fatally broken, but it is still worrying. Another problem is simply that the Python developers don't have the same very public voice that other language developers do. It doesn't necessarily have to be a blog, but python-dev is fast-paced and intimidating, and a vehicle for discussion among those in the know, rather than dissimenation to the community at large. It's a constant source of anxiety to me that I might miss some key feature addition to Python which breaks or distorts some key bit of Twisted functionality (as the new-style exceptions, or recent ImportWarning almost did) because I don't have enough time to follow all the threads here. I really appreciate the work that Steve Bethard et. al. are doing on the python-dev summaries, but they're still pretty dry and low level. While the new python.org is very nice, I do note that there's no "blogs" entry on the front page, something which has become a fixture on almost every other website I visit regularly. The news page is not very personal, mainly a listing of releases and events. There's no forum for getting the community _excited_ about new features (especially new features which are explicitly enabled by potential breakages), and selling them on the cool uses. Who knows, maybe I'll even start using decorators syntax all over the place if I see them presented somewhere by someone who is very excited about the feature and thinks it's worthwhile, rather than as a defense on a mailing list against a criticism, or a simple announcement of the feature's existence. I've seen the other side of this problem as well, so I can appreciate that it is quite difficult to get this kind of thing right: lots of applications using Twisted break when we change broken or deprecated APIs. Twisted is lucky though; it has numerous subprojects, and I maintain a half-dozen unrelated projects in a different repository. Twisted itself is a fairly representative "application using Twisted", so when something breaks "average" Twisted code, I know about it right away. Python is less an application using Python: the standard library is rather passive (there is no "end-to-end" application path to test, only individual functions and classes), and the test coverage of included Python modules is rather spotty. I hope someone finds some of these suggestions helpful. I only wish I had the time and energy to act on some of them.

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new security doc using object-capabilities
by Brett Cannon Sept. 7, 2006

Sept. 7, 2006

After various people suggesting object-capabilities, takling with Mark S. Miller of the E programming language, and the people Mark works with at HP Labs (who have been giving talks every week during this month here at Google on object-capabilities), I have decided to go with object-capabilities for securing interpreters. I have rewritten my design doc from scratch and deleted the old one. The new doc is named securing_python.txt and can be found through the svn web interface at http://svn.python.org/view/python/branches/bcannon-sandboxing/securing_pyth…. I have pretty much ignored any concrete API and such and gone more with a conceptual doc to make sure the API does not get in the way of the core security model. Using object-capabilities should make the implementation much cleaner. There is much less work directly on the interpreter and more of it gets pushed up to extension modules. I also have the okay of my supervisor to use this approach in my dissertation so this will get done. Two things do fall out of all of this which will make development much more modular and easier. First, the memory cap work just becomes a special build on its own; no need to tie into the security work. So I will be cleaning up the bcannon-sandboxing branch code as it stands, and then either create a separate branch for the object-capabilities work, or create another branch for the memory cap stuff and shift the changes over there. I will most likely do the former so as to not lose the history on the checkins. I also plan to rewrite the import machinery in pure Python. This will make the code much more maintainable and make creating proxies for the import machinery much easier. I will be doing that in a directory in the sandbox initially since it needs to work from what Python has now (and possibly some new extension module code) before it can be integrated into the interpreter directly. Anyone who wants to help with that can. I already have some perliminary notes on the whole thing and I think it will be reasonably doable. Anyway, there you go. Here is to hoping I have thought this all through properly. =) -Brett

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httplib and bad response chunking
by Greg Ward Aug. 9, 2006

Aug. 9, 2006

So I accidentally discovered the other day that httplib does not handle a particular type of mangled HTTP response very well. In particular, it tends to blow up with an undocumented ValueError when the server screws up "chunked" encoding. I'm not the first to discover this, either: see http://www.python.org/sf/1486335 . <digression> HTTP 1.1 response chunking allows clients to know how many bytes of response to expect for dynamic content, i.e. when it's not possible to include a "Content-length" header. A chunked response might look like this: 0005\r\nabcd\n\r\n0004\r\nabc\n\r\n0\r\n\r\n which means: 0x0005 bytes in first chunk, which is "abcd\n" 0x0004 bytes in second chunk, which is "abc\n" Each chunk size is terminated with "\r\n"; each chunk is terminated with "\r\n"; end of response is indicated by a chunk of 0 bytes, hence the "\r\n\r\n" at the end. Details in RFC 2616: http://www.w3.org/Protocols/rfc2616/rfc2616-sec3.html#sec3.6.1 </digression> Anyways, what I discovered in the wild the other day was a response like this: 0005\r\nabcd\n\r\n0004\r\nabc\n\r\n\r\n i.e. the chunk-size for the terminating empty chunk was missing. This cause httplib.py to blow up with ValueError because it tried to call int(line, 16) assuming that 'line' contained a hex number, when in fact it was the empty string. Oops. IMHO the minimal fix is to turn ValueError into HTTPException (or a subclass thereof); httplib should not raise ValueError just because some server sends a bad response. (The server in question was Apache 2.0.52 running PHP 4.3.9 sending a big hairy error page because the database was down.) Where I'm getting hung up is how far to test this stuff. I have discovered other hypothetical cases of bad chunking that cause httplib to go into an infinite loop or block forever on socket.readline(). Should we worry about those cases as well, despite not having seen them happen in the wild? More annoying, I can reproduce the "block forever" case using a real socket, but not using the StringIO-based FakeSocket class in test_httplib. Anyways, I've cobbled together a crude hack to test_httplib.py that exposes the problem: http://sourceforge.net/tracker/download.php?group_id=5470&atid=105470&file_… Feedback welcome. (Fixing the inadvertent ValueError is trivial, so I'm concentrating on getting the tests right first.) Oh yeah, my patch is relative to the 2.4 branch. Greg -- Greg Ward <gward(a)python.net> http://www.gerg.ca/ I don't believe there really IS a GAS SHORTAGE.. I think it's all just a BIG HOAX on the part of the plastic sign salesmen -- to sell more numbers!!

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