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:
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>
I've been thinking about this a lot, but haven't made much
progess. Here's a brain dump.
I've been thinking about integrating PEP 325 (Resource-Release Support
for Generators) into the for-loop code, so that you could replace
the_lock.acquire()
try:
BODY
finally:
the_lock.release()
with
for dummy in synchronized(the_lock):
BODY
or perhaps even (making "for VAR" optional in the for-loop syntax)
with
in synchronized(the_lock):
BODY
Then synchronized() could be written cleanly as follows:
def synchronized(lock):
lock.acquire()
try:
yield None
finally:
lock.release()
But then every for-loop would have to contain an extra try-finally
clause; the translation of
for VAR in EXPR:
BODY
would become
__it = iter(EXPR)
try:
while True:
try:
VAR = __it.next()
except StopIteration:
break
BODY
finally:
if hasattr(__it, "close"):
__it.close()
which I don't particularly like: most for-loops DON'T need this, since
they don't use a generator but some other form of iterator, or even if
they use a generator, not all generators have a try/finally loop. But
the bytecode compiler can't know that, so it will always have to
generate this code. It also changes the semantics of using a
generator in a for-loop slightly: if you break out of the for-loop
before the generator is exhausted you will still get the close() call.
It's also a bit funny to see this approach used with the only other
use case for try/finally we've looked at, which requires passing a
variable into the block: the "with_file" use case. We now can write
with_file as a nice and clean generator:
def with_file(filename):
f = open(filename)
try:
yield f
finally:
f.close()
but the use looks very odd because it is syntactically a for-loop but
there's only one iteration:
for f in with_file("/etc/passwd"):
for line in f:
print line[:line.find(":")]
Seeing this example makes me cringe -- why two nested for loops to
loop over the lines of one file???
So I think that this is probably not the right thing to pursue, and we
might be better off with something along the lines of PEP 310. The
authors of PEP 310 agree; under Open Issues they wrote:
There are some simiralities in concept between 'with ...' blocks
and generators, which have led to proposals that for loops could
implement the with block functionality[3]. While neat on some
levels, we think that for loops should stick to being loops.
(Footnote [3] references the tread that originated PEP 325.)
Perhaps the most important lesson we've learned in this thread is that
the 'with' keyword proposed in PEP 310 is redundant -- the syntax
could just be
[VAR '=']* EXPR ':'
BODY
IOW the regular assignment / expression statement gets an optional
colon-plus-suite at the end.
So now let's assume we accept PEP 310 with this change. Does this
leave any use cases for anonymous blocks uncovered? Ruby's each()
pattern is covered by generators; personally I prefer Python's
for var in seq: ...
over Ruby's much-touted
seq.each() {|var| ...}
The try/finally use case is covered by PEP 310. (If you want to
combine this with a for-loop in a single operation, you'll need PEP
325.)
The use cases where the block actually returns a value are probably
callbacks for things like sort() or map(); I have to admit that I'd
rather keep lambda for these (and use named functions for longer
blocks) than introduce an anonymous block syntax that can return
values! I also note that if you *already* have a comparison function,
Ruby's Array sort method doesn't let you pass it in as a function
argument; you have to give it a block that calls the comparison
function, because blocks are not the same as callables (and I'm not
sure that Ruby even *has* callables -- everything seems to be a
block).
My tentative conclusion remains: Python doesn't need Ruby blocks.
Brian Sabbey ought to come up with more examples rather than arguments
why his preferred syntax and semantics are best.
--Guido van Rossum (home page: http://www.python.org/~guido/)
How about, instead of trying to emphasize how different a
block-statement is from a for-loop, we emphasize their similarity?
A regular old loop over a sequence or iterable is written as:
for VAR in EXPR:
BLOCK
A variation on this with somewhat different semantics swaps the keywords:
in EXPR for VAR:
BLOCK
If you don't need the variable, you can leave the "for VAR" part out:
in EXPR:
BLOCK
Too cute? :-)
--
--Guido van Rossum (home page: http://www.python.org/~guido/)
I don't know whether it's true for all the PEP 340 use cases, but the all the
current examples would read very naturally if the block-template could be
specified in an extended try statement:
> 1. A template for ensuring that a lock, acquired at the start of a
> block, is released when the block is left:
try with_lock(myLock):
# Code here executes with myLock held. The lock is
# guaranteed to be released when the block is left (even
# if by an uncaught exception).
> 2. A template for opening a file that ensures the file is closed
> when the block is left:
try opening("/etc/passwd") as f:
for line in f:
print line.rstrip()
>
> 3. A template for committing or rolling back a database
> transaction:
>
try transaction(mydb):
> 4. A template that tries something up to n times:
>
try auto_retry(3):
f = urllib.urlopen("http://python.org/peps/pep-0340.html")
print f.read()
> 5. It is possible to nest blocks and combine templates:
try with_lock(myLock):
try opening("/etc/passwd") as f:
for line in f:
print line.rstrip()
Michael
I haven't heard back from Greg Stein, Jim Fulton, or Paul Prescod.
If anyone can get in touch with them, that would be great.
I suspect that Jim may want to keep the commit privileges active
and that Paul and Greg are done with commits for the time being.
Raymond Hettinger
Brian Sabbey:
> It is possible to implement thunks without them creating their own
> frame. They can reuse the frame of the surrounding function ...
> The implementation just needs to take care
> to save and restore members of the frame that get clobbered when the
> thunk is running.
Michael Hudson:
> Woo. That's cute.
It *sounds* horrendous, but is actually pretty reasonable.
Conceptually, a thunk replaces a suite in the caller.
Most frame members are intended to be shared, and changes
should be visible -- so they don't have to (and shouldn't) be restored.
The only members that need special attention are (f_code, f_lasti)
and possibly (f_blockstack, f_iblock).
(f_code, f_lasti) would need to be replaced with a stack of pairs.
Finishing a code string would mean popping this stack, rather
than popping the whole frame.
Since a completed suite leaves the blockstack where it started,
(f_blockstack, f_iblock) *can* be ignored, though debugging and
CO_MAXBLOCKS both *suggest* replacing the pair with a stack of
pairs.
-jJ
Michael Spencer:
> I don't know whether it's true for all the PEP 340 use cases, but the all the
> current examples would read very naturally if the block-template could be
> specified in an extended try statement:
>> 1. A template for ensuring that a lock, acquired at the start of a
>> block, is released when the block is left:
> try with_lock(myLock):
> # Code here executes with myLock held. The lock is
> # guaranteed to be released when the block is left (even
> # if by an uncaught exception).
So we would have
try ... finally, try ... except, and try (no close).
It works for me, and should be backwards-compatible.
The cases where it doesn't work as well are
(1) You want to insert several different suites.
But the anonymous yield syntax doesn't work well for that either.
(That is one of the arguments for thunks instead of generator abuse.)
(2) You really do want to loop over the suite. Try doesn't imply a loop.
But this is a *good* thing. Resources are not loops, and you can always
make the loop explicit as iteration over the resource
def opener(file):
f=open(file)
try:
yield f
finally:
f.close()
try opener(file) as f:
for line in f:
process(line)
Nick Coghlan:
> Python offers two variants on the basic iterative loop.
> "for NAME in EXPR:" skips the finalisation step. At loop
> completion, a well-behaved iterator may still contain additional values.
> "for NAME from EXPR:" enforces finalisation of the iterator.
> ... At loop completion, a well-behaved [finalizing] iterator is
> always completely exhausted.
(nitpick):
"from" isn't really different from "in". Perhaps
for NAME inall EXPR:
for NAME draining EXPR:
for NAME finalizing EXPR: # too hard to spell, because of s/z?
(substance):
"finalized or not" is a very useful distinction, but I'm not sure it
is something the user should have to worry about. Realistically,
most of my loops intend to drain the iterator (which the compiler
knows because I have no "break:". Regardless of whether I
use a break, I still want the iterator cleaned up if it is drained.
The only thing this second loop form does is set a flag saying
"No, I won't continue -- and I happen to know that no one else
ever will either, even if they do have a reference that prevents
garbage collection. I'm *sure* they won't use it."
That strikes me as a dangerous thing to get in the habit of saying.
Why not just agressively run the finalization on both forms when the
reference count permits?
> This form supports block management operations,
And this seems unrelated to finalization. I understand that as an
implementation detail, you need to define the finalizers somehow.
But the decision to aggressively finalize (in some manner) and
desire to pass a block (that could be for finalization) seem like
orthogonal issues.
-jJ
Guido van Rossum:
> -- but it's more efficient, since calling yield doesn't create a frame.
Neither should a thunk.
> The other problem with thunks is that once we think of them as the
> anonymous functions they are, we're pretty much forced to say that a
> return statement in a thunk returns from the thunk rather than from
> the containing function.
Why should a thunk be a function? We already have first class
functions. What we're missing is a way to pass around a suite.
def foo(a):
if a > 4:
b = a
c = process(a) # thunk line 1
print a # thunk line 2
return # thunk line 3
else:
a.something()
We don't have a good way to package up "c = process(a); print a; return"
The return should exit the whole function, not just (part of) the if clause.
Greg:
>> I'd like to reconsider a thunk implementation. It
>> would be a lot simpler, doing just what is required
>> without any jiggery pokery with exceptions and
>> break/continue/return statements. It would be easy
>> to explain what it does and why it's useful.
> I don't know. In order to obtain the required local variable sharing
> between the thunk and the containing function I believe that every
> local variable used or set in the thunk would have to become a 'cell'
> (our mechanism for sharing variables between nested scopes).
Cells only work if you have a complete set of names at compile-time.
Your own resource-example added "item" to the namespace inside
a block. If you don't know which blocks could be used with a pattern,
cells are out.
That said, the compiler code is already two-pass. Once to find names,
and another time to resolve them. This just means that for thunks
(and functions that call them) the adjustment will be to LOAD_NAME
instead of getting a LOAD_FAST index.
-jJ
