python-peps/pep-0343.txt

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PEP: 343
Title: The "with" Statement
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Version: $Revision$
Last-Modified: $Date$
Author: Guido van Rossum, Nick Coghlan
Status: Accepted
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Type: Standards Track
Content-Type: text/plain
Created: 13-May-2005
Post-History: 2-Jun-2005, 16-Oct-2005, 29-Oct-2005, 23-Apr-2006, 1-May-2006
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Abstract
This PEP adds a new statement "with" to the Python language to make
it possible to factor out standard uses of try/finally statements.
In this PEP, context managers provide __enter__() and __exit__()
methods that are invoked on entry to and exit from the managed
context that forms the body of the with statement.
Author's Note
This PEP was originally written in first person by Guido, and
subsequently updated by Nick Coghlan to reflect later discussion
on python-dev. Any first person references are from Guido's
original.
Python's alpha release cycle revealed terminology problems in this
PEP and in the associated documentation and implementation [14].
So while the PEP is already accepted in principle, it won't really
be considered stable until the status becomes Final.
The current version of the PEP reflects the discussions that
occurred on python-dev shortly after the release of Python 2.5a2.
The PEP will continue to be updated to reflect any changes made to
the details of the feature prior to the final Python 2.5 release.
Yes, the verb tense is messed up in a few places. We've been
working on this PEP for nearly a year now, so things that were
originally in the future are now in the past :)
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Introduction
After a lot of discussion about PEP 340 and alternatives, I
decided to withdraw PEP 340 and proposed a slight variant on PEP
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310. After more discussion, I have added back a mechanism for
raising an exception in a suspended generator using a throw()
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method, and a close() method which throws a new GeneratorExit
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exception; these additions were first proposed on python-dev in
[2] and universally approved of. I'm also changing the keyword to
'with'.
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Following acceptance of this PEP, the following PEPs have been
rejected due to overlap:
- PEP 310, Reliable Acquisition/Release Pairs. This is the
original with-statement proposal.
- PEP 319, Python Synchronize/Asynchronize Block. Its use cases
can be covered by the current PEP by providing suitable
with-statement controllers: for 'synchronize' we can use the
"locking" template from example 1; for 'asynchronize' we can use
a similar "unlocking" template. I don't think having an
"anonymous" lock associated with a code block is all that
important; in fact it may be better to always be explicit about
the mutex being used.
PEP 340 and PEP 346 also overlapped with this PEP, but were
voluntarily withdrawn when this PEP was submitted.
Some discussion of earlier incarnations of this PEP took place on
the Python Wiki [3].
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Motivation and Summary
PEP 340, Anonymous Block Statements, combined many powerful ideas:
using generators as block templates, adding exception handling and
finalization to generators, and more. Besides praise it received
a lot of opposition from people who didn't like the fact that it
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was, under the covers, a (potential) looping construct. This
meant that break and continue in a block-statement would break or
continue the block-statement, even if it was used as a non-looping
resource management tool.
But the final blow came when I read Raymond Chen's rant about
flow-control macros[1]. Raymond argues convincingly that hiding
flow control in macros makes your code inscrutable, and I find
that his argument applies to Python as well as to C. I realized
that PEP 340 templates can hide all sorts of control flow; for
example, its example 4 (auto_retry()) catches exceptions and
repeats the block up to three times.
However, the with-statement of PEP 310 does *not* hide control
flow, in my view: while a finally-suite temporarily suspends the
control flow, in the end, the control flow resumes as if the
finally-suite wasn't there at all.
Remember, PEP 310 proposes roughly this syntax (the "VAR =" part is
optional):
with VAR = EXPR:
BLOCK
which roughly translates into this:
VAR = EXPR
VAR.__enter__()
try:
BLOCK
finally:
VAR.__exit__()
Now consider this example:
with f = open("/etc/passwd"):
BLOCK1
BLOCK2
Here, just as if the first line was "if True" instead, we know
that if BLOCK1 completes without an exception, BLOCK2 will be
reached; and if BLOCK1 raises an exception or executes a non-local
goto (a break, continue or return), BLOCK2 is *not* reached. The
magic added by the with-statement at the end doesn't affect this.
(You may ask, what if a bug in the __exit__() method causes an
exception? Then all is lost -- but this is no worse than with
other exceptions; the nature of exceptions is that they can happen
*anywhere*, and you just have to live with that. Even if you
write bug-free code, a KeyboardInterrupt exception can still cause
it to exit between any two virtual machine opcodes.)
This argument almost led me to endorse PEP 310, but I had one idea
left from the PEP 340 euphoria that I wasn't ready to drop: using
generators as "templates" for abstractions like acquiring and
releasing a lock or opening and closing a file is a powerful idea,
as can be seen by looking at the examples in that PEP.
Inspired by a counter-proposal to PEP 340 by Phillip Eby I tried
to create a decorator that would turn a suitable generator into an
object with the necessary __enter__() and __exit__() methods.
Here I ran into a snag: while it wasn't too hard for the locking
example, it was impossible to do this for the opening example.
The idea was to define the template like this:
@contextmanager
def opening(filename):
f = open(filename)
try:
yield f
finally:
f.close()
and used it like this:
with f = opening(filename):
...read data from f...
The problem is that in PEP 310, the result of calling EXPR is
assigned directly to VAR, and then VAR's __exit__() method is
called upon exit from BLOCK1. But here, VAR clearly needs to
receive the opened file, and that would mean that __exit__() would
have to be a method on the file.
While this can be solved using a proxy class, this is awkward and
made me realize that a slightly different translation would make
writing the desired decorator a piece of cake: let VAR receive the
result from calling the __enter__() method, and save the value of
EXPR to call its __exit__() method later. Then the decorator can
return an instance of a wrapper class whose __enter__() method
calls the generator's next() method and returns whatever next()
returns; the wrapper instance's __exit__() method calls next()
again but expects it to raise StopIteration. (Details below in
the section Optional Generator Decorator.)
So now the final hurdle was that the PEP 310 syntax:
with VAR = EXPR:
BLOCK1
would be deceptive, since VAR does *not* receive the value of
EXPR. Borrowing from PEP 340, it was an easy step to:
with EXPR as VAR:
BLOCK1
Additional discussion showed that people really liked being able
to "see" the exception in the generator, even if it was only to
log it; the generator is not allowed to yield another value, since
the with-statement should not be usable as a loop (raising a
different exception is marginally acceptable). To enable this, a
new throw() method for generators is proposed, which takes one to
three arguments representing an exception in the usual fashion
(type, value, traceback) and raises it at the point where the
generator is suspended.
Once we have this, it is a small step to proposing another
generator method, close(), which calls throw() with a special
exception, GeneratorExit. This tells the generator to exit, and
from there it's another small step to proposing that close() be
called automatically when the generator is garbage-collected.
Then, finally, we can allow a yield-statement inside a try-finally
statement, since we can now guarantee that the finally-clause will
(eventually) be executed. The usual cautions about finalization
apply -- the process may be terminated abruptly without finalizing
any objects, and objects may be kept alive forever by cycles or
memory leaks in the application (as opposed to cycles or leaks in
the Python implementation, which are taken care of by GC).
Note that we're not guaranteeing that the finally-clause is
executed immediately after the generator object becomes unused,
even though this is how it will work in CPython. This is similar
to auto-closing files: while a reference-counting implementation
like CPython deallocates an object as soon as the last reference
to it goes away, implementations that use other GC algorithms do
not make the same guarantee. This applies to Jython, IronPython,
and probably to Python running on Parrot.
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(The details of the changes made to generators can now be found in
PEP 342 rather than in the current PEP)
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Use Cases
See the Examples section near the end.
Specification: The 'with' Statement
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A new statement is proposed with the syntax:
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with EXPR as VAR:
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BLOCK
Here, 'with' and 'as' are new keywords; EXPR is an arbitrary
expression (but not an expression-list) and VAR is a single
assignment target. It can *not* be a comma-separated sequence of
variables, but it *can* be a *parenthesized* comma-separated
sequence of variables. (This restriction makes a future extension
possible of the syntax to have multiple comma-separated resources,
each with its own optional as-clause.)
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The "as VAR" part is optional.
The translation of the above statement is:
mgr = (EXPR)
exit = mgr.__exit__ # Not calling it yet
value = mgr.__enter__()
exc = True
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try:
try:
VAR = value # Only if "as VAR" is present
BLOCK
except:
# The exceptional case is handled here
exc = False
if not exit(*sys.exc_info()):
raise
# The exception is swallowed if exit() returns true
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finally:
# The normal and non-local-goto cases are handled here
if exc:
exit(None, None, None)
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Here, the lowercase variables (mgr, exit, value, exc) are internal
variables and not accessible to the user; they will most likely be
implemented as special registers or stack positions.
The details of the above translation are intended to prescribe the
exact semantics. If either of the relevant methods are not found
as expected, the interpreter will raise AttributeError, in the
order that they are tried (__exit__, __enter__).
Similarly, if any of the calls raises an exception, the effect is
exactly as it would be in the above code. Finally, if BLOCK
contains a break, continue or return statement, the __exit__()
method is called with three None arguments just as if BLOCK
completed normally. (I.e. these "pseudo-exceptions" are not seen
as exceptions by __exit__().)
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If the "as VAR" part of the syntax is omitted, the "VAR =" part of
the translation is omitted (but mgr.__enter__() is still called).
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The calling convention for mgr.__exit__() is as follows. If the
finally-suite was reached through normal completion of BLOCK or
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through a non-local goto (a break, continue or return statement in
BLOCK), mgr.__exit__() is called with three None arguments. If
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the finally-suite was reached through an exception raised in
BLOCK, mgr.__exit__() is called with three arguments representing
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the exception type, value, and traceback.
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IMPORTANT: if mgr.__exit__() returns a "true" value, the exception
is "swallowed". That is, if it returns "true", execution
continues at the next statement after the with-statement, even if
an exception happened inside the with-statement. However, if the
with-statement was left via a non-local goto (break, continue or
return), this non-local return is resumed when mgr.__exit__()
returns regardless of the return value. The motivation for this
detail is to make it possible for mgr.__exit__() to swallow
exceptions, without making it too easy (since the default return
value, None, is false and this causes the exception to be
re-raised). The main use case for swallowing exceptions is to
make it possible to write the @contextmanager decorator so
that a try/except block in a decorated generator behaves exactly
as if the body of the generator were expanded in-line at the place
of the with-statement.
The motivation for passing the exception details to __exit__(), as
opposed to the argument-less __exit__() from PEP 310, was given by
the transactional() use case, example 3 below. The template in
that example must commit or roll back the transaction depending on
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whether an exception occurred or not. Rather than just having a
boolean flag indicating whether an exception occurred, we pass the
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complete exception information, for the benefit of an
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exception-logging facility for example. Relying on sys.exc_info()
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to get at the exception information was rejected; sys.exc_info()
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has very complex semantics and it is perfectly possible that it
returns the exception information for an exception that was caught
ages ago. It was also proposed to add an additional boolean to
distinguish between reaching the end of BLOCK and a non-local
goto. This was rejected as too complex and unnecessary; a
non-local goto should be considered unexceptional for the purposes
of a database transaction roll-back decision.
To facilitate chaining of contexts in Python code that directly
manipulates context managers, __exit__() methods should *not*
re-raise the error that is passed in to them. It is always the
responsibility of the *caller* of the __exit__() method to do any
reraising in that case.
That way, if the caller needs to tell whether the __exit__()
invocation *failed* (as opposed to successfully cleaning up before
propagating the original error), it can do so.
If __exit__() returns without an error, this can then be
interpreted as success of the __exit__() method itself (regardless
of whether or not the original error is to be propagated or
suppressed).
However, if __exit__() propagates an exception to its caller, this
means that __exit__() *itself* has failed. Thus, __exit__()
methods should avoid raising errors unless they have actually
failed. (And allowing the original error to proceed isn't a
failure.)
Transition Plan
In Python 2.5, the new syntax will only be recognized if a future
statement is present:
from __future__ import with_statement
This will make both 'with' and 'as' keywords. Without the future
statement, using 'with' or 'as' as an identifier will cause a
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Warning to be issued to stderr.
In Python 2.6, the new syntax will always be recognized; 'with'
and 'as' are always keywords.
Generator Decorator
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With PEP 342 accepted, it is possible to write a decorator
that makes it possible to use a generator that yields exactly once
to control a with-statement. Here's a sketch of such a decorator:
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class GeneratorContextManager(object):
def __init__(self, gen):
self.gen = gen
def __enter__(self):
try:
return self.gen.next()
except StopIteration:
raise RuntimeError("generator didn't yield")
def __exit__(self, type, value, traceback):
if type is None:
try:
self.gen.next()
except StopIteration:
return
else:
raise RuntimeError("generator didn't stop")
else:
try:
self.gen.throw(type, value, traceback)
raise RuntimeError("generator didn't stop after throw()")
except StopIteration:
return True
except:
# only re-raise if it's *not* the exception that was
# passed to throw(), because __exit__() must not raise
# an exception unless __exit__() itself failed. But
# throw() has to raise the exception to signal
# propagation, so this fixes the impedance mismatch
# between the throw() protocol and the __exit__()
# protocol.
#
if sys.exc_info()[1] is not value:
raise
def contextmanager(func):
def helper(*args, **kwds):
return GeneratorContextManager(func(*args, **kwds))
return helper
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This decorator could be used as follows:
@contextmanager
def opening(filename):
f = open(filename) # IOError is untouched by GeneratorContext
try:
yield f
finally:
f.close() # Ditto for errors here (however unlikely)
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A robust implementation of this decorator will be made
part of the standard library.
Context Managers in the Standard Library
It would be possible to endow certain objects, like files,
sockets, and locks, with __enter__() and __exit__() methods so
that instead of writing:
with locking(myLock):
BLOCK
one could write simply:
with myLock:
BLOCK
I think we should be careful with this; it could lead to mistakes
like:
f = open(filename)
with f:
BLOCK1
with f:
BLOCK2
which does not do what one might think (f is closed before BLOCK2
is entered).
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OTOH such mistakes are easily diagnosed; for example, the
generator context decorator above raises RuntimeError when a
second with-statement calls f.__enter__() again. A similar error
can be raised if __enter__ is invoked on a closed file object.
For Python 2.5, the following types have been identified as
context managers:
- file
- thread.LockType
- threading.Lock
- threading.RLock
- threading.Condition
- threading.Semaphore
- threading.BoundedSemaphore
A context manager will also be added to the decimal module to
support using a local decimal arithmetic context within the body
of a with statement, automatically restoring the original context
when the with statement is exited.
Standard Terminology
This PEP proposes that the protocol consisting of the __enter__()
and __exit__() methods be known as the "context management protocol",
and that objects that implement that protocol be known as "context
managers". [4]
The code in the body of the with statement is a "managed context".
This term refers primarily to the code location, rather than to the
runtime environment established by the context manager.
The expression immediately following the with keyword in the
statement is a "context expression" as that expression provides the
main clue as to the runtime environment the context manager
establishes for the duration of the managed context.
The value assigned to the target list after the as keyword is the
"context entry value", as that value is returned as the result of
entering the context.
These terms are based on the idea that the context expression
provides a context manager to appropriately handle entry into the
managed context. The context manager may also provide a meaningful
context entry value and perform clean up operations on exit from
the managed context.
The general term "context" is unfortunately ambiguous. If necessary,
it can be made more explicit by using the terms "context manager"
for the concrete object created by the context expression,
"managed context" for the code in the body of the with statement,
and "runtime context" or (preferebly) "runtime environment" for the
actual state modifications made by the context manager. When solely
discussing use of the with statement, the distinction between these
shouldn't matter too much as the context manager fully defines the
changes made to the runtime environment, and those changes apply for
the duration of the managed context. The distinction is more
important when discussing the process of implementing context
managers and the mechanics of the with statement itself.
Caching Context Managers
Many context managers (such as files and generator-based contexts)
will be single-use objects. Once the __exit__() method has been
called, the context manager will no longer be in a usable state
(e.g. the file has been closed, or the underlying generator has
finished execution).
Requiring a fresh manager object for each with statement is the
easiest way to avoid problems with multi-threaded code and nested
with statements trying to use the same context manager. It isn't
coincidental that all of the standard library context managers
that support reuse come from the threading module - they're all
already designed to deal with the problems created by threaded
and nested usage.
This means that in order to save a context manager with particular
initialisation arguments to be used in multiple with statements, it
will typically be necessary to store it in a zero-argument callable
that is then called in the context expression of each statement
rather than caching the context manager directly.
When this restriction does not apply, the documentation of the
affected context manager should make that clear.
Open Issues
1. Greg Ewing raised the question of whether or not the term
"context manager" was too generic and suggested "context guard"
as an alternative name.
2. In Python 2.5a2, the decorator in contextlib to create a
context manager from a generator function is called
@contextfactory. This made sense when the __context__()
method existed and the result of the factory function was
a managed context object.
With the elimination of the __context__() method, the
result of the factory function is once again a context
manager, suggesting the decorator should be renamed to
either @contextmanager or @managerfactory.
The PEP currently uses @contextmanager.
Resolved Issues
The following issues were resolved by BDFL approval (and a lack
of any major objections on python-dev).
1. What exception should GeneratorContextManager raise when the
underlying generator-iterator misbehaves? The following quote is
the reason behind Guido's choice of RuntimeError for both this
and for the generator close() method in PEP 342 (from [8]):
"I'd rather not introduce a new exception class just for this
purpose, since it's not an exception that I want people to catch:
I want it to turn into a traceback which is seen by the
programmer who then fixes the code. So now I believe they
should both raise RuntimeError.
There are some precedents for that: it's raised by the core
Python code in situations where endless recursion is detected,
and for uninitialized objects (and for a variety of
miscellaneous conditions)."
2. It is fine to raise AttributeError instead of TypeError if the
relevant methods aren't present on a class involved in a with
statement. The fact that the abstract object C API raises
TypeError rather than AttributeError is an accident of history,
rather than a deliberate design decision [11].
Rejected Options
For several months, the PEP prohibited suppression of exceptions
in order to avoid hidden flow control. Implementation
revealed this to be a right royal pain, so Guido restored the
ability [13].
Another aspect of the PEP that caused no end of questions and
terminology debates was providing a __context__() method that
was analogous to an iterable's __iter__() method [5, 7, 9].
The ongoing problems [10, 13] with explaining what it was and why
it was and how it was meant to work eventually lead to Guido
killing the concept outright [15] (and there was much rejoicing!).
The notion of using the PEP 342 generator API directly to define
the with statement was also briefly entertained [6], but quickly
dismissed as making it too difficult to write non-generator
based context managers.
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Examples
The generator based examples rely on PEP 342. Also, some of the
examples are likely to be unnecessary in practice, as the
appropriate objects, such as threading.RLock, will be able to be
used directly in with statements.
The tense used in the names of the example contexts is not
arbitrary. Past tense ("-ed") is used when the name refers to an
action which is done in the __enter__ method and undone in the
__exit__ method. Progressive tense ("-ing") is used when the name
refers to an action which is to be done in the __exit__ method.
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1. A template for ensuring that a lock, acquired at the start of a
block, is released when the block is left:
@contextmanager
def locked(lock):
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lock.acquire()
try:
yield
finally:
lock.release()
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Used as follows:
with locked(myLock):
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# Code here executes with myLock held. The lock is
# guaranteed to be released when the block is left (even
# if via return or by an uncaught exception).
2. A template for opening a file that ensures the file is closed
when the block is left:
@contextmanager
def opened(filename, mode="r"):
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f = open(filename, mode)
try:
yield f
finally:
f.close()
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Used as follows:
with opened("/etc/passwd") as f:
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for line in f:
print line.rstrip()
3. A template for committing or rolling back a database
transaction:
@contextmanager
def transaction(db):
db.begin()
try:
yield None
except:
db.rollback()
raise
else:
db.commit()
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4. Example 1 rewritten without a generator:
class locked:
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def __init__(self, lock):
self.lock = lock
def __enter__(self):
self.lock.acquire()
def __exit__(self, type, value, tb):
self.lock.release()
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(This example is easily modified to implement the other
relatively stateless examples; it shows that it is easy to avoid
the need for a generator if no special state needs to be
preserved.)
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5. Redirect stdout temporarily:
@contextmanager
def stdout_redirected(new_stdout):
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save_stdout = sys.stdout
sys.stdout = new_stdout
try:
yield None
finally:
sys.stdout = save_stdout
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Used as follows:
with opened(filename, "w") as f:
with stdout_redirected(f):
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print "Hello world"
This isn't thread-safe, of course, but neither is doing this
same dance manually. In single-threaded programs (for example,
in scripts) it is a popular way of doing things.
6. A variant on opened() that also returns an error condition:
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@contextmanager
def opened_w_error(filename, mode="r"):
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try:
f = open(filename, mode)
except IOError, err:
yield None, err
else:
try:
yield f, None
finally:
f.close()
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Used as follows:
with opened_w_error("/etc/passwd", "a") as (f, err):
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if err:
print "IOError:", err
else:
f.write("guido::0:0::/:/bin/sh\n")
7. Another useful example would be an operation that blocks
signals. The use could be like this:
import signal
with signal.blocked():
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# code executed without worrying about signals
An optional argument might be a list of signals to be blocked;
by default all signals are blocked. The implementation is left
as an exercise to the reader.
8. Another use for this feature is the Decimal context. Here's a
simple example, after one posted by Michael Chermside:
import decimal
@contextmanager
def extra_precision(places=2):
c = decimal.getcontext()
saved_prec = c.prec
c.prec += places
try:
yield None
finally:
c.prec = saved_prec
Sample usage (adapted from the Python Library Reference):
def sin(x):
"Return the sine of x as measured in radians."
with extra_precision():
i, lasts, s, fact, num, sign = 1, 0, x, 1, x, 1
while s != lasts:
lasts = s
i += 2
fact *= i * (i-1)
num *= x * x
sign *= -1
s += num / fact * sign
# The "+s" rounds back to the original precision,
# so this must be outside the with-statement:
return +s
9. Here's a proposed context manager for the decimal module:
# This would be a new decimal.Context method
@contextmanager
def localcontext(ctx=None):
"""Set a new local decimal context for the block"""
# Default to using the current context
if ctx is None:
ctx = getcontext()
# We set the thread context to a copy of this context
# to ensure that changes within the block are kept
# local to the block.
newctx = ctx.copy()
oldctx = decimal.getcontext()
decimal.setcontext(newctx)
try:
yield newctx
finally:
# Always restore the original context
decimal.setcontext(oldctx)
Sample usage:
from decimal import localcontext, ExtendedContext
def sin(x):
with localcontext() as ctx:
ctx.prec += 2
# Rest of sin calculation algorithm
# uses a precision 2 greater than normal
return +s # Convert result to normal precision
def sin(x):
with localcontext(ExtendedContext):
# Rest of sin calculation algorithm
# uses the Extended Context from the
# General Decimal Arithmetic Specification
return +s # Convert result to normal context
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10. A generic "object-closing" context manager:
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class closing(object):
def __init__(self, obj):
self.obj = obj
def __enter__(self):
return self.obj
def __exit__(self, *exc_info):
try:
close_it = self.obj.close
except AttributeError:
pass
else:
close_it()
This can be used to deterministically close anything with a
close method, be it file, generator, or something else. It
can even be used when the object isn't guaranteed to require
closing (e.g., a function that accepts an arbitrary
iterable):
# emulate opening():
with closing(open("argument.txt")) as contradiction:
for line in contradiction:
print line
# deterministically finalize an iterator:
with closing(iter(data_source)) as data:
for datum in data:
process(datum)
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(Python 2.5's contextlib module contains a version
of this context manager)
11. PEP 319 gives a use case for also having a released()
context to temporarily release a previously acquired lock;
this can be written very similarly to the locked context
manager above by swapping the acquire() and release() calls.
class released:
def __init__(self, lock):
self.lock = lock
def __enter__(self):
self.lock.release()
def __exit__(self, type, value, tb):
self.lock.acquire()
Sample usage:
with my_lock:
# Operations with the lock held
with released(my_lock):
# Operations without the lock
# e.g. blocking I/O
# Lock is held again here
12. A "nested" context manager that automatically nests the
supplied contexts from left-to-right to avoid excessive
indentation:
@contextmanager
def nested(*contexts):
exits = []
vars = []
try:
try:
for context in contexts:
mgr = context.__context__()
exit = mgr.__exit__
enter = mgr.__enter__
vars.append(enter())
exits.append(exit)
yield vars
except:
exc = sys.exc_info()
else:
exc = (None, None, None)
finally:
while exits:
exit = exits.pop()
try:
exit(*exc)
except:
exc = sys.exc_info()
else:
exc = (None, None, None)
if exc != (None, None, None):
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# sys.exc_info() may have been
# changed by one of the exit methods
# so provide explicit exception info
raise exc[0], exc[1], exc[2]
Sample usage:
with nested(a, b, c) as (x, y, z):
# Perform operation
Is equivalent to:
with a as x:
with b as y:
with c as z:
# Perform operation
(Python 2.5's contextlib module contains a version
of this context manager)
Reference Implementation
This PEP was first accepted by Guido at his EuroPython
keynote, 27 June 2005.
It was accepted again later, with the __context__ method added.
The PEP was implemented in subversion for Python 2.5a1
The __context__() method will be removed in Python 2.5a3
Ackowledgements
Many people contributed to the ideas and concepts in this PEP,
including all those mentioned in the acknowledgements for PEP 340
and PEP 346.
Additional thanks goes to (in no meaningful order): Paul Moore,
Phillip J. Eby, Greg Ewing, Jason Orendorff, Michael Hudson,
Raymond Hettinger, Walter D<>rwald, Aahz, Georg Brandl, Terry Reedy,
A.M. Kuchling, Brett Cannon, and all those that participated in the
discussions on python-dev.
References
[1] Raymond Chen's article on hidden flow control
http://blogs.msdn.com/oldnewthing/archive/2005/01/06/347666.aspx
[2] Guido suggests some generator changes that ended up in PEP 342
http://mail.python.org/pipermail/python-dev/2005-May/053885.html
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[3] Wiki discussion of PEP 343
http://wiki.python.org/moin/WithStatement
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[4] Early draft of some documentation for the with statement
http://mail.python.org/pipermail/python-dev/2005-July/054658.html
[5] Proposal to add the __with__ method
http://mail.python.org/pipermail/python-dev/2005-October/056947.html
[6] Proposal to use the PEP 342 enhanced generator API directly
http://mail.python.org/pipermail/python-dev/2005-October/056969.html
[7] Guido lets me (Nick Coghlan) talk him into a bad idea ;)
http://mail.python.org/pipermail/python-dev/2005-October/057018.html
[8] Guido raises some exception handling questions
http://mail.python.org/pipermail/python-dev/2005-June/054064.html
[9] Guido answers some questions about the __context__ method
http://mail.python.org/pipermail/python-dev/2005-October/057520.html
[10] Guido answers more questions about the __context__ method
http://mail.python.org/pipermail/python-dev/2005-October/057535.html
[11] Guido says AttributeError is fine for missing special methods
http://mail.python.org/pipermail/python-dev/2005-October/057625.html
[12] Original PEP 342 implementation patch
http://sourceforge.net/tracker/index.php?func=detail&aid=1223381&group_id=5470&atid=305470
[13] Guido restores the ability to suppress exceptions
http://mail.python.org/pipermail/python-dev/2006-February/061909.html
[14] A simple question kickstarts a thorough review of PEP 343
http://mail.python.org/pipermail/python-dev/2006-April/063859.html
[15] Guido kills the __context__() method
http://mail.python.org/pipermail/python-dev/2006-April/064632.html
[16] Greg propose 'context guard' instead of 'context manager'
http://mail.python.org/pipermail/python-dev/2006-May/064676.html
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Copyright
This document has been placed in the public domain.