python-peps/pep-0343.txt

PEP: 343
Title: The "with" Statement
Version: $Revision$
Last-Modified: $Date$
Author: Guido van Rossum, Nick Coghlan
Status: Accepted
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

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.

    The PEP was approved in principle by the BDFL, but there were
    still a couple of implementation details to be worked out (see the
    section on Resolved Issues). It's still at Draft status until
    Guido gives a final blessing to the updated PEP.


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, this refers to the
    implementation rather than the exact terminology.

    The current version of the PEP reflects the implementation and
    documentation as at Python 2.5a2. The PEP will be updated to
    reflect any changes made to the terminology prior to the final
    Python 2.5 release.

Introduction

    After a lot of discussion about PEP 340 and alternatives, I
    decided to withdraw PEP 340 and proposed a slight variant on PEP
    310.  After more discussion, I have added back a mechanism for
    raising an exception in a suspended generator using a throw()
    method, and a close() method which throws a new GeneratorExit
    exception; these additions were first proposed on python-dev in
    [2] and universally approved of.  I'm also changing the keyword to
    'with'.

    On-line discussion of this PEP should take place in the Python
    Wiki [3].

    If this PEP is approved, the following PEPs will be 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 have already been withdrawn.)

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
    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 rougly 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.

Use Cases

    See the Examples section near the end.

Specification: The 'with' Statement

    A new statement is proposed with the syntax:

        with EXPR as VAR:
            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.)

    The "as VAR" part is optional.

    The translation of the above statement is:

        mgr = (EXPR).__context__()
        exit = mgr.__exit__  # Not calling it yet
        value = mgr.__enter__()
        exc = True
        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
        finally:
            # The normal and non-local-goto cases are handled here
            if exc:
                exit(None, None, None)

    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 any of the relevant methods are not found as
    expected, the interpreter will raise AttributeError, in the order
    that they are tried (__context__, __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__().)

    The call to the __context__() method serves a similar purpose to
    that of the __iter__() method of iterator and iterables. A context
    specifier with simple state requirements (such as
    threading.RLock) may provide its own __enter__() and __exit__()
    methods, and simply return 'self' from its __context__ method. On
    the other hand, a context specifier with more complex state
    requirements (such as decimal.Context) may return a distinct
    context manager each time its __context__ method is invoked.

    If the "as VAR" part of the syntax is omitted, the "VAR =" part of
    the translation is omitted (but mgr.__enter__() is still called).

    The calling convention for mgr.__exit__() is as follows.  If the
    finally-suite was reached through normal completion of BLOCK or
    through a non-local goto (a break, continue or return statement in
    BLOCK), mgr.__exit__() is called with three None arguments.  If
    the finally-suite was reached through an exception raised in
    BLOCK, mgr.__exit__() is called with three arguments representing
    the exception type, value, and traceback.

    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
    whether an exception occurred or not.  Rather than just having a
    boolean flag indicating whether an exception occurred, we pass the
    complete exception information, for the benefit of an
    exception-logging facility for example.  Relying on sys.exc_info()
    to get at the exception information was rejected; sys.exc_info()
    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 specifiers and managers, __exit__() methods
    should *not* re-raise the error that is passed in to them, because
    it is always the responsibility of the *caller* 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 (whether 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.)
    
    Objects returned by __context__() methods should also provide a 
    __context__() method that returns self. This allows a program to
    retrieve the context manager directly without breaking anything.
    For example, the following should work just as well as the normal
    case where the extra variable isn't used:

        mgr = (EXPR).__context__()
        with mgr as VAR:
            BLOCK

    The with statement implementation and examples like the nested()
    function require this behaviour in order to be able to deal
    transparently with both context specifiers and context managers.

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
    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

    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:

        class GeneratorContextManager(object):

           def __init__(self, gen):
               self.gen = gen

           def __context__(self):
               return self

           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

    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)

    A robust implementation of this decorator will be made
    part of the standard library.

    Just as generator-iterator functions are very useful for writing
    __iter__() methods for iterables, generator context functions will
    be very useful for writing __context__() methods for context
    specifiers. These methods will still need to be decorated using the
    contextmanager decorator. To ensure an obvious error message if the
    decorator is left out, generator-iterator objects will NOT be given
    a native context - if you want to ensure a generator is closed
    promptly, use something similar to the duck-typed "closing" context
    manager in the examples.

Optional Extensions

    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).

    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 candidates have been identified for
    native context managers:
        - file
        - decimal.Context
        - thread.LockType
        - threading.Lock
        - threading.RLock
        - threading.Condition
        - threading.Semaphore and threading.BoundedSemaphore

Standard Terminology

    Discussions about iterators and iterables are aided by the standard
    terminology used to discuss them. The protocol used by the for
    statement is called the iterator protocol and an iterator is any
    object that properly implements that protocol. The term "iterable"
    then encompasses all objects with an __iter__() method that
    returns an iterator.

    This PEP proposes that the protocol consisting of the __enter__()
    and __exit__() methods, and a __context__() method that returns
    self be known as the "context management protocol", and that
    objects that implement that protocol be known as "context
    managers".

    The term "context specifier" then encompasses all objects with a
    __context__() method that returns a context manager.  The protocol
    these objects implement is called the "context specification
    protocol". This means that all context managers are context
    specifiers, but not all context specifiers are context managers,
    just as all iterators are iterables, but not all iterables are
    iterators.

    These terms are based on the concept that the context specifier
    defines a context of execution for the code that forms the body of
    the with statement. The role of the context manager is to
    translate the context specifier's stored state into an active
    manipulation of the runtime environment to setup and tear down the
    desired runtime context for the duration of the with statement.
    For example, a synchronisation lock's context manager acquires the
    lock when entering the with statement, and releases the lock when
    leaving it. The runtime context established within the body of the
    with statement is that the synchronisation lock is currently held.

    The general term "context" is unfortunately ambiguous. If necessary,
    it can be made more explicit by using the terms "context specifier"
    for objects providing a __context__() method and "runtime context"
    for the runtime environment modifications made by the context
    manager. When solely discussing use of the with statement, the
    distinction between the two shouldn't matter as the context
    specifier fully defines the changes made to the runtime context.
    The distinction is more important when discussing the process of
    implementing context specifiers and context managers.

Open Issues

    1. After this PEP was originally approved, a subsequent discussion
       on python-dev [4] settled on the term "context manager" for
       objects which provide __enter__ and __exit__ methods, and
       "context management protocol" for the protocol itself. With the
       addition of the __context__ method to the protocol, the natural
       adjustment is to call all objects which provide a __context__
       method "context managers", and the objects with __enter__ and
       __exit__ methods "contexts" (or "manageable contexts" in
       situations where the general term "context" would be ambiguous).

       As noted above, the Python 2.5 release cycle revealed problems
       with the previously agreed terminology. The updated standard
       terminology section has not yet met with consensus on
       python-dev. It will be refined throughout the Python 2.5 release
       cycle based on user feedback on the usability of the
       documentation.
       The first change made as a result of the current discussion is
       replacement of the term "context object" with
       "context specifier".

    2. The original resolution was for the decorator to make a context
       manager from a generator to be a builtin called "contextmanager".
       The shorter term "context" was considered too ambiguous and
       potentially confusing [9].
       The different flavours of generators could then be described as:
        - A "generator function" is an undecorated function containing
          the 'yield' keyword, and the objects produced by
          such functions are "generator-iterators". The term
          "generator" may refer to either a generator function or a
          generator-iterator depending on the situation.
        - A "generator context function" is a generator function to
          which the "contextmanager" decorator is applied and the
          objects produced by such functions are "generator-context-
          managers". The term "generator context" may refer to either
          a generator context function or a generator-context-manager
          depending on the situation.

       In the Python 2.5 implementation, the decorator is actually part
       of the standard library module contextlib. The ongoing
       terminology review may lead to it being renamed
       "contextlib.context" (with the existence of the underlying context
       manager being an implementation detail).


Resolved Issues

    The following issues were resolved either by BDFL approval,
    consensus on python-dev, or a simple lack of objection to
    proposals in the original version of this PEP.

    1. The __exit__() method of the GeneratorContextManager class
       catches StopIteration and considers it equivalent to re-raising
       the exception passed to throw().  Is allowing StopIteration
       right here?

       This is so that a generator doing cleanup depending on the
       exception thrown (like the transactional() example below) can
       *catch* the exception thrown if it wants to and doesn't have to
       worry about re-raising it.  I find this more convenient for the
       generator writer.  Against this was brought in that the
       generator *appears* to suppress an exception that it cannot
       suppress: the transactional() example would be more clear
       according to this view if it re-raised the original exception
       after the call to db.rollback().  I personally would find the
       requirement to re-raise the exception an annoyance in a
       generator used as a with-template, since all the code after
       yield is used for is cleanup, and it is invoked from a
       finally-clause (the one implicit in the with-statement) which
       re-raises the original exception anyway.

    2. 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)."

    3. See item 1 in open issues :)


    4. The originally approved version of this PEP did not include a
       __context__ method - the method was only added to the PEP after
       Jason Orendorff pointed out the difficulty of writing
       appropriate __enter__ and __exit__ methods for decimal.Context
       [5]. This approach allows a class to define a native context
       manager using generator syntax. It also allows a class to use an
       existing independent context as its native context object by
       applying the independent context to 'self' in its __context__ 
       method.  It even allows a class written in C to
       use a generator context manager written in Python.
       The __context__ method parallels the __iter__ method which forms
       part of the iterator protocol.
       An earlier version of this PEP called this the __with__ method.
       This was later changed to match the name of the protocol rather
       than the keyword for the statement [9].

    5. The suggestion was made by Jason Orendorff that the __enter__
       and __exit__ methods could be removed from the context
       management protocol, and the protocol instead defined directly
       in terms of the enhanced generator interface described in PEP
       342 [6].
       Guido rejected this idea [7]. The following are some of benefits
       of keeping the __enter__ and __exit__ methods:
          - it makes it easy to implement a simple context in C
            without having to rely on a separate coroutine builder
          - it makes it easy to provide a low-overhead implementation
            for contexts that don't need to maintain any
            special state between the __enter__ and __exit__ methods
            (having to use a generator for these would impose
            unnecessary overhead without any compensating benefit)
          - it makes it possible to understand how the with statement
            works without having to first understand the mechanics of
            how generator context managers are implemented.

    6. See item 2 in open issues :)

    7. A generator function used to implement a __context__ method will
       need to be decorated with the contextmanager decorator in order
       to have the correct behaviour. Otherwise, you will get an
       AttributeError when using the class in a with statement, as
       normal generator-iterators will NOT have __enter__ or __exit__
       methods.
       Getting deterministic closure of generators will require a
       separate context manager such as the closing example below.
       As Guido put it, "too much magic is bad for your health" [10].

    8. 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].

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.

    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):
            lock.acquire()
            try:
                yield
            finally:
                lock.release()

       Used as follows:

        with locked(myLock):
            # 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).

       PEP 319 gives a use case for also having an unlocked()
       context; this can be written very similarly (just swap the
       acquire() and release() calls).

    2. A template for opening a file that ensures the file is closed
       when the block is left:

        @contextmanager
        def opened(filename, mode="r"):
            f = open(filename, mode)
            try:
                yield f
            finally:
                f.close()

       Used as follows:

        with opened("/etc/passwd") as f:
            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()

    4. Example 1 rewritten without a generator:

        class locked:
           def __init__(self, lock):
               self.lock = lock
           def __context__(self):
               return self
           def __enter__(self):
               self.lock.acquire()
           def __exit__(self, type, value, tb):
               self.lock.release()
               if type is not None:
                   raise type, value, tb

       (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.)

    5. Redirect stdout temporarily:

        @contextmanager
        def stdout_redirected(new_stdout):
            save_stdout = sys.stdout
            sys.stdout = new_stdout
            try:
                yield None
            finally:
                sys.stdout = save_stdout

       Used as follows:

        with opened(filename, "w") as f:
            with stdout_redirected(f):
                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:

        @contextmanager
        def opened_w_error(filename, mode="r"):
            try:
                f = open(filename, mode)
            except IOError, err:
                yield None, err
            else:
                try:
                    yield f, None
                finally:
                    f.close()

       Used as follows:

        with opened_w_error("/etc/passwd", "a") as (f, err):
            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():
            # 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 native context manager for decimal.Context:

         # This would be a new decimal.Context method
         @contextmanager
         def __context__(self):
             # We set the thread context to a copy of this context
             # to ensure that changes within the block are kept
             # local to the block. This also gives us thread safety
             # and supports nested usage of a given context.
             newctx = self.copy()
             oldctx = decimal.getcontext()
             decimal.setcontext(newctx)
             try:
                 yield newctx
             finally:
                 decimal.setcontext(oldctx)

        Sample usage:

         def sin(x):
             with decimal.getcontext() 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 decimal.ExtendedContext:
                 # Rest of sin calculation algorithm
                 # uses the Extended Context from the
                 # General Decimal Arithmetic Specification
             return +s # Convert result to normal context

     10. A generic "object-closing" template:

         @contextmanager
         def closing(obj):
             try:
                 yield obj
             finally:
                 try:
                     close = obj.close
                 except AttributeError:
                     pass
                 else:
                     close()

         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)

     11. Native contexts for objects with acquire/release methods:

         # This would be a new method of e.g., threading.RLock
         def __context__(self):
             return locked(self)

         def released(self):
             return unlocked(self)

         Sample usage:

         with my_lock:
             # Operations with the lock held
             with my_lock.released():
                 # 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):
                     raise

         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


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 for Python 2.5a1


References

    [1] http://blogs.msdn.com/oldnewthing/archive/2005/01/06/347666.aspx

    [2] http://mail.python.org/pipermail/python-dev/2005-May/053885.html

    [3] http://wiki.python.org/moin/WithStatement

    [4]
    http://mail.python.org/pipermail/python-dev/2005-July/054658.html

    [5]
    http://mail.python.org/pipermail/python-dev/2005-October/056947.html

    [6]
    http://mail.python.org/pipermail/python-dev/2005-October/056969.html

    [7]
    http://mail.python.org/pipermail/python-dev/2005-October/057018.html

    [8]
    http://mail.python.org/pipermail/python-dev/2005-June/054064.html

    [9]
    http://mail.python.org/pipermail/python-dev/2005-October/057520.html

    [10]
    http://mail.python.org/pipermail/python-dev/2005-October/057535.html

    [11]
    http://mail.python.org/pipermail/python-dev/2005-October/057625.html

    [12]
    http://sourceforge.net/tracker/index.php?func=detail&aid=1223381&group_id=5470&atid=305470

    [13]
    http://mail.python.org/pipermail/python-dev/2006-February/061903.html

    [14]
    http://mail.python.org/pipermail/python-dev/2006-April/063859.html

Copyright

    This document has been placed in the public domain.