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PEP: 343
Title: The "with" Statement
Version: c25fa0913267
Last-Modified:  2011-06-13 01:39:23 +1000 (Mon, 13 Jun 2011)
Author: Guido van Rossum, Nick Coghlan
Status: Final
Type: Standards Track
Content-Type: text/plain
Created: 13-May-2005
Python-Version: 2.5
Post-History: 2-Jun-2005, 16-Oct-2005, 29-Oct-2005, 23-Apr-2006, 1-May-2006, 30-Jul-2006


    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 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

    Python's alpha release cycle revealed terminology problems in this
    PEP and in the associated documentation and implementation [14].
    The PEP stabilised around the time of the first Python 2.5 beta

    Yes, the verb tense is messed up in a few places. We've been
    working on this PEP for over a year now, so things that were
    originally in the future are now in the past :)


    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

    After acceptance of this PEP, the following PEPs were 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].

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 roughly this syntax (the "VAR =" part is

        with VAR = EXPR:

    which roughly translates into this:

        VAR = EXPR

    Now consider this example:

        with f = open("/etc/passwd"):

    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:

        def opening(filename):
            f = open(filename)
                yield f

    and used it like this:

        with f = opening(filename):
   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:

    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:

    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.

    (The details of the changes made to generators can now be found in
     PEP 342 rather than in the current PEP)

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:

    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)
        exit = type(mgr).__exit__  # Not calling it yet
        value = type(mgr).__enter__(mgr)
        exc = True
                VAR = value  # Only if "as VAR" is present
                # The exceptional case is handled here
                exc = False
                if not exit(mgr, *sys.exc_info()):
                # The exception is swallowed if exit() returns true
            # The normal and non-local-goto cases are handled here
            if exc:
                exit(mgr, 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 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__().)

    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 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

    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 

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 __enter__(self):
               except StopIteration:
                   raise RuntimeError("generator didn't yield")

           def __exit__(self, type, value, traceback):
               if type is None:
                   except StopIteration:
                       raise RuntimeError("generator didn't stop")
                       self.gen.throw(type, value, traceback)
                       raise RuntimeError("generator didn't stop after throw()")
                   except StopIteration:
                       return True
                       # 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:

        def contextmanager(func):
           def helper(*args, **kwds):
               return GeneratorContextManager(func(*args, **kwds))
           return helper

    This decorator could be used as follows:

        def opening(filename):
           f = open(filename) # IOError is untouched by GeneratorContext
               yield f
               f.close() # Ditto for errors here (however unlikely)

    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):

    one could write simply:

        with myLock:

    I think we should be careful with this; it could lead to mistakes

        f = open(filename)
        with f:
        with f:

    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 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 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 statement body.

    The code in the body of the with statement and the variable name
    (or names) after the as keyword don't really have special terms at
    this point in time. The general terms "statement body" and "target
    list" can be used, prefixing with "with" or "with statement" if the
    terms would otherwise be unclear.

    Given the existence of objects such as the decimal module's
    arithmetic context, the term "context" is unfortunately ambiguous.
    If necessary, it can be made more specific by using the terms
    "context manager" for the concrete object created by the context
    expression and "runtime context" or (preferably) "runtime
    environment" for the actual state modifications made by the context
    manager. When simply discussing use of the with statement, the
    ambiguity shouldn't matter too much as the context expression fully
    defines the changes made to the runtime environment.
    The distinction is more important when discussing the mechanics of
    the with statement itself and how to go about actually implementing
    context managers.

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.

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].

    3. Objects with __enter__/__exit__ methods are called "context
       managers" and the decorator to convert a generator function
       into a context manager factory is ``contextlib.contextmanager``.
       There were some other suggestions [16] during the 2.5 release
       cycle but no compelling arguments for switching away from the
       terms that had been used in the PEP implementation were made.

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.


    The generator based examples rely on PEP 342. Also, some of the
    examples are unnecessary in practice, as the appropriate objects,
    such as threading.RLock, are able to be used directly in with

    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:

        def locked(lock):

       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).

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

        def opened(filename, mode="r"):
            f = open(filename, mode)
                yield f

       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

        def transaction(db):
                yield None

    4. Example 1 rewritten without a generator:

        class locked:
           def __init__(self, lock):
               self.lock = lock
           def __enter__(self):
           def __exit__(self, 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

    5. Redirect stdout temporarily:

        def stdout_redirected(new_stdout):
            save_stdout = sys.stdout
            sys.stdout = new_stdout
                yield None
                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:

        def opened_w_error(filename, mode="r"):
                f = open(filename, mode)
            except IOError, err:
                yield None, err
                    yield f, None

       Used as follows:

        with opened_w_error("/etc/passwd", "a") as (f, err):
            if err:
                print "IOError:", err

    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

        def extra_precision(places=2):
            c = decimal.getcontext()
            saved_prec = c.prec
            c.prec += places
                yield None
                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 simple context manager for the decimal module:

         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()
                 yield newctx
                 # Always restore the original context

        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

     10. A generic "object-closing" context manager:

         class closing(object):
             def __init__(self, obj):
                 self.obj = obj
             def __enter__(self):
                 return self.obj
             def __exit__(self, *exc_info):
                     close_it = self.obj.close
                 except AttributeError:

         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

         # 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:

         (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):
           def __exit__(self, type, value, tb):

         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

         def nested(*contexts):
             exits = []
             vars = []
                     for context in contexts:
                         mgr = context.__context__()
                         exit = mgr.__exit__
                         enter = mgr.__enter__
                     yield vars
                     exc = sys.exc_info()
                     exc = (None, None, None)
                 while exits:
                     exit = exits.pop()
                         exc = sys.exc_info()
                         exc = (None, None, None)
                 if exc != (None, None, None):
                     # 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


    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 Dörwald, Aahz, Georg Brandl, Terry Reedy,
    A.M. Kuchling, Brett Cannon, and all those that participated in the
    discussions on python-dev.


    [1] Raymond Chen's article on hidden flow control

    [2] Guido suggests some generator changes that ended up in PEP 342

    [3] Wiki discussion of PEP 343

    [4] Early draft of some documentation for the with statement

    [5] Proposal to add the __with__ method

    [6] Proposal to use the PEP 342 enhanced generator API directly

    [7] Guido lets me (Nick Coghlan) talk him into a bad idea ;)

    [8] Guido raises some exception handling questions

    [9] Guido answers some questions about the __context__ method

    [10] Guido answers more questions about the __context__ method

    [11] Guido says AttributeError is fine for missing special methods

    [12] Original PEP 342 implementation patch

    [13] Guido restores the ability to suppress exceptions

    [14] A simple question kickstarts a thorough review of PEP 343

    [15] Guido kills the __context__() method

    [16] Proposal to use 'context guard' instead of 'context manager'


    This document has been placed in the public domain.