"contextlib" --- Utilities for "with"-statement contexts
********************************************************

**Source code:** Lib/contextlib.py

======================================================================

This module provides utilities for common tasks involving the "with"
statement. For more information see also Tipi di gestori di contesti
and With Statement Context Managers.


Utilities
=========

Functions and classes provided:

class contextlib.AbstractContextManager

   An *abstract base class* for classes that implement "__enter__()"
   and "__exit__()". A default implementation for "__enter__()" is
   provided which returns "self" while "__exit__()" is an abstract
   method which by default returns "None". See also the definition of
   Tipi di gestori di contesti.

   Added in version 3.6.

class contextlib.AbstractAsyncContextManager

   An *abstract base class* for classes that implement "__aenter__()"
   and "__aexit__()". A default implementation for "__aenter__()" is
   provided which returns "self" while "__aexit__()" is an abstract
   method which by default returns "None". See also the definition of
   Asynchronous Context Managers.

   Added in version 3.7.

@contextlib.contextmanager

   This function is a *decorator* that can be used to define a factory
   function for "with" statement context managers, without needing to
   create a class or separate "__enter__()" and "__exit__()" methods.

   While many objects natively support use in with statements,
   sometimes a resource needs to be managed that isn't a context
   manager in its own right, and doesn't implement a "close()" method
   for use with "contextlib.closing".

   An abstract example would be the following to ensure correct
   resource management:

      from contextlib import contextmanager

      @contextmanager
      def managed_resource(*args, **kwds):
          # Code to acquire resource, e.g.:
          resource = acquire_resource(*args, **kwds)
          try:
              yield resource
          finally:
              # Code to release resource, e.g.:
              release_resource(resource)

   The function can then be used like this:

      >>> with managed_resource(timeout=3600) as resource:
      ...     # Resource is released at the end of this block,
      ...     # even if code in the block raises an exception

   The function being decorated must return a *generator*-iterator
   when called. This iterator must yield exactly one value, which will
   be bound to the targets in the "with" statement's "as" clause, if
   any.

   At the point where the generator yields, the block nested in the
   "with" statement is executed.  The generator is then resumed after
   the block is exited. If an unhandled exception occurs in the block,
   it is reraised inside the generator at the point where the yield
   occurred.  Thus, you can use a "try"..."except"..."finally"
   statement to trap the error (if any), or ensure that some cleanup
   takes place. If an exception is trapped merely in order to log it
   or to perform some action (rather than to suppress it entirely),
   the generator must reraise that exception. Otherwise the generator
   context manager will indicate to the "with" statement that the
   exception has been handled, and execution will resume with the
   statement immediately following the "with" statement.

   "@contextmanager" uses "ContextDecorator" so the context managers
   it creates can be used as decorators as well as in "with"
   statements. When used as a decorator, a new generator instance is
   implicitly created on each function call (this allows the otherwise
   "one-shot" context managers created by "@contextmanager" to meet
   the requirement that context managers support multiple invocations
   in order to be used as decorators).

   Cambiato nella versione 3.2: Use of "ContextDecorator".

@contextlib.asynccontextmanager

   Similar to "@~contextlib.contextmanager", but creates an
   asynchronous context manager.

   This function is a *decorator* that can be used to define a factory
   function for "async with" statement asynchronous context managers,
   without needing to create a class or separate "__aenter__()" and
   "__aexit__()" methods. It must be applied to an *asynchronous
   generator* function.

   A simple example:

      from contextlib import asynccontextmanager

      @asynccontextmanager
      async def get_connection():
          conn = await acquire_db_connection()
          try:
              yield conn
          finally:
              await release_db_connection(conn)

      async def get_all_users():
          async with get_connection() as conn:
              return conn.query('SELECT ...')

   Added in version 3.7.

   Context managers defined with "@asynccontextmanager" can be used
   either as decorators or with "async with" statements:

      import time
      from contextlib import asynccontextmanager

      @asynccontextmanager
      async def timeit():
          now = time.monotonic()
          try:
              yield
          finally:
              print(f'it took {time.monotonic() - now}s to run')

      @timeit()
      async def main():
          # ... async code ...

   When used as a decorator, a new generator instance is implicitly
   created on each function call. This allows the otherwise "one-shot"
   context managers created by "@asynccontextmanager" to meet the
   requirement that context managers support multiple invocations in
   order to be used as decorators.

   Cambiato nella versione 3.10: Async context managers created with
   "@asynccontextmanager" can be used as decorators.

contextlib.closing(thing)

   Return a context manager that closes *thing* upon completion of the
   block.  This is basically equivalent to:

      from contextlib import contextmanager

      @contextmanager
      def closing(thing):
          try:
              yield thing
          finally:
              thing.close()

   And lets you write code like this:

      from contextlib import closing
      from urllib.request import urlopen

      with closing(urlopen('https://www.python.org')) as page:
          for line in page:
              print(line)

   without needing to explicitly close "page".  Even if an error
   occurs, "page.close()" will be called when the "with" block is
   exited.

   Nota:

     Most types managing resources support the *context manager*
     protocol, which closes *thing* on leaving the "with" statement.
     As such, "closing()" is most useful for third party types that
     don't support context managers. This example is purely for
     illustration purposes, as "urlopen()" would normally be used in a
     context manager.

contextlib.aclosing(thing)

   Return an async context manager that calls the "aclose()" method of
   *thing* upon completion of the block.  This is basically equivalent
   to:

      from contextlib import asynccontextmanager

      @asynccontextmanager
      async def aclosing(thing):
          try:
              yield thing
          finally:
              await thing.aclose()

   Significantly, "aclosing()" supports deterministic cleanup of async
   generators when they happen to exit early by "break" or an
   exception.  For example:

      from contextlib import aclosing

      async with aclosing(my_generator()) as values:
          async for value in values:
              if value == 42:
                  break

   This pattern ensures that the generator's async exit code is
   executed in the same context as its iterations (so that exceptions
   and context variables work as expected, and the exit code isn't run
   after the lifetime of some task it depends on).

   Added in version 3.10.

contextlib.nullcontext(enter_result=None)

   Return a context manager that returns *enter_result* from
   "__enter__()", but otherwise does nothing. It is intended to be
   used as a stand-in for an optional context manager, for example:

      def myfunction(arg, ignore_exceptions=False):
          if ignore_exceptions:
              # Use suppress to ignore all exceptions.
              cm = contextlib.suppress(Exception)
          else:
              # Do not ignore any exceptions, cm has no effect.
              cm = contextlib.nullcontext()
          with cm:
              # Do something

   An example using *enter_result*:

      def process_file(file_or_path):
          if isinstance(file_or_path, str):
              # If string, open file
              cm = open(file_or_path)
          else:
              # Caller is responsible for closing file
              cm = nullcontext(file_or_path)

          with cm as file:
              # Perform processing on the file

   It can also be used as a stand-in for asynchronous context
   managers:

      async def send_http(session=None):
          if not session:
              # If no http session, create it with aiohttp
              cm = aiohttp.ClientSession()
          else:
              # Caller is responsible for closing the session
              cm = nullcontext(session)

          async with cm as session:
              # Send http requests with session

   Added in version 3.7.

   Cambiato nella versione 3.10: *asynchronous context manager*
   support was added.

contextlib.suppress(*exceptions)

   Return a context manager that suppresses any of the specified
   exceptions if they occur in the body of a "with" statement and then
   resumes execution with the first statement following the end of the
   "with" statement.

   As with any other mechanism that completely suppresses exceptions,
   this context manager should be used only to cover very specific
   errors where silently continuing with program execution is known to
   be the right thing to do.

   For example:

      from contextlib import suppress

      with suppress(FileNotFoundError):
          os.remove('somefile.tmp')

      with suppress(FileNotFoundError):
          os.remove('someotherfile.tmp')

   This code is equivalent to:

      try:
          os.remove('somefile.tmp')
      except FileNotFoundError:
          pass

      try:
          os.remove('someotherfile.tmp')
      except FileNotFoundError:
          pass

   This context manager is reentrant.

   If the code within the "with" block raises a "BaseExceptionGroup",
   suppressed exceptions are removed from the group.  Any exceptions
   of the group which are not suppressed are re-raised in a new group
   which is created using the original group's "derive()" method.

   Added in version 3.4.

   Cambiato nella versione 3.12: "suppress" now supports suppressing
   exceptions raised as part of a "BaseExceptionGroup".

contextlib.redirect_stdout(new_target)

   Context manager for temporarily redirecting "sys.stdout" to another
   *file object*.

   This tool adds flexibility to existing functions or classes whose
   output is hardwired to "sys.stdout".

   For example, the output of "help()" normally is sent to
   *sys.stdout*. You can capture that output in a string by
   redirecting the output to an "io.StringIO" object. The replacement
   stream is returned from the "__enter__()" method and so is
   available as the target of the "with" statement:

      with redirect_stdout(io.StringIO()) as f:
          help(pow)
      s = f.getvalue()

   To send the output of "help()" to a file on disk, redirect the
   output to a regular file:

      with open('help.txt', 'w') as f:
          with redirect_stdout(f):
              help(pow)

   To send the output of "help()" to *sys.stderr*:

      with redirect_stdout(sys.stderr):
          help(pow)

   Note that the global side effect on "sys.stdout" means that this
   context manager is not suitable for use in library code and most
   threaded applications. It also has no effect on the output of
   subprocesses. However, it is still a useful approach for many
   utility scripts.

   This context manager is reentrant.

   Added in version 3.4.

contextlib.redirect_stderr(new_target)

   Similar to "redirect_stdout()" but redirecting the global
   "sys.stderr" to another *file object*.

   This context manager is reentrant.

   Added in version 3.5.

contextlib.chdir(path)

   Non parallel-safe context manager to change the current working
   directory. As this changes a global state, the working directory,
   it is not suitable for use in most threaded or async contexts. It
   is also not suitable for most non-linear code execution, like
   generators, where the program execution is temporarily relinquished
   -- unless explicitly desired, you should not yield when this
   context manager is active.

   This is a simple wrapper around "chdir()", it changes the current
   working directory upon entering and restores the old one on exit.

   This context manager is reentrant.

   Added in version 3.11.

class contextlib.ContextDecorator

   A base class that enables a context manager to also be used as a
   decorator.

   Context managers inheriting from "ContextDecorator" have to
   implement "__enter__()" and "__exit__()" as normal. "__exit__"
   retains its optional exception handling even when used as a
   decorator.

   "ContextDecorator" is used by "@contextmanager", so you get this
   functionality automatically.

   Example of "ContextDecorator":

      from contextlib import ContextDecorator

      class mycontext(ContextDecorator):
          def __enter__(self):
              print('Starting')
              return self

          def __exit__(self, *exc):
              print('Finishing')
              return False

   The class can then be used like this:

      >>> @mycontext()
      ... def function():
      ...     print('The bit in the middle')
      ...
      >>> function()
      Starting
      The bit in the middle
      Finishing

      >>> with mycontext():
      ...     print('The bit in the middle')
      ...
      Starting
      The bit in the middle
      Finishing

   This change is just syntactic sugar for any construct of the
   following form:

      def f():
          with cm():
              # Do stuff

   "ContextDecorator" lets you instead write:

      @cm()
      def f():
          # Do stuff

   It makes it clear that the "cm" applies to the whole function,
   rather than just a piece of it (and saving an indentation level is
   nice, too).

   Existing context managers that already have a base class can be
   extended by using "ContextDecorator" as a mixin class:

      from contextlib import ContextDecorator

      class mycontext(ContextBaseClass, ContextDecorator):
          def __enter__(self):
              return self

          def __exit__(self, *exc):
              return False

   Nota:

     As the decorated function must be able to be called multiple
     times, the underlying context manager must support use in
     multiple "with" statements. If this is not the case, then the
     original construct with the explicit "with" statement inside the
     function should be used.

   When the decorated callable is a generator function, coroutine
   function, or asynchronous generator function, the returned wrapper
   is of the same kind and keeps the context manager open for the
   lifetime of the iteration or await rather than only for the call
   that creates the generator or coroutine object.  Wrapped generators
   and asynchronous generators are explicitly closed when iteration
   ends, as if by "closing()" or "aclosing()".

   Nota:

     For asynchronous generators the wrapper re-yields each value with
     "async for"; values sent with "asend()" and exceptions thrown
     with "athrow()" are not forwarded to the wrapped generator.

   Added in version 3.2.

   Cambiato nella versione 3.15: Decorating a generator function,
   coroutine function, or asynchronous generator function now keeps
   the context manager open across iteration or await.  Previously the
   context manager exited as soon as the generator or coroutine object
   was created.

class contextlib.AsyncContextDecorator

   Similar to "ContextDecorator", but the context manager is entered
   and exited with "async with".  Decorate coroutine functions and
   asynchronous generator functions with this class; the returned
   wrapper is of the same kind.

   Nota:

     Synchronous functions and generators are accepted, but the
     wrapper is always asynchronous, so the decorated callable must
     then be awaited or iterated with "async for".  If that change of
     calling convention is not intended, use "ContextDecorator"
     instead.

   Example of "AsyncContextDecorator":

      from asyncio import run
      from contextlib import AsyncContextDecorator

      class mycontext(AsyncContextDecorator):
          async def __aenter__(self):
              print('Starting')
              return self

          async def __aexit__(self, *exc):
              print('Finishing')
              return False

   The class can then be used like this:

      >>> @mycontext()
      ... async def function():
      ...     print('The bit in the middle')
      ...
      >>> run(function())
      Starting
      The bit in the middle
      Finishing

      >>> async def function():
      ...    async with mycontext():
      ...         print('The bit in the middle')
      ...
      >>> run(function())
      Starting
      The bit in the middle
      Finishing

   Added in version 3.10.

   Cambiato nella versione 3.15: Decorating an asynchronous generator
   function now keeps the context manager open across iteration.
   Previously the context manager exited as soon as the generator
   object was created.  Synchronous functions and synchronous
   generator functions are also now accepted, with an asynchronous
   wrapper returned.

class contextlib.ExitStack

   A context manager that is designed to make it easy to
   programmatically combine other context managers and cleanup
   functions, especially those that are optional or otherwise driven
   by input data.

   For example, a set of files may easily be handled in a single with
   statement as follows:

      with ExitStack() as stack:
          files = [stack.enter_context(open(fname)) for fname in filenames]
          # All opened files will automatically be closed at the end of
          # the with statement, even if attempts to open files later
          # in the list raise an exception

   The "__enter__()" method returns the "ExitStack" instance, and
   performs no additional operations.

   Each instance maintains a stack of registered callbacks that are
   called in reverse order when the instance is closed (either
   explicitly or implicitly at the end of a "with" statement). Note
   that callbacks are *not* invoked implicitly when the context stack
   instance is garbage collected.

   This stack model is used so that context managers that acquire
   their resources in their "__init__" method (such as file objects)
   can be handled correctly.

   Since registered callbacks are invoked in the reverse order of
   registration, this ends up behaving as if multiple nested "with"
   statements had been used with the registered set of callbacks. This
   even extends to exception handling - if an inner callback
   suppresses or replaces an exception, then outer callbacks will be
   passed arguments based on that updated state.

   This is a relatively low level API that takes care of the details
   of correctly unwinding the stack of exit callbacks. It provides a
   suitable foundation for higher level context managers that
   manipulate the exit stack in application specific ways.

   Added in version 3.3.

   enter_context(cm)

      Enters a new context manager and adds its "__exit__()" method to
      the callback stack. The return value is the result of the
      context manager's own "__enter__()" method.

      These context managers may suppress exceptions just as they
      normally would if used directly as part of a "with" statement.

      Cambiato nella versione 3.11: Raises "TypeError" instead of
      "AttributeError" if *cm* is not a context manager.

      Cambiato nella versione 3.15: Added support for arbitrary
      descriptors "__enter__()" and "__exit__()".

   push(exit)

      Adds a context manager's "__exit__()" method to the callback
      stack.

      As "__enter__" is *not* invoked, this method can be used to
      cover part of an "__enter__()" implementation with a context
      manager's own "__exit__()" method.

      If passed an object that is not a context manager, this method
      assumes it is a callback with the same signature as a context
      manager's "__exit__()" method and adds it directly to the
      callback stack.

      By returning true values, these callbacks can suppress
      exceptions the same way context manager "__exit__()" methods
      can.

      The passed in object is returned from the function, allowing
      this method to be used as a function decorator.

      Cambiato nella versione 3.15: Added support for arbitrary
      descriptors "__exit__()".

   callback(callback, /, *args, **kwds)

      Accepts an arbitrary callback function and arguments and adds it
      to the callback stack.

      Unlike the other methods, callbacks added this way cannot
      suppress exceptions (as they are never passed the exception
      details).

      The passed in callback is returned from the function, allowing
      this method to be used as a function decorator.

   pop_all()

      Transfers the callback stack to a fresh "ExitStack" instance and
      returns it. No callbacks are invoked by this operation -
      instead, they will now be invoked when the new stack is closed
      (either explicitly or implicitly at the end of a "with"
      statement).

      For example, a group of files can be opened as an "all or
      nothing" operation as follows:

         with ExitStack() as stack:
             files = [stack.enter_context(open(fname)) for fname in filenames]
             # Hold onto the close method, but don't call it yet.
             close_files = stack.pop_all().close
             # If opening any file fails, all previously opened files will be
             # closed automatically. If all files are opened successfully,
             # they will remain open even after the with statement ends.
             # close_files() can then be invoked explicitly to close them all.

   close()

      Immediately unwinds the callback stack, invoking callbacks in
      the reverse order of registration. For any context managers and
      exit callbacks registered, the arguments passed in will indicate
      that no exception occurred.

class contextlib.AsyncExitStack

   An asynchronous context manager, similar to "ExitStack", that
   supports combining both synchronous and asynchronous context
   managers, as well as having coroutines for cleanup logic.

   The "close()" method is not implemented; "aclose()" must be used
   instead.

   async enter_async_context(cm)

      Similar to "ExitStack.enter_context()" but expects an
      asynchronous context manager.

      Cambiato nella versione 3.11: Raises "TypeError" instead of
      "AttributeError" if *cm* is not an asynchronous context manager.

      Cambiato nella versione 3.15: Added support for arbitrary
      descriptors "__aenter__()" and "__aexit__()".

   push_async_exit(exit)

      Similar to "ExitStack.push()" but expects either an asynchronous
      context manager or a coroutine function.

      Cambiato nella versione 3.15: Added support for arbitrary
      descriptors "__aexit__()".

   push_async_callback(callback, /, *args, **kwds)

      Similar to "ExitStack.callback()" but expects a coroutine
      function.

   async aclose()

      Similar to "ExitStack.close()" but properly handles awaitables.

   Continuing the example for "@asynccontextmanager":

      async with AsyncExitStack() as stack:
          connections = [await stack.enter_async_context(get_connection())
              for i in range(5)]
          # All opened connections will automatically be released at the end of
          # the async with statement, even if attempts to open a connection
          # later in the list raise an exception.

   Added in version 3.7.


Examples and Recipes
====================

This section describes some examples and recipes for making effective
use of the tools provided by "contextlib".


Supporting a variable number of context managers
------------------------------------------------

The primary use case for "ExitStack" is the one given in the class
documentation: supporting a variable number of context managers and
other cleanup operations in a single "with" statement. The variability
may come from the number of context managers needed being driven by
user input (such as opening a user specified collection of files), or
from some of the context managers being optional:

   with ExitStack() as stack:
       for resource in resources:
           stack.enter_context(resource)
       if need_special_resource():
           special = acquire_special_resource()
           stack.callback(release_special_resource, special)
       # Perform operations that use the acquired resources

As shown, "ExitStack" also makes it quite easy to use "with"
statements to manage arbitrary resources that don't natively support
the context management protocol.


Catching exceptions from "__enter__" methods
--------------------------------------------

It is occasionally desirable to catch exceptions from an "__enter__()"
method implementation, *without* inadvertently catching exceptions
from the "with" statement body or the context manager's "__exit__()"
method. By using "ExitStack" the steps in the context management
protocol can be separated slightly in order to allow this:

   stack = ExitStack()
   try:
       x = stack.enter_context(cm)
   except Exception:
       # handle __enter__ exception
   else:
       with stack:
           # Handle normal case

Actually needing to do this is likely to indicate that the underlying
API should be providing a direct resource management interface for use
with "try"/"except"/"finally" statements, but not all APIs are well
designed in that regard. When a context manager is the only resource
management API provided, then "ExitStack" can make it easier to handle
various situations that can't be handled directly in a "with"
statement.


Cleaning up in an "__enter__" implementation
--------------------------------------------

As noted in the documentation of "ExitStack.push()", this method can
be useful in cleaning up an already allocated resource if later steps
in the "__enter__()" implementation fail.

Here's an example of doing this for a context manager that accepts
resource acquisition and release functions, along with an optional
validation function, and maps them to the context management protocol:

   from contextlib import contextmanager, AbstractContextManager, ExitStack

   class ResourceManager(AbstractContextManager):

       def __init__(self, acquire_resource, release_resource, check_resource_ok=None):
           self.acquire_resource = acquire_resource
           self.release_resource = release_resource
           if check_resource_ok is None:
               def check_resource_ok(resource):
                   return True
           self.check_resource_ok = check_resource_ok

       @contextmanager
       def _cleanup_on_error(self):
           with ExitStack() as stack:
               stack.push(self)
               yield
               # The validation check passed and didn't raise an exception
               # Accordingly, we want to keep the resource, and pass it
               # back to our caller
               stack.pop_all()

       def __enter__(self):
           resource = self.acquire_resource()
           with self._cleanup_on_error():
               if not self.check_resource_ok(resource):
                   msg = "Failed validation for {!r}"
                   raise RuntimeError(msg.format(resource))
           return resource

       def __exit__(self, *exc_details):
           # We don't need to duplicate any of our resource release logic
           self.release_resource()


Replacing any use of "try-finally" and flag variables
-----------------------------------------------------

A pattern you will sometimes see is a "try-finally" statement with a
flag variable to indicate whether or not the body of the "finally"
clause should be executed. In its simplest form (that can't already be
handled just by using an "except" clause instead), it looks something
like this:

   cleanup_needed = True
   try:
       result = perform_operation()
       if result:
           cleanup_needed = False
   finally:
       if cleanup_needed:
           cleanup_resources()

As with any "try" statement based code, this can cause problems for
development and review, because the setup code and the cleanup code
can end up being separated by arbitrarily long sections of code.

"ExitStack" makes it possible to instead register a callback for
execution at the end of a "with" statement, and then later decide to
skip executing that callback:

   from contextlib import ExitStack

   with ExitStack() as stack:
       stack.callback(cleanup_resources)
       result = perform_operation()
       if result:
           stack.pop_all()

This allows the intended cleanup behaviour to be made explicit up
front, rather than requiring a separate flag variable.

If a particular application uses this pattern a lot, it can be
simplified even further by means of a small helper class:

   from contextlib import ExitStack

   class Callback(ExitStack):
       def __init__(self, callback, /, *args, **kwds):
           super().__init__()
           self.callback(callback, *args, **kwds)

       def cancel(self):
           self.pop_all()

   with Callback(cleanup_resources) as cb:
       result = perform_operation()
       if result:
           cb.cancel()

If the resource cleanup isn't already neatly bundled into a standalone
function, then it is still possible to use the decorator form of
"ExitStack.callback()" to declare the resource cleanup in advance:

   from contextlib import ExitStack

   with ExitStack() as stack:
       @stack.callback
       def cleanup_resources():
           ...
       result = perform_operation()
       if result:
           stack.pop_all()

Due to the way the decorator protocol works, a callback function
declared this way cannot take any parameters. Instead, any resources
to be released must be accessed as closure variables.


Using a context manager as a function decorator
-----------------------------------------------

"ContextDecorator" makes it possible to use a context manager in both
an ordinary "with" statement and also as a function decorator.

For example, it is sometimes useful to wrap functions or groups of
statements with a logger that can track the time of entry and time of
exit.  Rather than writing both a function decorator and a context
manager for the task, inheriting from "ContextDecorator" provides both
capabilities in a single definition:

   from contextlib import ContextDecorator
   import logging

   logging.basicConfig(level=logging.INFO)

   class track_entry_and_exit(ContextDecorator):
       def __init__(self, name):
           self.name = name

       def __enter__(self):
           logging.info('Entering: %s', self.name)

       def __exit__(self, exc_type, exc, exc_tb):
           logging.info('Exiting: %s', self.name)

Instances of this class can be used as both a context manager:

   with track_entry_and_exit('widget loader'):
       print('Some time consuming activity goes here')
       load_widget()

And also as a function decorator:

   @track_entry_and_exit('widget loader')
   def activity():
       print('Some time consuming activity goes here')
       load_widget()

Note that there is one additional limitation when using context
managers as function decorators: there's no way to access the return
value of "__enter__()". If that value is needed, then it is still
necessary to use an explicit "with" statement.

Vedi anche:

  **PEP 343** - The "with" statement
     The specification, background, and examples for the Python "with"
     statement.


Single use, reusable and reentrant context managers
===================================================

Most context managers are written in a way that means they can only be
used effectively in a "with" statement once. These single use context
managers must be created afresh each time they're used - attempting to
use them a second time will trigger an exception or otherwise not work
correctly.

This common limitation means that it is generally advisable to create
context managers directly in the header of the "with" statement where
they are used (as shown in all of the usage examples above).

Files are an example of effectively single use context managers, since
the first "with" statement will close the file, preventing any further
IO operations using that file object.

Context managers created using "@contextmanager" are also single use
context managers, and will complain about the underlying generator
failing to yield if an attempt is made to use them a second time:

   >>> from contextlib import contextmanager
   >>> @contextmanager
   ... def singleuse():
   ...     print("Before")
   ...     yield
   ...     print("After")
   ...
   >>> cm = singleuse()
   >>> with cm:
   ...     pass
   ...
   Before
   After
   >>> with cm:
   ...     pass
   ...
   Traceback (most recent call last):
       ...
   RuntimeError: generator didn't yield


Reentrant context managers
--------------------------

More sophisticated context managers may be "reentrant". These context
managers can not only be used in multiple "with" statements, but may
also be used *inside* a "with" statement that is already using the
same context manager.

"threading.RLock" is an example of a reentrant context manager, as are
"suppress()", "redirect_stdout()", and "chdir()". Here's a very simple
example of reentrant use:

   >>> from contextlib import redirect_stdout
   >>> from io import StringIO
   >>> stream = StringIO()
   >>> write_to_stream = redirect_stdout(stream)
   >>> with write_to_stream:
   ...     print("This is written to the stream rather than stdout")
   ...     with write_to_stream:
   ...         print("This is also written to the stream")
   ...
   >>> print("This is written directly to stdout")
   This is written directly to stdout
   >>> print(stream.getvalue())
   This is written to the stream rather than stdout
   This is also written to the stream

Real world examples of reentrancy are more likely to involve multiple
functions calling each other and hence be far more complicated than
this example.

Note also that being reentrant is *not* the same thing as being thread
safe. "redirect_stdout()", for example, is definitely not thread safe,
as it makes a global modification to the system state by binding
"sys.stdout" to a different stream.


Reusable context managers
-------------------------

Distinct from both single use and reentrant context managers are
"reusable" context managers (or, to be completely explicit, "reusable,
but not reentrant" context managers, since reentrant context managers
are also reusable). These context managers support being used multiple
times, but will fail (or otherwise not work correctly) if the specific
context manager instance has already been used in a containing with
statement.

"threading.Lock" is an example of a reusable, but not reentrant,
context manager (for a reentrant lock, it is necessary to use
"threading.RLock" instead).

Another example of a reusable, but not reentrant, context manager is
"ExitStack", as it invokes *all* currently registered callbacks when
leaving any with statement, regardless of where those callbacks were
added:

   >>> from contextlib import ExitStack
   >>> stack = ExitStack()
   >>> with stack:
   ...     stack.callback(print, "Callback: from first context")
   ...     print("Leaving first context")
   ...
   Leaving first context
   Callback: from first context
   >>> with stack:
   ...     stack.callback(print, "Callback: from second context")
   ...     print("Leaving second context")
   ...
   Leaving second context
   Callback: from second context
   >>> with stack:
   ...     stack.callback(print, "Callback: from outer context")
   ...     with stack:
   ...         stack.callback(print, "Callback: from inner context")
   ...         print("Leaving inner context")
   ...     print("Leaving outer context")
   ...
   Leaving inner context
   Callback: from inner context
   Callback: from outer context
   Leaving outer context

As the output from the example shows, reusing a single stack object
across multiple with statements works correctly, but attempting to
nest them will cause the stack to be cleared at the end of the
innermost with statement, which is unlikely to be desirable behaviour.

Using separate "ExitStack" instances instead of reusing a single
instance avoids that problem:

   >>> from contextlib import ExitStack
   >>> with ExitStack() as outer_stack:
   ...     outer_stack.callback(print, "Callback: from outer context")
   ...     with ExitStack() as inner_stack:
   ...         inner_stack.callback(print, "Callback: from inner context")
   ...         print("Leaving inner context")
   ...     print("Leaving outer context")
   ...
   Leaving inner context
   Callback: from inner context
   Leaving outer context
   Callback: from outer context
