# `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 Context Manager Types and With Statement Context Managers.

## Utilities

Functions and classes provided:

class contextlib.AbstractContextManager

  An abstract base class for classes that implement `object.__enter__()` and `object.__exit__()`. A default implementation for `object.__enter__()` is provided which returns `self` while `object.__exit__()` is an abstract method which by default returns `None`. See also the definition of Context Manager Types.

  Added in version 3.6.

class contextlib.AbstractAsyncContextManager

  An abstract base class for classes that implement `object.__aenter__()` and `object.__aexit__()`. A default implementation for `object.__aenter__()` is provided which returns `self` while `object.__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).

  Changed in version 3.2: Use of `ContextDecorator`.

@contextlib.asynccontextmanager

  Similar to `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.

  Changed in version 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.

  Note

  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.

  Changed in version 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.

  Changed in version 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 or file-like object.

  This tool adds flexibility to existing functions or classes whose output is hardwired to 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 `sys.stderr` to another file or file-like 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

  Note

  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.

  Added in version 3.2.

class contextlib.AsyncContextDecorator

  Similar to `ContextDecorator` but only for asynchronous functions.

  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.

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.

    Changed in version 3.11: Raises `TypeError` instead of `AttributeError` if cm is not a context manager.

  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.

  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.

  coroutine enter_async_context(cm)

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

    Changed in version 3.11: Raises `TypeError` instead of `AttributeError` if cm is not an asynchronous context manager.

  push_async_exit(exit)

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

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

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

  coroutine 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.

See also

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