contextlib2 — Updated utilities for context management

This module provides backports of features in the latest version of the standard library’s contextlib module to earlier Python versions. It also serves as a real world proving ground for potential future enhancements to that module.

Like contextlib, this module provides utilities for common tasks involving the with and async with statements.

Additions Relative to the Standard Library

This module is primarily a backport of the Python 3.10 version of contextlib to earlier releases. The async context management features require asynchronous generator support in the language runtime, so the oldest supported version is now Python 3.6 (contextlib2 0.6.0 and earlier support older Python versions by omitting all asynchronous features).

This module is also a proving ground for new features not yet part of the standard library. There are currently no such features in the module.

Finally, this module contains some deprecated APIs which never graduated to standard library inclusion. These interfaces are no longer documented, but may still be present in the code (emitting DeprecationWarning if used).

Using the Module

API Reference

Functions and classes provided:

class 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.

New in version 0.6.0: Part of the standard library in Python 3.6 and later

class 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.

New in version 21.6.0: Part of the standard library in Python 3.7 and later

@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)

>>> 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 tryexceptfinally 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).

@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 ...')

New in version 21.6.0: Part of the standard library in Python 3.7 and later, enhanced in Python 3.10 and later to allow created async context managers to be used as async function decorators.

Context managers defined with asynccontextmanager() can be used either as decorators or with async with statements:

import time

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.

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('http://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.

class 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).

New in version 21.6.0: Part of the standard library in Python 3.10 and later

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

New in version 0.6.0: Part of the standard library in Python 3.7 and later

Changed in version 21.6.0: Updated to Python 3.10 version with asynchronous context manager support

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.

New in version 0.5: Part of the standard library in Python 3.4 and later

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.

New in version 0.5: Part of the standard library in Python 3.4 and later

redirect_stderr(new_target)

Similar to redirect_stdout() but redirecting sys.stderr to another file or file-like object.

This context manager is reentrant.

New in version 0.5: Part of the standard library in Python 3.5 and later

class 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

>>> @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.

class 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

>>> @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

New in version 21.6.0: Part of the standard library in Python 3.10 and later

class 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

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.

New in version 0.4: Part of the standard library in Python 3.3 and later

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.

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 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.

enter_async_context(cm)

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

push_async_exit(exit)

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

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

Similar to callback() but expects a coroutine function.

aclose()

Similar to 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.

New in version 21.6.0: Part of the standard library in Python 3.7 and later

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 up 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() and redirect_stdout(). 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

Obtaining the Module

This module can be installed directly from the Python Package Index with pip:

pip install contextlib2

Alternatively, you can download and unpack it manually from the contextlib2 PyPI page.

There are no operating system or distribution specific versions of this module - it is a pure Python module that should work on all platforms.

Supported Python versions are currently 3.6+.

Development and Support

contextlib2 is developed and maintained on GitHub. Problems and suggested improvements can be posted to the issue tracker.

Release History

21.6.0 (2021-06-27)

  • License update: due to the inclusion of type hints from the typeshed project, the contextlib2 project is now under a combination of the Python Software License (existing license) and the Apache License 2.0 (typeshed license)
  • Switched to calendar based versioning using a “year”-“month”-“serial” scheme, rather than continuing with pre-1.0 semantic versioning
  • Due to the inclusion of asynchronous features from Python 3.7+, the minimum supported Python version is now Python 3.6 (#29)
  • Synchronised with the Python 3.10 version of contextlib (#12), making the following new features available on Python 3.6+:
    • asyncontextmanager (added in Python 3.7, enhanced in Python 3.10)
    • aclosing (added in Python 3.10)
    • AbstractAsyncContextManager (added in Python 3.7)
    • AsyncContextDecorator (added in Python 3.10)
    • AsyncExitStack (added in Python 3.7)
    • async support in nullcontext (Python 3.10)
  • contextlib2 now includes an adapted copy of the contextlib type hints from typeshed (the adaptation removes the Python version dependencies from the API definition) (#33)
  • to incorporate the type hints stub file and the py.typed marker file, contextlib2 is now installed as a package rather than as a module
  • Updates to the default compatibility testing matrix:
    • Added: CPython 3.9, CPython 3.10
    • Dropped: CPython 2.7, CPython 3.5, PyPy2

0.6.0.post1 (2019-10-10)

  • Issue #24: Correctly update NEWS.rst for the 0.6.0 release.

0.6.0 (2019-09-21)

  • Issue #16: Backport AbstractContextManager from Python 3.6 and nullcontext from Python 3.7 (patch by John Vandenberg)

0.5.5 (2017-04-25)

  • Issue #13: setup.py now falls back to plain distutils if setuptools is not available (patch by Allan Harwood)
  • Updates to the default compatibility testing matrix:
    • Added: PyPy3, CPython 3.6 (maintenance), CPython 3.7 (development)
    • Dropped: CPython 3.3

0.5.4 (2016-07-31)

  • Thanks to the welcome efforts of Jannis Leidel, contextlib2 is now a [Jazzband](https://jazzband.co/) project! This means that I (Nick Coghlan) am no longer a single point of failure for backports of future contextlib updates to earlier Python versions.
  • Issue #7: Backported fix for CPython issue #27122, preventing a potential infinite loop on Python 3.5 when handling RuntimeError (CPython updates by Gregory P. Smith & Serhiy Storchaka)

0.5.3 (2016-05-02)

  • ExitStack now correctly handles context managers implemented as old-style classes in Python 2.x (such as codecs.StreamReader and codecs.StreamWriter)
  • setup.py has been migrated to setuptools and configured to emit a universal wheel file by default

0.5.2 (2016-05-02)

  • development migrated from BitBucket to GitHub
  • redirect_stream, redirect_stdout, redirect_stderr and suppress now explicitly inherit from object, ensuring compatibility with ExitStack when run under Python 2.x (patch contributed by Devin Jeanpierre).
  • MANIFEST.in is now included in the published sdist, ensuring the archive can be precisely recreated even without access to the original source repo (patch contributed by Guy Rozendorn)

0.5.1 (2016-01-13)

  • Python 2.6 compatilibity restored (patch contributed by Armin Ronacher)
  • README converted back to reStructured Text formatting

0.5.0 (2016-01-12)

  • Updated to include all features from the Python 3.4 and 3.5 releases of contextlib (also includes some ExitStack enhancements made following the integration into the standard library for Python 3.3)
  • The legacy ContextStack and ContextDecorator.refresh_cm APIs are no longer documented and emit DeprecationWarning when used
  • Python 2.6, 3.2 and 3.3 have been dropped from compatibility testing
  • tox is now supported for local version compatibility testing (patch by Marc Abramowitz)

0.4.0 (2012-05-05)

  • (BitBucket) Issue #8: Replace ContextStack with ExitStack (old ContextStack API retained for backwards compatibility)
  • Fall back to unittest2 if unittest is missing required functionality

0.3.1 (2012-01-17)

  • (BitBucket) Issue #7: Add MANIFEST.in so PyPI package contains all relevant files (patch contributed by Doug Latornell)

0.3 (2012-01-04)

  • (BitBucket) Issue #5: ContextStack.register no longer pointlessly returns the wrapped function
  • (BitBucket) Issue #2: Add examples and recipes section to docs
  • (BitBucket) Issue #3: ContextStack.register_exit() now accepts objects with __exit__ attributes in addition to accepting exit callbacks directly
  • (BitBucket) Issue #1: Add ContextStack.preserve() to move all registered callbacks to a new ContextStack object
  • Wrapped callbacks now expose __wrapped__ (for direct callbacks) or __self__ (for context manager methods) attributes to aid in introspection
  • Moved version number to a VERSION.txt file (read by both docs and setup.py)
  • Added NEWS.rst (and incorporated into documentation)

0.2 (2011-12-15)

  • Renamed CleanupManager to ContextStack (hopefully before anyone started using the module for anything, since I didn’t alias the old name at all)

0.1 (2011-12-13)

Indices and tables