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__()
andobject.__exit__()
. A default implementation forobject.__enter__()
is provided which returnsself
whileobject.__exit__()
is an abstract method which by default returnsNone
. See also the definition of Context Manager Types.New in version 3.6.
-
class
contextlib.
AbstractAsyncContextManager
¶ An abstract base class for classes that implement
object.__aenter__()
andobject.__aexit__()
. A default implementation forobject.__aenter__()
is provided which returnsself
whileobject.__aexit__()
is an abstract method which by default returnsNone
. See also the definition of Asynchronous Context Managers.New 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 withcontextlib.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’sas
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 atry
…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 thewith
statement that the exception has been handled, and execution will resume with the statement immediately following thewith
statement.contextmanager()
usesContextDecorator
so the context managers it creates can be used as decorators as well as inwith
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 bycontextmanager()
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 ...')
New in version 3.7.
Context managers defined with
asynccontextmanager()
can be used either as decorators or withasync 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://python.domainunion.de')) 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 thewith
block is exited.
-
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 bybreak
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 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
New 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 thewith
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 3.4.
-
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 anio.StringIO
object. The replacement stream is returned from the__enter__
method and so is available as the target of thewith
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 3.4.
-
contextlib.
redirect_stderr
(new_target)¶ Similar to
redirect_stdout()
but redirectingsys.stderr
to another file or file-like object.This context manager is reentrant.
New in version 3.5.
-
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 bycontextmanager()
, 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 explicitwith
statement inside the function should be used.New 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
New 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 theExitStack
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.
New 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.
-
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 awith
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
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.
-
coroutine
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 3.7.
-
coroutine
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.
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