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
statement.
Additions Relative to the Standard Library¶
This module is primarily a backport of the Python 3.5 version of
contextlib
to earlier releases. However, it is also a proving ground
for new features not yet part of the standard library.
There are currently no such features in the module.
Refer to the contextlib
documentation for details of which
versions of Python 3 introduce the various APIs provided in this module.
API Reference¶
Functions and classes provided:
-
@
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.A simple example (this is not recommended as a real way of generating HTML!):
from contextlib import contextmanager @contextmanager def tag(name): print("<%s>" % name) yield print("</%s>" % name) >>> with tag("h1"): ... print("foo") ... <h1> foo </h1>
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).
-
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 thewith
block is exited.
-
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 aio.StringIO
object:f = io.StringIO() with redirect_stdout(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 redirectingsys.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 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 >>> @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
-
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 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.
-
Examples and Recipes¶
This section describes some examples and recipes for making effective use of
the tools provided by contextlib2
. Some of them may also work with
contextlib
in sufficiently recent versions of Python. When this is the
case, it is noted at the end of the example.
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 contextlib2 import ExitStack
class ResourceManager(object):
def __init__(self, acquire_resource, release_resource, check_resource_ok=None):
self.acquire_resource = acquire_resource
self.release_resource = release_resource
self.check_resource_ok = check_resource_ok
def __enter__(self):
resource = self.acquire_resource()
if self.check_resource_ok is not None:
with ExitStack() as stack:
stack.push(self)
if not self.check_resource_ok(resource):
msg = "Failed validation for {!r}"
raise RuntimeError(msg.format(resource))
# 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()
return resource
def __exit__(self, *exc_details):
# We don't need to duplicate any of our resource release logic
self.release_resource()
This example will also work with contextlib
in Python 3.3 or later.
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 contextlib2 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 you find yourself using this pattern a lot, it can be simplified even further by means of a small helper class:
from contextlib2 import ExitStack
class Callback(ExitStack):
def __init__(self, callback, *args, **kwds):
super(Callback, self).__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 contextlib2 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.
This example will also work with contextlib
in Python 3.3 or later.
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. The
ContextDecorator.refresh_cm()
method even makes it possible to use
otherwise single use context managers (such as those created by
contextmanager()
) that way.
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,
contextmanager()
provides both capabilities in a single
definition:
from contextlib2 import contextmanager
import logging
logging.basicConfig(level=logging.INFO)
@contextmanager
def track_entry_and_exit(name):
logging.info('Entering: {}'.format(name))
yield
logging.info('Exiting: {}'.format(name))
This 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.
This example will also work with contextlib
in Python 3.2.1 or later.
Context Management Concepts¶
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 is
suppress()
. Here’s a toy example of reentrant use (real world
examples of reentrancy are more likely to occur with objects like recursive
locks and are likely to be far more complicated than this example):
>>> from contextlib import suppress
>>> ignore_raised_exception = suppress(ZeroDivisionError)
>>> with ignore_raised_exception:
... with ignore_raised_exception:
... 1/0
... print("This line runs")
... 1/0
... print("This is skipped")
...
This line runs
>>> # The second exception is also suppressed
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.
An example of a reusable context manager is redirect_stdout()
:
>>> from contextlib import redirect_stdout
>>> from io import StringIO
>>> f = StringIO()
>>> collect_output = redirect_stdout(f)
>>> with collect_output:
... print("Collected")
...
>>> print("Not collected")
Not collected
>>> with collect_output:
... print("Also collected")
...
>>> print(f.getvalue())
Collected
Also collected
However, this context manager is not reentrant, so attempting to reuse it within a containing with statement fails:
>>> with collect_output:
... # Nested reuse is not permitted
... with collect_output:
... pass
...
Traceback (most recent call last):
...
RuntimeError: Cannot reenter <...>
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 2.7 and 3.2+.
Development and Support¶
contextlib2 is developed and maintained on GitHub. Problems and suggested improvements can be posted to the issue tracker.
Release History¶
0.5.2 (not yet released)¶
- development migrated from BitBucket to GitHub
redirect_stream
,redirect_stdout
,redirect_stderr
andsuppress
now explicitly inherit fromobject
, ensuring compatibility withExitStack
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 (although 2.6 is still missing from the current CI configuration) (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
andContextDecorator.refresh_cm
APIs are no longer documented and emitDeprecationWarning
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)¶
- 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)¶
- Issue #7: Add MANIFEST.in so PyPI package contains all relevant files (patch contributed by Doug Latornell)
0.3 (2012-01-04)¶
- Issue #5: ContextStack.register no longer pointlessly returns the wrapped function
- Issue #2: Add examples and recipes section to docs
- Issue #3: ContextStack.register_exit() now accepts objects with __exit__ attributes in addition to accepting exit callbacks directly
- 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)¶
- Initial release as a backport module
- Added CleanupManager (based on a Python feature request)
- Added ContextDecorator.refresh_cm() (based on a Python tracker issue)