contextlib
--- 为 with
语句上下文提供的工具¶
此模块为涉及 with
语句的常见任务提供了实用的工具。更多信息请参见 上下文管理器类型 和 with 语句上下文管理器。
工具¶
提供的函数和类:
-
class
contextlib.
AbstractContextManager
¶ 一个为实现了
object.__enter__()
与object.__exit__()
的类提供的 abstract base class。为object.__enter__()
提供的一个默认实现是返回self
而object.__exit__()
是一个默认返回None
的抽象方法。 参见 上下文管理器类型 的定义。3.6 新版功能.
-
class
contextlib.
AbstractAsyncContextManager
¶ 一个为实现了
object.__aenter__()
与object.__aexit__()
的类提供的 abstract base class。 为object.__aenter__()
提供的一个默认实现是返回self
而object.__aexit__()
是一个默认返回None
的抽象方法。 参见 异步上下文管理器 的定义。3.7 新版功能.
-
@
contextlib.
contextmanager
¶ 这个函数是一个 decorator ,它可以定义一个支持
with
语句上下文管理器的工厂函数, 而不需要创建一个类或区__enter__()
与__exit__()
方法。尽管许多对象原生支持使用 with 语句,但有些需要被管理的资源并不是上下文管理器,并且没有实现
close()
方法而不能使用contextlib.closing
。下面是一个抽象的示例,展示如何确保正确的资源管理:
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
被装饰的函数在被调用时,必须返回一个 generator 迭代器。 这个迭代器必须只 yield 一个值出来,这个值会被用在
with
语句中,绑定到as
后面的变量,如果给定了的话。当生成器发生 yield 时,嵌套在
with
语句中的语句体会被执行。 语句体执行完毕离开之后,该生成器将被恢复执行。 如果在该语句体中发生了未处理的异常,则该异常会在生成器发生 yield 时重新被引发。 因此,你可以使用try
...except
...finally
语句来捕获该异常(如果有的话),或确保进行了一些清理。 如果仅出于记录日志或执行某些操作(而非完全抑制异常)的目的捕获了异常,生成器必须重新引发该异常。 否则生成器的上下文管理器将向with
语句指示该异常已经被处理,程序将立即在with
语句之后恢复并继续执行。contextmanager()
使用ContextDecorator
因此它创建的上下文管理器不仅可以用在with
语句中,还可以用作一个装饰器。当它用作一个装饰器时,每一次函数调用时都会隐式创建一个新的生成器实例(这使得contextmanager()
创建的上下文管理器满足了支持多次调用以用作装饰器的需求,而非“一次性”的上下文管理器)。在 3.2 版更改:
ContextDecorator
的使用。
-
@
contextlib.
asynccontextmanager
¶ 与
contextmanager()
类似,但创建的是 asynchronous context manager 。这个函数是一个 decorator ,它可以定义一个支持
async with
语句的异步上下文管理器的工厂函数, 而不需要创建一个类或区分__aenter__()
与__aexit__()
方法。它必须被作用在一个 asynchronous generator 函数上一个简单的示例:
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 ...')
3.7 新版功能.
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.在 3.10 版更改: Async context managers created with
asynccontextmanager()
can be used as decorators.
-
contextlib.
closing
(thing)¶ 返回一个在语句块执行完成时关闭 things 的上下文管理器。这基本上等价于:
from contextlib import contextmanager @contextmanager def closing(thing): try: yield thing finally: thing.close()
并允许你编写这样的代码:
from contextlib import closing from urllib.request import urlopen with closing(urlopen('https://www.python.org')) as page: for line in page: print(line)
而无需显式地关闭
page
。 即使发生错误,在退出with
语句块时,page.close()
也同样会被调用。
-
class
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).
3.10 新版功能.
-
contextlib.
nullcontext
(enter_result=None)¶ 返回一个从
__enter__
返回 enter_result 的上下文管理器,除此之外不执行任何操作。它旨在用于可选上下文管理器的一种替代,例如: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
一个使用 enter_result 的例子:
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
3.7 新版功能.
在 3.10 版更改: 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.与完全抑制异常的任何其他机制一样,该上下文管理器应当只用来抑制非常具体的错误,并确保该场景下静默地继续执行程序是通用的正确做法。
例如:
from contextlib import suppress with suppress(FileNotFoundError): os.remove('somefile.tmp') with suppress(FileNotFoundError): os.remove('someotherfile.tmp')
这段代码等价于:
try: os.remove('somefile.tmp') except FileNotFoundError: pass try: os.remove('someotherfile.tmp') except FileNotFoundError: pass
该上下文管理器是 reentrant 。
3.4 新版功能.
-
contextlib.
redirect_stdout
(new_target)¶ 用于将
sys.stdout
临时重定向到一个文件或类文件对象的上下文管理器。该工具给已有的将输出硬编码写到 stdout 的函数或类提供了额外的灵活性。
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()
如果要把
help()
的输出写到磁盘上的一个文件,重定向该输出到一个常规文件:with open('help.txt', 'w') as f: with redirect_stdout(f): help(pow)
如果要把
help()
的输出写到 sys.stderr :with redirect_stdout(sys.stderr): help(pow)
需要注意的点在于,
sys.stdout
的全局副作用意味着此上下文管理器不适合在库代码和大多数多线程应用程序中使用。它对子进程的输出没有影响。不过对于许多工具脚本而言,它仍然是一个有用的方法。该上下文管理器是 reentrant 。
3.4 新版功能.
-
contextlib.
redirect_stderr
(new_target)¶ 与
redirect_stdout()
类似,不过是将sys.stderr
重定向到一个文件或类文件对象。该上下文管理器是 reentrant 。
3.5 新版功能.
-
class
contextlib.
ContextDecorator
¶ 一个使上下文管理器能用作装饰器的基类。
与往常一样,继承自
ContextDecorator
的上下文管理器必须实现__enter__
与__exit__
。即使用作装饰器,__exit__
依旧会保持可能的异常处理。ContextDecorator
被用在contextmanager()
中,因此你自然获得了这项功能。ContextDecorator
的示例: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
这个改动只是针对如下形式的一个语法糖:
def f(): with cm(): # Do stuff
ContextDecorator
使得你可以这样改写:@cm() def f(): # Do stuff
这能清楚地表明,
cm
作用于整个函数,而不仅仅是函数的一部分(同时也能保持不错的缩进层级)。现有的上下文管理器即使已经有基类,也可以使用
ContextDecorator
作为混合类进行扩展:from contextlib import ContextDecorator class mycontext(ContextBaseClass, ContextDecorator): def __enter__(self): return self def __exit__(self, *exc): return False
注解
由于被装饰的函数必须能够被多次调用,因此对应的上下文管理器必须支持在多个
with
语句中使用。如果不是这样,则应当使用原来的具有显式with
语句的形式使用该上下文管理器。3.2 新版功能.
-
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 >>> @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
3.10 新版功能.
-
class
contextlib.
ExitStack
¶ 该上下文管理器的设计目标是使得在编码中组合其他上下文管理器和清理函数更加容易,尤其是那些可选的或由输入数据驱动的上下文管理器。
例如,通过一个如下的 with 语句可以很容易处理一组文件:
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
每个实例维护一个注册了一组回调的栈,这些回调在实例关闭时以相反的顺序被调用(显式或隐式地在
with
语句的末尾)。请注意,当一个栈实例被垃圾回收时,这些回调将 不会 被隐式调用。通过使用这个基于栈的模型,那些通过
__init__
方法获取资源的上下文管理器(如文件对象)能够被正确处理。由于注册的回调函数是按照与注册相反的顺序调用的,因此最终的行为就像多个嵌套的
with
语句用在这些注册的回调函数上。这个行为甚至扩展到了异常处理:如果内部的回调函数抑制或替换了异常,则外部回调收到的参数是基于该更新后的状态得到的。这是一个相对底层的 API,它负责正确处理栈里回调退出时依次展开的细节。它为相对高层的上下文管理器提供了一个合适的基础,使得它能根据应用程序的需求使用特定方式操作栈。
3.3 新版功能.
-
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.
3.7 新版功能.
-
coroutine
例子和配方¶
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