29.6. contextlib — Utilities for with-statement contexts

源代码 Lib/contextlib.py

---

此模块为涉及 with 语句的常见任务提供了实用的程序。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。

29.6.1. 工具

提供的函数和类：

@contextlib.contextmanager

这个函数是一个 decorator ，它可以定义一个支持 with 语句上下文的工厂函数， 而不需要创建一个类或区 __enter__() 与 __exit__() 方法。

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’s as clause, if any.

At the point where the generator yields, the block nested in the with statement is executed. The generator is then resumed after the block is exited. If an unhandled exception occurs in the block, it is reraised inside the generator at the point where the yield occurred. Thus, you can use a try…except…finally statement to trap the error (if any), or ensure that some cleanup takes place. If an exception is trapped merely in order to log it or to perform some action (rather than to suppress it entirely), the generator must reraise that exception. Otherwise the generator context manager will indicate to the with statement that the exception has been handled, and execution will resume with the statement immediately following the with statement.

contextmanager() 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）。

3.2 版更變: ContextDecorator 的使用。

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('http://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。

contextlib.suppress(*exceptions)

返回一个上下文管理器，如果任何一个指定的异常发生在使用该上下文管理器的 with 语句中，该异常将被它抑制，然后程序将从 with 语句结束后的第一个语句开始恢复执行。

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 版新加入.

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。

例如， help() 通常把输出写到 sys.stdout 。你可以通过重定向到一个 io.StringIO 来捕获该输出到一个字符串中。

f = io.StringIO()
with redirect_stdout(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 版新加入.

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 版新加入.

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

備註

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.

3.2 版新加入.

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 版新加入.

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.

29.6.2. 例子和配方

This section describes some examples and recipes for making effective use of the tools provided by contextlib.

29.6.2.1. 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.

29.6.2.2. Simplifying support for single optional context managers

In the specific case of a single optional context manager, ExitStack instances can be used as a 「do nothing」 context manager, allowing a context manager to easily be omitted without affecting the overall structure of the source code:

def debug_trace(details):
    if __debug__:
        return TraceContext(details)
    # Don't do anything special with the context in release mode
    return ExitStack()

with debug_trace():
    # Suite is traced in debug mode, but runs normally otherwise

29.6.2.3. 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.

29.6.2.4. 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, ExitStack

class ResourceManager:

    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()

29.6.2.5. 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(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 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.

29.6.2.6. 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: {}'.format(self.name))

    def __exit__(self, exc_type, exc, exc_tb):
        logging.info('Exiting: {}'.format(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.

也參考

PEP 343 - 「with」 语句

Python with 语句的规范描述、背景和示例。

29.6.3. 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

29.6.3.1. 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.

29.6.3.2. 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