Understanding Python's "with" statement

转帖自：http://effbot.org/zone/python-with-statement.htm

Judging from comp.lang.python and other forums, Python 2.5’s new with statementseems to be a bit confusing even for experienced Python programmers.

As most other things in Python, the with statement is actually very simple, once you understand the problem it’s trying to solve. Consider this piece of code:

    set things up
    try:
        do something
    finally:
        tear things down

Here, “set things up” could be opening a file, or acquiring some sort of external resource, and “tear things down” would then be closing the file, or releasing or removing the resource. The try-finally construct guarantees that the “tear things down” part is always executed, even if the code that does the work doesn’t finish.

If you do this a lot, it would be quite convenient if you could put the “set things up” and “tear things down” code in a library function, to make it easy to reuse. You can of course do something like

    def controlled_execution(callback):
        set things up
        try:
            callback(thing)
        finally:
            tear things down

    def my_function(thing):
        do something

    controlled_execution(my_function)

But that’s a bit verbose, especially if you need to modify local variables. Another approach is to use a one-shot generator, and use the for-in statement to “wrap” the code:

    def controlled_execution():
        set things up
        try:
            yield thing
        finally:
            tear things down

    for thing in controlled_execution():
        do something with thing

But yield isn’t even allowed inside a try-finally in 2.4 and earlier. And while that could be fixed (and it has been fixed in 2.5), it’s still a bit weird to use a loop construct when you know that you only want to execute something once.

So after contemplating a number of alternatives, GvR and the python-dev team finally came up with a generalization of the latter, using an object instead of a generator to control the behaviour of an external piece of code:

    class controlled_execution:
        def __enter__(self):
            set things up
            return thing
        def __exit__(self, type, value, traceback):
            tear things down

    with controlled_execution() as thing:
         some code

Now, when the “with” statement is executed, Python evaluates the expression, calls the__enter__ method on the resulting value (which is called a “context guard”), and assigns whatever __enter__ returns to the variable given by as. Python will then execute the code body, and no matter what happens in that code, call the guard object’s__exit__ method.

As an extra bonus, the __exit__ method can look at the exception, if any, and suppress it or act on it as necessary. To suppress the exception, just return a true value. For example, the following __exit__ method swallows any TypeError, but lets all other exceptions through:

    def __exit__(self, type, value, traceback):
        return isinstance(value, TypeError)

In Python 2.5, the file object has been equipped with __enter__ and __exit__ methods; the former simply returns the file object itself, and the latter closes the file:

    >>> f = open("x.txt")
    >>> f
    <open file 'x.txt', mode 'r' at 0x00AE82F0>
    >>> f.__enter__()
    <open file 'x.txt', mode 'r' at 0x00AE82F0>
    >>> f.read(1)
    'X'
    >>> f.__exit__(None, None, None)
    >>> f.read(1)
    Traceback (most recent call last):
      File "<stdin>", line 1, in <module>
    ValueError: I/O operation on closed file

so to open a file, process its contents, and make sure to close it, you can simply do:

with open("x.txt") as f:
    data = f.read()
    do something with data

This wasn’t very difficult, was it?