Python's with statement supports the concept of a runtime context defined by a context manager. This is implemented using two separate methods that allow user-defined classes to define a runtime context that is entered before the statement body is executed and exited when the statement ends.
The context management protocol consists of a pair of methods that need to be provided for a context manager object to define a runtime context:
) |
An example of a context manager that returns itself is a file object. File objects return themselves from __enter__() to allow open() to be used as the context expression in a with statement.
An example of a context manager that returns a related
object is the one returned by decimal.Context.get_manager()
.
These managers set the active decimal context to a copy of the
original decimal context and then return the copy. This allows
changes to be made to the current decimal context in the body of
the with statement without affecting code outside
the with statement.
exc_type, exc_val, exc_tb) |
Returning a true value from this method will cause the with statement to suppress the exception and continue execution with the statement immediately following the with statement. Otherwise the exception continues propagating after this method has finished executing. Exceptions that occur during execution of this method will replace any exception that occurred in the body of the with statement.
The exception passed in should never be reraised explicitly - instead,
this method should return a false value to indicate that the method
completed successfully and does not want to suppress the raised
exception. This allows context management code (such as
contextlib.nested
) to easily detect whether or not an
__exit__() method has actually failed.
Python defines several context managers to support easy thread synchronisation, prompt closure of files or other objects, and simpler manipulation of the active decimal arithmetic context. The specific types are not treated specially beyond their implementation of the context management protocol.
Python's generators and the contextlib.contextfactory
decorator
provide a convenient way to implement these protocols. If a generator
function is decorated with the contextlib.contextfactory
decorator, it will return a context manager implementing the necessary
__enter__() and __exit__() methods, rather than the
iterator produced by an undecorated generator function.
Note that there is no specific slot for any of these methods in the type structure for Python objects in the Python/C API. Extension types wanting to define these methods must provide them as a normal Python accessible method. Compared to the overhead of setting up the runtime context, the overhead of a single class dictionary lookup is negligible.
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