import contextlib import time @contextlib.contextmanager def time_print(task_name): t = time.time() try: yield finally: print task_name, "took", time.time() - t, "seconds." def doproc(): x=1+1 with time_print("processes"): [doproc() for _ in range(500)] # processes took 15.236166954 seconds.
when does doproc get executed when using this decorator?
Context managers allow you to allocate and release resources precisely when you want to. The most widely used example of context managers is the with statement. Suppose you have two related operations which you'd like to execute as a pair, with a block of code in between.
What Is Yield In Python? The Yield keyword in Python is similar to a return statement used for returning values or objects in Python. However, there is a slight difference. The yield statement returns a generator object to the one who calls the function which contains yield, instead of simply returning a value.
The main difference between them is: In python the return statement stops the execution of the function. Whereas, the yield statement only pauses the execution of the function.
A context manager usually takes care of setting up some resource, e.g. opening a connection, and automatically handles the clean up when we are done with it. Probably, the most common use case is opening a file. The code above will open the file and will keep it open until we are out of the with statement.
yield
expression returns control to the whatever is using the generator. The generator pauses at this point, which means that the @contextmanager
decorator knows that the code is done with the setup part.
In other words, everything you want to do in the context manager __enter__
phase has to take place before the yield
.
Once your context exits (so the block under the with
statement is done), the @contextmanager
decorator is called for the __exit__
part of the context manager protocol and will do one of two things:
If there was no exception, it'll resume your generator. So your generator unpauses at the yield
line, and you enter the cleanup phase, the part
If there was an exception, the decorator uses generator.throw()
to raise that exception in the generator. It'll be as if the yield
line caused that exception. Because you have a finally
clause, it'll be executed before your generator exits because of the exception.
So, in your specific example the sequence is as follows:
with time_print("processes"):
This creates the context manager and calls __enter__
on that.
The generator starts execution, t = time.time()
is run.
The yield
expression pauses the generator, control goes back to the decorator. This takes whatever was yielded and returns that to the with
statement, in case there is an as target
part. Here None
is yielded (there is only a plain yield
expression).
[doproc() for _ in range(500)]
is run and completes.
The context manager __exit__
method is run, no exception is passed in.
The decorator resumes the generator, it continues where it left off.
The finally:
block is entered and print task_name, "took", time.time() - t, "seconds."
is executed.
The generator exits, the decorator __exit__
method exits, all is done.
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