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Very easy multithreading

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meanwhile - Very Easy Multithreading

If you want to call the same function on many inputs, in a multithreaded fashion, meanwhile makes it easy.

It can make your code significantly faster, especially if the function requires I/O operations, like file access or HTTP(S) queries.


pip3 install meanwhile

Simple Usage Example

Suppose you have a function named test_url, that gets a URL, downloads its content, and tests whether it contains the word "meanwhile". Also, suppose you have a file, named urls.txt, where each line contains a URL you would like to apply test_url to.

You can do the following:

>>> from meanwhile import Job
>>> job = Job(test_url, 10)    # at most 10 threads will be used concurrently.
>>> urls = open("urls.txt").read().splitlines()
>>> job.add_many(urls)
>>> job.wait()
>>> results = job.get_results()

The target function (in this case: test_url) should get one argument, and this argument should be hashable.

Note that if your function prints output, you probably want to use meanwhile.print() instead of Python's built-in print() function. This function prevents conflicts both with other threads, and with the progress updates shown by the wait method.

In More Details

The Job object holds a queue of inputs to process. It automatically spawns and kills threads, as needed (up to the maximal number of concurrent threads set by the user).

The methods add and add_many can be used to add inputs to the queue.

The method wait stops until the queue is empty. By default, it shows the job's progress, like this:

pending: 19	 running: 20	 finished: 11	 failed: 0

In order to wait without showing the progress, one can set the keyword argument show_status to be False. Also, it's possible to show the job's progress without wait-ing, using the method print_status.

wait also supports a keyword argument, timeout. If it is set, the method will unconditionally return after timeout seconds. wait can also be stopped safely by a KeyboardInterrupt.

The return values of the target function can be inspected using the methods get_result, has_result and get_results.

Fix Mistakes On The Fly

meanwhile also makes it easy to debug your code and fix it while the job is already in progress.

First, almost everything can be changed at any time. For example:

  • You can always add new inputs to the queue using add and add_many (even after all previous inputs were already processed, and all threads were killed);
  • You can always change the maximal number of threads allowed to run concurrently using the method set_n_threads;
  • You can always change the target function using the method set_target (this will apply only to inputs that weren't successfully processed yet).

Also, you can inspect the exceptions raised by the target function using the method get_exceptions (and also has_exception and get_exception).

After you fix the cause for the exceptions, you can use the methods retry, retry_many and retry_all to return inputs that raised exceptions into the job's queue.

In case your target function sometimes randomly fails (i.e. raises exception), you can also use the method set_n_attempts, to make the job retry inputs automatically for a limited number of attempts (and note that the Job class'es constructor also can take the keyword argument n_attempts).

Finally, note the methods pause, resume and kill, that also can be useful when you debug a job in progress (don't be afraid of kill: it is just equivalent to set_n_threads(0)).

Resource Reuse

Sometimes it's useful to have a thread reusing resources whlie sequentially processing inputs. For example, if your target function makes an HTTPS request, you may want to reuse the same session, in order to save the TLS handshake time.

That's why meanwhile allows you to provide a target factory instead of a target function. The factory is used to create a different target function for each thread spawned.

A target factory can be either a function that does not take arguments, and returns a target function, or a callable class (that is initialized without arguments, and its __call__ method is used as the target function.

In order to provide a target factory instead of target function, one must set the keyword argument factory to be True (this is true for both the Job class constructor and the set_target method).

Module Reference

For the full module reference, see help(meanwhile).

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