tools.py

from concurrent.futures import ProcessPoolExecutor, as_completed

from tqdm import tqdm


def parallel_process(array,
                     function,
                     n_jobs=16,
                     use_kwargs=False,
                     front_num=3,
                     tqdm=tqdm):
    """
        This function was copied from here:
        http://danshiebler.com/2016-09-14-parallel-progress-bar/

        A parallel version of the map function with a progress bar.

        Args:
            array (array-like): An array to iterate over.
            function (function):
                A python function to apply to the elements of array
            n_jobs (int, default=16): The number of cores to use
            use_kwargs (boolean, default=False):
                Whether to consider the elements of array as dictionaries of
                keyword arguments to function
            front_num (int, default=3): The number of iterations to run serially
            before kicking off the parallel job.
                Useful for catching bugs
        Returns:
            [function(array[0]), function(array[1]), ...]
    """
    # We run the first few iterations serially to catch bugs
    if front_num > 0:
        front = [function(**a) if use_kwargs else function(a)
                 for a in array[:front_num]]
    # If we set n_jobs to 1, just run a list comprehension. This is useful for
    # benchmarking and debugging.
    if n_jobs == 1:
        return front + [function(**a) if use_kwargs else function(a)
                        for a in tqdm(array[front_num:])]
    # Assemble the workers
    with ProcessPoolExecutor(max_workers=n_jobs) as pool:
        # Pass the elements of array into function
        if use_kwargs:
            futures = [pool.submit(function, **a) for a in array[front_num:]]
        else:
            futures = [pool.submit(function, a) for a in array[front_num:]]
        kwargs = {
            'total': len(futures),
            'unit': 'it',
            'unit_scale': True,
            'leave': True
        }
        # Print out the progress as tasks complete
        for _ in tqdm(as_completed(futures), **kwargs):
            pass
    out = []
    # Get the results from the futures.
    for _, future in tqdm(enumerate(futures)):
        try:
            out.append(future.result())
        except Exception as e:
            out.append(e)
    return front + out