schwimmbad 0.2.1

Example

If you can write your code following the MapReduce programming model, you can trivially parallelize it using The Schwimmbad. For example, if you can structure your code so that a ‘worker’ function operates on elements from a list of tasks, like this:

def worker(task):
    # do something with the task!
    return task**2

def main():
    tasks = range(100)
    results = map(worker, tasks)

if __name__ == "__main__":
    main()

with a few added lines of code, you can make it runnable with multiprocessing and MPI at the switch of a command-line flag:

import schwimmbad

def worker(task):
    # do something with the task!
    return task**2

def main(pool):
    tasks = range(100)
    results = pool.map(worker, tasks)
    pool.close()

if __name__ == "__main__":
    from argparse import ArgumentParser
    parser = ArgumentParser(description="")

    group = parser.add_mutually_exclusive_group()
    group.add_argument("--ncores", dest="n_cores", default=1,
                       type=int, help="Number of processes (uses multiprocessing).")
    group.add_argument("--mpi", dest="mpi", default=False,
                       action="store_true", help="Run with MPI.")
    args = parser.parse_args()

    pool = schwimmbad.choose_pool(mpi=args.mpi, processes=args.n_cores)
    main(pool)

Installation

The easiest way to install is via pip:

pip install schwimmbad

The project is also installable by cloning or downloading the source and using the standard:

python setup.py install

Dependencies

• six

• mpi4py (optional - needed for MPI pool support)

License

Copyright 2016 Adrian Price-Whelan.

schwimmbad is free software made available under the MIT License. For details see the LICENSE file.