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"""
An undecorated example of a script that allocates memory in multiprocessing
workers to demonstrate the use of memory_profiler with multiple processes.
Run this script with mprof run -M multiprocessing_example.py
You can then visualize the usage with mprof plot.
"""
import time
import multiprocessing as mp
# Big numbers
X6 = 10 ** 6
X7 = 10 ** 7
def worker(num, wait, amt=X6):
"""
A function that allocates memory over time.
"""
frame = []
for idx in range(num):
frame.extend([1] * amt)
time.sleep(wait)
del frame
def main_sequential():
"""
A sequential version of the work, where one worker is called at a time.
"""
worker(5, 5, X6)
worker(5, 2, X7)
worker(5, 5, X6)
worker(5, 2, X7)
def main_multiproc():
"""
A multiprocessing version of the work, where workers work in their own
child processes and are collected by the master process.
"""
pool = mp.Pool(processes=4)
tasks = [
pool.apply_async(worker, args) for args in
[(5, 5, X6), (5, 2, X7), (5, 5, X6), (5, 2, X7)]
]
results = [p.get() for p in tasks]
if __name__ == '__main__':
main_multiproc()
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