Parallelizing a list comprehension in Python

Question

someList = [x for x in someList if not isOlderThanXDays(x, XDays, DtToday)]

I have this line and the function isOlderThanXDays makes some API calls causing it to take a while. I would like to perform this using multi/parrellel processing in python. The order in which the list is done doesn't matter (so asynchronous I think)

The function isOlderThanXDays essentially returns a boolean value and everything newer than is kept in the new list using List Comprehension.

Edit: Params of function: So the XDays is for the user to pass in lets say 60 days. and DtToday is today's date (date time object). Then I make API calls to see metaData of the file's modified date and return if it is older I return true otherwise false.

I am looking for something similar to the question below. The difference is this question for every list input there is an output, whereas mine is like filtering the list based on boolean value from the function used, so I don't know how to apply it in my scenario

How to parallelize list-comprehension calculations in Python?

Answer 1

This should run all of your checks in parallel, and then filter out the ones that failed the check.

import multiprocessing

try:
    cpus = multiprocessing.cpu_count()
except NotImplementedError:
    cpus = 2   # arbitrary default


def MyFilterFunction(x):
    if not isOlderThanXDays(x, XDays, DtToday):
        return x
    return None

pool = multiprocessing.Pool(processes=cpus)
parallelized = pool.map(MyFilterFunction, someList)
newList = [x for x in parallelized if x]

Answer 2

you can use ThreadPool:

from multiprocessing.pool import ThreadPool # Class which supports an async version of applying functions to arguments
from functools import partial

NUMBER_CALLS_SAME_TIME = 10 # take care to avoid throttling
# Asume that isOlderThanXDays signature is isOlderThanXDays(x, XDays, DtToday)
my_api_call_func = partial(isOlderThanXDays, XDays=XDays, DtToday=DtToday)
pool = ThreadPool(NUMBER_CALLS_SAME_TIME)
responses = pool.map(my_api_call_func, someList)