README.md

Python ProcessIO

Running functions with multiprocessing hassle free

A nice package to help you run functions with multiprocessing and get their result.

Installation

pip install processio

Usage

Run function in own process

import time
from processio import ProcessIO


def get_company_name():
    # Do work in own process
    time.sleep(5)
    return 'Adapted'


def do_some_work():
    get_name = ProcessIO(get_company_name)

    # do stuff or run a while loop to wait for result

    while get_name.doing_work():
        print('Waiting for process to finnish')

    # You can also call .result() and the main thread will wait 
    # for the thread to return your result.

    company_name = get_name.result()

    print(company_name) # Outputs -> Adapted

    
if __name__ == '__main__': # <- its required to execute the function main
    do_some_work() 
    

Main commands

# Import the module
from processio import ProcessIO

# Start your function with or without arguments
var = ProcessIO(function, args, kwargs)

# Wait for the function to finnish or get the result if its finished
var.result()

Optional commands

# Check if your thread is still working on the function.
# This will return True if the function is not completed.

var.doing_work()

Use parseIO to save a lot of time on list parsing

import time
from processio import ParseIO


def list_parser(list):
    result = 0
    for line in list:
        result += get_total_amout(line)
    return result


def do_some_work():
    # this will split the list into 4 and run the function on
    # 4 different processes, that in most cases will almost speed
    # up the work time by 4.

    # you can define the number of processes you want to run, but as a
    # default the module runs on the systems cpu cores - 1

    parser = ParseIO(list_parser, huge_list)

    # do stuff or run a while loop to wait for result

    while parser.doing_work():
        print('Waiting for processes to finnish')

    # You can also call .result() and the main thread will wait 
    # for the thread to return your result.

    result = parser.result()
    
    # result comes back as list pr process, so in this case we will get 
    # a list with 4 numbers that we can loop thru.
    
    print(result) # Outputs -> [1000, 1000, 1000, 1000] <- example

    
    total = 0
    for res in result:
        total += res


    print(total) # Outputs -> 4000 <- example
    
if __name__ == '__main__': # <- its required to execute the function main
    do_some_work() 

Testing

Use the following command to run tests.

python -m unittest threadit.tests.test_threadit

Changelog:

See CHANGELOG.md