main.py

import threading

from data import get_sp500, load_stocks_to_memory
from digestors import digest_stocks_signals

# TODO work with processors and not threads
# https://medium.com/@urban_institute/using-multiprocessing-to-make-python-code-faster-23ea5ef996ba
# https://stackoverflow.com/questions/20887555/dead-simple-example-of-using-multiprocessing-queue-pool-and-locking
# https://www.journaldev.com/15631/python-multiprocessing-example


def main(all_stocks):
    offset = 1
    multiply = 26
    num_of_threads = 8

    threads = []

    for i in range(0, num_of_threads):
        # TODO convert to processes and not threads
        # choose digest function to parallel
        t = threading.Thread(target=digest_stocks_signals, args=(all_stocks, i * multiply, i * multiply + offset))
        t.start()
        threads.append(t)
    for t in threads:
        t.join()

    print("here")


SP500 = get_sp500()
stocks_data_dict = load_stocks_to_memory(SP500[0:10])
main(SP500)