Note
Refer Threading vs Multiprocessing vs Asyncio
Multiprocessing can utilize multiple CPUs (bypassing GIL), while Threading could only utilize 1 CPU.
For IO bound task, you might want to consider Asyncio
Multiple Process
import multiprocessing as mpfrom time import sleepdef run(name): for i in range(10): sleep(0.5) print(name, end='', flush=True) print(f"{name}[END]", end='', flush=True)for name in ['a', 'b', 'c']: p = mp.Process(target=run, args=(name,)) p.start() print('STOP')STOP
acbcbacabbaccabcabbacbacbcabcc[END]b[END]aa[END]You realize the main process stop before all the child process end.
To wait for all the child process, do the following.
jobs = []for name in ['a', 'b', 'c']: p = mp.Process(target=run, args=(name,)) p.start() jobs.append(p)# wait for all child process to endfor p in jobs: p.join()print('STOP')Shared Value
Increment a counter value
import multiprocessing as mpfrom time import sleepdef run(name, count): for i in range(10): sleep(0.5) with count.get_lock(): count.value += 1 print(f"{name}[{count.value}]", end='', flush=True) print(f"{name}[END]", end='', flush=True)jobs = []count = mp.Value('l', 0) # https://docs.python.org/3/library/array.htmlfor name in ['a', 'b', 'c']: p = mp.Process(target=run, args=(name,count)) p.start() jobs.append(p)for p in jobs: p.join()print(f"STOP[{count.value}]")a[1]c[2]b[3]c[4]a[5]b[6]c[7]a[8]b[9]c[10]a[11]b[12]c[13]a[14]b[15]c[16]a[17]b[18]c[19]a[20]b[21]c[22]a[23]b[24]c[25]b[26]a[27]c[28]c[END]b[29]b[END]a[30]a[END]STOP[30]