Concurrency, or parallel computing, allows for multiple operations to be performed simultaneously. In the past, the speed of individual processor cores grew at an exponential rate, but due to power and thermal constraints, this increase came to an abrupt end. Since then, CPU manufacturers began to place cores in a single processor, allowing for more operations to be performed concurrently.
Parallelism in Python
In threading, multiple "threads" of execution exist within a single interpreter. Each thread executes code independently from the others, though they share the same data.
>>> import threading >>> def thread_hello(): other = threading.Thread(target=thread_say_hello, args=()) other.start() thread_say_hello() >>> def thread_say_hello(): print('hello from', threading.current_thread().name) >>> thread_hello() hello from Thread-1 hello from MainThread
Multiprocessing allows a program to spawn multiple interpreters, or processes, each of which can run code independently, without sharing data.
>>> import multiprocessing >>> def process_hello(): other = multiprocessing.Process(target=process_say_hello, args=()) other.start() process_say_hello() >>> def process_say_hello(): print('hello from', multiprocessing.current_process().name) >>> process_hello() hello from MainProcess >>> hello from Process-1