![]() The most controversial topic among Python developers, the GIL stands for Global Interpreter Lock, which is basically a lock that prevents two threads from executing simultaneously in the same Python interpreter, some people don't like that, while the others claiming that it isn't a problem, as there are libraries such as Numpy that bypass this limitation by running programs in external C code. Now you're maybe wondering, why do we need to use threads if they can't run simultaneously? Before we answer that question, let's see why threads can't run at the same time. Running multiple threads is only effective for I/O-bound tasks.Two threads in a single Python program cannot execute at the same time.Threads share the same memory space and can read and write to shared variables (with synchronization, of course).Running multiple processes is only effective for CPU-bound tasks.Processes have more overhead than threads (creating and destroying processes takes more time).Two processes can run on different CPU cores (which leads to communication problems, but better CPU performance). ![]() A process can contain one or more threads.But in fact, they are quite different, here are the main differences between threads and processes in Python: Process Threads are like mini-processes, in fact, some people call them lightweight processes, that's because threads can live inside a process and does the job of a process. ![]() Unlike processes, threads in Python don't run on a separate CPU core, they share memory space and efficiently read and write to the same variables. ![]() In computing, a thread is a sequence of programmed instructions to be executed in a program, two threads running in a single program means that they are running concurrently (i.e, and not in parallel). Start converting now!ĭisclosure: This post may contain affiliate links, meaning when you click the links and make a purchase, we receive a commission. It's the ultimate tool for multi-language programming. Turn your code into any language with our Code Converter. ![]()
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