Multiprocessing
Definition:
Multiprocessing involves running multiple processes simultaneously. Each process has its own memory space and Python interpreter, allowing it to run independently.
Importance:
It's ideal for CPU-bound tasks (tasks that require a lot of computational power) because it can utilize multiple CPU cores effectively.
Use Case:
For example, processing large datasets or performing complex calculations can benefit from multiprocessing.
Multithreading
Definition:
Multithreading allows multiple threads (smaller units of a process) to run within the same process. Threads share the same memory space, which makes communication between them easier but can lead to complications like race conditions.
Importance:
It's best suited for I/O-bound tasks (tasks that spend time waiting for input/output operations, like reading from a file or making network requests).
Use Case:
For instance, a web scraper can use multithreading to handle multiple requests simultaneously.
Global Interpreter Lock (GIL)
Definition:
The GIL is a mutex (mutual exclusion) that protects access to Python objects, preventing multiple threads from executing Python bytecode simultaneously. This means that even if you have multiple threads, only one can execute Python code at a time.
Importance:
The GIL can be a limitation for CPU-bound multithreaded programs in Python because it prevents them from fully utilizing multiple CPU cores.
Impact:
However, it simplifies memory management and helps avoid certain threading-related issues.
Summary
- Multiprocessing: Better for CPU-bound tasks and can run in parallel across multiple CPU cores.
- Multithreading: More efficient for I/O-bound tasks but is limited by the GIL for CPU-bound tasks.
- GIL: A characteristic of CPython (the standard Python implementation) that affects how threads are executed.
Expert Words
Definition: Running multiple processes simultaneously, with independent memory spaces.
Definition: Multiple threads within a single process, sharing memory space.
Definition: A mutex that prevents multiple threads from executing Python bytecode at the same time.