Threading in Python allows you to run multiple threads (smaller units of a process) simultaneously. It’s useful for I/O-bound tasks but has limitations due to the Global Interpreter Lock (GIL).
Why Use Threading?
- Concurrency: Perform multiple operations at once.
- I/O-bound Tasks: Efficiently handle tasks like file I/O or network operations.
Creating a Thread
Use the threading module:
import threading
def print_numbers():
for i in range(5):
print(i)
thread = threading.Thread(target=print_numbers)
thread.start()
Joining Threads
Wait for a thread to finish execution:
thread.join()
Thread Synchronization
Use locks to prevent race conditions:
lock = threading.Lock()
with lock:
# Thread-safe operations
Limitations Due to GIL
The Global Interpreter Lock allows only one thread to execute Python bytecode at a time, which can limit performance in CPU-bound tasks.
Conclusion
Threading in Python is a powerful tool for concurrent programming, especially for I/O-bound applications. Understanding how to create and manage threads can greatly enhance the efficiency of your programs.