You now know how to avoid race conditions in a multithreaded environment, and how to use the synchronization primitives provided by Python’s threading
module. These tools are essential for ensuring that your code behaves correctly and predictably when multiple threads are involved, preventing issues that can arise from concurrent execution.
In this video course, you’ve learned how to:
- Identify race conditions in code
- Use
Lock
andRLock
objects for mutual exclusion - Use
Semaphore
objects to limit concurrent access to resources - Leverage
Event
objects for simple signaling between threads - Use
Condition
objects to make threads conditionally wait - Use
Barrier
objects to coordinate thread execution
More Real Python resources to explore:
- Speed Up Python With Concurrency
- Understanding Python’s Global Interpreter Lock (GIL)
- Concurrency and Async Programming Learning Path
- Programming Sockets in Python
Congratulations, you made it to the end of the course! What’s your #1 takeaway or favorite thing you learned? How are you going to put your newfound skills to use? Leave a comment in the discussion section and let us know.