This content originally appeared on DEV Community and was authored by Aidas Petryla
Just finished an excellent course on Concurrent and Parallel Programming in Python, and I'm excited to share my experience!
As a lead engineer, I'm always looking for ways to optimize performance and expand my knowledge. This course by Max S on Udemy was a fantastic refresher on async programming, parallel computing, and threading.
What stood out:
- Clear explanations of complex concepts
- Practical, real-world examples
- Hands-on coding opportunities
The instructor breaks down threading, multiprocessing, and asynchronous programming in Python with ease. We built a multi-threaded program that fetches data from the internet, parses it, and saves it to a local database - a common scenario many of us face in our daily work.
Key takeaways:
- Optimizing IO-bound operations with multi-threading and async programming
- Leveraging multiprocessing for CPU-bound tasks
- Combining async and multiprocessing for maximum efficiency
Whether you're looking to speed up data processing, improve API performance, or just refresh your understanding of concurrent programming in Python, I highly recommend this course.
Have you taken any courses lately that improved your coding skills? Let's discuss in the comments!
This content originally appeared on DEV Community and was authored by Aidas Petryla
Aidas Petryla | Sciencx (2024-07-22T07:02:00+00:00) Concurrent and Parallel Programming in Python (course). Retrieved from https://www.scien.cx/2024/07/22/concurrent-and-parallel-programming-in-python-course/
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