Concurrent and Parallel Programming in Python
Speed up your programs with concurrency and parallelism in Python
Created by Maximilian Schallwig
Unlock the power of Python to make your programs run faster by mastering concurrency and parallelism. Explore how to use threading, multiprocessing, and asynchronous programming to handle intensive IO tasks and maximize CPU usage. Build practical skills to tackle performance bottlenecks in real-world applications.
Packt | Nov 2022 | 367 min
What You Will Learn
You will work through hands-on coding exercises that introduce threading, multiprocessing, and async programming in Python. Step-by-step projects like building data readers and schedulers help you apply each concept in practical scenarios. By combining these techniques, you will learn how to optimize performance and resource usage.
Key Features
- Identify and resolve common speed bottlenecks in Python applications
- Build multi-threaded and multi-process programs for faster data processing
- Combine async and multiprocessing to fully utilize your machine's CPU cores
Target Audience
Ideal for Python developers with a solid grasp of the basics who want to advance their skills in high-performance programming. If you are an API, web, or application developer looking to speed up data-heavy or IO-bound tasks, you will gain actionable techniques to make your code more efficient and scalable.
