Executive Development Programme in Concurrency in Python: Threads, Processes, and Asyncio

This course is designed for experienced Python developers and IT managers looking to enhance their skills in building scalable and efficient applications. It covers advanced concurrency techniques including threads, processes, and the asyncio library, essential for modern Python development.

Participants will gain a deep understanding of how to implement concurrency in Python effectively, learn to manage race conditions and deadlocks, and master the art of asynchronous programming with asyncio. This will enable them to develop applications that can handle high loads efficiently and write more robust and performant code.

1. 1. Introduction to Concurrency in Python: Learners will understand the basics of concurrency, including the need for concurrency in modern applications and the differences between threads and processes. They will gain foundational knowledge on how to write and run simple concurrent programs in Python.
2. 2. Thread Basics in Python: This module covers the creation, management, and synchronization of threads in Python. Learners will learn to use the `threading` module and understand thread safety and common synchronization primitives like locks and condition variables.
3. 3. Advanced Thread Techniques: Learners will explore advanced thread concepts such as thread pools, daemon threads, and thread local storage. They will gain practical skills in optimizing thread usage and handling thread lifecycle issues.
4. 4. Process Basics in Python: This module introduces learners to the `multiprocessing` module, covering process creation, inter-process communication, and parallelism. Learners will understand the benefits and limitations of using processes over threads.
5. 5. Advanced Process Techniques: Learners will delve into more advanced process management techniques, including managing shared memory, using pipes and queues for inter-process communication, and handling process lifecycle issues.
6. 6. Introduction to Asyncio: This module provides an introduction to asynchronous programming in Python with the `asyncio` framework, covering the basics of coroutines, event loops, and asynchronous I/O operations.
7. 7. Advanced Asyncio Concepts: Learners will explore deeper concepts in `asyncio`, such as task scheduling, exception handling, and working with multiple tasks concurrently. They will gain practical skills in designing and implementing complex asynchronous workflows.
8. 8. Concurrency Patterns and Design: This module focuses on common concurrency patterns and best practices, including producer-consumer patterns, the actor model, and reactive programming. Learners will learn to apply these patterns effectively in their Python applications.
9. 9. Performance Optimization in Concurrency: Learners will study techniques for optimizing concurrent Python applications, including profiling tools, thread pool optimization, and reducing context switching. They will gain skills in identifying and resolving performance bottlenecks.
10. 10. Real-world Case Studies: Learners will analyze real-world case studies of concurrency in Python applications, gaining insights into how to apply the concepts learned in practical scenarios. They will work on a final project that integrates all aspects of the programme.