Concurrent and Parallel Programming in Python Online Course

Concurrent and Parallel Programming in Python Online Course

This course teaches you how to optimize Python applications by overcoming speed bottlenecks with concurrency (threading) and parallelism (multiprocessing). You’ll start by understanding performance limitations, then build practical projects like a Wikipedia Reader, Yahoo Finance Reader, Queues, and a Master Scheduler. Through hands-on coding, you’ll implement multi-threaded programs, use multiprocessing to leverage multiple CPUs, and apply asynchronous programming techniques. Key topics include threading, multiprocessing queues, async/await, locking, Pool Map, and combining async with multiprocessing. By the end, you’ll be able to create fast, efficient Python applications that fully utilize CPU resources and minimize IO wait times.

Who should take this Course?

he Concurrent and Parallel Programming in Python Online Course is ideal for Python developers, software engineers, data scientists, and system programmers who want to improve application performance and efficiency by mastering concurrency and parallelism. It is also valuable for students, researchers, and professionals working with large datasets, high-performance computing, or real-time applications who wish to optimize their Python code for speed and scalability.

What you will learn

• Learn to use concurrency and parallelism in Python
• Write multi-threaded programs in Python to reduce coding lengths
• Write multi-process programs that execute even faster
• Understand the differences between concurrency and parallelism
• Create asynchronous programs in Python by adding concurrency
• Spread workload over all the cores available on a machine being used

Course Outline 

Threading

• Threading, Multiprocessing, Async Introduction
• Threading in Python
• Creating a Threading Class
• Creating a Wikipedia Reader
• Creating a Yahoo Finance Reader
• Queues and Master Scheduler
• Creating a Postgres Worker
• Integrating the Postgres Worker
• Yaml File Introduction
• Creating a Yaml Reader
• Improving Our Wiki Worker
• Improving All Workers and Adding Monitoring
• Final Program Cleanup
• Locking

Multiprocessing

• Multiprocessing Introduction
• Multiprocessing Queues
• Multiprocessing Pool
• Multiprocessing Pool Map Multiple Arguments
• Multiprocessing Multiple Varying Arguments
• Multiprocessing Checking Elements in List in Certain Ranges

Asynchronous

• Introduction to Writing Asynchronous Programs
• Asynchronous Tasks
• Async Gather Method
• Using Async Timeouts
• Creating Asynchronous For Loops
• Using Asynchronous Libraries
• The Async Wait Statement
• Combining Async and Multiprocessing