Python Concurrency (original) (raw)

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In this section, you’ll learn about Python concurrency including multithreading, multiprocessing, and asynchronous programming from scratch.

What you’ll learn:

• Build high-performance & responsive Python applications using concurrency techniques.
• Develop multithreaded applications using multithreading.
• Develop a program that processes tasks in parallel.
• Understand the single-threaded concurrency model.

Section 1. Multithreading #

In this section, you’ll have a good understanding of processes and threads and how to develop multithreaded programs.

• Understanding Processes and Threads – help you understand the processes and threads, and the main differences between them.
• Threading – show you how to use the threading module to develop a multi-threaded application.
• Extending the Thread class – learn how to extend the Thread class to run multiple threads in a program.
• Returning values from a Thread – show you how to return values from a thread by extending the Thread class.
• Multithreading Example – build a multithreaded program that scraps stock prices.
• Daemon threads – learn about daemon threads.
• Thread Pools – guide you on managing multiple threads efficiently using the thread pool.

Section 2. Thread Synchronization Techniques #

In this section, you’ll learn various techniques to synchronize between threads using a lock, event, thread-safe queue, and semaphore.

• Lock – show you how to use a lock object to control access to a shared variable safely from multiple threads.
• Event – learn how to use the threading Event to communicate between threads.
• How to stop a thread – learn how to stop a child thread from the main thread.
• Semaphore – explain the semaphore concept and how to use the Semaphore object to limit the number of threads that can access a shared resource simultaneously.

Section 3. Sharing Data Between Threads #

In this section, you’ll learn various techniques to share data between threads.

• Thread-safe Queue – show you how to use a thread-safe queue to exchange data safely between multiple threads.

Section 4. Multiprocessing #

In this section, you’ll learn how to utilize the multiprocessing package to develop programs that run tasks in parallel.

• Multiprocessing – show you how to run code in parallel using the multiprocessing module.
• Process Pools – learn how to manage processes more efficiently by using a process pool.

Section 5. Async I/O #

In this section, you’ll how to utilize concurrency provided by the asyncio package to improve program performance, throughput, and responsiveness.

• Understanding Event Loop – explain how the event loop works and how asyncio package uses the event loop to achieve a single-threaded concurrency model.
• async/await – introduce to you coroutines and how to use the async and await keywords to define and pause coroutines.
• Creating tasks – learn how to create tasks and schedule them for running on the event loop.
• Canceling tasks – show you how to cancel a task using the cancel() method of the Task object.
• Canceling a task with a timeout – show you how to use the asyncio.wait_for() function to cancel a task with a timeout.
• asyncio.wait() – learn about the asyncio.wait() function to run an iterable of awaitable objects concurrently.
• Future – explain to you the Future object and awaitables.
• Running multiple tasks concurrently with gather() – run a list of tasks concurrently with the asyncio.gather() function.

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