Talk Python: Async Techniques and Examples is the first liveVideo course in the exciting Talk Python series from podcaster and software trainer Michael Kennedy. In this hands-on and visuals-first video, you’ll learn the entire spectrum of Python's parallel programming APIs. You’ll get started with the new and powerful async and await keywords of Python 3.5+, as well as the underpinning module: asyncio. Then you’ll cover Python's threads for parallelizing older operations and multiprocessing for CPU bound operations. You'll close out the course with a host of additional async topics such as async Flask, task coordination, thread safety, and C-based parallelism with Cython.
Distributed by Manning Publications
This course was created independently by Python expert Michael Kennedy and is distributed by Manning through our exclusive liveVideo platform.
About the subject
Asynchronous Python code runs faster, scales better, and can take advantage of modern, multicore CPUs. To get the performance benefits of parallelism, you’ll need to overhaul the way you write your programs, and this course will show you exactly how.About the video
Talk Python: Async Techniques and Examples is a comprehensive course on parallel programming in Python. It covers tried and true foundational concepts such as threads and multiprocessing, as well as modern async features based on Python 3.7+ with async and await. In addition to the core concepts and APIs for concurrent programming, you’ll learn best practices for concurrency, how to choose between the various APIs, and how to use APIs together for the biggest advantage. All concepts are backed up by clear and precise visuals, and you’ll get the chance to code along and explore detailed code samples for each new parallel technique.
Table of Contents detailed table of contents
Welcome to the course
Course introduction
Async for taking full advantage of modern CPUs
Topics covered
Student prerequisites
Meet your instructor
Setup and following along
Do you have Python 3?
Getting Python 3
Recommended text editor
Hardware requirements
Get the source code
Why async?
Async for computational speed
Demo: Why you need async for speed
An upper bound for async speed improvement
Async for scalability
Concept: Visualizing a synchronous request
Concept: Visualizing an asynchronous request
Python’s async landscape
Why threads don’t perform in Python
async and await with asyncio
Python async landscape: asyncio
I/O-driven concurrency
Demo: Understanding basic generators
Demo: The producer-consumer app
Demo: Make the producer-consumer async
Demo: Make the producer-consumer async (methods)
Concept: asyncio
Performance improvements of producer consumer with asyncio
Faster asyncio loops with uvloop
Let’s do some real work
Synchronous web scraping
Async web scraping
Concept: async web scraping
Other async-enabled libraries
Threads
Python async landscape: Threads
Visual of thread execution
How to choose between asyncio and threads
Demo: hello threads
Demo: Waiting on more than one thread
Demo: Something productive with threads
Concept: Thread API
Concept: Tips for multiple threads
Cancelling threads with user input
Concept: Timeouts
Demo: Attempting to leverage multiple cores with threads
Thread safety
Python async landscape: Thread Safety landscape
Threads are dangerous
Visualizing the need for thread safety
Demo: An unsafe bank
Demo: Make the bank safe (global)
Demo: A missed lock in our bank (global)
Demo: Make the bank safe (fine-grained)
Demo: Breaking a deadlock
Concept: Basic thread safety
Leveraging CPU cores with multiprocessing
Python async landscape: multiprocessing
Introduction to scaling CPU-bound operations
Demo: Scaling CPU-bound operations with multiprocessing
Concept: Scaling CPU-bound operations
Multiprocessing return values
Concept: Return values
Common APIs with execution pools
Python async landscape: Execution pools
Demo: Executor app introduction
Demo: Executor app (threaded-edition)
Demo: Executor app (process-edition)
Concept: Execution pools
Built on asyncio
Python async landscape: asyncio derivatives
Why do we need more libraries?
Introducing unsync
Demo: unsync app introduction
Demo: unsync app for mixed-mode parallelism
Concept: Mixed-mode parallelism with unsync
Introducing Trio
Demo: Starter code for Trio app
Demo: Converting from asyncio to Trio
Demo: Cancellation with Trio
Concept: Trio nurseries
The trio-async package
Asyncio-based web frameworks
Python async landscape: Async web
Review: Request latency again
Demo: Introducing our Flask API
There is no async support for Flask
Demo: Introducing Quart for async Flask
Demo: Converting from Flask to Quart
Demo: Making our API async
Demo: An async weather endpoint
Concept: Flask to Quart
Load testing web apps with wrk
A note about rate limiting with external services
Performance results
Remember to run on an ASGI server
Parallelism in C with Cython
Python async landscape: Cython
C and Python are friends
Why Cython
Cython syntax compared
Demo: Hello Cython
Concept: Getting started with Cython
Demo: Fast threading with Cython (app review)
Demo: Fast threading with Cython (hotspot)
Demo: Fast threading with Cython (conversion)
Demo: Fast threading with Cython (GIL-less)
Demo: Fast threading with Cython (int overflow issues)
Concept: Cython’s nogil
Course conclusion and review
The finish line
Review: Why async?
Review: asyncio
Review: Threads
Review: Thread safety
Review: multiprocessing
Review: Execution pools
Review: Mixed-mode parallelism
Review: Coordination with Trio
Review: Async Flask
Review: Cython
Thanks and goodbye
What you will learn
- How concurrency improves performance and scalability
- Build async-capable code with the new async and await keywords
- Add asynchrony to your app
- Work with multiple threads to run CPU-bound work in Python
- Use locks and thread safety mechanisms to protect shared data
- Take full advantage of multicore CPUs with multiprocessing
- Add massive speedups with Cython to circumvent Python’s GIL
- Create async view methods in Flask web apps
About the instructor
Michael Kennedy is the host of the #1 Python podcast, Talk Python to Me. He’s interviewed many of the leaders and creators in the Python community and brings that perspective to all the courses he creates. He has been a professional software trainer for over 10 years.placing your order...
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