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This course takes you on a journey from the basics of operating in a Python development environment through to advanced topics and master-level techniques. It presents you with a guide to Python and its standard library, focusing on language and library elements that are particularly useful for tool authors and system programmers.
We start off with the basics to set up a functioning environment, creating packages, and running them on the command line. Through our journey, we'll highlight the major aspects of managing our Python development environment, handling parallel computation, and mastering asynchronous I/O for improved performance of our system. Finally, we'll learn the secrets of metaprogramming and unit testing in Python arming you with the perfect skillset to be a Python expert.
Mastering Python will get you up to speed in everything from basic programming practices to high-end tools and techniques that will help you set apart as a successful Python programmer.
About the Author
Daniel Arbuckle holds a doctorate in Computer Science, and works as a Python programming consultant.
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|Section 1: Setting Up the Work Environment|
|Get a high-level view of what this course will do for you.|
Get a functional Python development environment.
|Learn how to perform quick experiments and access documentation.|
|Learn how to easily download and install third-party packages.|
|Discover available resources so that you don't have to reinvent the wheel.|
|Section 2: Creating a Package|
Learn the filesystem structure that defines a Python package.
|Add code files to the package.|
|Combine code from multiple modules.|
Include data alongside the modules in your package.
|Section 3: Basic Best Practices|
|Make your code more readable for yourself and others using Python's communal coding standard.|
Manage changes, versions, and branches in your source code.
|Create a development area that remains stable for the duration of your development process.|
Format your docstrings to maximize their usefulness.
Run the examples in your docstrings as tests.
|Section 4: Creating a Command-line Utility|
|Create a package entry point to make the package executable.|
|Create full-featured command-line parsers.|
|Get the input and provide the output while the program is running.|
|Execute and interact with other programs.|
Reduce the effort needed to run executable packages.
|Section 5: Parallel Processing|
|Use a high-level interface to distribute computational tasks to worker processes and collect the results.|
|Use a mid-level interface to create cooperative parallel processes.|
|Section 6: Coroutines and Asynchronous I/O|
The API looks a lot like concurrent.futures, but it's doing something very different.
|How to get the asyncio scheduler running and add asynchronous tasks.|
How asyncio futures behave and what to do with them.
How to use synchronization, waiting, and communication channels.
|Easily use stream sockets to communicate.|
|Section 7: Metaprogramming|
|Automatically post-process functions.|
|Add new semantics to functions.|
Automatically post-process classes.
|Change what it means to be a class.|
Set up special rules for regions of code.
|Control what happens when attributes are accessed.|
|Section 8: Unit Testing|
Get more benefits out of testing with less work.
Write tests, run them, and understand the results.
Use mock objects to keep tests local.
|Run tests even more easily with test discovery.|
Take advantage of more complete test discovery and integrated reporting.
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