Mastering Python
Get to grips with Python best practices and advanced tools to design, distribute, and test your programs
Get to grips with Python best practices and advanced tools to design, distribute, and test your programsAbout This Video
Explore the immense Python libraries to write efficient, reusable code
Create adaptable programs that run on multiple processors with parallel programming
Become a Python expert with the help of detailed discussions, illustrated with concrete examples
In Detail
Python is one of the most powerful, flexible, and popular programming languages in the world. Even though Python programs are simple to work with, writing code that is efficient, maintainable, and reusable can be a little tricky for some. The presence of Python's “batteries included” toolbox allows you to easily produce application prototypes or implement new algorithms with minimum efforts.
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.
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Course Curriculum
Setting Up the Work Environment
- The Course Overview (3:41)
- Downloading and Installing Python (3:02)
- Using the Command Line and the Interactive Shell (3:30)
- Installing Packages with pip (2:55)
- Finding Packages in the Python Package Index (3:08)
Creating a Package
- Creating an Empty Package (4:10)
- Adding Modules to the Package (4:36)
- Importing One of the Package's Modules from Another (5:01)
- Adding Data Files to the Package (2:33)
Basic Best Practices
- PEP 8 and Writing Readable Code (6:19)
- Using Version Control (6:00)
- Using venv to Create a Stable and Isolated Work Area (3:26)
- Getting the Most Out of docstrings Part 1 – PEP 257 and Sphinx (6:23)
- Getting the Most Out of docstrings Part 2 – doctest (2:51)t
Creating a Command-line Utility
- Making a Package Executable via python – m (4:15)
- Handling Command-line Arguments with argparse (5:20)
- Text-mode Interactivity (3:38)
- Executing Other Programs (5:04)
- Using Shell Scripts or Batch Files to Launch Programs (1:53)
Parallel Processing
- Using concurrent.futures (9:57)t
- Using Multiprocessing (8:37)
Coroutines and Asynchronous I/O
- Understanding Why Asynchronous I/O Isn't Like Parallel Processing (5:50)
- Using the asyncio Event Loop and Coroutine Scheduler (5:26)
- Futures (6:04)t
- Making Asynchronous Tasks Interoperate (5:51)
- Communicating across the Network (3:15)
Metaprogramming
- Using Function Decorators (5:01)
- Using Function Annotations (4:55)t
- Using Class Decorators (4:28)
- Using Metaclasses (4:55)
- Using Context Managers (4:41)
- Using Descriptors (5:37)
Unit Testing
- Understanding the Principles of Unit Testing (3:31)
- Using unittest (5:36)
- Using unittest.mock (5:39)
- Using unittest's Test Discovery (3:56)
- Using Nose for Unified Test Discovery and Reporting (3:58)
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