Python 开发人员

In this chapter, you'll learn what it means to write efficient Python code. You'll explore Python's Standard Library, learn about NumPy arrays, and practice using some of Python's built-in tools. This chapter builds a foundation for the concepts covered ahead.

In this chapter, you will learn how to gather and compare runtimes between different coding approaches. You'll practice using the line_profiler and memory_profiler packages to profile your code base and spot bottlenecks. Then, you'll put your learnings to practice by replacing these bottlenecks with efficient Python code.

This chapter covers more complex efficiency tips and tricks. You'll learn a few useful built-in modules for writing efficient code and practice using set theory. You'll then learn about looping patterns in Python and how to make them more efficient.

Discover the fundamentals of Git for version control in your software and data projects.

Discover branches and remote repos for version control in collaborative software and data projects using Git!

Build your OOP skills with descriptors, multilevel inheritance, and abstract base classes!

Learn to create your own Python packages to make your code easier to use and share with others.

Learn to retrieve and parse information from the internet using the Python library scrapy.

Develop a new app feature with your Python skills to calculate calories and nutrition values from user input.

Explore data structures such as linked lists, stacks, queues, hash tables, and graphs; and search and sort algorithms!

Master Python testing: Learn methods, create checks, and ensure error-free code with pytest and unittest.