Beyond the Standard Library
Discover how to leverage essential Python packages from PyPI that extend functionality beyond the standard library. Learn to use NumPy and pandas for data analysis, Requests and HTTPX for web communication, Matplotlib for visualization, and Beautiful Soup with Selenium for web automation and scraping. This lesson equips you with practical skills to build advanced Python applications by integrating community-developed libraries.
We'll cover the following...
Although Python’s standard library is known for its “batteries included” philosophy, much of Python’s ecosystem is built around the Python Package Index (PyPI). PyPI hosts hundreds of thousands of open-source packages that address a wide range of technical tasks. In practice, Python development rarely involves implementing every algorithm from scratch. Instead, it focuses on selecting existing libraries and integrating them effectively. This lesson introduces commonly used libraries across three areas of Python development: data science, web communication, and automation.
Data handling and analysis
Python is the dominant language in data science because of two foundational libraries: NumPy and pandas.
NumPy (Numerical Python) provides the ndarray object. Unlike standard Python lists, which are flexible but slow, NumPy arrays are fixed-type and densely packed in memory. This allows for mathematical operations that are orders of magnitude faster, making Python suitable for ...