Python Guides

Self-directed guides for learning Python, written for second-year data science students and free for anyone.

Each guide follows the same four-part shape: Learn (step-by-step tutorials you can run in the browser), Recipes (short task-focused how-tos), Reference (quick lookups), and Concepts (short pieces explaining why things work the way they do).

Conditional logic Making decisions in code: if/elif/else, boolean operators, truthiness, match/case. Learn · 1Recipes · 0Reference · 0Concepts · 0

Data structures Lists, tuples, dictionaries, sets, comprehensions, slicing, and when to reach for each. Learn · 6Recipes · 4Reference · 5Concepts · 4

Functions Defining functions, parameters, lambdas, type hints, docstrings, closures, and decorators. Learn · 7Recipes · 5Reference · 4Concepts · 4

String processing Working with text: methods, formatting, searching, cleaning, and Unicode gotchas. Learn · 4Recipes · 4Reference · 3Concepts · 2

File handling Reading and writing files, paths with pathlib, CSV and JSON, context managers, encodings. Learn · 4Recipes · 4Reference · 3Concepts · 2

Error handling Exceptions from first principles: raising, catching, custom exceptions, and when not to catch. Learn · 4Recipes · 4Reference · 3Concepts · 2

Logging and debugging The logging module, log levels, and debugging with pdb and breakpoints. Learn · 4Recipes · 4Reference · 3Concepts · 2

Regular expressions Pattern matching with the re module: syntax, groups, flags, and practical extraction. Learn · 4Recipes · 4Reference · 3Concepts · 2

Unit testing Writing tests with unittest: fixtures, assertions, testing exceptions, good test names. Learn · 4Recipes · 3Reference · 3Concepts · 2

Run Python in your browser

Every tutorial in Agilearn is a Jupyter notebook, and every notebook can be opened in the Lab — a browser-side Python environment that needs no install, no signup, and no server. Your edits stay on your own machine.