Python Learning Path

This group of documents is meant to solve two problems:

• When you need to fill in Python fundamentals in order, you should not have to jump around a pile of scattered notes.
• When you meet a concrete problem, you should still be able to return quickly to high-frequency topics such as slicing, sets, string methods, and input reading.

So this section is organized into two layers:

• Main path: read in learning order to connect the concepts.
• Quick references: organized around frequent questions for later lookup.

Recommended Reading Order

1. Expressions, Numbers, and Operations
2. Control Flow and Iteration
3. Core Data Types and Containers
4. Strings and Formatting
5. Function Arguments and Calls
6. Return Values, Unpacking, and Multi-result Design
7. Files, Input/Output, and Exception Handling
8. Modules, Imports, and Common Standard Libraries

Data Processing Branch

After the main path feels familiar, continue with these two notes:

• NumPy Basics
• Pandas Basics

The goal here is not to cover all of data science, but to explain the most common data structures, indexing patterns, cleaning operations, and aggregation workflows used in everyday work.

Quick Reference Entries

• Input/Output and Common Reading Patterns
• High-frequency Built-in Functions
• Slicing
• Copying, References, and Mutable Objects
• Sets
• Common String Methods
• Python Tips 01

Scope

• The default baseline is Python 3.10+.
• Engineering topics such as venv, pytest, and typing are not merged into the main path yet.
• The writing style still keeps the feel of learning notes, while reducing question-and-answer phrasing and repeated explanations.

Archive Note

The older long article Python Final Review (Archive) is still kept in the Python archive, but it no longer serves as the main entry. Reusable parts will gradually be split into the main path and quick reference pages above.