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Python Learning Curriculum

Purpose

This repository is designed to help you learn Python through hands-on practice with personalized assignments generated by Claude. Work at your own pace, jump between topics as needed, and build a strong foundation in Python programming.

How It Works

Create your own branch from main
Copy the progress tracking template to track your learning journey
Ask Claude for assignments based on where you are in the curriculum
Complete assignments, commit your work, and request feedback
Update your progress file as you complete each topic segment

Python Concepts Covered

1. Fundamentals

1.1 Getting Started

Installing Python and setting up your environment
Running Python scripts
Using the Python interactive shell (REPL)
Basic syntax and indentation rules

1.2 Variables and Data Types

Variables and assignment
Basic data types: int, float, str, bool
Type conversion and casting
Understanding None

1.3 Basic Operations

Arithmetic operators (+, -, *, /, //, %, **)
Comparison operators (==, !=, <, >, <=, >=)
Logical operators (and, or, not)
String operations and concatenation

2. Control Flow

2.1 Conditional Statements

if, elif, else statements
Nested conditionals
Ternary operator
Truthy and falsy values

2.2 Loops

while loops
for loops and the range() function
Loop control: break, continue, pass
Nested loops
Loop else clauses

3. Data Structures

3.1 Lists

Creating and accessing lists
List methods (append, extend, insert, remove, pop, etc.)
List slicing
List comprehensions
Nested lists

3.2 Tuples

Creating and using tuples
Tuple unpacking
Immutability of tuples
When to use tuples vs lists

3.3 Dictionaries

Creating and accessing dictionaries
Dictionary methods (keys, values, items, get, etc.)
Dictionary comprehensions
Nested dictionaries

3.4 Sets

Creating and using sets
Set operations (union, intersection, difference)
Set comprehensions
Frozen sets

4. Functions

4.1 Function Basics

Defining and calling functions
Parameters and arguments
Return values
Default parameters
Keyword arguments

4.2 Advanced Function Concepts

*args and **kwargs
Lambda functions
Scope and namespaces (local, global, nonlocal)
Recursive functions

5. Strings and Text Processing

5.1 String Manipulation

String methods (split, join, strip, replace, etc.)
String formatting (f-strings, format(), %-formatting)
String slicing and indexing
Raw strings and escape characters

5.2 Regular Expressions

Pattern matching basics
re module functions (search, match, findall, sub)
Common regex patterns
Groups and capturing

6. File Handling

6.1 File Operations

Opening and closing files
Reading files (read, readline, readlines)
Writing to files
File modes (r, w, a, r+, etc.)
Using context managers (with statement)

6.2 Working with Different File Types

Text files
CSV files
JSON files
Working with file paths (os.path, pathlib)

7. Error Handling

7.1 Exceptions

Understanding exceptions
try, except, else, finally blocks
Catching specific exceptions
Raising exceptions
Custom exceptions

8. Object-Oriented Programming (OOP)

8.1 Classes and Objects

Defining classes
Creating instances
Instance attributes and methods
The init method
The self parameter

8.2 OOP Principles

Encapsulation
Inheritance and super()
Polymorphism
Class methods and static methods
Property decorators

8.3 Special Methods

str and repr
len, getitem, setitem
Operator overloading
Context managers (enter, exit)

9. Modules and Packages

9.1 Using Modules

Importing modules
from...import statements
Module aliases
The name variable

9.2 Creating Modules and Packages

Creating your own modules
Package structure
init.py files
Relative vs absolute imports

10. Intermediate Concepts

10.1 Iterators and Generators

Understanding iterators
The iter() and next() functions
Creating generators with yield
Generator expressions

10.2 Decorators

Function decorators
Creating custom decorators
Decorators with arguments
Class decorators

10.3 Context Managers

Understanding context managers
Creating custom context managers
Using contextlib

11. Standard Library Highlights

11.1 Commonly Used Modules

datetime and time
collections (Counter, defaultdict, namedtuple, deque)
itertools
functools
math and random

11.2 System and OS Interaction

sys module
os module
subprocess
argparse for command-line arguments

12. Advanced Topics

12.1 List, Dict, and Set Advanced Techniques

Copying vs referencing
Deep copy vs shallow copy
ChainMap and other advanced collections

12.2 Functional Programming

map, filter, reduce
Partial functions
Higher-order functions

12.3 Type Hints and Annotations

Basic type hints
Optional and Union types
Type checking with mypy

13. Testing and Debugging

13.1 Testing

Writing unit tests with unittest
Using pytest
Test-driven development basics
Mocking and fixtures

13.2 Debugging

Using print debugging effectively
Python debugger (pdb)
Understanding tracebacks
Common debugging strategies

14. Working with External Libraries

14.1 Package Management

pip basics
requirements.txt
Virtual environments (venv)

14.2 Popular Libraries Introduction

requests (HTTP library)
pandas (data analysis)
numpy (numerical computing)
matplotlib (plotting)

Notes for Learners

This curriculum is designed to be flexible - you don't need to go in order
Some topics build on others, so check prerequisites
Return to difficult topics as many times as needed
Ask Claude to generate assignments at appropriate difficulty levels
Request additional practice on topics where you struggle