Python Foundations – Curated Learning Path

Overview

This repository hosts a structured and curated learning path for mastering the Python programming language. It aggregates and synthesizes curriculum materials from industry-standard sources including CS50 (Harvard), Apna College, CodeWithHarry, and freeCodeCamp.

The content is designed for engineers and developers seeking a rigorous understanding of Python fundamentals, best practices in software design, and readiness for advanced domains such as backend development and data engineering. This is not strictly a tutorial repository, but a record of disciplined engineering practice.

Goals

• Foundational Mastery: Establish a deep understanding of Python's memory model, data structures, and execution flow.
• Code Quality: Enforce clean, readable, and PEP 8 compliant code standards.
• Engineering Discipline: cultivate habits of testing, documentation, and version control from the outset.
• System Readiness:Prepare for complex systems programming, including concurrency and backend architecture.

Learning Philosophy

The approach adopted in this repository prioritizes "first principles" thinking over syntax memorization.

1. Concept Acquisition: Theoretical study from curated high-quality lectures.
2. Implementation: Writing code from scratch to solve specific algorithmic problems.
3. Analysis: documenting edge cases, performance implications, and language behavior options.
4. Refinement: Refactoring code for readability and efficiency, followed by rigorous unit testing.
5. Application: Integrating concepts into small-scale, modular projects.

Repository Structure

The repository is organized into progressive modules, each adhering to a specific domain of the language.

python-foundations/
├── 00-introduction-setup/      # Environment configuration and CLI basics
├── 01-variables-datatypes/     # Memory management and type systems
├── 02-strings-conditionals/    # Text processing and control flow logic
├── 03-lists-tuples/            # Sequence types and mutability
├── 04-dictionaries-sets/       # Hash maps and set theory
├── 05-loops/                   # Iteration protocols and efficiency
├── 06-functions-recursion/     # Stack frames, scope, and functional patterns
├── 07-file-io/                 # Persistence and context management
├── 08-oops/                    # Inheritance, polymorphism, and encapsulation
├── 09-exceptions/              # Error handling strategies
├── 10-unit-testing/            # Test-driven development with pytest
├── 11-regex/                   # Pattern matching and text extraction
├── 12-advanced-python/         # Decorators, generators, and introspection
├── 13-concurrency/             # Threading and multiprocessing
├── projects/                   # Capstone applications
│   ├── cli-todo/
│   └── expense-tracker/
├── requirements.txt            # Dependency definitions
└── README.md

Topics Covered

• Core Syntax & Semantics: Complete coverage of built-in types and operators.
• Data Structures: In-depth analysis of list implementations, hashing mechanisms in dictionaries, and algorithmic complexity.
• Control Flow: Advanced iteration, list comprehensions, and structural pattern matching.
• Object-Oriented Programming: Design patterns, dunder methods, and interface design.
• Software Testing: Unit testing methodologies using pytest.
• System Operations: File I/O, serialization (json, pickle), and environment management.
• Advanced Concepts:
  • Decorators and closures
  • Iterators and Generators
  • Context Managers
  • Regular Expressions
  • Concurrency models

Tools & Technologies

• Language: Python 3.x
• Testing: pytest
• Version Control: Git & GitHub
• Environment: Virtual Environments (venv)
• Editor: VS Code

Projects

CLI To-Do Application

A command-line interface application demonstrating distinct separation of concerns, persistent storage, and user input validation.

File-based Expense Tracker

An analytical tool focusing on data serialization, file handling reliability, and basic data aggregation algorithms.

Progress Status

This repository is currently Active. Content is being added and refined continuously as the learning path progresses.

License

This project is released under the MIT License. See the LICENSE file for details.

Acknowledgements

Curriculum structure and concepts are derived from the following educational resources:

• CS50 (Harvard University): Introduction to Computer Science
• Apna College: Comprehensive Python Tutorials
• CodeWithHarry: Practical Python implementation
• freeCodeCamp: Specialized modules and project ideas