🐍 42 Python Bootcamp

Master Python from scratch through peer-to-peer learning at 42

"The way of the sword is found in walking. There is nothing outside of this." — Musashi Miyamoto

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📚 Overview

This is my journey through the 42 School AI Bootcamp — a comprehensive Python curriculum designed to take you from zero to hero. The bootcamp covers everything from basic syntax to advanced topics like NumPy, data structures, and functional programming.

Status: 🚀 In Progress
School: 42 Paris
Focus: Python fundamentals, algorithms, data manipulation

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🎯 What You'll Find Here

✅ Completed Modules

• Module 00 - Basics 0 (Setup, Hello World, Variables)
• Module 01 - Basics 1 (Functions, Loops, Conditionals)
• Module 02 - Basics 3 (Advanced functions, decorators, context managers)
  • 🔹 ft_reduce — Functional programming with iterables
  • 🔹 what_are_the_vars — Dynamic attributes & introspection
  • 🔹 Log decorator — Timing & performance monitoring
  • 🔹 CsvReader — File handling & context managers

🔄 Current Module

• Module 03 - NumPy (Scientific computing, arrays, matrices)

📋 Upcoming

• Module 04+ - Data structures, algorithms, OOP deep-dive

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🛠️ Key Concepts Learned

Functional Programming

• map(), filter(), reduce()
• Lambda functions & closures
• Function composition & decorators

Advanced Functions

• Decorators with parameters
• Context managers (__enter__, __exit__)
• Generator functions & yield

File I/O & Data Handling

• Reading/writing CSV files
• Validation & error handling
• Memory-efficient data processing

Introspection & Metaprogramming

• getattr(), setattr(), hasattr()
• Dynamic attribute detection
• Type checking & validation

Timing & Performance

• time.perf_counter() for precise measurements
• Converting nanoseconds to human-readable format
• Decorator-based profiling

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💡 Notable Exercises

1️⃣ ft_reduce - Functional Reduce

Implements Python's reduce() with custom logic.
Master: Iterables, accumulators, edge cases

2️⃣ what_are_the_vars - Dynamic Introspection

Detects conflicting variable names in function scope.
Master: getattr(), try-except, dynamic analysis

3️⃣ Log Decorator - Performance Monitoring

Wraps functions to log execution time with formatting.
Master: Decorators, timing, string manipulation

4️⃣ CsvReader - Context Manager

Custom CSV reader with corruption detection.
Master: Context managers, file handling, validation

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📖 Skills Developed

Category	Skills
Python Fundamentals	Syntax, data types, control flow
Functional Programming	Map, filter, reduce, decorators
File I/O	Reading, writing, parsing CSV
OOP	Classes, inheritance, context managers
Algorithms	Sorting, searching, optimization
Data Science	NumPy, vectorization, matrices
Testing	Unit tests, assertions, debugging

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🔧 Tech Stack

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📊 Progress

Module 00: ████████████████████ 100% ✅
Module 01: ████████████████████ 100% ✅
Module 02: ████████████████████ 100% ✅
Module 03: ████████░░░░░░░░░░░░  40% 🔄
Module 04: ░░░░░░░░░░░░░░░░░░░░   0% 📋

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🤝 Contributing

This is a personal learning project, but feel free to:

• ⭐ Star if you find it helpful
• 🔍 Review the code and suggest improvements
• 💬 Discuss Python concepts
• 🐛 Report any issues

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📚 Resources Used

• Official Python Docs: https://docs.python.org/3/
• Real Python: https://realpython.com/
• 42 School Intranet: Internal curriculum materials
• PEP 8: Python style guide

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Made at 42 Paris