This project has been created as part of the 42 curriculum by wkratos.

PythonPool

A structured collection of Python exercises completed across eleven progressive modules, from basic syntax and control flow to object-oriented design, package management, data validation, functional programming, closures, and decorators.

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Overview

PythonPool documents my progression through Python by combining focused exercises with small themed applications.

The repository covers:

• Python syntax and control structures
• Functions and recursion
• Object-oriented programming
• Inheritance and encapsulation
• Exception handling
• Command-line arguments
• Built-in collections
• Generators and data streams
• File and stream management
• Abstract classes and protocols
• Packages and import systems
• Virtual environments and dependencies
• Environment variables
• Pydantic data validation
• Functional programming
• Closures and decorators

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Repository Structure

PythonPool/
├── Module00/
├── Module01/
├── Module02/
├── Module03/
├── Module04/
├── Module05/
├── Module06/
├── Module07/
├── Module08/
├── Module09/
├── Module10/
├── .gitignore
└── README.md

Each module contains independent exercises that focus on a specific group of Python concepts.

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Module Overview

Module	Main Concepts
Module00	Python basics, input/output, conditions, loops, functions, recursion and type hints
Module01	Classes, objects, attributes, methods, encapsulation, inheritance, class methods and static methods
Module02	Exceptions, custom exceptions, raising errors, cleanup with finally and error-safe program design
Module03	Command-line arguments, lists, tuples, sets, dictionaries, generators and data analysis
Module04	File handling, streams, context management, archive creation and safe resource cleanup
Module05	Abstract base classes, polymorphism, protocols, reusable processors, pipelines and advanced type hints
Module06	Python packages, modules, imports, relative imports, nested packages and circular-import management
Module07	Advanced OOP, abstract interfaces, multiple inheritance, factories, strategies and tournament systems
Module08	Virtual environments, package installation, dependency management and environment variables
Module09	Structured data models, Pydantic validation, enums, field constraints and model-level validation
Module10	Lambdas, higher-order functions, closures, scope, functools, decorators and function composition

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Highlights

Object-Oriented Programming

The modules gradually introduce:

• class creation;
• instance and class attributes;
• inheritance;
• encapsulation;
• abstract base classes;
• multiple inheritance;
• polymorphism;
• factory and strategy design patterns.

Module07 applies these concepts through a card-game system containing cards, decks, combat interfaces, factories, strategies, a game engine and a tournament platform.

Error Handling

Module02 explores reliable error management through:

• try and except;
• multiple exception types;
• custom exception hierarchies;
• explicit raise statements;
• cleanup using finally;
• validation before state changes.

Generators and Data Processing

The repository includes:

• generator-based streams;
• score and inventory analytics;
• numeric and text processors;
• abstract data streams;
• reusable processing pipelines;
• input, transformation and output stages.

Packages and Imports

Module06 builds a complete nested package structure:

alchemy/
├── elements.py
├── potions.py
├── grimoire/
│   ├── spellbook.py
│   └── validator.py
└── transmutation/
    ├── basic.py
    └── advanced.py

It demonstrates:

• absolute imports;
• relative imports;
• package initialization;
• aliases;
• nested modules;
• circular dependency considerations.

Functional Programming

Module10 focuses on:

• lambda expressions;
• map, filter and sorted;
• higher-order functions;
• closures and nonlocal;
• functools.reduce;
• function composition;
• reusable decorators;
• preserving metadata with functools.wraps.

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Requirements

Most exercises only require:

Python 3.10+

Some later modules use additional packages:

pip install pandas numpy matplotlib requests python-dotenv pydantic

Using a virtual environment is recommended:

python3 -m venv .venv
source .venv/bin/activate
pip install pandas numpy matplotlib requests python-dotenv pydantic

On Windows:

python -m venv .venv
.venv\Scripts\activate
pip install pandas numpy matplotlib requests python-dotenv pydantic

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Running an Exercise

Each exercise can generally be executed independently.

Example:

python3 Module00/ex0/ft_hello_garden.py

Run an object-oriented exercise:

python3 Module01/ex6/ft_garden_analytics.py

Run the card game engine from Module07:

cd Module07
python3 -m ex3.main

Run a functional-programming exercise:

python3 Module10/ex4/decorator_mastery.py

Some exercises accept command-line arguments:

python3 Module03/ex0/ft_command_quest.py hello python 42

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Environment Variables

Module08 contains an environment-configuration exercise.

Create the local environment file from the example:

cp Module08/ex2/.env.example Module08/ex2/.env

Then edit the values before running:

python3 Module08/ex2/oracle.py

The real .env file is intentionally excluded from Git.

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Learning Objectives

The main objectives of this repository were to:

• understand Python syntax and conventions;
• write readable and reusable functions;
• model systems with classes and inheritance;
• handle errors safely;
• work with Python collections effectively;
• process data through generators and pipelines;
• organize code into packages and modules;
• manage project environments and dependencies;
• validate structured data;
• understand functional programming techniques;
• build progressively larger Python applications.

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Notes

• Every module represents a different stage of the learning process.
• Exercises are intentionally kept separate to preserve their original scope.
• The repository contains educational implementations rather than one single production application.
• Some programs use themed scenarios such as gardens, games, alchemy, space stations and magic to demonstrate technical concepts.

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Author

wkratos

42 Network.