Python Piscine — 42 School

User:jericard

This repository contains the completed modules from the 42 School Python Piscine. Each module introduces a new set of skills, building upon the previous ones to progressively master the language.

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Index

• Module00 — Python Fundamentals
• Module01 — Object-Oriented Programming
• Module02 — Exception Handling
• Module03 — Advanced Data Structures
• Module04 — File Input/Output
• Module05 — Abstract Classes and Polymorphism
• Module06 — Packages and Module System
• Module07 — Advanced Design Patterns
• Module08 — Virtual Environments and Configuration
• Module09 — Data Validation with Pydantic
• Module10 — Functional Programming

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Module00 — Python Fundamentals

Objective: Introduction to basic Python syntax. Covers defining functions with type annotations, handling variables, reading user input, applying conditionals, iterating with loops, formatting strings with f-strings, and building both iterative and recursive solutions. The exercises follow a garden and harvest theme.

Exercise	Main concept
ft_hello_garden.py	Function definition and type annotations
ft_plot_area.py	Variables, user input, and arithmetic
ft_harvest_total.py	Summing multiple inputs
ft_plant_age.py	if/else conditionals
ft_water_reminder.py	More conditionals with numeric comparisons
ft_count_harvest_*.py	for loops vs. recursion
ft_garden_summary.py	String formatting with f-strings
ft_seed_inventory.py	Functions with multiple parameters and conditional logic

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Module01 — Object-Oriented Programming

Objective: Master the pillars of OOP in Python. Covers designing classes with __init__ and __str__, applying encapsulation through private attributes and getters/setters, building inheritance hierarchies using super(), and exploring static methods, class methods, and nested classes. The entire module uses a plant and garden ecosystem as its metaphor.

Exercise	Main concept
ft_garden_intro.py	Script structure with if __name__ == "__main__"
ft_garden_data.py	Basic class with __init__ and __str__
ft_plant_growth.py	Instance methods that modify state
ft_plant_factory.py	Creating multiple instances and typed lists
ft_garden_security.py	Encapsulation: private attributes, getters and setters
ft_plant_types.py	Multiple inheritance: Plant → Flower, Tree, Vegetable
ft_garden_analytics.py	Nested classes, static methods, class methods, polymorphism

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Module02 — Exception Handling

Objective: Learn to write robust code through Python's exception system. Covers try/except blocks for specific error types, the finally clause to guarantee cleanup, using raise to throw exceptions manually, and creating custom exception hierarchies that inherit from Exception. The context is a garden management system with watering and plant health errors.

Exercise	Main concept
ft_first_exception.py	Basic try/except, ValueError, error codes
ft_different_errors.py	Multiple exception types in a single block
ft_custom_errors.py	Custom exception classes with inheritance (GardenError, PlantError, WaterError)
ft_finally_block.py	finally clause for guaranteed cleanup
ft_raise_errors.py	Explicit raise with descriptive messages
ft_garden_management.py	Combining all concepts: error recovery patterns

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Module03 — Advanced Data Structures

Objective: Explore Python's native collections beyond lists: tuples, sets, and nested dictionaries. Also covers command-line arguments (sys.argv), generators with yield, and all three comprehension forms (list, dict, and set comprehensions). The theme revolves around video game analytics.

Exercise	Main concept
ft_command_quest.py	sys.argv, argument parsing
ft_score_analytics.py	Lists: sum, average, min, max
ft_coordinate_system.py	Tuples, unpacking, 3D distance calculation
ft_achievement_tracker.py	Sets: union, intersection, difference
ft_inventory_system.py	Nested dictionaries, iteration, .items()
ft_data_stream.py	Generators with yield (primes, Fibonacci, events)
ft_analytics_dashboard.py	List, dictionary, and set comprehensions

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Module04 — File Input/Output

Objective: Handle text files and I/O streams in Python. Covers opening modes (r, w), the importance of closing files correctly, using context managers (with) as best practice, accessing standard streams (sys.stdin, sys.stdout, sys.stderr), and handling file access errors such as FileNotFoundError and PermissionError. The theme is a file archive and vault system.

Exercise	Main concept
ft_ancient_text.py	Reading files with open() and manual close
ft_archive_creation.py	Writing files and FileExistsError
ft_stream_management.py	sys.stdin, sys.stdout, sys.stderr, readline() and write()
ft_vault_security.py	Context managers (with) for safe file handling
ft_crisis_response.py	Multiple exceptions: FileNotFoundError, PermissionError

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Module05 — Abstract Classes and Polymorphism

Objective: Deepen OOP knowledge through abstract base classes (ABC) that define mandatory interfaces. Covers implementing multiple concrete classes that fulfill the same contract, practicing true polymorphism (a function works with any subtype without knowing it), and introducing duck typing with Protocol for composition without inheritance. The scenario is a data processing pipeline with different input types.

Exercise	Main concept
data_processor.py	ABC, abstract methods, three concrete implementations (NumericProcessor, TextProcessor, LogProcessor)
data_stream.py	Polymorphic orchestrator, @staticmethod for validation, automatic routing
data_pipeline.py	Duck typing with Protocol, CSV and JSON export plugins

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Module06 — Packages and Module System

Objective: Understand how Python organizes code into packages and modules. Covers different import styles (import module, from module import name), subpackage structure with __init__.py, controlled symbol exposure with __all__, and import aliasing. The module uses an alchemy package (alchemy) with subpackages for spells and recipes.

Exercise	Main concept
ft_alembic_0.py / ft_alembic_1.py	import module vs. from module import name
ft_distillation_*.py	Imports from nested subpackages
ft_transmutation_*.py	Full namespace paths in deep hierarchies
alchemy/__init__.py	__all__, aliasing with as, re-exporting subpackages

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Module07 — Advanced Design Patterns

Objective: Apply classic software engineering design patterns in Python. Covers the Factory Pattern (creating objects without specifying the concrete class), the Mixin Pattern (adding capabilities through multiple inheritance), and the Strategy Pattern (encapsulating interchangeable algorithms). The scenario is a Pokémon-style creature battle system.

Exercise	Main concept
ex0/ — battle.py	Factory Pattern: CreatureFactory, FlameFactory, AquaFactory
ex1/ — capacitor.py	Mixin interfaces: HealCapability, TransformCapability, multiple inheritance
ex2/ — tournament.py	Strategy Pattern: NormalStrategy, DefensiveStrategy, AggressiveStrategy, isinstance() for dynamic dispatch

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Module08 — Virtual Environments and Configuration

Objective: Master the infrastructure needed for real Python projects. Covers creating and detecting virtual environments (venv), managing dependencies with pip and poetry, consuming external APIs with requests, analyzing data with pandas and numpy, generating charts with matplotlib, and handling sensitive configuration through environment variables with python-dotenv. The theme is the Matrix universe.

Exercise	Main concept
construct.py	Virtual environment detection, sys.prefix, site.getsitepackages()
loading.py	Dependencies with importlib.metadata, Binance API, data analysis with pandas/numpy, visualization with matplotlib
oracle.py	Environment variables with dotenv, environment-based config (dev/prod), secret validation

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Module09 — Data Validation with Pydantic

Objective: Use Pydantic v2 to guarantee data integrity in Python. Covers creating models with BaseModel, declaring field constraints with Field (numeric ranges, string lengths, default values), defining Enum for controlled values, building custom validators with @model_validator for cross-field business rules, and composing nested models with collection-level validation. The scenario is a space station.

Exercise	Main concept
ex0/space_station.py	BaseModel, Field with ge, le, min_length, model_validate(), ValidationError
ex1/alien_contact.py	Enum, @model_validator(mode='after'), cross-field validations
ex2/space_crew.py	Nested models (List[CrewMember]), collection validators, experience and leadership rules

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Module10 — Functional Programming

Objective: Master the functional programming paradigm in Python. Covers lambda functions, filter(), map(), and sorted() with custom keys; building higher-order functions that receive and return functions; exploring closures and the nonlocal keyword for encapsulated state; using the functools module (reduce, partial, lru_cache, singledispatch); and implementing decorators with and without parameters using @functools.wraps. The context is a world of wizards and spells.

Exercise	Main concept
ex0/lambda_spells.py	Lambdas, sorted(), filter(), map(), max(), min() with key functions
ex1/higher_magic.py	Higher-order functions, composition, Callable type hints
ex2/scope_mysteries.py	Closures, nonlocal, stateful functions, functional factory pattern
ex3/functools_artifacts.py	reduce, partial, lru_cache, singledispatch
ex4/decorator_mastery.py	Simple and parameterized decorators, @functools.wraps, timer, validator, retry

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42 School — Python Piscine | jericard