Python Fundamentals

Overview

This skill covers the foundational elements of Python programming including syntax, data types, control structures, functions, object-oriented programming, and the standard library.

Learning Objectives

• Write clean, Pythonic code following PEP 8 guidelines
• Master all Python data structures (lists, tuples, dicts, sets)
• Understand and implement object-oriented programming concepts
• Navigate and utilize the Python standard library effectively
• Manage virtual environments and packages with pip/venv

Core Topics

1. Python Syntax & Data Types

• Variables and naming conventions
• Numeric types (int, float, complex)
• Strings and string methods
• Boolean logic and None
• Type hints (PEP 484)
• F-strings and formatting

Code Example:

# Type hints and f-strings
def greet_user(name: str, age: int) -> str:
    return f"Hello {name}, you are {age} years old!"

# Using the function
message = greet_user("Alice", 30)
print(message)  # Hello Alice, you are 30 years old!

2. Control Flow & Functions

• Conditional statements (if/elif/else)
• Loops (for, while)
• List/dict/set comprehensions
• Function parameters and arguments
• Lambda functions
• Decorators basics

Code Example:

# List comprehension with conditional
numbers = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
even_squares = [x**2 for x in numbers if x % 2 == 0]
print(even_squares)  # [4, 16, 36, 64, 100]

# Decorator example
def timing_decorator(func):
    import time
    def wrapper(*args, **kwargs):
        start = time.time()
        result = func(*args, **kwargs)
        end = time.time()
        print(f"{func.__name__} took {end - start:.4f} seconds")
        return result
    return wrapper

@timing_decorator
def slow_function():
    import time
    time.sleep(1)
    return "Done!"

3. Object-Oriented Programming

• Classes and instances
• Inheritance and composition
• Polymorphism and duck typing
• Encapsulation (public/private)
• Magic methods (init, str, repr, etc.)
• Abstract base classes

Code Example:

from abc import ABC, abstractmethod

class Vehicle(ABC):
    def __init__(self, brand: str, model: str):
        self.brand = brand
        self.model = model

    @abstractmethod
    def start_engine(self) -> str:
        pass

    def __str__(self) -> str:
        return f"{self.brand} {self.model}"

class Car(Vehicle):
    def __init__(self, brand: str, model: str, doors: int):
        super().__init__(brand, model)
        self.doors = doors

    def start_engine(self) -> str:
        return f"{self} engine started with {self.doors} doors"

# Usage
car = Car("Toyota", "Camry", 4)
print(car.start_engine())  # Toyota Camry engine started with 4 doors

4. Standard Library

• File operations (open, read, write)
• Path handling with pathlib
• datetime for date/time operations
• collections (Counter, defaultdict, namedtuple)
• itertools and functools
• json and csv modules

Code Example:

from pathlib import Path
from datetime import datetime, timedelta
from collections import Counter
import json

# Path operations
data_dir = Path("data")
data_dir.mkdir(exist_ok=True)

config_file = data_dir / "config.json"
config = {"app_name": "MyApp", "version": "1.0.0"}

# Write JSON
with open(config_file, "w") as f:
    json.dump(config, f, indent=2)

# Read JSON
with open(config_file, "r") as f:
    loaded_config = json.load(f)

# Date operations
today = datetime.now()
next_week = today + timedelta(days=7)
formatted = today.strftime("%Y-%m-%d %H:%M:%S")

# Counter for frequency analysis
words = ["apple", "banana", "apple", "cherry", "banana", "apple"]
word_count = Counter(words)
print(word_count.most_common(2))  # [('apple', 3), ('banana', 2)]

Hands-On Practice

Project 1: File Management Tool

Build a command-line tool that organizes files by extension.

Requirements:

• Accept directory path as input
• Scan for files recursively
• Group files by extension
• Move files to organized folders
• Generate summary report

Key Skills: pathlib, file I/O, os module

Project 2: Contact Manager (OOP)

Create a contact management system using object-oriented principles.

Requirements:

• Contact class with name, email, phone
• ContactBook class to manage contacts
• CRUD operations (Create, Read, Update, Delete)
• Search and filter functionality
• Persist data to JSON file

Key Skills: OOP, JSON serialization, data structures

Project 3: Text Analyzer

Analyze text files for statistics and patterns.

Requirements:

• Word frequency analysis
• Character count (with/without spaces)
• Average word length
• Most common words (exclude stop words)
• Export results to CSV

Key Skills: String manipulation, collections.Counter, CSV

Assessment Criteria

• [ ] Write PEP 8 compliant Python code
• [ ] Use appropriate data structures for different scenarios
• [ ] Implement classes with proper OOP principles
• [ ] Utilize standard library modules effectively
• [ ] Manage virtual environments and dependencies
• [ ] Handle exceptions properly
• [ ] Write clear docstrings and comments

Resources

Official Documentation

• Python.org - Official Python documentation
• PEP 8 - Python style guide
• Python Tutorial - Official tutorial

Learning Platforms

• Real Python - Comprehensive tutorials
• Python for Everybody - Free course
• Automate the Boring Stuff - Practical Python

Tools

• VS Code - Recommended editor
• PyCharm - Professional IDE
• pylint - Code linter
• black - Code formatter

Next Steps

After mastering Python fundamentals, proceed to:

• Django Framework - Build web applications
• Pandas Data Analysis - Work with data
• Pytest Testing - Write comprehensive tests
• Asyncio Programming - Asynchronous Python