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Chapter 18: Lists, Tuples, and Dictionary

This chapter teaches Python's three foundational collection structures: lists (mutable sequences), tuples (immutable sequences), and dictionaries (key-value mappings). You'll learn when to use each structure, how to manipulate them effectively, and how to combine them in real-world applications.

By the end of this chapter, you'll build a complete Data Processing Pipeline that ingests CSV data, filters it with comprehensions, aggregates statistics with dictionaries, and outputs formatted reports—demonstrating how all three structures work together in production code.

What You'll Learn​

Core Concepts (46+ unique concepts across 11 lessons)​

Lists (Lessons 1-5):

  • Creating and accessing lists with type hints
  • Indexing, slicing, and length operations
  • Mutation methods: append(), extend(), insert(), remove(), pop(), clear()
  • Sorting and reversing: sort() vs sorted(), reverse() vs [::-1]
  • List comprehensions with filtering
  • Aliasing vs copying

Tuples (Lesson 6):

  • Immutability as a design guarantee
  • Single-element tuple syntax (1,)
  • Unpacking for multiple assignment
  • Using tuples as dict keys (hashable property)
  • When to choose tuples over lists

Dictionaries (Lessons 7-9):

  • Key-value mappings with union types
  • CRUD operations: create, read, update, delete
  • Safe access with .get() and in operator
  • Iteration: .keys(), .values(), .items()
  • Dict comprehensions for transformation
  • Accumulator patterns for aggregation

Architectural Thinking (Lessons 10-11):

  • Decision matrix: When to use which structure
  • Performance implications (O(1) vs O(n))
  • Mutability vs immutability trade-offs
  • Integration patterns in real applications