Chapter 4 — Control Flow
Making decisions in Python
Branching, conditions, and controlling what runs when.
Chapter 5 — Data Structures
How Python stores and organises data
Lists, tuples, sets, and dictionaries — explained with the official docs as the base.
§ 5.1
Data Structures
Lists — All Methods Explained
Every list method from the Python docs — append, extend, insert, sort, pop, and more — with the famous fruits example.
append / extend
sort vs sorted
pop / remove
index / count
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§ 5.1.1 / 5.1.2
Data Structures
Lists as Stack & Queue
Using lists as a LIFO stack with append/pop, why lists are slow as queues, and how collections.deque fixes it.
stack (LIFO)
queue (FIFO)
collections.deque
time complexity
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§ 5.1.3
Data Structures
List Comprehensions
Build a new list from an existing one in one readable line — filtering, transforming, and combining in a single expression.
syntax breakdown
filtering with if
multiple for clauses
real-world uses
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§ 5.1.4
Data Structures
Nested List Comprehensions
Comprehensions inside comprehensions — matrix transposition, 2D data, and when to use zip() instead.
matrix transpose
inner comp. evaluation
zip(*matrix)
flatten 2D list
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§ 5.3
Data Structures
Tuples and Sequences
Immutable sequences — what makes them different from lists, when to use them, and how packing and unpacking work.
immutability
tuple packing
sequence unpacking
singleton tuples
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§ 5.4
Data Structures
Sets
Unordered collections with no duplicates — built for fast membership testing and mathematical set operations.
union / intersection
difference
set comprehensions
frozenset
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§ 5.5
Data Structures
Dictionaries
Key-value pairs — Python's most versatile data structure. get(), comprehensions, nested dicts, and all 17 methods.
get() vs d[key]
dict comprehensions
nested dicts
list(d) / sorted(d)
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Mini Projects
Build something real
Short projects that bring multiple concepts together — the best way to make things stick.
Coming Soon
More pages in progress
These sections are being written — same format, same quality, dropping soon.
Coming soon
for Loops
§ 4.2 — Iterating over sequences, the range() function, break, continue, and the else clause on loops.
Coming soon
While Loops
Condition-based looping — when to use while instead of for, infinite loops, and break/continue patterns.
Coming soon
Functions
§ 4.7 — Defining functions, default arguments, *args and **kwargs, return values, and docstrings.
Coming soon
Lambda Expressions
§ 4.9 — Anonymous functions, when to use lambda vs def, and practical uses with map(), filter(), and sorted().
Coming soon
Variables and Data Types
Integers, floats, strings, booleans — Python's basic types explained with type conversion and common operations.
Coming soon
String Methods
Everything you can do with strings — split, join, strip, replace, format, f-strings, and more.
Coming soon
Error Handling
try, except, finally, and raise — how to handle errors gracefully instead of letting your program crash.
Coming soon
Modules and Imports
§ 6 — How to import and use Python's standard library, create your own modules, and understand namespaces.
Coming soon
File Handling
Reading and writing files — open(), read(), write(), with statements, and working with CSV and JSON.
Coming soon
Classes and Objects
§ 9 — Object-oriented Python. Defining classes, __init__, instance methods, inheritance, and why OOP matters.
Not sure where to start?
If you're brand new to Python, start with if Statements — it's short, fundamental, and sets up everything that comes after. If you've got the basics down, jump straight to Lists or Dictionaries.
Start with if Statements →