Python Notes

Python
Complete Notes

From your very first line of code to advanced OOP — everything you need, in one place.

🎬 Watch alongside! This book is designed to work hand-in-hand with the video series on Sheryians AI on YouTube. Every concept here has a matching video explanation.
made with ❤️  ·  Python Notes
Introduction

What is Python?

🐍 Python in Simple Words

Python is a high-level, general-purpose programming language created by Guido van Rossum and first released in 1991. The name comes not from the snake, but from the British comedy show Monty Python's Flying Circus — because Guido wanted the language to be fun to use.

Python is designed to be simple to read and write. Its syntax looks almost like plain English, which is why it's the most beginner-friendly language in the world — and at the same time, powerful enough to run Instagram, YouTube, and NASA systems.

👶 Easy to Learn

No semicolons, no curly braces, no type declarations. Just clean, readable code that looks like English.

💪 Incredibly Powerful

Used in AI, web development, data science, automation, game dev, cybersecurity and more.

⚙️ How Does Code Actually Run?

Before Python makes sense, you need to understand how computers run code. There are two main approaches — Compiled and Interpreted.

🏗️ Compiled Languages — Build First, Run Later

Think of it like translating an entire book from Hindi to English before giving it to someone. The whole translation happens upfront — this is called compiling. Once compiled, the program runs extremely fast because the computer already has the translation ready.

📝 Source Code
→
🔨 Compiler
→
⚡ Machine Code
→
🖥️ Runs!

Examples: C, C++, Rust, Go

🎭 Interpreted Languages — Translate Line by Line

Think of it like a live interpreter at a conference who translates speech sentence by sentence as the speaker talks. There's no pre-translation — each line is read, translated, and executed one at a time.

📝 Source Code
→
🔄 Interpreter
(line by line)
→
🖥️ Runs!

Examples: Python, JavaScript, Ruby

🐍
Where does Python fit? Python is an interpreted language. When you run a Python file, the Python interpreter reads your code line by line and executes it immediately. That's why errors show up one at a time — it stops at the first problem it hits.

⚖️ Compiled vs Interpreted — Side by Side

Feature Compiled Interpreted (Python)
Translation All at once before running Line by line while running
Speed ⚡ Faster execution 🐢 Slightly slower
Error Detection All errors found before running Stops at the first error
Portability Platform-specific binary Runs anywhere Python is installed
Development Speed Slower to write & test ✅ Fast to write & test
Examples C, C++, Rust, Go Python, JavaScript, Ruby
💡
Fun fact: Python actually compiles your code to bytecode (.pyc files) first, then interprets that bytecode using the Python Virtual Machine (PVM). So technically it's a bit of both — but we call it interpreted because you never see or manage the compiled step.

🌍 Why Python? Where is it Used?

Python's simplicity and the massive ecosystem of libraries make it useful in almost every field of technology. Here's where Python truly shines:

🤖

AI & Machine Learning

Libraries like TensorFlow, PyTorch, and scikit-learn make Python the #1 language for AI. ChatGPT, Gemini, and most modern AI tools are built with Python.

📊

Data Science & Analytics

Pandas, NumPy, Matplotlib — companies use Python to analyse millions of rows of data and turn them into insights and charts.

🌐

Web Development

Django and Flask are powerful Python frameworks. Instagram, Pinterest, and Spotify's backend all run on Python.

⚙️

Automation & Scripting

Automate boring tasks — rename 1000 files, scrape websites, send automated emails, schedule tasks. Python makes it simple.

🔐

Cybersecurity

Python is the go-to language for ethical hacking and penetration testing. Tools like Metasploit and many security scripts are Python-based.

🎮

Game Development

Pygame lets you build 2D games with Python. It's a great way to practise programming while building something fun.

✨ Key Features of Python

🧹 Clean SyntaxReads like English. Indentation is mandatory, making all Python code look consistent.
🆓 Free & Open SourcePython is completely free to download, use, and distribute — even commercially.
📦 Huge Library EcosystemPyPI has over 400,000 packages. Whatever you want to build, there's probably already a library for it.
🌍 Cross-PlatformWrite once, run anywhere — Windows, macOS, Linux. Same Python code works on all of them.
🔗 Great CommunityMillions of developers, endless tutorials, Stack Overflow answers, and active forums.
🧩 Multi-ParadigmSupports functional, procedural, and object-oriented programming styles.

🐍 Python vs Other Languages — A Quick Taste

Let's print "Hello, World!" in three different languages to see how clean Python really is:

Java

public class Main { public static void main(String[] args) { System.out.println("Hello, World!"); } }

5 lines just to print one thing 😅

🐍 Python

print("Hello, World!")

1 line. That's it. ✅

🚀
You're all set! Now that you know what Python is, where it came from, how it runs, and where it's used — let's get it installed and write some actual code. Head to Chapter 01!
Chapter 01

Installation

Downloading Python

  • Open any browser → go to python.org → download Python for your operating system.
  • Run the installer. This gives you the Python Virtual Machine which converts your code into byte code that your computer can run.
⚠️
ImportantCheck "Add Python to PATH" during installation on Windows — otherwise your terminal won't find Python!

Downloading an IDE

An IDE (Integrated Development Environment) is where you write and run your code. Popular choices are VS Code, PyCharm, and Jupyter — but we'll use VS Code throughout this book.

Setting Up VS Code

  • Open VS Code → go to the Extensions panel (Ctrl+Shift+X)
  • Search for and install: Python (by Microsoft) and Code Runner
  • Create a new file ending in .py and you're ready to go!
Chapter 02

Comments & Variables

Comments

Comments are notes you write in your code for yourself (or other developers). Python completely ignores them — they don't affect how the program runs.

# This is a single-line comment """ This is a multiline comment written using a docstring """
💡
Python doesn't have a true multiline comment syntax. We "borrow" the triple-quote string """...""" for this purpose.

Variables

Think of a variable as a labelled box — you put a value inside and refer to it by the label whenever you need it.

name = "Akarsh" age = 20 city = "Indore"
🚫
Rules — these will cause errors:
❌  1name = "x"  → can't start with a number
❌  my name = "x"  → no spaces allowed
❌  my-name = "x"  → no special characters (except underscore)

Naming Conventions

camelCase → myVariableName PascalCase → MyVariableName snake_case → my_variable_name # ✅ Python prefers this
Chapter 03

Data Types

What are Data Types?

Every value in Python has a type that tells Python what kind of data it is and what you can do with it. You don't need to declare types — Python figures it out automatically.

The Main Data Types

intWhole numbers: 1, 42, -7
floatDecimal numbers: 3.14, -0.5
complexReal + imaginary: 3+4j
strText in quotes: "hello"
boolOnly two values: True or False
NoneTypeRepresents nothing: None

Checking the Type

print(type(42)) # <class 'int'> print(type(3.14)) # <class 'float'> print(type("hello")) # <class 'str'> print(type(True)) # <class 'bool'>
Chapter 04

Strings & Type Conversion

How Strings Work Internally

Each character in a string is stored with its own Unicode number. That's why strings use more memory than integers.

ord("A") # → 65 (Unicode of A) chr(65) # → "A" (Character from Unicode)

String Indexing

Every character in a string has a position number called an index. Positive indexes count from the left (starting at 0), negative from the right (starting at -1).

a = "Hello" # H e l l o # 0 1 2 3 4 ← positive # -5 -4 -3 -2 -1 ← negative print(a[0]) # H print(a[-1]) # o

String Slicing

Slicing cuts out a piece of a string. Syntax: string[start : stop : step] — note that stop index is excluded.

a = "hello" print(a[1:4]) # ell (index 1,2,3 — 4 excluded) print(a[::-1]) # olleh (reversed!)

Type Conversion

You can convert a value from one type to another using these built-in functions:

int()→ whole number
float()→ decimal number
str()→ text
bool()→ True or False

⚡ Implicit (Automatic)

Python converts automatically when needed.

a = 12 print(a / 2) # 6.0 # int ÷ int → float!

🔧 Explicit (Manual)

You tell Python to convert.

a = 12 a = str(a) print(a) # "12"

The 7 Falsy Values

Everything converts to True with bool() — except these 7 values which become False:

0
0.0
False
""
[]
{}
()
Chapter 05

Input, Output & Operators

Output — print()

name = "Akarsh" age = 20 print("Hello!") # basic print(f"My name is {name}") # f-string print("Name:", name, "Age:", age) # multiple values

Input — input()

⚠️
Remember: input() always returns a string. If you need a number, convert it manually with int() or float().
name = input("What is your name? ") age = int(input("How old are you? ")) print(f"Hello {name}, you are {age} years old!")

Arithmetic Operators

Operator Name Example Result
+ Addition 10 + 3 13
- Subtraction 10 - 3 7
* Multiplication 10 * 3 30
/ Division 10 / 3 3.333…
// Floor Division 10 // 3 3
% Modulus (remainder) 10 % 3 1
** Exponentiation 2 ** 8 256

Comparison Operators

Always return True or False.

Operator Meaning Example Result
== Equal to 5 == 5 True
!= Not equal to 5 != 3 True
> Greater than 5 > 3 True
< Less than 5 < 3 False
>= Greater or equal 5 >= 5 True
<= Less or equal 3 <= 5 True

Logical Operators

Operator Returns True when… Example
and Both conditions are True age > 18 and has_id == True
or At least one condition is True is_admin or is_staff
not Reverses the boolean not is_banned

Assignment Operators

Operator Meaning Equivalent to
+= Add and assign x = x + n
-= Subtract and assign x = x - n
*= Multiply and assign x = x * n
/= Divide and assign x = x / n
//= Floor divide and assign x = x // n
%= Modulus and assign x = x % n
**= Power and assign x = x ** n
Chapter 06

Conditional Statements

Making Decisions in Code

Real programs don't run the same code every time — they make decisions. Conditional statements let your program choose what to do based on a condition. That's why they're also called control flow statements.

if condition: # runs when condition is True elif another_condition: # runs if the above was False, this is True else: # runs when nothing above was True

Types at a Glance

Statement When to use it
if You have one condition to check
if-else Two paths — True or False
if-elif-else Multiple conditions checked one by one

📝 Practice Questions

Q1
Accept two numbers and print the greatest between them.
Input: 14, 7Output: 14 is greater
Q2
Accept gender from user and print a greeting message.
Input: MOutput: Good Morning Sir
Q3
Accept an integer and check if it is even or odd.
Input: 9Output: 9 is Odd
Q4
Accept name and age — check if the user is a valid voter (18+).
Input: Shery, 20Output: Hello Shery, you are a valid voter ✅
Q5
Accept a year and check if it is a leap year.
Input: 2024Output: 2024 is a leap year ✅
Q6 — Temperature Ladder
Accept temperature in °C and print a description.
Input: -5Freezing Cold 🥶
Input: 25Pleasant 😊
Input: 45Very Hot 🔥
Chapter 07

Loops

Why Loops?

Imagine printing "Hello" 100 times. Without loops: 100 lines of code. With a loop: just 2 lines. Loops let you repeat a block of code without rewriting it.

Python has 2 types of loops: for and while.

The Bucket Analogy 🪣

Two buckets, one mug — which loop do you use?

🔢 FOR loop — known iterations

Transfer exactly 4 mugs. You know the count → use for.

🔁 WHILE loop — known condition

Transfer until bucket is empty. You don't know the count, but you know when to stop → use while.

Chapter 08

For Loop

The range() Function

range() generates a sequence of numbers. Think of it as saying "count from here to there".

range(stop) # 0 up to stop-1 range(start, stop) # start up to stop-1 range(start, stop, step)# start, jumping by step list(range(5)) # [0, 1, 2, 3, 4] list(range(1,6)) # [1, 2, 3, 4, 5] list(range(0,10,2)) # [0, 2, 4, 6, 8]

For Loop with Numbers

for i in range(1, 6): print(i) # Output: 1 2 3 4 5

For Loop with Strings

name = "hello" # Method 1 — via index for i in range(len(name)): print(name[i]) # Method 2 — direct (simpler!) for char in name: print(char)

break, continue & else — The Traffic Light Analogy 🚦

🚦 Imagine you're driving through 10 traffic signals on your way home

Each signal = one loop iteration. Here's what each keyword does:

🛑
break
You spot an accident ahead — you immediately stop and take a U-turn. Loop ends completely.
⏭️
continue
One signal is broken — you skip it and keep driving to the next one. Loop skips this iteration.
🏠
else
You crossed all signals with no problems — you reached home safely. Runs only when loop finishes without a break.
for i in range(1, 11): if i == 5: break # stop at signal 5 (accident!) if i == 3: continue # skip signal 3 (broken light) print(f"Signal {i} — passed ✅") else: print("Reached home safely! 🏠") # only if no break

📝 For Loop Questions

Q1
Print "Hello World" n times.
Input: 3Hello World × 3 lines
Q2
Print natural numbers from 1 to n.
Input: 51 2 3 4 5
Q3
Reverse for loop — print n down to 1.
Input: 55 4 3 2 1
Q4
Print the multiplication table of a number.
Input: 55×1=5, 5×2=10 … 5×10=50
Q5
Sum of first n natural numbers.
Input: 5Sum = 15
Q6
Factorial of a number.
Input: 55! = 120
Q7
Print sum of all even and odd numbers in a range separately.
Input: 1 to 10Even sum = 30, Odd sum = 25
Q8
Print all factors of a number.
Input: 121 2 3 4 6 12
Q9
Check if a number is perfect (sum of factors = the number itself).
Input: 66 is a Perfect Number ✅ (1+2+3=6)
Q10
Check if a number is prime.
Input: 1717 is Prime ✅Input: 99 is NOT Prime ❌
Q11
Reverse a string without using built-in functions.
Input: "Python"nohtyP
Q12
Check if a string is a palindrome.
Input: "racecar"Palindrome ✅Input: "hello"Not a palindrome ❌
Q13
Count letters, digits, and special symbols in a string.
Input: "P@#yn26at^&i5ve"Chars=8, Digits=3, Symbols=4
Chapter 09

While Loop

While Loop

The while loop keeps running as long as a condition is True. You use it when you don't know how many times you'll need to repeat.

count = 1 while count <= 5: print(count) count += 1 # Output: 1 2 3 4 5
⚠️
Infinite Loop Danger! Always make sure your condition will eventually become False — otherwise your program runs forever!
💡
While loops also support break, continue, and else exactly like for loops.

📝 While Loop Questions

Q1
Separate each digit of a number and print on a new line.
Input: 12344 → 3 → 2 → 1
Q2
Accept a number and print its reverse.
Input: 1234554321
Q3
Check if a number is palindromic (equal to its reverse).
Input: 121Palindrome ✅Input: 123Not Palindrome ❌
Q4
Build a number guessing game — computer picks a random number, user keeps guessing until correct.
Guess: 50 → Too low! Guess: 75 → Too high! Guess: 63 → 🎉 Correct!
Chapter 10

Functions

What are Functions?

A function is a reusable block of code with a name. Instead of writing the same logic 10 times, you write it once as a function and call it 10 times.

def greet(): print("Hello, welcome to Python!") greet() # ← this is calling the function

Parameters & Arguments

📋 Parameter

The variable name in the function definition. Like a placeholder.

def greet(name): # ← parameter ...

📦 Argument

The actual value you pass when calling the function.

greet("Alice") # ← argument

Types of Arguments

# 1. Positional — order matters def add(a, b): return a + b add(5, 3) # → 8 # 2. Default — works even without passing a value def greet(name="Guest"): print(f"Hello {name}") greet() # Hello Guest greet("Akarsh") # Hello Akarsh # 3. Keyword — pass in any order def info(name, age): print(f"{name} is {age}") info(age=25, name="Akarsh") # order doesn't matter
Chapter 11

Data Structures

The 4 Built-in Data Structures

When you need to store multiple values in one variable, you use a data structure. Python gives you 4 ready to use:

Structure Ordered? Mutable? Duplicates? Access by
List ✅ Yes ✅ Yes ✅ Yes Index
Tuple ✅ Yes ❌ No ✅ Yes Index
Set ❌ No ✅ Yes ❌ No Methods
Dictionary ✅ Yes ✅ Yes Keys: ❌ Key
Chapter 12

List

Creating and Accessing Lists

fruits = ["apple", "banana", "mango"] print(fruits[0]) # apple print(fruits[-1]) # mango print(fruits[0:2]) # ['apple', 'banana'] fruits[1] = "grape" # mutation — lists allow this!

Key List Methods

lst = [3, 1, 4, 1, 5] lst.append(9) # [3,1,4,1,5,9] — add to end lst.insert(0, 0) # [0,3,1,4,1,5,9] — insert at index lst.remove(1) # removes first 1 lst.pop() # removes last element lst.sort() # sort ascending lst.reverse() # reverse in place len(lst) # number of items

📝 List Questions

Q1
Print all positive and negative elements separately.
Input: [3, -1, 4, -5, 9]Positive: [3,4,9] Negative: [-1,-5]
Q2
Find the mean (average) of all list elements.
Input: [10, 20, 30, 40]Mean = 25.0
Q3
Find the greatest element and print its index.
Input: [4, 8, 2, 9, 1]Greatest = 9 at index 3
Q4
Find the second greatest element.
Input: [4, 8, 2, 9, 1]Second greatest = 8
Q5
Check if the list is already sorted.
Input: [1, 3, 5, 7]List is sorted ✅Input: [3, 1, 4]Not sorted ❌
Chapter 13

Tuple

Tuple — The Immutable List

A tuple is exactly like a list, except you cannot change it once created. Use tuples for data that should stay constant — like days of the week, coordinates, or config values.

days = ("Mon", "Tue", "Wed") print(days[0]) # Mon days[0] = "X" # ❌ TypeError — tuples are immutable

Tuple Methods (Only 2!)

t = (1, 2, 3, 2, 1) t.index(2) # → 1 (first position of 2) t.count(2) # → 2 (2 appears twice)
Chapter 14

Set

Set — Unique Values Only

A set automatically removes duplicates and has no guaranteed order. Great for checking membership and performing math-style set operations.

s = {1, 2, 2, 3, 3, 3} print(s) # {1, 2, 3} — duplicates removed!

Set Operations

a = {1, 2, 3, 4} b = {3, 4, 5, 6} a | b # Union → {1,2,3,4,5,6} a & b # Intersection → {3,4} a - b # Difference → {1,2} a ^ b # Symmetric diff→ {1,2,5,6}
Chapter 15

Dictionary

Key-Value Storage

A dictionary stores data as key: value pairs — like a real dictionary where you look up a word (key) to find its meaning (value).

person = {"name": "Akarsh", "age": 20, "city": "Indore"} # Read print(person["name"]) # Akarsh # Update person["age"] = 21 # Add new key person["course"] = "Python" # Delete del person["city"] # Traverse for key, val in person.items(): print(key, "→", val)

📝 Dictionary Questions

Q1
Merge two dictionaries into one.
d1={a:1}, d2={b:2}{a:1, b:2}
Q2
Sum all values in a dictionary.
{"a":10,"b":20,"c":30}Sum = 60
Q3
Count the frequency of each element in a list using a dictionary.
["a","b","a","c","b","a"]{"a":3,"b":2,"c":1}
Q4
Combine two dicts, adding values for common keys.
d1={a:5,b:3}, d2={b:4,c:2}{a:5, b:7, c:2}
Chapter 16

Exception Handling

Errors vs Exceptions

❌ Errors (unfixable)

  • SyntaxError — wrong syntax
  • IndentationError — bad spacing
  • TabError — mixing tabs/spaces

✅ Exceptions (handleable!)

  • ZeroDivisionError
  • TypeError
  • ValueError
  • FileNotFoundError

Handling Exceptions

try: result = 10 / 0 except ZeroDivisionError: print("Can't divide by zero!") else: print("Success:", result) finally: print("This always runs.")
Keyword Purpose
try Wrap the risky code
except Handle the exception
else Runs only if no exception occurred
finally Always runs — good for cleanup
raise Manually throw your own exception
Chapter 17

File Handling

File Modes

Mode Meaning Creates file?
'r' Read only ❌ (must exist)
'w' Write (overwrites!) ✅
'a' Append to end ✅
'x' Create (fails if exists) ✅

Reading & Writing

# Writing with open("notes.txt", "w") as f: f.write("Hello from Python!") # Reading with open("notes.txt", "r") as f: content = f.read() print(content) # Appending with open("notes.txt", "a") as f: f.write("\nAdded a new line!")
✅
Always use the with statement — it automatically closes the file for you, even if an error occurs.
Chapter 18

OOP in Python

Three Ways to Write the Same Program

# Imperative — simple but not reusable a, b = 5, 3 print(a + b) # Functional — reusable def add(a, b): return a + b # Object Oriented — scalable & organised class Calculator: def add(self, a, b): return a + b calc = Calculator() print(calc.add(5, 3))
🎯
OOP key concepts: Classes · Objects · Encapsulation · Inheritance · Polymorphism · Abstraction
Chapter 19

Classes

Class = Blueprint

A class is a blueprint — like an architect's plan for a house. The plan itself isn't a house, but you can build many houses from it. Each house is an object.

class Dog: species = "Canis lupus" # ← Attribute def bark(self): # ← Method print("Woof!") my_dog = Dog() # create object print(my_dog.species) # Canis lupus my_dog.bark() # Woof!
Chapter 20

Objects

Objects = Instances of a Class

🏭
Think of a Bag Factory. The factory has a blueprint (class) that needs material, zips, and pockets. Reebok and Campus both use this blueprint but provide their own specifications — they become two different objects.
class Bag: def __init__(self, material, zips): self.material = material self.zips = zips reebok = Bag("leather", 3) # object 1 campus = Bag("nylon", 2) # object 2 print(reebok.material) # leather print(campus.material) # nylon
Chapter 21

Constructor

__init__ — The Constructor

The constructor is a special method that runs automatically the moment you create an object. You use it to set up the object's initial data.

self is the object itself — it's how the method knows which object's data to set.

class Student: def __init__(self, name, grade): self.name = name # stored on THIS object self.grade = grade s1 = Student("Akarsh", "A") s2 = Student("Shery", "B") print(s1.name) # Akarsh print(s2.name) # Shery
Chapter 22

Attributes & Methods

Attributes

Class Attribute

Shared by all objects of the class.

class Dog: species = "Canis" # class

Instance Attribute

Unique to each object.

def __init__(self, name): self.name = name # instance

Methods

class Example: count = 0 def instance_method(self): # needs self return "Works with object" @classmethod def class_method(cls): # needs cls return cls.count @staticmethod def static_method(): # needs neither return "Just a helper function"
Chapter 23

Inheritance

Child Inherits from Parent

Just like children inherit traits from parents, a child class automatically gets all attributes and methods of the parent class.

class Animal: def breathe(self): print("Breathing...") class Dog(Animal): # Dog inherits from Animal def bark(self): print("Woof!") d = Dog() d.breathe() # inherited from Animal ✅ d.bark() # Dog's own method ✅

Types of Inheritance

# Single — one parent class Child(Parent): ... # Multiple — two parents class Child(Parent1, Parent2): ... # MRO: Parent1's methods take priority # Multilevel — grandparent → parent → child class Child(Parent): def __init__(self, name, grade): super().__init__(name) # call Parent's __init__ self.grade = grade
Chapter 24

Polymorphism

Same Name, Different Behaviour

Polymorphism = "many forms". The same method name behaves differently depending on which object calls it.

class Dog: def speak(self): print("Woof! 🐕") class Cat: def speak(self): print("Meow! 🐈") class Duck: def speak(self): print("Quack! 🦆") # Same function call — different results! for animal in [Dog(), Cat(), Duck()]: animal.speak()
🦆
Duck Typing: "If it walks like a duck and quacks like a duck — it's a duck." Python doesn't care about the type of object, only whether it has the method you're calling.
Chapter 25

Encapsulation

Hiding Internal Details

Encapsulation means keeping data safe inside a class and only exposing what's necessary. Think of it like a medicine capsule — the drug is inside, protected.

class BankAccount: def __init__(self): self.owner = "Akarsh" # public self._balance = 1000 # protected (convention) self.__pin = 1234 # private (enforced) def get_balance(self): # safe accessor return self._balance acc = BankAccount() print(acc.owner) # ✅ Akarsh print(acc._balance) # ⚠️ works but bad practice print(acc.__pin) # ❌ AttributeError
Chapter 26

Abstraction

Hide Complexity, Show Simplicity

Abstraction means showing only what the user needs to see, and hiding how it actually works. Like a TV remote — you press a button, you don't need to know the electronics inside.

from abc import ABC, abstractmethod class Shape(ABC): @abstractmethod def area(self): # defined, not implemented pass class Circle(Shape): def __init__(self, r): self.r = r def area(self): return 3.14 * self.r ** 2 c = Circle(5) print(c.area()) # 78.5
Chapter 27

Dunder Methods

Magic Methods

Dunder (double underscore) methods let your objects behave like built-in Python types. They're called automatically when you use operators or built-in functions.

class Vector: def __init__(self, x, y): self.x, self.y = x, y def __str__(self): # called by print() return f"({self.x}, {self.y})" def __add__(self, other): # called by + return Vector(self.x + other.x, self.y + other.y) def __len__(self): # called by len() return 2 v1 = Vector(1, 2) v2 = Vector(3, 4) print(v1) # (1, 2) print(v1 + v2) # (4, 6) print(len(v1)) # 2
Chapter 28

Advanced Topics

Decorators

A decorator wraps a function to add extra behaviour without modifying its code. Think of it as gift wrapping — the gift (function) is still the same, but it now has a wrapper around it.

def timer(func): def wrapper(): print("⏱ Starting...") func() print("✅ Done!") return wrapper @timer def greet(): print("Hello!") greet() # ⏱ Starting... # Hello! # ✅ Done!

*args and **kwargs

When you don't know how many arguments a function will receive, use *args (for positional) and **kwargs (for keyword).

def total(*args): # args is a tuple return sum(args) print(total(1, 2, 3, 4)) # 10 print(total(10, 20)) # 30 def profile(**kwargs): # kwargs is a dict for k, v in kwargs.items(): print(f"{k}: {v}") profile(name="Akarsh", age=20)

Comprehensions — One-liners

# List comprehension squares = [x**2 for x in range(5)] # [0,1,4,9,16] evens = [x for x in range(10) if x%2==0] # [0,2,4,6,8] # Dict comprehension squared = {x: x**2 for x in range(5)} # {0:0,1:1,2:4...} # Set comprehension unique = {x%3 for x in range(10)} # {0,1,2}

Lambda Functions

# Lambda = anonymous one-line function square = lambda x: x ** 2 add = lambda a, b: a + b check = lambda x: "even" if x%2==0 else "odd" print(square(5)) # 25 print(add(3, 7)) # 10 print(check(4)) # even

map(), filter(), zip()

nums = [1, 2, 3, 4, 5] # map — transform every item doubled = list(map(lambda x: x*2, nums)) # [2,4,6,8,10] # filter — keep items that pass the test evens = list(filter(lambda x: x%2==0, nums)) # [2,4] # zip — combine two lists into pairs names = ["A", "B", "C"] scores = [90, 85, 78] pairs = list(zip(names, scores)) # [('A',90),('B',85),...]

Modules & Packages

# Built-in modules import math import random from datetime import datetime print(math.sqrt(16)) # 4.0 print(random.randint(1, 100)) # random number print(datetime.now()) # current date/time # Third-party (install with pip) # pip install numpy pandas matplotlib

🚀 Advanced Challenge Questions

Pattern 1
Print a right-angle triangle with stars.
Input: 4* / ** / *** / ****
Pattern 2
Print a mirrored right-angle triangle.
Input: 4**** / *** / ** / *
Pattern 3
Print a centred diamond with stars.
Input: 5Diamond shape
Q1 — Strong Number
A number is strong if sum of factorials of its digits equals the number.
Input: 145Strong ✅ (1!+4!+5! = 145)
Q2 — Prime Range
Print all prime numbers between two numbers.
Input: 10, 3011 13 17 19 23 29
Q3 — Most Frequent
Find which element occurred most in a list.
Input: [1,3,3,2,1,3,4]3 (appeared 3 times)

A message from the creator

"We'll be learning all of this and so much more on this channel. I, Akarsh Vyas, as a creator and representative of Sheryians AI, would like to sincerely thank each and every one of you who stayed with us till the end. You are truly precious to us. Much love! 💙"

Python Notes