Detailed analysis of python as a programing language and its data structure
🐍 Python Complete Notes
Python is a high-level, interpreted, object-oriented, general-purpose programming language. It is popular for its simplicity, readability, and vast libraries.
🔹 1. Features of Python
Simple & Easy → Easy to learn and read.
Interpreted → Executes line by line.
Cross-Platform → Runs on Windows, Mac, Linux.
Object-Oriented → Supports OOP concepts.
Dynamic Typing → No need to declare variable types.
Huge Libraries → Rich collection of built-in & external modules.
🔹 2. Python Basics
2.1 Hello World
print("Hello, World!")
2.2 Variables & Data Types
x = 10 # int y = 3.14 # float name = "Utkarsh" # string is_active = True # boolean
2.3 Type Casting
a = int("5") # string to int b = str(123) # int to string c = float(4) # int to float
2.4 Input/Output
name = input("Enter your name: ") print("Hello,", name)
🔹 3. Operators
Arithmetic: + - * / % ** //
Comparison: == != > < >= <=
Logical: and or not
Assignment: = += -= *= /=
Membership: in, not in
Identity: is, is not
🔹 4. Conditional Statements
x = 20 if x > 10: print("Greater") elif x == 10: print("Equal") else: print("Smaller")
🔹 5. Loops
For Loop
for i in range(5): print(i)
While Loop
n = 5 while n > 0: print(n) n -= 1
Loop Control
break → exit loop
continue → skip iteration
pass → placeholder
🔹 6. Functions
def add(a, b): return a + b
print(add(5, 10))
Default Arguments
def greet(name="User"): print("Hello", name)
Lambda Functions
square = lambda x: x * x print(square(5))
🔹 7. Data Structures in Python
7.1 Lists
Ordered, mutable, allows duplicates.
fruits = ["apple", "banana", "cherry"] fruits.append("mango") fruits.remove("banana") print(fruits[0])
7.2 Tuples
Ordered, immutable, allows duplicates.
t = (1, 2, 3, 4) print(t[1])
7.3 Sets
Unordered, mutable, no duplicates.
s = {1, 2, 3, 3, 4} s.add(5) s.remove(2)
7.4 Dictionaries
Key-Value pairs, unordered, mutable.
student = {"name": "Utkarsh", "age": 20} print(student["name"]) student["age"] = 21
🔹 8. Strings
s = "Hello Python" print(s.lower()) print(s.upper()) print(s.split()) print(s[0:5])
String Formatting:
name = "Utkarsh" age = 20 print(f"My name is {name} and I am {age} years old.")
🔹 9. File Handling
with open("test.txt", "w") as f: f.write("Hello World")
with open("test.txt", "r") as f: data = f.read() print(data)
🔹 10. Exception Handling
try: x = 10 / 0 except ZeroDivisionError: print("Division by zero error!") finally: print("Always executed")
🔹 11. Object-Oriented Programming (OOP) in Python
class Car: def init(self, brand, speed): self.brand = brand self.speed = speed
def drive(self):
print(f"{self.brand} is driving at {self.speed} km/h")
car1 = Car("Tesla", 120) car1.drive()
OOP Concepts
Encapsulation – using private variables (_var or __var)
Inheritance
class ElectricCar(Car): def init(self, brand, speed, battery): super().init(brand, speed) self.battery = battery
Polymorphism – method overriding
Abstraction – via abstract classes (abc module)
🔹 12. Python Modules & Packages
import math print(math.sqrt(16))
Custom Module:
def greet(name): return f"Hello {name}"
import mymodule print(mymodule.greet("Utkarsh"))
Popular Libraries:
NumPy → Arrays & Math
Pandas → Data Analysis
Matplotlib → Visualization
Requests → HTTP requests
Flask/Django → Web frameworks
🔹 13. Data Structures & Algorithms (DSA) in Python
Stack (LIFO)
stack = [] stack.append(1) stack.append(2) print(stack.pop())
Queue (FIFO)
from collections import deque queue = deque([1,2,3]) queue.append(4) print(queue.popleft())
Linked List (Implementation Example)
class Node: def init(self, data): self.data = data self.next = None
Trees & Graphs
Implemented using classes + recursion + adjacency lists.
Libraries: networkx (for graphs).
🔹 14. Advanced Python Concepts
Generators & Iterators (yield)
Decorators (@decorator)
List Comprehensions
nums = [x**2 for x in range(5)]
Multithreading & Multiprocessing
Virtual Environments (venv)
Regular Expressions (re module)