Python Programming Cheatsheet (2025) – Syntax, Functions & Libraries for Quick Revision

Introduction

Python has become one of the most popular programming languages for engineering students, developers, and researchers. Its clean syntax, wide range of libraries, and beginner-friendly approach make it the first choice for learning coding.

If you’re an engineering student preparing for exams, practicals, or placement tests, a Python cheatsheet can be your best quick revision tool. Instead of reading long books or scattered notes, you’ll get all the essential syntax, functions, and libraries in one place.

This guide covers Python basics, control structures, functions, OOP concepts, libraries, and advanced topics — all structured for scannability and easy revision.

Why Use a Python Cheatsheet?

Saves time during exam preparation
Provides quick syntax reminders
Helps in practical lab exams and viva questions
Useful for coding interviews and placements
Aids beginners in building a solid foundation

Python Basics Cheatsheet

1. Variables and Data Types

x = 10          # Integer
y = 3.14        # Float
name = "BTech"  # String
flag = True     # Boolean

Python is dynamically typed (no need to declare type).
Use type(x) to check data type.

2. Basic Input and Output

name = input("Enter your name: ")
print("Hello", name)

3. Comments

# This is a single-line comment
"""
This is a 
multi-line comment
"""

Operators in Python

Arithmetic Operators

+, -, *, /, // (floor division), % (modulus), ** (power)

Comparison Operators

==, !=, >, <, >=, <=

Logical Operators

and, or, not

Assignment Operators

=, +=, -=, *=, /=

Control Flow in Python

If-Else Statement

x = 10
if x > 0:
    print("Positive")
elif x == 0:
    print("Zero")
else:
    print("Negative")

Loops

For Loop

for i in range(5):
    print(i)

While Loop

count = 0
while count < 5:
    print(count)
    count += 1

Functions in Python

Defining and Calling Functions

def greet(name):
    return "Hello, " + name

print(greet("Student"))

Lambda Functions

square = lambda x: x * x
print(square(5))

Built-in Functions to Remember

len(), max(), min(), sum(), sorted(), type(), id(), round()

Data Structures in Python

Lists

fruits = ["apple", "banana", "mango"]
fruits.append("orange")
print(fruits[0])   # apple

Tuples

numbers = (1, 2, 3)
print(numbers[1])  # 2

Sets

unique = {1, 2, 3, 3, 2}
print(unique)  # {1, 2, 3}

Dictionaries

student = {"name": "John", "age": 20}
print(student["name"])

Object-Oriented Programming (OOP) in Python

Class and Object

class Student:
    def __init__(self, name):
        self.name = name

    def show(self):
        print("Student:", self.name)

s1 = Student("Alice")
s1.show()

Inheritance

class A:
    def greet(self):
        print("Hello from A")

class B(A):
    pass

obj = B()
obj.greet()

Important Python Libraries

1. NumPy (Numerical Computing)

import numpy as np
arr = np.array([1, 2, 3])
print(arr.mean())

2. Pandas (Data Analysis)

import pandas as pd
df = pd.DataFrame({"Name": ["A", "B"], "Marks": [90, 85]})
print(df.head())

3. Matplotlib (Data Visualization)

import matplotlib.pyplot as plt
plt.plot([1,2,3],[4,5,6])
plt.show()

4. Scikit-learn (Machine Learning)

from sklearn.linear_model import LinearRegression

5. Flask & Django (Web Development)

Flask → Lightweight web framework
Django → Full-stack web framework

File Handling in Python

# Write to file
with open("file.txt", "w") as f:
    f.write("Hello World")

# Read from file
with open("file.txt", "r") as f:
    print(f.read())

Exception Handling

try:
    num = int("abc")
except ValueError:
    print("Invalid input")
finally:
    print("Done")

Python Shortcuts (One-Liners)

Swap variables: a, b = b, a
List comprehension: [x**2 for x in range(5)]
Dictionary comprehension: {i: i*2 for i in range(5)}
Ternary operator: result = "Even" if x%2==0 else "Odd"

Advanced Python Topics (Quick Revision)

Decorators → Functions that modify other functions.
Generators → Use yield instead of return.
Modules & Packages → import module_name.
Virtual Environments → venv for project isolation.

Python Cheatsheet Summary

Syntax → Clean and simple
Functions → Defined with def and lambda
Libraries → NumPy, Pandas, Matplotlib, Django, Flask
Data Structures → Lists, Tuples, Sets, Dictionaries
OOP → Classes, Objects, Inheritance
Exam Prep → File handling, exceptions, shortcuts

FAQs

Q1. Why is Python so popular among engineering students?
Python is beginner-friendly, widely used in industries, and supports applications like data science, AI, and web development, making it essential for engineering students.

Q2. What are the most important Python libraries for students?
NumPy, Pandas, Matplotlib, Scikit-learn, Flask, and Django are the most useful for practicals, projects, and placements.

Q3. How can I prepare for Python viva exams quickly?
Go through this cheatsheet, practice short programs, and revise basic concepts like loops, functions, and file handling.

Q4. Is Python enough for placements?
Yes, Python is widely used in coding rounds and technical interviews, especially for problem-solving and project-based questions.

Q5. Where can I practice Python coding problems?
You can use platforms like LeetCode, HackerRank, or Codeforces to improve problem-solving with Python.

Conclusion

Python is not just a programming language; it’s a career-building skill. With its simple syntax, powerful libraries, and wide applications, mastering Python can help you in academics, research, and placements.

This Python Cheatsheet is designed for quick revision before exams, coding interviews, and lab practicals. Bookmark it, practice the examples, and you’ll feel much more confident in using Python effectively.

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