Python Cheat Sheet for Interview Preparation

Preparing for a Python interview? This Python Cheat Sheet is your ultimate guide to quickly revise key concepts, syntax, and examples. Whether you’re a beginner or an experienced programmer, this cheat sheet will help you ace your technical interviews with confidence.

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Why Use This Python Cheat Sheet?

• Quick Revision: Covers all essential Python topics in one place.
• Easy to Understand: Clear examples and explanations.
• Interview Ready: Focuses on concepts frequently asked in interviews.
• Practice Material: Includes examples to help you practice and test your knowledge.

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Python Cheat Sheet: Key Concepts, Syntax, and Examples

Below is a structured cheat sheet with Python concepts, syntax, and examples. Use this to revise and practice before your interview.

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1. Variables and Data Types

Concept	Description	Example
Variables	Store data values. Python is dynamically typed.	x = 10 name = "Alice" is_active = True
Data Types	Common types: int, float, str, bool, list, tuple, dict, set.	age = 25 # int price = 19.99 # float name = "Bob" # str

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2. Lists and Tuples

Concept	Description	Example
Lists	Ordered, mutable collections.	fruits = ["apple", "banana", "cherry"] fruits.append("orange")
Tuples	Ordered, immutable collections.	coordinates = (10, 20) print(coordinates[0]) # Output: 10

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3. Dictionaries and Sets

Concept	Description	Example
Dictionaries	Key-value pairs, unordered, mutable.	person = {"name": "Alice", "age": 25} person["age"] = 26
Sets	Unordered, unique elements.	unique_numbers = {1, 2, 3, 3} # Output: {1, 2, 3}

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4. Control Flow

Concept	Description	Example
If-Else	Conditional statements.	if x > 10: print("x is greater than 10") else: print("x is small")
For Loop	Iterate over a sequence.	for i in range(5): print(i) # Output: 0 1 2 3 4
While Loop	Execute while a condition is true.	while x > 0: print(x); x -= 1

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5. Functions

Concept	Description	Example
Defining Functions	Use def to define a function.	def greet(name): return f"Hello, {name}" print(greet("Alice"))
Lambda Functions	Anonymous functions defined with lambda.	square = lambda x: x**2 print(square(5)) # Output: 25

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6. List Comprehensions

Concept	Description	Example
List Comprehension	Concise way to create lists.	squares = [x**2 for x in range(5)] # Output: [0, 1, 4, 9, 16]

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7. Error Handling

Concept	Description	Example
Try-Except	Handle exceptions using try and except.	try: result = 10 / 0 except ZeroDivisionError: print("Error!")

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8. File Handling

Concept	Description	Example
Reading Files	Use open() to read files.	with open("file.txt", "r") as file: content = file.read()
Writing Files	Use open() to write files.	with open("file.txt", "w") as file: file.write("Hello, World!")

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9. Classes and Objects

Concept	Description	Example
Defining Classes	Use class to define a class.	class Dog: def __init__(self, name): self.name = name
Creating Objects	Instantiate objects using the class name.	my_dog = Dog("Buddy") print(my_dog.name) # Output: Buddy

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10. Common Libraries

Concept	Description	Example
Math	Perform mathematical operations.	import math print(math.sqrt(16)) # Output: 4.0
Datetime	Work with dates and times.	from datetime import datetime print(datetime.now())

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1. Basics

# Variables and Data Types
x = 10          # Integer
y = 3.14        # Float
name = "Alice"  # String
is_valid = True # Boolean

# Type Checking
print(type(x))  # Output: <class 'int'>

# Type Conversion
num = "100"
num_int = int(num)  # Convert string to integer

2. Operators

# Arithmetic Operators
x, y = 10, 3
print(x + y)   # Addition
print(x - y)   # Subtraction
print(x * y)   # Multiplication
print(x / y)   # Division
print(x // y)  # Floor Division
print(x ** y)  # Exponentiation

# Comparison and Logical Operators
print(x > y)    # Greater than
print(x == y)   # Equal to
print(x != y)   # Not equal
print(x > 5 and y < 5)  # Logical AND
print(x > 5 or y > 5)   # Logical OR

3. Data Structures

Lists

fruits = ["apple", "banana", "cherry"]
fruits.append("orange")  # Add element
fruits.remove("banana")  # Remove element
print(fruits[0])         # Access element
print(len(fruits))       # Length of list

Tuples

tuple1 = (1, 2, 3)
print(tuple1[0])

Dictionaries

person = {"name": "Alice", "age": 25}
print(person["name"])  # Access value
person["age"] = 26      # Modify value

4. Control Flow

# If-Else
num = 10
if num > 0:
    print("Positive")
elif num < 0:
    print("Negative")
else:
    print("Zero")

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

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

5. Functions

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

print(greet("Alice"))

6. OOP (Object-Oriented Programming)

class Person:
    def __init__(self, name, age):
        self.name = name
        self.age = age

    def introduce(self):
        return f"Hi, I am {self.name} and I am {self.age} years old."

person1 = Person("Alice", 25)
print(person1.introduce())

7. Exception Handling

try:
    result = 10 / 0
except ZeroDivisionError:
    print("Cannot divide by zero")
finally:
    print("Execution completed")

8. File Handling

# Writing to a file
with open("sample.txt", "w") as file:
    file.write("Hello, World!")

# Reading from a file
with open("sample.txt", "r") as file:
    content = file.read()
    print(content)

9. Lambda Functions

square = lambda x: x * x
print(square(5))  # Output: 25

10. Important Libraries

import math
print(math.sqrt(16))  # Square root

import random
print(random.randint(1, 10))  # Random integer

import datetime
print(datetime.datetime.now())  # Current date and time

I. Core Concepts

• Data Types:
  • Numbers: int, float, complex (e.g., 10, 3.14, 2+3j)
  • Strings: str (e.g., "hello", 'world') – Immutable sequences of characters.
  • Booleans: bool (e.g., True, False)
  • Lists: list (e.g., [1, 2, 3]) – Mutable, ordered sequences.
  • Tuples: tuple (e.g., (1, 2, 3)) – Immutable, ordered sequences.
  • Sets: set (e.g., {1, 2, 3}) – Unordered collections of unique elements.
  • Dictionaries: dict (e.g., {"key": "value"}) – Key-value pairs.
• Variables: Dynamically typed. No explicit type declaration needed. (e.g., name = "Alice")
• Operators:
  • Arithmetic: +, -, *, /, // (floor division), % (modulo), ** (exponentiation)
  • Comparison: ==, !=, >, <, >=, <=
  • Logical: and, or, not
  • Assignment: =, +=, -=, *=, /=, etc.
  • Membership: in, not in
  • Identity: is, is not
• Control Flow:
  • Conditional: if, elif, else
  • Loops: for, while
  • Loop Control: break, continue, pass
• Functions: Defined using def. Can have parameters and return values.

II. Syntax and Examples

A. Basic Syntax

Python

# Comments start with #

# Printing
print("Hello, World!")

# Variable assignment
x = 10
y = "Python"

# Multiple assignment
a, b, c = 1, 2, 3

# Indentation is crucial in Python
if x > 5:
    print("x is greater than 5")  # Indented block

B. Data Structures

Python

# Lists
my_list = [1, 2, 3, "a", "b"]
my_list.append(4)
my_list[0]  # Access first element (index 0)
my_list[1:3] # Slicing

# Tuples
my_tuple = (1, 2, 3)
# my_tuple[0] = 4  # Error: Tuples are immutable

# Sets
my_set = {1, 2, 3, 3}  # Duplicates are removed
my_set.add(4)

# Dictionaries
my_dict = {"name": "Alice", "age": 30}
my_dict["name"]  # Access value by key
my_dict["city"] = "New York" # Add new key-value pair

C. Control Flow

Python

# if-elif-else
age = 20
if age < 18:
    print("Minor")
elif age >= 18 and age < 65:
    print("Adult")
else:
    print("Senior")

# for loop
for i in range(5):  # 0 to 4
    print(i)

# while loop
count = 0
while count < 3:
    print(count)
    count += 1

# List comprehension (concise way to create lists)
squares = [x**2 for x in range(10)]

# Dictionary comprehension
squared_dict = {x: x**2 for x in range(5)}

D. Functions

Python

def greet(name):
    """Docstring: This function greets the person passed in as a parameter."""
    return "Hello, " + name + "!"

message = greet("Bob")
print(message)

# Lambda functions (anonymous functions)
square = lambda x: x * x
print(square(5))

E. File Handling

Python

# Reading from a file
with open("my_file.txt", "r") as f:
    content = f.read()
    print(content)

# Writing to a file
with open("output.txt", "w") as f:
    f.write("Hello, file!")

F. Modules and Packages

Python

import math  # Import a module
print(math.sqrt(25))

# From a module import specific function
from random import randint
print(randint(1, 10))

III. Important Built-in Functions

• len(): Returns the length of a sequence.
• type(): Returns the type of an object.
• str(), int(), float(): Type conversion.
• range(): Generates a sequence of numbers.
• input(): Reads input from the user.
• sorted(): Returns a new sorted list from an iterable.
• map(): Applies a function to each item of an iterable.
• filter(): Constructs an iterator from those elements of iterable for which a function returns true.
• enumerate(): Returns an enumerate object.

IV. Object-Oriented Programming (OOP) (Key Concepts)

• Classes: Blueprints for creating objects.
• Objects: Instances of classes.
• Attributes: Variables associated with objects.
• Methods: Functions associated with objects.
• Inheritance: Creating new classes based on existing ones.
• Polymorphism: Ability of objects of different classes to respond to the same method call in their own specific ways.
• Encapsulation: Bundling data and methods that operate on that data within a class.

V. Exception Handling

Python

try:
    result = 10 / 0
except ZeroDivisionError:
    print("Cannot divide by zero!")
except Exception as e: # Catching general exceptions
    print(f"An error occurred: {e}")
finally: # Code that always runs
    print("This will always execute.")

VI. Regular Expressions (Regex)

Python

import re

text = "This is a test string."
pattern = r"test"

match = re.search(pattern, text)

if match:
    print("Match found!")
    print(match.group())

VII. Tips for Interviews

• Practice: The more you practice, the better you’ll become.
• Explain your reasoning: Don’t just write code; explain your thought process.
• Ask clarifying questions: If you’re unsure about something, ask!
• Test your code: Think about edge cases and test your code thoroughly.
• Be confident: You’ve prepared, so believe in yourself!

This cheat sheet provides a solid foundation. Remember to explore and practice further for a comprehensive understanding of Python! Good luck with your interviews!

Frequently Asked Interview Questions

1. Variables & Data Types:

• “What are the differences between a list and a tuple?”
• “How would you convert a string to an integer?”

1. Functions:

• “Write a function to check if a number is prime.”
• “What is the difference between return and print in a function?”

1. Error Handling:

• “How would you handle a file-not-found error in Python?”

1. Classes & Objects:

• “What is the purpose of the __init__ method in a class?”

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Conclusion

This Python Cheat Sheet is your go-to resource for interview preparation. It covers all the essential Python concepts, syntax, and examples in an easy-to-understand format. Use it to revise, practice, and ace your Python interviews with confidence.

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