Python - Theory Questions and Answers

1. Introduction to Python

• Python is a high-level, interpreted, dynamically typed, and object-oriented programming language.
• It is widely used for web development, data science, automation, AI, and more.

Key Features:

• Simple and easy-to-learn syntax.
• Interpreted language (no need for compilation).
• Dynamically typed (no need to declare variable types).
• Extensive standard library support.
• Supports multiple programming paradigms (Object-Oriented, Functional, and Procedural).

2. Python Data Types

Basic Data Types:

• int → Integer values, e.g., x = 10
• float → Decimal numbers, e.g., y = 3.14
• str → Sequence of characters, e.g., name = "Python"
• bool → Boolean values, True or False

Collection Data Types:

• List → Ordered, mutable collection, e.g., fruits = ["apple", "banana"]
• Tuple → Ordered, immutable collection, e.g., numbers = (1, 2, 3)
• Set → Unordered, unique elements, e.g., s = {1, 2, 3}
• Dictionary → Key-value pairs, e.g., student = {"name": "John", "age": 25}

3. Variables and Operators

Variables:

• Variables store data and do not require explicit type declaration.
• Example:

  x = 10  # Integer
  y = "Python"  # String

Operators:

• Arithmetic: +, -, *, /, %, **, //
• Comparison: ==, !=, >, <, >=, <=
• Logical: and, or, not
• Assignment: =, +=, -=, *=, /=
• Membership: in, not in
• Identity: is, is not

4. Control Flow Statements

Conditional Statements:

• Used for decision-making.
• Example:

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

Loops:

• For Loop: Iterates over a sequence.

  for i in range(5):
      print(i)  # Output: 0 1 2 3 4

• While Loop: Repeats a block of code while a condition is true.

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

Loop Control Statements:

• break → Exits the loop early.
• continue → Skips the current iteration.
• pass → Placeholder for future code.

5. Functions in Python

• Functions help reuse code and improve modularity.
• Example:

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

  print(greet("John"))  # Output: Hello, John

• Lambda (Anonymous) Functions:

  square = lambda x: x * x
  print(square(4))  # Output: 16

6. Object-Oriented Programming (OOP) in Python

Key OOP Concepts:

• Class & Object:

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

      def greet(self):
          return f"Hello, my name is {self.name}"

  p1 = Person("Alice", 25)
  print(p1.greet())  # Output: Hello, my name is Alice

• Encapsulation: Hiding data inside classes.
• Inheritance: Reusing features of a parent class.
• Polymorphism: Using a single method name for different types.

7. Exception Handling

• Used to handle runtime errors.
• Example:

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

8. File Handling

Opening and Reading a File:

with open("file.txt", "r") as file:
    content = file.read()
    print(content)

Writing to a File:

with open("file.txt", "w") as file:
    file.write("Hello, Python!")

9. Python Modules and Packages

• Modules are files with Python code (.py).

  import math
  print(math.sqrt(16))  # Output: 4.0

• Creating a Custom Module:

  # mymodule.py
  def greet(name):
      return f"Hello, {name}"

  # main.py
  import mymodule
  print(mymodule.greet("Alice"))

10. Decorators in Python

• Used to modify functions without changing their code.
• Example:

  def decorator_function(original_function):
      def wrapper_function():
          print("Wrapper executed before", original_function.__name__)
          return original_function()
      return wrapper_function

  @decorator_function
  def display():
      print("Display function executed")

  display()

11. Python’s map(), filter(), and reduce() Functions

Using map():

• Applies a function to all elements of an iterable.

  nums = [1, 2, 3, 4]
  squared = list(map(lambda x: x**2, nums))
  print(squared)  # Output: [1, 4, 9, 16]

Using filter():

• Filters elements based on a condition.

  nums = [1, 2, 3, 4, 5]
  even = list(filter(lambda x: x % 2 == 0, nums))
  print(even)  # Output: [2, 4]

Using reduce():

• Performs a cumulative operation on elements.

  from functools import reduce
  nums = [1, 2, 3, 4]
  result = reduce(lambda x, y: x + y, nums)
  print(result)  # Output: 10

12. Python Memory Management

• Python uses automatic garbage collection to manage memory.
• Objects are deleted when their reference count becomes zero.
• Example:

  import sys
  x = "Hello"
  print(sys.getrefcount(x))  # Output: Reference count of object