Python interview question answers.. ( AI Generated)

 Here’s a list of Python interview questions and answers categorized by levels of difficulty, from beginner to advanced:

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Beginner Questions

1. What is Python?

Python is a high-level, interpreted, and general-purpose programming language. It emphasizes code readability with its significant indentation and supports multiple programming paradigms, such as procedural, object-oriented, and functional programming.

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2. What are Python's key features?

• Easy to Learn and Use: Syntax is simple and clean.
• Interpreted Language: Executes code line by line.
• Dynamically Typed: No need to declare variable types.
• Extensive Libraries: Built-in modules for diverse tasks.
• Cross-Platform: Runs on various platforms like Windows, macOS, and Linux.

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3. What are Python's data types?

• Numeric: int, float, complex
• Sequence: list, tuple, range, str
• Set: set, frozenset
• Mapping: dict
• Boolean: bool
• Binary: bytes, bytearray, memoryview

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4. How is memory managed in Python?

• Memory is managed by the Python Memory Manager.
• It handles:
  • Reference Counting: Tracks the number of references to an object.
  • Garbage Collection: Removes objects no longer in use.

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5. What is a Python virtual environment?

A virtual environment is an isolated workspace that allows you to manage dependencies for different projects independently.

Command to create one:

python -m venv env_name

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Intermediate Questions

1. What is the difference between is and ==?

• is: Compares object identity.
• ==: Compares object values.

a = [1, 2, 3]
b = a
c = [1, 2, 3]

print(a is b)  # True (same object)
print(a == c)  # True (same value)
print(a is c)  # False (different objects)

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2. What are Python's mutable and immutable data types?

• Mutable: Can be changed after creation (e.g., list, dict, set).
• Immutable: Cannot be changed after creation (e.g., int, tuple, str).

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3. Explain Python's list comprehension.

List comprehensions provide a concise way to create lists.

Example:

squares = [x**2 for x in range(10)]
print(squares)

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4. What is the purpose of the with statement in Python?

The with statement simplifies resource management by ensuring proper acquisition and release.

Example:

with open('file.txt', 'r') as f:
    data = f.read()  # File is automatically closed after this block

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5. What is the difference between deepcopy and copy?

• copy: Shallow copy; copies the object but not nested objects.
• deepcopy: Copies the object and all nested objects.

import copy

list1 = [[1, 2], [3, 4]]
list2 = copy.copy(list1)
list3 = copy.deepcopy(list1)

list1[0][0] = 99
print(list2)  # [[99, 2], [3, 4]] (shallow copy affected)
print(list3)  # [[1, 2], [3, 4]] (deep copy unaffected)

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Advanced Questions

1. Explain Python's GIL (Global Interpreter Lock).

The GIL is a mutex in CPython that prevents multiple native threads from executing Python bytecodes simultaneously. This simplifies memory management but can limit performance in multi-threaded applications.

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2. How do you implement a decorator in Python?

A decorator is a function that modifies another function.

Example:

def decorator(func):
    def wrapper():
        print("Before the function call")
        func()
        print("After the function call")
    return wrapper

@decorator
def say_hello():
    print("Hello!")

say_hello()

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3. What is the difference between @staticmethod and @classmethod?

• @staticmethod: Defines a method that doesn't access the class or instance.
• @classmethod: Accesses the class via cls but not the instance.

class MyClass:
    @staticmethod
    def static_method():
        print("Static method")

    @classmethod
    def class_method(cls):
        print(f"Class method: {cls}")

MyClass.static_method()
MyClass.class_method()

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4. How does Python handle multiple inheritance?

Python uses the Method Resolution Order (MRO), following the C3 linearization algorithm.

class A: pass
class B: pass
class C(A, B): pass

print(C.mro())

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5. How would you optimize performance in a Python program?

• Use built-in functions and libraries.
• Opt for list comprehensions over loops.
• Use tools like NumPy for numerical computations.
• Profile your code with cProfile.

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If you'd like detailed examples or specific areas covered, let me know!

( Content provided with the assistance of ChatGPT, an AI model by OpenAI )