Python Interview Questions – Part 3
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01. What is a Decorator in Python?

A decorator is a function that modifies or extends another function's behavior without changing its original source code.

Key Points
- Uses the @decorator syntax
- Supports reusable functionality
- Commonly used for logging and access control

02. What is a Generator in Python?

A generator produces values one at a time instead of storing the entire sequence in memory.

Key Points
- Commonly uses the yield keyword
- Generates values lazily
- Useful for processing large datasets

03. What is an Iterator in Python?

An iterator is an object that returns values one at a time using the __next__() method until the sequence is exhausted.

Key Points
- Supports the iterator protocol
- Works with iter() and next()
- Raises StopIteration when exhausted

04. What is the Use of the yield Keyword?

The yield keyword returns a value from a generator while preserving its execution state. Execution resumes when the next value is requested.

Key Points
- Produces values lazily
- Preserves local state between yields
- Helps reduce memory usage for large sequences

05. What is the Difference Between Shallow Copy and Deep Copy?

A shallow copy creates a new outer object but keeps references to nested objects. A deep copy recursively copies nested objects as well.

Key Points
- Shallow copy may share nested objects
- Deep copy duplicates nested structures
- Python provides copy.copy() and copy.deepcopy()

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Advanced Python Interview Questions
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01. What is a Decorator in Python?

A decorator adds or modifies a function's behavior without changing the original function's source code.

Code Example:

def log_call(func):
    def wrapper(*args, **kwargs):
        print("Function called")
        return func(*args, **kwargs)
    return wrapper

@log_call
def greet(name):
    return f"Hello, {name}"

print(greet("Akshay"))

**Output:**

Function called
Hello, Akshay

02. What is a Generator in Python?

A generator produces values one at a time using yield, which can reduce memory usage when processing large sequences.

Code Example:

def squares(n):
    for i in range(n):
        yield i * i

for value in squares(5):
    print(value)

Output:

0
1
4
9
16

03. What is the Difference Between `is` and `==`?

The == operator checks whether two objects have equal values, whereas is checks whether both references point to the same object.

Code Example:

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

print(a == b)
print(a is b)

Output:

True
False

04. What is a Context Manager in Python?

A context manager manages resources such as files or database connections. The with statement ensures that cleanup happens when the block exits.

Code Example:

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

print("File operation completed")

Key Points
- Uses the with statement
- Helps release resources safely
- Custom context managers can implement __enter__() and __exit__()

05. What is a Metaclass in Python?

A metaclass defines how classes are created. The default metaclass for most Python classes is type.

Code Example:

class Meta(type):
    def __new__(mcls, name, bases, namespace):
        namespace["category"] = "Advanced"
        return super().__new__(
            mcls, name, bases, namespace
        )

class AIModel(metaclass=Meta):
    pass

print(AIModel.category)

Output:

Advanced

Key Points
- Classes are objects in Python
- Metaclasses customize class creation
- Useful in frameworks and advanced libraries

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Python Interview Questions – Part 3
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11. What is a Decorator in Python?

A decorator modifies or extends a function's behavior without changing its original source code.

Code Example

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

@decorator
def greet():
    print("Hello")

greet()

Output

Before function
Hello

12. What is a Generator in Python?

A generator produces values one at a time, usually using the yield keyword, instead of storing the entire sequence in memory.

Code Example

def numbers():
    yield 1
    yield 2
    yield 3

for n in numbers():
    print(n)

Output

1
2
3

13. What is an Iterator in Python?

An iterator is an object that returns values one at a time through __next__() until the sequence is exhausted.

Code Example

items = iter([10, 20, 30])

print(next(items))
print(next(items))

Output

10
20

14. What is the Difference Between `yield` and `return`?

return ends a function and returns a result. yield produces a value while preserving the generator's execution state for later continuation.

Key Points
- return ends the function call
- yield pauses generator execution
- Generators can produce multiple values

15. What is the Difference Between Shallow Copy and Deep Copy?

A shallow copy creates a new outer object but may share nested objects. A deep copy recursively copies nested objects.

Code Example

import copy

original = [[1, 2], [3, 4]]
shallow = copy.copy(original)
deep = copy.deepcopy(original)

original[0][0] = 99

print(shallow)
print(deep)

Output

[[99, 2], [3, 4]]
[[1, 2], [3, 4]]

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Advanced Python Interview Questions – Part 2
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06. What is a Closure in Python?

A closure is an inner function that remembers variables from its enclosing scope even after the outer function has finished executing.

Code Example

def multiplier(n):
    def multiply(x):
        return x * n
    return multiply

double = multiplier(2)
print(double(5))

Output

10

07. What is a Lambda Function in Python?

A lambda function is a small anonymous function created using the lambda keyword.

Code Example

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

Output

25

08. What is the Global Interpreter Lock (GIL)?

In standard GIL-enabled CPython builds, the Global Interpreter Lock allows only one thread at a time to execute Python bytecode within a process.

Key Points
- Affects CPU-bound multithreading
- Threads can still help with I/O-bound tasks
- Python also offers multiprocessing for CPU-heavy work

09. What is `asyncio` in Python?

asyncio is a library for asynchronous programming using async and await, especially useful for handling many I/O-bound operations.

Code Example

import asyncio

async def greet():
    print("Hello")
    await asyncio.sleep(1)
    print("World")

asyncio.run(greet())

Output

Hello
World

10. What is a Python Virtual Environment?

A virtual environment creates an isolated Python environment for a project, helping manage dependencies separately.

Commands

python -m venv .venv

Activate on Windows:

.venv\Scripts\activate

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