Python Interview Questions – Level 4: Advanced Python

Take your Python knowledge to the next level. This section covers memory management, concurrency, asynchronous programming, and internal implementation details that distinguish expert Python developers.

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161. What is iterator?

An iterator is an object that contains a countable number of values and can be iterated upon. It implements the iterator protocol: __iter__() and __next__().

nums = [1, 2, 3]
it = iter(nums)

print(next(it)) # 1
print(next(it)) # 2

162. What is iterable?

An iterable is an object capable of returning its members one at a time, such as list, str, tuple, or dict. You can get an iterator from an iterable using iter().

# Strings are iterable
for char in "Hi":
    print(char)

163. What is generator?

A generator is a function that returns an iterator object using the yield keyword. It is memory-efficient because it generates values lazily.

def my_gen():
    yield 1
    yield 2

g = my_gen()
print(list(g)) # [1, 2]

164. Difference between yield and return?

• return: Exits the function and returns a final value.
• yield: Pauses the function, yields a value, and saves state to be resumed later.

def count_up_to(n):
    count = 1
    while count <= n:
        yield count
        count += 1

165. What is generator expression?

A compact, memory-efficient way to create a generator using parentheses: (x**2 for x in range(10)).

# List comprehension (creates full list)
squares_list = [x**2 for x in range(5)]

# Generator expression (lazy evaluation)
squares_gen = (x**2 for x in range(5))

print(next(squares_gen)) # 0

166. What is comprehension?

A concise syntax for creating collections (lists, sets, dicts) from existing iterables.

evens = [x for x in range(10) if x % 2 == 0]
print(evens) # [0, 2, 4, 6, 8]

167. Types of comprehensions?

• List: [x for x in r]
• Set: {x for x in r}
• Dict: {k: v for k, v in r}

# Dict comprehension example
names = ["Alice", "Bob"]
name_lengths = {name: len(name) for name in names}
# {'Alice': 5, 'Bob': 3}

168. What is memory-efficient programming?

Techniques to minimize memory usage, such as using generators, __slots__, and avoid loading large datasets into memory at once.

import sys
# Generator Size vs List Size
gen = (i for i in range(10000))
lst = [i for i in range(10000)]
print(sys.getsizeof(gen)) # ~100 bytes
print(sys.getsizeof(lst)) # ~85000 bytes

169. What is deepcopy vs shallow copy?

• Shallow Copy: New object with references to original nested objects.
• Deep Copy: New object with recursive copies of all nested objects.

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

original[0][0] = 99
print(shallow[0][0]) # 99 (Affected)
print(deep[0][0])    # 1 (Unaffected)

170. What is copy module?

Provides copy.copy() (shallow) and copy.deepcopy() (deep) functions.

import copy
a = [1, 2, 3]
b = copy.copy(a)

171. What is threading?

Running multiple threads within a single process. Best for I/O-bound tasks.

Example:

import threading
import time

def print_numbers():
    for i in range(5):
        time.sleep(1)
        print(i)

thread = threading.Thread(target=print_numbers)
thread.start()
print("Main thread continues...")

172. What is multiprocessing?

Running multiple separate processes, each with its own GIL. Best for CPU-bound tasks.

Example:

from multiprocessing import Process

def square_numbers():
    for i in range(5):
        print(i*i)

if __name__ == "__main__":
    process = Process(target=square_numbers)
    process.start()
    process.join()

173. What is GIL?

The Global Interpreter Lock (GIL) is a mutex that prevents multiple native threads from executing Python bytecodes at once, ensuring thread safety for the interpreter.

Example:

# Even with threads, CPU-bound tasks don't speed up much because of GIL
import threading
import time

def count(n):
    while n > 0:
        n -= 1

start = time.time()
t1 = threading.Thread(target=count, args=(10000000,))
t2 = threading.Thread(target=count, args=(10000000,))
t1.start()
t2.start()
t1.join()
t2.join()
end = time.time()
print(f"Time: {end - start:.2f}s")

174. Difference between process and thread?

• Thread: Shares memory, affected by GIL, lightweight.
• Process: Isolated memory, bypasses GIL, heavier.

Example:

import multiprocessing
import threading

# Shared vs isolated memory demo (conceptual)
shared_list = []

def add_to_list_worker(name):
    shared_list.append(name)

# Threads share memory
t1 = threading.Thread(target=add_to_list_worker, args=("Thread 1",))
t2 = threading.Thread(target=add_to_list_worker, args=("Thread 2",))
t1.start()
t2.start()
t1.join()
t2.join()
print("From threads:", shared_list)  # Likely has both entries

175. What is async programming?

Non-blocking execution style, allowing a single thread to handle multiple tasks by switching between them during I/O waits.

Example:

import asyncio

async def greet(name):
    await asyncio.sleep(1)
    print(f"Hello {name}!")

async def main():
    await asyncio.gather(greet("Alice"), greet("Bob"))

asyncio.run(main())

176. What is asyncio?

The standard library for writing concurrent code using async/await.

Example:

import asyncio

async def count():
    print("One")
    await asyncio.sleep(1)
    print("Two")

async def main():
    await asyncio.gather(count(), count(), count())

asyncio.run(main())

177. What is await?

A keyword used to yield control back to the event loop while waiting for an asynchronous task to finish.

Example:

import asyncio

async def slow_task():
    await asyncio.sleep(2)
    return "Done!"

async def main():
    result = await slow_task()  # Wait here
    print(result)

asyncio.run(main())

178. What is event loop?

The engine that runs asyncio tasks, managing their execution and I/O events.

Example:

import asyncio

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

loop = asyncio.get_event_loop()  # Get the loop
loop.run_until_complete(hello()) # Run task

179. What is context manager?

An object that implements __enter__ and __exit__, usually used with the with statement for resource management.

Example:

class MyContext:
    def __enter__(self):
        print("Entering")
        return "Resource"
    def __exit__(self, exc_type, exc_val, exc_tb):
        print("Exiting")

with MyContext() as res:
    print(f"Using {res}")

180. What is with statement?

Simplifies exception handling by encapsulating common preparation and cleanup tasks (e.g., closing a file).

Example:

# Safe file handling
with open("test.txt", "w") as f:
    f.write("Hello World!")
# File is automatically closed!

181. What is file handling?

Reading from and writing to files using open() and related methods.

Example:

# Writing to file
with open("example.txt", "w") as f:
    f.write("Line 1\nLine 2\n")

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

182. Modes of file opening?

'r' (read), 'w' (write), 'a' (append), 'b' (binary), 'r+' (read/write).

Example:

# Append
with open("log.txt", "a") as f:
    f.write("New log entry\n")

# Read binary
with open("image.jpg", "rb") as f:
    image_data = f.read()

183. What is pickle?

A module for serializing and deserializing Python objects into byte streams.

Example:

import pickle

data = {"name": "Alice", "age": 30}

# Serialize (dump)
with open("data.pkl", "wb") as f:
    pickle.dump(data, f)

# Deserialize (load)
with open("data.pkl", "rb") as f:
    loaded_data = pickle.load(f)
    print(loaded_data)

184. What is serialization?

Converting an object into a storable/transmittable format (e.g., JSON, Pickle).

Example:

import json

data = {"key": "value"}
json_str = json.dumps(data)  # Serialize to JSON string
print(json_str)

185. What is deserialization?

Reconstructing an object from its serialized format.

Example:

import json

json_str = '{"name": "Bob", "age": 25}'
data = json.loads(json_str)  # Deserialize from JSON string
print(data["name"])

186. What is regular expression?

A sequence of characters that forms a search pattern (Regex), used with the re module.

Example:

import re

text = "My email is user@example.com"
pattern = r'\w+@\w+\.\w+'
match = re.search(pattern, text)
if match:
    print("Email found:", match.group())

187. What is re module?

The Python module for working with Regular Expressions.

Example:

import re

# Find all numbers
text = "There are 3 apples and 5 oranges"
numbers = re.findall(r'\d+', text)
print(numbers)  # ['3', '5']

188. What is pattern matching?

Checking if a string matches a pattern. Python 3.10+ also supports Structural Pattern Matching (match/case).

Example:

def http_error(status):
    match status:
        case 400:
            return "Bad request"
        case 404:
            return "Not found"
        case _:
            return "Other error"

print(http_error(404))

189. What is unit testing?

Testing individual units of code to ensure correctness.

Example:

def add(a, b):
    return a + b

# Simple test
assert add(2, 3) == 5
assert add(-1, 1) == 0
print("All tests passed!")

190. What is unittest module?

The built-in testing framework for Python.

Example:

import unittest

def add(a, b):
    return a + b

class TestMath(unittest.TestCase):
    def test_add(self):
        self.assertEqual(add(2, 3), 5)

if __name__ == "__main__":
    unittest.main()

191. What is pytest?

A powerful third-party testing framework known for its simplicity and extensive plugin support.

Example:

# test_math.py
def add(a, b):
    return a + b

def test_add():
    assert add(2, 3) == 5

# Run with: pytest test_math.py

192. What is logging?

A flexible system for tracking events during program execution, preferred over print().

Example:

import logging

logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

logger.info("Program started")
logger.warning("Low disk space warning")

193. What is virtualenv?

A tool for creating isolated Python environments to manage project-specific dependencies.

Example:

# Create virtual env (command line)
# virtualenv my_env
# Activate on Windows: my_env\Scripts\activate
# Activate on Mac/Linux: source my_env/bin/activate

194. What is poetry?

A modern tool for dependency management and packaging that uses pyproject.toml.

Example:

# pyproject.toml (conceptual)
[tool.poetry]
name = "my-project"
version = "0.1.0"
description = ""
authors = ["Your Name <you@example.com>"]

[tool.poetry.dependencies]
python = "^3.8"
requests = "^2.25.1"

195. What is pip freeze?

Outputs all installed packages and their versions, often piped to requirements.txt.

Example:

# Command line
# pip freeze > requirements.txt
# Then install from requirements: pip install -r requirements.txt

196. What is wheel?

The standard binary distribution format for Python packages.

Example:

# Command line to build a wheel
# python setup.py bdist_wheel

197. What is CPython?

The reference implementation of Python, written in C and Python.

Example:

# Check implementation
import platform
print(platform.python_implementation())  # 'CPython'

198. What is PyPy?

An alternative implementation using JIT compilation for high performance.

Example:

# PyPy runs loops much faster! (conceptual)
def loop():
    total = 0
    for i in range(1000000):
        total += i
    return total

199. What is C-extension?

High-performance modules written in C/C++ and used within Python.

Example:

// Simple C extension (conceptual)
#include <Python.h>

static PyObject* hello(PyObject* self) {
    return PyUnicode_FromString("Hello from C!");
}

200. What is Python used for in AI & ML?

Python is the industry standard for AI/ML due to libraries like NumPy, Pandas, Scikit-learn, TensorFlow, and PyTorch.

Example:

import numpy as np

# Simple numpy example
a = np.array([1, 2, 3])
b = np.array([4, 5, 6])
print(a + b)  # [5 7 9]