1
What is Python? Easy
Python is a high-level, interpreted, dynamically typed programming language known for its simplicity and readability. It supports multiple paradigms including object-oriented, procedural, and functional programming.
2
What are Python data types? Easy
Python has built-in data types such as int, float, str, list, tuple, set, dict, and bool. It also supports custom data types using classes.
3
What is the difference between list and tuple? Easy
Lists are mutable (can be changed), while tuples are immutable (cannot be changed). Tuples are faster and more memory-efficient.
4
What is a dictionary in Python? Easy
A dictionary is a collection of key-value pairs. It is unordered, mutable, and indexed by keys.
5
What are functions in Python? Easy
Functions are reusable blocks of code defined using the def keyword. They help organize and reuse logic.
6
What is lambda function? Easy
A lambda function is an anonymous function defined using the lambda keyword. It is used for short, single-expression functions.
7
Explain OOP in Python. Medium
Object-Oriented Programming in Python includes concepts like class, object, inheritance, polymorphism, encapsulation, and abstraction.
8
What is inheritance? Medium
Inheritance allows one class (child) to inherit properties and methods from another class (parent). It promotes code reusability.
9
What is polymorphism? Medium
Polymorphism allows methods to have the same name but behave differently based on context.
10
What are decorators? Medium
Decorators are functions that modify the behavior of other functions or methods without changing their code.
11
What are generators? Medium
Generators are functions that use the yield keyword to return values one at a time, making them memory efficient.
12
What is the difference between deep copy and shallow copy? Medium
Shallow copy copies references of objects, while deep copy copies the complete object including nested objects.
13
What is GIL in Python? Hard
GIL (Global Interpreter Lock) ensures that only one thread executes Python bytecode at a time. It affects multi-threaded CPU-bound programs.
14
What is multithreading? Medium
Multithreading allows concurrent execution of multiple threads within a program. It is useful for I/O-bound tasks.
15
What is multiprocessing? Hard
Multiprocessing uses multiple CPU cores to execute tasks in parallel. It bypasses GIL and is used for CPU-bound tasks.
16
What is exception handling? Easy
Exception handling uses try, except, finally blocks to manage runtime errors gracefully.
17
What is virtual environment? Medium
A virtual environment allows you to create isolated Python environments to manage dependencies separately.
18
What is PIP? Easy
PIP is Python package installer used to install and manage third-party libraries.
19
What is Django? Medium
Django is a high-level Python web framework that follows the MVT architecture and helps build secure web applications.
20
What is Flask? Medium
Flask is a lightweight Python web framework used for building simple web applications and APIs.
21
What is REST API? Medium
REST API is an architectural style for designing networked applications using HTTP methods like GET, POST, PUT, DELETE.
22
What is list comprehension? Easy
List comprehension is a concise way to create lists using a single line of code.
23
What is the difference between Python 2 and Python 3? Medium
Python 3 has improved syntax, better Unicode support, and print is a function. Python 2 is deprecated.
24
How does Python manage memory? Hard
Python uses reference counting and garbage collection to manage memory automatically.
25
What is __init__ method? Easy
__init__ is a constructor method automatically called when a class object is created.
26
What is the Global Interpreter Lock (GIL)? Hard
GIL is a mutex that ensures only one thread executes Python bytecode at a time. It prevents true parallel execution of threads in CPython.
27
How does Python memory management work? Hard
Python uses reference counting and a cyclic garbage collector to manage memory automatically.
28
What is metaclass in Python? Hard
A metaclass defines how a class behaves. It is a class of a class and controls class creation.
29
What are descriptors in Python? Hard
Descriptors are objects that define how attribute access is interpreted using __get__, __set__, and __delete__ methods.
30
Explain MRO (Method Resolution Order). Hard
MRO defines the order in which base classes are searched when executing a method.
31
What is monkey patching? Hard
Monkey patching modifies classes or modules at runtime dynamically.
32
What are coroutines? Hard
Coroutines are special functions defined with async and await that allow asynchronous programming.
33
Difference between async and threading? Hard
Async is single-threaded concurrency using event loop, threading uses multiple threads.
34
What is asyncio? Hard
Asyncio is Python library to write concurrent code using async/await syntax.
35
What is context manager? Hard
Context managers manage resources using with statement and implement __enter__ and __exit__.
36
Explain deep vs shallow copy. Hard
Shallow copy copies references, deep copy copies entire nested structure.
37
What is __slots__? Hard
__slots__ restricts dynamic attribute creation and reduces memory usage.
38
Explain Python bytecode. Hard
Python compiles code into bytecode which runs on Python Virtual Machine.
39
What is Python Virtual Machine? Hard
PVM executes compiled bytecode and handles memory management.
40
Explain difference between multiprocessing and threading. Hard
Multiprocessing uses multiple CPU cores, threading shares memory but limited by GIL.
41
What is pickling? Hard
Pickling converts Python object into byte stream for storage or transfer.
42
What is GIL limitation workaround? Hard
Use multiprocessing or C extensions to bypass GIL limitations.
43
What is dynamic typing? Hard
Python determines variable type at runtime.
44
Explain static typing in Python. Hard
Static typing can be implemented using type hints and mypy.
45
What is Cython? Hard
Cython is superset of Python that compiles to C for performance.
46
What are decorators with arguments? Hard
Decorators can accept parameters and return nested wrapper functions.
47
Explain closures in Python. Hard
Closure is inner function that remembers variables from enclosing scope.
48
What is partial function? Hard
functools.partial creates new function with pre-filled arguments.
49
Explain Python import system. Hard
Python uses sys.path and module cache to locate and load modules.
50
What is memory leak in Python? Hard
Occurs when objects are referenced but not released properly.
51
Explain weak references. Hard
Weak references allow object to be garbage collected.
52
What is Python GIL impact on CPU tasks? Hard
CPU-bound tasks do not scale with threads due to GIL.
53
Explain __new__ vs __init__. Hard
__new__ creates instance, __init__ initializes it.
54
What is dataclass? Hard
Dataclass auto-generates boilerplate code like __init__, __repr__.
55
Explain Abstract Base Classes. Hard
ABC enforces method implementation in subclasses.
56
What is dependency injection? Hard
Technique where dependencies are provided externally.
57
Explain Python GIL removal proposals. Hard
Alternative interpreters like Jython and IronPython do not use GIL.
58
What is lru_cache? Hard
functools.lru_cache caches function results for performance.
59
Explain Python packaging. Hard
Uses setup.py or pyproject.toml to distribute packages.
60
What is event loop? Hard
Event loop schedules async tasks and callbacks.
61
Explain thread safety. Hard
Thread safety ensures shared resources are accessed properly.
62
What is race condition? Hard
Race condition occurs when threads access shared resource unsafely.
63
Explain GIL vs Jython. Hard
Jython does not use GIL because it runs on JVM.
64
What is memory profiling? Hard
Memory profiling analyzes memory usage in applications.
65
Explain Python interpreter types. Hard
CPython, PyPy, Jython, IronPython are Python implementations.
66
What is Python AST? Hard
AST (Abstract Syntax Tree) represents parsed Python code.
67
Explain concurrency vs parallelism. Hard
Concurrency is managing tasks, parallelism is executing tasks simultaneously.
68
What is greenlet? Hard
Greenlet enables lightweight coroutine-based concurrency.
69
Explain Python memory model. Hard
Python memory model handles stack, heap and reference counting.
70
What is contextvars? Hard
contextvars provides context-local state for async tasks.
71
Explain Python threading limitations. Hard
Threads share memory but limited by GIL.
72
What is type hinting? Hard
Type hints provide optional static typing information.
73
Explain Python optimization techniques. Hard
Use caching, multiprocessing, C extensions, profiling tools.
74
How to improve Python performance? Hard
Use PyPy, optimize algorithms, reduce object creation.
75
Explain Python security best practices. Hard
Use virtual environments, sanitize inputs, avoid eval.
76
Design a rate limiter in Python. Hard
Use a token bucket or sliding window approach. Store timestamps in a queue and allow requests within time window.
77
Build an LRU Cache from scratch. Hard
Use OrderedDict or implement doubly linked list with hashmap for O(1) operations.
78
Implement a thread-safe counter. Medium
Use threading.Lock() to synchronize increments.
79
Create a retry decorator for API calls. Medium
Use decorator with loop and exception handling to retry function execution.
80
Design a URL shortener service. Hard
Generate unique hash, store mapping in DB, redirect using lookup.
81
Write a program to detect memory leak. Hard
Use tracemalloc or memory_profiler to monitor object allocation.
82
Implement producer-consumer problem. Hard
Use queue.Queue with threading or multiprocessing.
83
Design a logging system. Medium
Use logging module with different handlers and log levels.
84
Build a file upload validator. Medium
Check file type, size and sanitize filename before saving.
85
Implement pagination in API. Medium
Use limit and offset parameters in database queries.
86
Write a Python script to scrape website data. Medium
Use requests and BeautifulSoup libraries.
87
Design a background job queue. Hard
Use Redis with Celery or Bull-like system.
88
Implement custom context manager. Medium
Define class with __enter__ and __exit__ methods.
89
Design a chat application backend. Hard
Use WebSockets and event-driven architecture.
90
Implement authentication using JWT. Medium
Generate token after login and validate on each request.
91
Build a REST API with input validation. Medium
Use FastAPI or Flask with Pydantic or Marshmallow.
92
Design a caching layer. Hard
Use Redis or in-memory caching with expiration.
93
Implement exponential backoff strategy. Medium
Retry with increasing delay using time.sleep.
94
Write a function to merge overlapping intervals. Medium
Sort intervals and merge if overlapping.
95
Implement custom iterator. Medium
Define __iter__ and __next__ methods.
96
Design a task scheduler. Hard
Use cron-like scheduling or APScheduler.
97
Implement multi-threaded file downloader. Hard
Use threading or concurrent.futures module.
98
Create a CLI tool in Python. Medium
Use argparse module to parse command-line arguments.
99
Design a notification system. Hard
Use pub-sub pattern and message broker.
100
Write a Python script for log parsing. Medium
Read file line by line and use regex to extract data.
101
Implement role-based access control. Hard
Store roles and check permissions before action.
102
Design a payment processing module. Hard
Handle transaction states, retries and idempotency.
103
Build a concurrent web crawler. Hard
Use asyncio and aiohttp for async crawling.
104
Implement circuit breaker pattern. Hard
Stop calls to failing service after threshold.
105
Design a distributed cache invalidation strategy. Hard
Use versioning or pub-sub to invalidate across nodes.
📊 Questions Breakdown
🟢 Easy
10
🟡 Medium
26
🔴 Hard
69
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