Interview Prep V2

Table of Contents

1. Python Basics
2. OOP Concepts
3. Python Advanced Topics
4. AWS
5. Scenario-Based Questions
6. Coding Questions
7. System Design
8. Flask/Django
9. REST APIs
10. Databases
11. Testing
12. Concurrency
13. Hashing
14. Other Topics

---

Python Basics

Questions and Answers

Q: What is the main purpose of a constructor in OOP?
A:

• Primary role: Initialize object state with default/initial values
• Called automatically during object instantiation
• In Python, implemented via __init__ method
• Enables encapsulation by validating initial data

class User:
    def __init__(self, name: str, id: int):
        self.name = name  # Initialize instance variables
        self.id = id

Q: Which data types are hashable in Python?
A:

Hashable	Non-Hashable
int, float, bool	list, dict
str	set
tuple (if immutable)	bytearray
frozenset	custom objects*

*Objects are hashable if they implement __hash__ and __eq__ methods

Q: What is the role of __name__ in Flask applications?
A:

• Special Python variable storing module name
• Helps Flask locate:
  • Template directories
  • Static assets
  • Root path for relative file paths
• Critical for proper app initialization:
  app = Flask(__name__)

Q: How does file uploading work in Flask?
A:

1. Client sends multipart/form-data request
2. Access files via request.files dictionary
3. Security considerations:
   • Limit file extensions (ALLOWED_EXTENSIONS)
   • Validate content type
   • Store in secure location

@app.route('/upload', methods=['POST'])
def upload_file():
    file = request.files['file']
    if file and allowed_file(file.filename):
        file.save(os.path.join(app.config['UPLOAD_FOLDER'], filename))

Q: What is Flask-JWT?
A:

• Extension for JSON Web Token authentication
• Typical workflow:
  1. User logs in → returns access token
  2. Token sent in Authorization header
  3. Protected routes verify token
• Key features:
  • Token expiration
  • Refresh tokens
  • Blacklist management

from flask import Flask, jsonify, request
from flask_jwt import JWT, jwt_required, current_identity
from werkzeug.security import safe_str_cmp
 
# Sample user database (replace with real database in production)
users = {
    "user1": {
        "username": "user1",
        "password": "password1"  # In real app, use hashed passwords
    }
}
 
class User(object):
    def __init__(self, username):
        self.username = username
 
# Flask app setup
app = Flask(__name__)
app.secret_key = 'super-secret-key'  # Replace with actual secret key
 
# JWT authentication setup
def authenticate(username, password):
    user = users.get(username)
    if user and safe_str_cmp(user['password'], password):
        return User(username)
 
def identity(payload):
    username = payload['identity']
    return users.get(username)
 
jwt = JWT(app, authenticate, identity)
 
# Protected route
@app.route('/protected')
@jwt_required()
def protected():
    return jsonify({'message': f'Hello {current_identity.username}! This is a protected route'})
 
# Login endpoint (automatically created by Flask-JWT at /auth)
# curl -X POST -H "Content-Type: application/json" -d '{"username":"user1","password":"password1"}' http://localhost:5000/auth
 
# Example usage
if __name__ == '__main__':
    app.run(debug=True)

---

OOP Concepts

Questions and Answers

Q: Explain the diamond problem in multiple inheritance
A:

• Occurs when class inherits from two classes sharing a common ancestor
• Python resolves using MRO (Method Resolution Order) with C3 linearization
• Example resolution order: Child → Parent1 → Parent2 → Grandparent

class Grandparent:
    def method(self):
        print("Grandparent")
 
class Parent1(Grandparent):
    def method(self):
        print("Parent1")
 
class Parent2(Grandparent):
    def method(self):
        print("Parent2")
 
class Child(Parent1, Parent2):
    pass
 
# MRO: Child → Parent1 → Parent2 → Grandparent

---

Python Advanced Topics

Questions and Answers

Q: How can you implement a custom iterator?
A:

1. Implement __iter__ returning self
2. Implement __next__ with iteration logic
3. Raise StopIteration when complete

class CountDown:
    def __init__(self, start):
        self.current = start
 
    def __iter__(self):
        return self
 
    def __next__(self):
        if self.current <= 0:
            raise StopIteration
        num = self.current
        self.current -= 1
        return num
 
# Usage:
for num in CountDown(5):
    print(num)  # 5,4,3,2,1

Q: What is the Global Interpreter Lock (GIL)?
A:

• Mutex protecting Python object access
• Impacts:
  • Allows only one thread execution at a time
  • Limits CPU-bound multithreading performance
  • Doesn’t affect I/O-bound operations
• Workarounds:
  • Multiprocessing
  • Asyncio for I/O tasks
  • C extensions releasing GIL

---

AWS

Questions and Answers

Q: How would you secure S3 buckets?
A:

• Access control methods:
  • IAM policies (principle of least privilege)
  • Bucket policies (resource-based)
  • ACLs (legacy, avoid)
  • Presigned URLs for temporary access
• Encryption:
  • SSE-S3, SSE-KMS, SSE-C
  • Client-side encryption
• Monitoring:
  • Enable S3 access logging
  • Use CloudTrail for API tracking
  • Set up Config rules for compliance

Q: Explain Lambda cold starts
A:

• Initialization phase when no idle instances available
• Factors affecting duration:
  • Runtime (Python < Java)
  • Package size
  • VPC configuration
• Mitigation strategies:
  • Provisioned concurrency
  • Keep packages lean
  • Avoid VPCs when possible
  • Periodic ping (keep-warm)

---

Coding Questions

Add Two Numbers (LeetCode Optimized)

class ListNode:
    def __init__(self, val=0, next=None):
        self.val = val
        self.next = next
 
def addTwoNumbers(l1: ListNode, l2: ListNode) -> ListNode:
    """
    Time Complexity: O(max(m,n))
    Space Complexity: O(max(m,n))
    """
    dummy = ListNode()  # Anchor node for result
    current = dummy
    carry = 0
    
    while l1 or l2 or carry:
        # Calculate sum of current digits
        val1 = l1.val if l1 else 0
        val2 = l2.val if l2 else 0
        total = val1 + val2 + carry
        
        # Update carry and create new node
        carry, digit = divmod(total, 10)
        current.next = ListNode(digit)
        current = current.next
        
        # Move to next nodes if available
        l1 = l1.next if l1 else None
        l2 = l2.next if l2 else None
    
    return dummy.next

Optimized Zero Sorting

def move_zeros_and_sort(arr: list) -> list:
    """
    Time Complexity: O(n log n) due to sort
    Space Complexity: O(n)
    """
    # Partition zeros and non-zeros in single pass
    zeros_count = 0
    non_zeros = []
    for num in arr:
        if num == 0:
            zeros_count += 1
        else:
            non_zeros.append(num)
    
    # In-place sort for memory efficiency
    non_zeros.sort()
    return [0]*zeros_count + non_zeros

---

System Design

Task Scheduler API Design

Key Components:

1. Authentication: JWT with refresh tokens
2. Authorization: RBAC (User/Admin roles)
3. Endpoints:

   POST /api/tasks       - Create task
   GET /api/tasks?status=active - Filter tasks
   PUT /api/tasks/{id}   - Update task
   DEL /api/tasks/{id}   - Delete task
   POST /api/tasks/reminders - Set reminder
   

4. Database Schema:

   CREATE TABLE tasks (
       id UUID PRIMARY KEY,
       user_id UUID REFERENCES users(id),
       title VARCHAR(255),
       status ENUM('pending', 'completed'),
       due_date TIMESTAMP,
       created_at TIMESTAMP DEFAULT NOW()
   );

5. Scalability:
   • Use Redis for rate limiting
   • Celery for async reminders
   • Sharding by user_id for horizontal scaling

---

Flask/Django

Questions and Answers

Q: Flask vs Django Middleware
A:

Feature	Flask	Django
Middleware Type	Decorator-based	Class-based
Execution Order	Route-specific	Global
Flexibility	High	Structured
Common Uses	Auth, Logging	CSRF, Session

Q: Optimize Flask Performance
A:

• Use production server (Gunicorn/uWSGI)
• Enable JIT compilation with PyPy
• Database optimizations:
  • Connection pooling
  • Index optimization
  • Query caching
• Enable compression with Flask-Compress
• Use CDN for static assets

---

REST APIs

Best Practices

1. Versioning: /api/v1/resource
2. Pagination: ?page=2&limit=50
3. Filtering: ?status=active&sort=-created_at
4. HATEOAS: Include resource links
5. Rate Limiting: X-RateLimit headers
6. Error Handling:

{
    "error": "InvalidRequest",
    "message": "Missing required field: email",
    "code": 400
}

---

Databases

Connection Pooling Pattern

from sqlalchemy import create_engine
from sqlalchemy.pool import QueuePool
 
engine = create_engine(
    'postgresql://user:pass@host/db',
    poolclass=QueuePool,
    pool_size=10,
    max_overflow=5,
    pool_timeout=30
)

---

Testing

Pytest Fixture Example

import pytest
 
@pytest.fixture
def db_connection():
    conn = create_test_connection()
    yield conn  # Setup/teardown
    conn.close()
 
def test_query(db_connection):
    result = db_connection.execute("SELECT 1")
    assert result.fetchone() == (1,)

---

Concurrency

Thread Pool Pattern

from concurrent.futures import ThreadPoolExecutor
 
def process_data(data):
    # CPU-intensive work
 
with ThreadPoolExecutor(max_workers=4) as executor:
    futures = [executor.submit(process_data, chunk) 
              for chunk in data_chunks]
    results = [f.result() for f in futures]

---

Hashing

Secure Password Handling

from werkzeug.security import generate_password_hash, check_password_hash
 
hashed_pw = generate_password_hash('secret', method='pbkdf2:sha512')
is_valid = check_password_hash(hashed_pw, 'secret')  # Returns bool

---

Other Topics

CI/CD Pipeline

graph LR
A[Git Commit] --> B[Run Tests]
B --> C{Build Docker}
C -->|Success| D[Deploy Staging]
D --> E[Integration Tests]
E --> F{Manual Approval}
F --> G[Deploy Prod]