Python Web Development Interview Questions and Answers

Updated: at 05:45 AM

Python is a popular general-purpose programming language that is well-suited for web development due to its extensive libraries and frameworks for building web applications. In job interviews for Python web developer roles, candidates are commonly asked a mix of general Python coding questions and web development-specific questions to assess their skills and knowledge.

This how-to guide provides an overview of common Python web development interview questions with example answers to help prepare for coding interviews or technical assessments.

Python Coding and Concepts

Python web development interviews will typically include questions testing your general Python proficiency before diving into web-specific topics. Be prepared to answer both basic and advanced questions on Python coding and OOP concepts.

Q: What are the key features of Python programming language?

Python is an interpreted, object-oriented, high-level programming language known for its clear and readable syntax. Some of its key features include:

Q: Explain how Python is interpreted.

Python is an interpreted language. When we run a Python program, the source code is fed to the Python interpreter which converts the code line-by-line into intermediate bytecode that is then executed.

The interpreter parses each line, compiles it to bytecode, and immediately executes it. This means the compilation and execution happen simultaneously rather than compilation occurring separately as a build step.

The bytecode is a platform-independent representation of the code that can then run on the Python virtual machine on any platform. The interpreter’s just-in-time compilation to bytecode makes Python programs portable across Operating Systems.

Q: What is monkey patching in Python? Give an example.

Monkey patching refers to dynamically modifying classes or objects at runtime. In Python, we can modify classes and methods as we please because of its dynamic nature.

For example:

class A:
  def func(self):
    print("func() is being called")

def monkey_func(self):
  print("This is monkey_func")

A.func = monkey_func

a = A()
a.func() # This is monkey_func

Here, we have monkey patched the func method on the A class to override its behavior at runtime. This allows modifying code dynamically without touching the source code.

Q: What is Dunder or magic methods in Python?

Dunder or magic methods in Python are special built-in methods that start and end with double underscores.

For example __init__, __add__, __len__ etc.

These methods can be used to emulate built-in behaviors in user-defined classes. For example, the __init__ method can be used to initialize objects, __add__ can be used to define custom behavior for the + operator and so on.

These double underscore methods are also called magic methods in Python. They provide powerful capabilities to classes including operator overloading, iterable/context management protocols and more.

Q: What is the difference between deep and shallow copy in Python?

import copy
old_list = [[1, 2], [3,4]]
new_list = copy.copy(old_list)
import copy
old_list = [[1, 2], [3,4]]
new_list = copy.deepcopy(old_list)

So the key difference is, changes made to shallow copy’s elements reflect in original elements but not in case of deep copy.

Python Web Frameworks

You should be well-versed in at least one Python web framework like Django or Flask which are commonly used for web development. Understand the framework’s architecture patterns as well as pros and cons.

Q: What are the key advantages and use cases of Django?

Django is a batteries-included web framework for Python providing an MVC architecture out of the box. Some of its major advantages:

Django is suitable for developing content-driven sites with complex data modeling requirements like CRUD web apps, news sites, e-commerce sites etc. The admin interface allows non-technical users to easily edit content.

Q: Explain Flask’s application and blueprint architecture.

Flask follows the Application Factory pattern where the app is created by instantiating a Flask class. Blueprints are used to organize different components like views, templates etc into separate modules that can be registered onto the application.

For example:

# blueprints.py
auth = Blueprint('auth', __name__)

@auth.route('/login')
...

# app.py
from flask import Flask
from blueprints import auth

app = Flask(__name__)
app.register_blueprint(auth)

if __name__ == "__main__":
   app.run()

The Blueprint allows splitting the app into self-contained components that can be registered with the application factory only when required.

Blueprints promote modularity by letting you break down a large app into discrete components.

Q: How are Flask and Django different? When would you pick one over the other?

FlaskDjango
Minimalist web frameworkBatteries included web framework
Uses external libsBundles many features & utilities
Simple routing using WerkzeugMore complex URL routing system
Uses Jinja templatingUses Django templating language (DTL)
More control for developerOpinionated, follows conventions
Better for small applicationsBetter for complex, scalable sites

I would choose Flask for simple web apps that require more customization and control. Django is preferred for feature-heavy sites due to its expansive set of utilities for rapid development following conventions.

Python for Web

You need a strong grasp of Python web development concepts like handling HTTP requests & responses, templating, and working with web APIs.

Q: How are HTTP requests handled in Python web frameworks?

Python web frameworks like Django and Flask provide helper classes to represent HTTP requests and responses as objects.

For example, in Flask, request contains the incoming request data. We can access request parameters, headers, form data, files etc using the request object.

Similarly, response is used to populate response data before returning it to the client.

@app.route("/login", methods=["POST"])
def login():
   username = request.form.get("username")
   # handle login
   ...
   response = make_response(redirect("/welcome"))
   return response

The framework handles parsing the raw HTTP request and populating the request object. We can then process the request parameters without dealing with low-level HTTP handling.

Q: Explain CSS and JS asset management in Django.

Django web applications typically use static files like CSS, Javascript and images that need to be handled properly:

Proper static file configuration improves performance and allows customizing asset handling.

Q: How do you implement authentication in a Flask application?

Flask has extensions like Flask-Login that implement authentication in a Flask app.

The steps would be:

  1. Install Flask-Login extension

  2. Create a User class that implements the UserMixin mixin

  3. Initialize Flask-Login by creating a LoginManager and configuring the User class

  4. Use the login_required and login_user methods to add authentication

For example:

from flask_login import LoginManager, UserMixin, login_required

# User class
class User(UserMixin):
  pass

login_manager = LoginManager()
login_manager.init_app(app)

@app.route("/protected")
@login_required
def protected():
  return "Logged in Successfully"

@app.route("/login")
def login():
   user = User()
   login_user(user)
   return redirect("/protected")

This allows adding full user authentication easily following Flask-Login best practices.

Q: How can you consume a REST API in Python?

To interact with a REST API in Python, we can use the requests module. The key steps are:

  1. Make a GET request to retrieve data:
import requests

url = "https://api.example.com/items"
response = requests.get(url)
items = response.json() # deserialize to dict
  1. Use POST request to create resource:
data = {"name": "Item1"}
response = requests.post(url, json=data)
item = response.json()
  1. PUT request to update resource:
item_id = "123"
url = f"https://api.example.com/items/{item_id}"
data = {"name": "New Item Name"}
requests.put(url, json=data)
  1. DELETE to remove resource:
requests.delete(url)

The requests module provides an easy API for consuming REST APIs in Python, abstracting away the low-level details.

Python for Web Scraping

Web scraping questions test your skills in using Python for extracting data from websites. Being able to scrape data is useful for a web developer.

Q: Write a simple Python script to scrape data from a web page.

Here is a simple script to scrape paragraphs from a web page using the requests and BeautifulSoup modules:

import requests
from bs4 import BeautifulSoup

url = "http://example.com"
resp = requests.get(url)

soup = BeautifulSoup(resp.content, 'html.parser')
paras = soup.find_all('p')

for p in paras:
  print(p.text)

This script makes a GET request to fetch the web page HTML using requests.

BeautifulSoup parses this HTML into a navigable DOM tree. We can use it to easily extract <p> tags containing paragraphs of text.

Finally, we print the paragraph text stripped of HTML tags.

Q: How can you scrape data from a site that blocks scraping?

There are several techniques to bypass blocks while scraping sites:

However, always check the site’s terms to avoid unethical scraping. Consider using their API if available instead of scraping.

Q: What are some best practices for web scraping?

Some web scraping best practices include:

Python Security and Best Practices

You need to demonstrate awareness of security issues and following best practices while building Python web apps.

Q: What are some common security issues that affect Python web applications?

Some common security risks include:

Python web frameworks provide protections against many issues but vulnerabilities can still be introduced by the developer.

Q: How can you prevent SQL injection attacks in Python code?

To prevent SQL injection in Python:

  1. Never concatenate or format raw user input into SQL queries.

  2. Use parameterized queries and prepared statements instead of string formatting.

For example, with psycopg2:

sql = "SELECT * FROM users WHERE id = %s"
cursor.execute(sql, (user_id))

  1. Use ORM libraries like SQLAlchemy that automatically handle escaping all parameters.

  2. Validate and sanitize all user inputs.

  3. Limit database permissions to only what is absolutely necessary.

  4. Use Python DB API’s builtin escaping for exceptional cases.

Q: What are some best practices for writing secure Python code?

Some Python code security best practices include:

Python Testing

Testing skills are highly valued in Python web development roles. Be ready for questions on unit, integration and end-to-end testing.

Q: How are tests written and run in Django?

Django has inbuilt support for writing tests using the django.test module and SimpleTestCase classes.

Some key points:

For example:

# tests.py
from django.test import SimpleTestCase

class LoginTestCase(SimpleTestCase):

  def test_login_page(self):
    response = self.client.get('/login/')
    assert response.status_code == 200

  def test_login_POST(self):
    # Test login view using POST
    ...

This allows testing Django views and functionality without running the server.

Q: What testing approaches are used for end-to-end tests?

End-to-end testing validates the complete application including its integration with external systems like databases, APIs etc. Some approaches used are:

UI Testing - Simulate user interactions and assert for expected outcomes. Done using Selenium browser automation.

API Testing - Test API endpoints directly using a testing library without going through UI. Allows for more granular tests.

Mocking - Isolate components like databases or APIs by mocking their interactions.

Smoke Tests - Broad tests to verify major features work end-to-end.

Exploratory Testing - Ad hoc testing aimed at breaking the software in unscripted ways.

Load Testing - Test application performance under expected traffic loads using tools like Locust.

A combination of these techniques allows thoroughly testing real world scenarios.

Q: How can you implement a mock database for testing in Flask?

Flask provides Flask.app.testing for app testing that can include mocking a database:

import unittest
from flask import Flask

app = Flask(__name__)

# This mock database replaces the real db for testing
app.config['DATABASE_URI'] = 'sqlite://'

class BasicTests(unittest.TestCase):

  def setUp(self):
    app.testing = True
    self.app = app.test_client()

  def test_home(self):
    response = self.app.get('/')
    # Assertions

  def tearDown(self):
    pass

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

We can mock the database by using a temporary in-memory sqlite database while testing. The real production database is not used. This allows running tests in isolation without persistence.

Other techniques like using fixtures or factory boy can also be used to create mock database records to run tests.

Python Deployment and DevOps

Deploying and operating Python applications in production requires DevOps skills like infrastructure configuration, monitoring, logging etc.

Q: How can you configure Python applications for production deployments?

Some key configuration for Python production deployments:

Q: Explain how you have deployed Python web apps to AWS cloud in the past.

Some ways I have deployed Python apps to AWS are:

Following AWS best practices allows taking advantage of its managed services for easier deployments.

Q: How would you monitor and log a live Python application?

Some ways to monitor and log a live Python web app:

This provides rich observability into a Python app for efficient diagnosing and alerting.

Wrapping Up

Python’s growing popularity in web development means that interviewers will test your expertise in areas like Python fundamentals, web frameworks, security, testing, and production deployments. Learning some commonly asked Python web development interview questions helps you better showcase your hands-on skills during technical interviews and land your next Python developer role.