Top 50 Python Full Stack Developer Interview Questions & Answers (2025)

Python Interview Questions For Freshers

Here are some Python Full Stack Developer interview questions for freshers, often asked in entry-level job interviews.

1. What is Python?

Python is a widely used, high-level programming language known for its readability and simplicity. Python, developed by Guido van Rossum and initially released in 1991, supports various programming paradigms such as procedural, object-oriented, and functional programming.

2. What are the key features of Python? 

Python is recognized for its ease of use, clarity, and wide range of available libraries. Key features include dynamic typing, interpreted nature, and a vast standard library.

3. What are the benefits of using Python language?

The benefits of using Python include:

• Easy to learn and read
• High-level language
• Large standard library
• Extensive third-party packages.
• Cross-platform
• Strong community support
• Good for prototyping
• Easily integrated with other languages.
• It is freely available for use and distribution, including for commercial applications.

4. What are some common Python libraries used in full-stack development?

Some common Python libraries for full-stack development are:

• Django – High-level web framework for rapid development and clean design.
• Flask – Lightweight and flexible web framework for building web applications.
• SQLAlchemy – ORM for working with databases in Python.
• Requests – HTTP requests and API handling.
• Pandas – Data manipulation and analysis; used extensively for backend processing.
• NumPy – Numerical computations and array operations.
• Celery – Asynchronous tasks and background jobs.
• Jinja2 – Template engine used with Flask and Django for rendering HTML.

5. How will you check if a class is a child of another class?

To check if a class is a child (subclass) of another class in Python, the built-in issubclass() function is used.

Syntax:

issubclass(child_class, parent_class_or_tuple_of_classes)

Parameters:

• child_class: The class to be checked for subclass status.
• parent_class_or_tuple_of_classes: The parent class, or a tuple of classes, against which the child_class is checked.

6. What does it mean to finalize in Python? 

It is used for finalization in Python. In Python, the term 'finalize' is related to resource management and garbage collection. It is part of the weakref module that allows objects, prior to being collected and destroyed by the garbage collector, to perform cleanup actions. This is usually used for releasing unmanaged resource.

7. Are access specifiers used in Python?

Python does not use access specifiers like private, protected, and public. Instead, it uses naming conventions to indicate the intended visibility

8. What does the ‘#’ symbol do in Python?

In Python, the ‘#’ symbol is used to indicate a comment. Everything following the ‘#’ on that line is ignored by the Python interpreter. Comments are used to explain code and make it more understandable to humans.

9. What is the difference between a mutable and an immutable data type in Python?

• Mutable Data Types: These can be modified after they are created. Examples include lists ‘(list)’ and dictionaries ‘(dict)’.
• Immutable Data Types: These cannot be modified after their creation. Examples include strings ‘(str)’ and tuples ‘(tuple)’.

10. How are arguments passed in Python: by value or by reference?

In Python, all arguments are passed by reference, but it’s important to understand that Python variables hold references to objects. This means that while you cannot change the reference itself (i.e., the variable points to a different object), you can modify the object if it is mutable.

11. What is encapsulation?

Encapsulation is the concept of wrapping data (variables) and methods into a single unit (class) and restricting access to some of the object's components.

12. What is inheritance and what are its different types?

In object-oriented programming (OOP), inheritance allows classes to derive attributes and methods from other classes thereby permitting code reusability and a hierarchical class structure. The types of inheritance in Python are:

• Single Inheritance: A class (subclass) inherits from one and only one parent class (superclass).
• Multiple Inheritance: It occurs when a class inherits from more than one parent class. This allows a subclass to combine functionality from multiple superclasses.
• Multilevel Inheritance: A class derives from one class, which itself is derived from another class. This creates a chain of inheritance.
• Hierarchical Inheritance: It occurs when multiple subclasses inherit from a single parent class. This allows different subclasses to share the same parent class functionality.
• Hybrid Inheritance: It involves merging two or more forms of inheritance. It can involve multiple, multilevel, hierarchical, or any other forms of inheritance.

13. What is the difference between `__init__` and `__new__` methods in Python?

•   `__init__` is the initializer (or constructor) method of a Python class, called when a new object is created. It initializes the attributes of the object after it has been created.
• `__new__` is responsible for creating a new instance of the class. It's called before `__init__`, and it determines the instance of `__init__` works on. `__new__` is rarely overridden unless works with immutable objects like tuples or strings.

14. Explain how to use the with statement in Python.

Python's with statement wraps a code block's execution in methods that a context manager defines (using __enter__ and __exit__). This statement makes resource management easier, like opening and closing files. It ensures that Python cleans up resources after use. For example, it closes files after reading or writing. The with statement means you don't need to write explicit cleanup code such as file.close().

15. What are Python’s built-in data types?

Python’s built-in data types include:

• Numeric types: int, float, complex.
• Sequence types: list, tuple, range, str.
• Mapping type: dict.
• Set types: set, frozen set.
• Boolean type: bool.
• Binary types: bytes, byte array, memory view.

16. What is DNS?

DNS, or Domain Name System, is like the "phonebook" of the internet. It translates human-friendly domain names (like google.com) into numerical IP addresses that computers use to identify each other on the network. This makes it easier for users to access websites without remembering complex number strings.

17. How does HTML5 differ from earlier versions of HTML?

HTML5 introduces new features and improvements over previous HTML versions:

• New semantic elements (like <header>, <footer>, <article>, and <section>) to enhance code structure and accessibility.
• Native audio and video support using <audio> and <video> tags, eliminating the need for third-party plugins.
• Improved support for graphics and animation through the <canvas> element and SVG.
• Better integration for mobile platforms and responsive design.
• Enhanced APIs (like drag-and-drop, offline storage, and geolocation).
• Previous versions lacked many of these integrated capabilities and relied more on external plugins, like Flash.

18. What does CORS (Cross-Origin Resource Sharing) mean?

CORS is a security feature in web browsers that allows or restricts web applications running on one domain to request resources from a different domain. It helps control cross-domain requests and prevents unauthorized access to resources, protecting sensitive information from malicious scripts.

19. What is meant by Multithreading?

Multithreading refers to the ability of a CPU or program to execute multiple tasks or threads concurrently, improving performance and resource utilization. Each thread runs as a separate unit of execution within a process, allowing applications to handle multiple operations at once, such as performing calculations while responding to user input.

20. What is an Interpreted Language?

An interpreted language is a type of programming language where most instructions are executed directly by an interpreter program, rather than being compiled into machine code beforehand. This means code can run immediately but may be slower compared to compiled languages. Examples include Python, JavaScript, and Ruby.

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Python Interview Questions For Experienced

Here are the Python interview questions for experienced professionals. Candidates in this category are often already working in python full stack developer jobs and might be looking to upgrade their skills or aim for higher python full stack developer salary packages.

1. Write a program to generate Fibonacci numbers.

def fibonacci_generator():
    a, b = 0, 1
    while True:
        yield a
        a, b = b, a + b

# Usage
fib_gen = fibonacci_generator()
for _ in range(10):
    print(next(fib_gen))

Output:

0
1
1
2
3
5
8
13
21
34

2. Difference Between Deep Copy and Shallow Copy

• Shallow Copy: A shallow copy generates a new object, but includes references to the objects contained in the original. If the original object contains other objects (like lists), the copied object will refer to the same internal objects. This can be done using the copy module’s ‘copy()’ function.

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

• Deep Copy: A deep copy creates a new object and recursively copies all objects found in the original, so no references to the original objects are maintained. This can be done using the copy module’s ‘deepcopy()’ function.

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

3. Write a Python function to merge two sorted lists.

def merge_sorted_lists(l1, l2):
    merged_list = []
    i = j = 0
    while i < len(l1) and j < len(l2):
        if l1[i] < l2[j]:
            merged_list.append(l1[i])
            i += 1
        else:
            merged_list.append(l2[j])
            j += 1
    merged_list.extend(l1[i:])
    merged_list.extend(l2[j:])
    return merged_list

# Example
l1 = [1, 3, 5]
l2 = [2, 4, 6]
print(merge_sorted_lists(l1, l2))  # Output: [1, 2, 3, 4, 5, 6]

4. Write a Python function to implement a binary search.

def binary_search(arr, target):
    low, high = 0, len(arr) - 1
    while low <= high:
        mid = (low + high) // 2
        if arr[mid] == target:
            return mid
        elif arr[mid] < target:
            low = mid + 1
        else:
            high = mid - 1
    return -1

# Example
arr = [1, 2, 3, 4, 5, 6]
target = 4
print(binary_search(arr, target))  # Output: 3

5. Write a Python function to check if the two strings are anagram

def are_anagrams(s1, s2):
    return sorted(s1) == sorted(s2)

# Example
print(are_anagrams("listen", "silent"))  # Output: True
print(are_anagrams("hello", "world"))    # Output: False

6. Write a Python function to find the largest element in an array.

def find_largest(arr):
    return max(arr)
# Example
arr = [3, 1, 4, 1, 5, 9, 2]
print(find_largest(arr))  # Output: 9

7. Write a Python function to perform a quicksort on the list.

def quicksort(arr):
    if len(arr) <= 1:
        return arr
    pivot = arr[len(arr) // 2]
    left = [x for x in arr if x < pivot]
    middle = [x for x in arr if x == pivot]
    right = [x for x in arr if x > pivot]
    return quicksort(left) + middle + quicksort(right)

# Example
arr = [3, 6, 8, 10, 1, 2, 1]
print(quicksort(arr))  # Output: [1, 1, 2, 3, 6, 8, 10]

8. Write a Python function to check if a given string is a palindrome.

def is_palindrome(s):
    return s == s[::-1]
# Example
print(is_palindrome('radar'))  # Output: True
print(is_palindrome('hello'))  # Output: False

9. What is the Global Interpreter Lock (GIL) in Python?

The Global Interpreter Lock (GIL) is a mutex in CPython that protects access to Python objects, preventing multiple native threads from executing Python bytecodes at once. It ensures that only one thread executes Python code at a time, even if run on multi-core processors. The GIL can be a problem for CPU-bound programs but does not affect I/O-bound programs significantly.

10. What are decorators in Python, and how do they work?

A decorator helps you change or extend some functionality to a function or method. A decorator takes in the function, extends it, and returns a new function after that. To use a decorator, one needs to use the syntax @decorator_name annotation that comes before the function implementation. When decorators are applied in Python, they are commonly used for logging, access control, or memoization.

Thus, the path to becoming a Full Stack Python Developer comprises the learning of front-end and back-end technologies, wherein Python and Django are the core technologies for back-end development. Frameworks, databases, APIs, and integration methods would be put to the test in the interviews for this position. For freshers, a good understanding of the basic concepts—often taught in a full stack python developer course—coupled with some hands-on experience would carry significant weight. Whether you choose a python full stack developer course free or a paid one, following a python full stack developer roadmap and mastering the python full stack developer skills will increase your chances of landing one of these roles.

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1. What are the key areas to focus on when preparing for Python Full Stack Developer interviews?

Focus on core Python concepts, Django, front-end technologies (HTML, CSS, JavaScript), databases (SQL and NoSQL), REST APIs, and deployment strategies.

2. What kind of Python Full Stack interview questions can I expect as a fresher?

Interview questions for freshers may include basic Python questions, database handling, and simple front-end integration.