40+ Senior Python Developer Interview Questions and Answers

Yes, we can update a tuple in a list of tuples. However, tuples are immutable, so we need to create a new tuple.

• To update a tuple in a list of tuples, we can convert the tuple to a list, update the desired element, and then convert it back to a tuple.

• For example, if we have a list of tuples called 'list_of_tuples' and we want to update the second tuple, we can do: list_of_tuples[1] = tuple(updated_list)

• Similarly, we can update a tuple in a tuple of lists by converting the inn...read more

The answer to the question is a Python function that finds all occurrences of a given substring in a string and returns the count.

• Use the `count()` method to find the count of occurrences of a substring in a string.

• Iterate through the string and use slicing to check for occurrences of the substring.

• Store the occurrences and their counts in a dictionary or a list of tuples.

Shallow copy and Deep copy in Python Difference and how to use?

• Shallow copy creates a new object but references the original object's memory address

• Deep copy creates a new object with a new memory address and copies the original object's values

• Shallow copy can be done using slicing, copy() method, or the built-in list() function

• Deep copy can be done using the deepcopy() method from the copy module

• Shallow copy is faster and uses less memory, but changes to the original object ...read more

Tuple is immutable and ordered, while list is mutable and ordered. Tuples are used for fixed data, lists for dynamic data.

• Tuple is created using parentheses (), while list is created using square brackets []

• Tuples are immutable, meaning their elements cannot be changed once defined, while lists are mutable and can be modified

• Tuples are typically used for fixed data that will not change, while lists are used for dynamic data that may need to be updated or modified

• Example: Tupl...read more

Different testing frameworks in Django include Django's built-in test framework, pytest, and unittest.

• Django's built-in test framework: Provides tools for testing Django applications and is easy to use.

• pytest: A popular testing framework that offers more features and flexibility compared to Django's built-in test framework.

• unittest: A standard Python testing framework that can also be used for testing Django applications.

Monolithic architecture is a single unified unit while microservices architecture is composed of small, independent services.

• Monolithic architecture is a single, indivisible unit where all components are tightly coupled.

• Microservices architecture breaks down the application into smaller, independent services that communicate with each other through APIs.

• Monolithic applications are easier to develop and deploy but can be harder to scale and maintain.

• Microservices allow for bet...read more

Sum numbers in a string with groups of numbers and strings

• Split the string into groups of numbers and strings

• Convert each group of numbers to integers and sum them

• Handle cases where the group contains both numbers and strings

List is mutable, Tuple is immutable in Python.

• List can be modified after creation, Tuple cannot be modified.

• List uses square brackets [], Tuple uses parentheses ().

• List is used for collections of items that may need to be changed, Tuple is used for collections of items that should not change.

• Example: list_example = [1, 2, 3], tuple_example = (4, 5, 6)

Django is a high-level Python web framework that encourages rapid development and clean, pragmatic design. Flask is a lightweight WSGI web application framework.

• Django is a full-featured framework with built-in ORM, admin panel, and authentication system, while Flask is more lightweight and flexible.

• Django follows the 'batteries included' philosophy, providing many built-in features out of the box, whereas Flask is more minimalistic and allows developers to choose their own t...read more

Scaling a database involves horizontal or vertical scaling, with types including sharding, replication, and partitioning. Flask handles multiple requests using a WSGI server like Gunicorn.

• Types of scaling include horizontal scaling (adding more servers), vertical scaling (upgrading server resources), sharding (splitting data across multiple servers), replication (copying data to multiple servers), and partitioning (dividing data into smaller parts).

• Flask handles multiple requ...read more

Django code to render hello world template

• Create a new Django project

• Create a new Django app within the project

• Create a template file with 'hello world' content

• Update views.py to render the template

• Update urls.py to map a URL to the view

Use indexing, partitioning, and sharding to handle large datasets in RDBMS.

• Create indexes on frequently queried columns to speed up search operations.

• Partition tables based on a specific column to distribute data across multiple disks.

• Use sharding to horizontally partition data across multiple servers.

• Consider using NoSQL databases for unstructured data or when scalability is a concern.

Use SQL to display the email for a given username from a data set, grouped by username.

• Use a SQL query to select the email for the input username from the data set

• Group the results by username using the GROUP BY clause

• Ensure to handle cases where the username may not exist in the data set

You can create a database from Python using libraries like SQLAlchemy or Django ORM.

• Use SQLAlchemy library to create a database in Python

• Define database models using classes in SQLAlchemy

• Use Django ORM to create a database in Python

• Run database migrations to create tables in Django ORM

To make a Flask application responsive, optimize code, use asynchronous tasks, implement caching, and utilize a CDN.

• Optimize code for faster response times

• Use asynchronous tasks to handle multiple requests concurrently

• Implement caching to store frequently accessed data

• Utilize a Content Delivery Network (CDN) for faster content delivery

MVC stands for Model-View-Controller, a design pattern used in Django to separate the application into three interconnected components.

• Model represents the data and business logic of the application.

• View handles the presentation layer and interacts with the user.

• Controller acts as an intermediary between the Model and View, handling user input and updating the Model and View accordingly.

• Django's implementation of MVC is slightly different, with the View and Controller combine...read more

To connect to a database, use a database driver and provide connection details.

• Choose a database driver that is compatible with your database management system.

• Provide the necessary connection details such as host, port, username, and password.

• Use the driver's connect() method to establish a connection to the database.

• Close the connection when done using the close() method.

Find min and max from a list without using function

• Iterate through the list and compare each element with current min and max values

• Update min and max values accordingly

The current project can be optimized by improving code efficiency and reducing redundancy.

• Identify and remove any unnecessary code or functions

• Use built-in Python functions and libraries to reduce code complexity

• Implement caching or memoization to reduce computation time

• Optimize database queries and indexing for faster data retrieval

• Use profiling tools to identify and fix performance bottlenecks

Mixins in Django are a way to reuse code across multiple classes by providing methods and attributes that can be inherited.

• Mixins are classes that provide methods and attributes to be inherited by other classes.

• They are used to add common functionality to multiple classes without repeating code.

• Mixins are not meant to be instantiated on their own, but rather to be inherited by other classes.

• An example of a mixin in Django is the LoginRequiredMixin which adds login required fu...read more

Decorator in Python is a design pattern that allows adding new functionality to an existing object without modifying its structure.

• Decorators are functions that modify the behavior of other functions or methods.

• They are denoted by @decorator_name above the function definition.

• Decorators can be used for logging, timing, authentication, etc.

• Example: @staticmethod, @classmethod, @property

The command 'print(Hello World)' will result in an error due to missing quotes around the string.

• The string 'Hello World' should be enclosed in quotes to be treated as a string literal.

• Correct command: print('Hello World')

SaaS and PaaS are cloud model types with different levels of service and control.

• SaaS (Software as a Service) provides software applications over the internet, with the provider managing everything from infrastructure to maintenance.

• PaaS (Platform as a Service) offers a platform allowing customers to develop, run, and manage applications without worrying about the underlying infrastructure.

• SaaS is more user-friendly and requires less technical expertise, while PaaS gives more...read more

Slicing a list in Python returns a new list containing a subset of elements from the original list.

• Slicing syntax: list[start:end:step]

• Start index is inclusive, end index is exclusive

• Omitting start index defaults to beginning of list, omitting end index defaults to end of list

• Negative indices count from the end of the list

• Examples: list[1:4] returns elements at index 1, 2, 3; list[:3] returns elements at index 0, 1, 2

Python code to merge lists into a single list

• Use the extend() method to merge lists

• Alternatively, use the + operator to concatenate lists

• Consider using list comprehension for merging multiple lists

List is mutable and tuple is immutable in Python.

• Lists use square brackets [] while tuples use parentheses ().

• Lists can be modified while tuples cannot be modified once created.

• Lists are used for collections of homogeneous items while tuples are used for heterogeneous items.

• Lists are slower than tuples in terms of performance.

• Lists are used for dynamic data while tuples are used for static data.

Indexes are data structures that improve the speed of data retrieval operations on a database table.

• Indexes are created on one or more columns of a table.

• They store a copy of the indexed data in a separate structure.

• This allows the database to quickly locate the data when a query is executed.

• Indexes can be unique or non-unique, clustered or non-clustered.

• Creating too many indexes can slow down data modification operations.

Use find() method to fetch data from MongoDB

• Use db.collection_name.find() to fetch all documents in a collection

• Add criteria inside find() to filter data, like db.collection_name.find({ key: value })

• Use projection to specify which fields to include or exclude, like db.collection_name.find({}, { field1: 1, field2: 0 })

Decorators are a way to modify or extend the behavior of functions or methods without changing their code.

• Decorators are functions that take another function as an argument and return a new function.

• They are commonly used to add functionality to existing functions, such as logging, timing, or authentication.

• Decorators can be used to enforce access control, modify the input or output of a function, or cache results for performance optimization.

Identifying and removing repetitive words or elements in a list.

• Iterate through the list and keep track of unique elements

• Use a set to efficiently remove duplicates

• Consider using list comprehension to filter out repetitive elements

An inline function is a function defined within the scope of another function, typically used for short and simple operations.

• Inline functions are defined within the body of another function.

• They are typically used for short and simple operations.

• Inline functions are often used to improve code readability and maintainability.

Iterators are objects that allow iteration over a sequence, generators are functions that yield values one at a time, and lambdas are anonymous functions.

• Iterators are objects that implement the iterator protocol, with methods like __iter__() and __next__().

• Generators are functions that use the yield keyword to return values one at a time, pausing execution between each yield.

• Lambdas are anonymous functions defined using the lambda keyword, typically used for simple, one-line...read more

Remove duplicate elements from a list of strings

• Use a set to store unique elements

• Iterate through the list and add elements to the set

• Convert the set back to a list to get the final result

Using lambda function to take the mark of 2.

• Use lambda function to define a function that takes a parameter and returns the mark of 2.

• Example: mark_of_2 = lambda x: x * 2

• Call the lambda function with the desired input to get the mark of 2.

API methods are functions or procedures that allow interaction with an API to perform specific tasks or access data.

• API methods define the actions that can be taken by a user or application when interacting with an API

• They can include methods such as GET, POST, PUT, DELETE for retrieving, creating, updating, and deleting data

• API methods often require specific parameters or data to be passed in order to perform the desired action

A decorator is a design pattern in Python that allows you to add new functionality to an existing object without modifying its structure.

• Decorators are functions that take another function as an argument and extend its behavior without modifying it directly.

• They are commonly used to modify or enhance the behavior of functions or methods.

• Decorators are denoted by the @ symbol followed by the decorator name above the function definition.

• They can be used for logging, timing, aut...read more

Merge two sorted lists into a single sorted list

• Create a new list to store the merged result

• Compare elements from both lists and add the smaller one to the result list

• Continue until all elements from both lists are merged

Merge Sort is a popular sorting algorithm that uses the divide and conquer approach.

• Divide the array into two halves

• Recursively sort each half

• Merge the sorted halves back together

Use the append() method to add a row to a dataframe in Python.

• Use the append() method with a dictionary of values to add a row to a dataframe.

• Make sure the keys in the dictionary match the column names in the dataframe.

• Example: df.append({'column1': value1, 'column2': value2}, ignore_index=True)

Prefetch is used to reduce database queries by fetching related objects in advance, while select_related fetches related objects in a single query.

• Prefetch is used when accessing related objects individually, while select_related is used when accessing related objects in a loop.

• Prefetch can be more efficient when dealing with many-to-many relationships, while select_related is more suitable for foreign key relationships.

• Prefetch can be combined with select_related to optimize...read more

Oops concepts refer to Object-Oriented Programming principles like Inheritance, Encapsulation, Polymorphism, and Abstraction.

• Inheritance: Allows a class to inherit attributes and methods from another class.

• Encapsulation: Bundling data and methods that operate on the data into a single unit.

• Polymorphism: Ability to present the same interface for different data types.

• Abstraction: Hiding the complex implementation details and showing only the necessary features.

A generator in Python is a function that returns an iterator object.

• Use the 'yield' keyword to return values one at a time

• Generators are memory efficient as they do not store all values in memory at once

• Example: def my_generator(): for i in range(5): yield i