100+ Python interview questions and answers for 2025

This basic Python interview question warms up the candidate for the interview and is important even for senior Python positions. How you tackle this question displays your experience and expertise with the programming language. Python is a high-level, object-oriented programming language that enhances user interaction through objects, modules, and automatic memory. Due to Python being a cross-platform programming language, it can run on a myriad of different Operating Systems such as Windows, Linux, Macintosh, and UNIX.

The language finds widespread use in data science, artificial intelligence, and machine learning because of its in-built data structures. Despite being a high-level language, the simplicity of its syntax makes Python a very easy language to grasp. Moreover, because Python supports various modules and packages, making applications using Python becomes extremely easy as less code is required.

Another basic Python interview question that tries to gauge the depth of your understanding of the language. Python is considered to be a multi-paradigm language, which means it supports multiple programming techniques including object-oriented and functional programming. Since most Python tools have bundled up data and functions, it is considered to be object-oriented. The functions of Python are important for data scientists and programmers alike because Python supports both object-oriented and functional programming.

In Python, variables are used for labeling and storing data. There are mainly two types of variables in Python - local and global. When a variable is not defined within a function, therefore is referenced within that function, its scope is global and it is called a global variable. When a variable is defined within a function, its scope is local and it is called a local variable.

Additionally, using the keyword, ‘global’, you can explicitly declare a variable, declared within a function, as a global variable. Since the local variable is defined within a function, when accessed outside that function, it will return an error. Global variables, on the other hand, can be accessed throughout the program.

Slicing in Python is about dividing a given string to obtain sub-strings. If you wish to access sequences such as lists, tuples, and strings, slicing is the feature that will help you do so. You can select a specific range or part of these sequences using slicing. You can change or delete parts of sequences like lists that can be changed. Slicing in Python helps you write clean, precise, and readable code. You can perform slicing in Python by either extending indexing or using the slice() Constructor.

This Python interview question delves somewhat deeper into the programming language. In order to give a distinct and unique name to every single object, Python has a system called, namespace. The value of the object, which can be a variable or a method, is connected to the unique name assigned to that object. While searching for the object, the key, which corresponds to the unique name, is mapped with the value assigned to the related object.. Python has its namespace maintained like a Python dictionary.

Pass is a placeholder for the future code in Python. When the pass statement is executed, no operation takes place. It basically depicts a blank space, however, in places, like loops, class definitions, conditional statements such as: if statements, or even in function definitions, where empty code is not permitted, a pass can be used to prevent an error.

The pass statement is not ignored by the Python interpreter, as it returns a null value, therefore it is different from a comment, which is ignored by the Python interpreter. This Python interview question can display your alertness and future orientation to the interviewer.

Unittest or unit testing is a way to test various codes in Python to ascertain whether they can be used safely or not. This framework is in-built in Python and helps to ensure the quality of code in Python. All the criteria, that are found to be useful and practical during the development process, are coded into the test script by the Python developer. This is done to ensure unit preciseness and accuracy. If any criterion fails, it is reported in the summary. This Python interview question can help the interviewer assess whether you are careful and stringent where the safety of code is concerned.

All programming languages use positive indexing in the arrays to locate and access elements. Python is the only language that allows both positive and negative indexing in arrays. A positive index would start from the first element of an array and go forward i.e. the first element would be 0, the second element would be 1, and so on. In negative indexing, the last element of the array would have the index -1, the penultimate element would be -2, and so on.

For example,

arr = [a, b, c, d, e]

print(arr[-1])

print(arr[-2])

Output

e

d

The Microsoft Open Database Connectivity is an interface for the C programming language. It is the standard for all APIs using database C. If you use a Python ODBC interface with the standard ODBC drivers that ship with most databases, you can likely connect your Python application with most databases in the market. The different Python ODBC modules are pyodbc, PythonWin ODBC, and MxODBC.

You can use a secure connection with the extensions SMTP_SSL() and .starttls(). Following this step, use the built-in smtplib library module to define the SMTP client session object. This object can then be used to send the email message using Python Script. To send the emails you can use HTML content, as well as, the attachments with the email package. If you use a CSV file that contains contact data, you can even send a number of personalized emails. If you add a few lines of code to your Gmail account, you can configure the Yagmail package to send emails. Through this Python interview question, interviewers can understand your knack for applying Python for different uses.

PEP means Python Enhancement Proposal, is an official design document that provides information for the Python community. It typically documents the style guidelines for Python code

Some of its features are:

• Dynamically typed
• An interpreted language
• Object-oriented
• Coding is quick

It means Python type-checks data types during execution. This implies that the Python interpreter type checks as the code runs.

A scope is a block of code in which an object is relevant. Examples of scopes in Python are local scope, module-level scope, outermost scope, and global scope.

The script file must begin with #!/usr/bin/env Python. This means that the first line must always begin with ‘#’.

A Docstring is a multiline string used to document a specific code segment. Therefore, developers using Python can easily understand what the code does without having to study the implementation details.

It is a constructor method automatically called to allocate memory when a new instance or object is created, and classes in Python have an init associated with them which initializes attributes declared in the class when an object of that class is created.

These are sequence data types used in a collection of objects. Both have different data types: lists are represented with square brackets and tuples are represented with parentheses.

Example of list:
[1,2,3,4,5,6,7]

Example of tuples:
(13, 90, 11)

In order to use arrays in Python, one must import either an array module or a NumPy package, whereas lists are already built into the language and do not require declaration.

It is used to represent the instance of the class. This is because in Python, the ‘@’ syntax is not used to refer to the instance attributes.

While and For are the major two-loop statements in Python.

Example:

Decorator is a very useful tool in Python that is used by programmers to alter the changes in the behavior of classes and functions.

The built-in types in Python include:

• Strings
• Integer
• Complex numbers
• Floating-point numbers
• Built-in functions

A file in Python with extension “.py” are source files while with extension “.pyc” are compiled bytecode files generated by the compiler.

In Python, functions can be created/defined using the def statement. To create these functions, firstly we declare them and name them. Then, we start a function definition.

They do so using the return statement. The statement can be used inside a function to refer the result back to the caller. The return statement has the return keyword and the optional return value. This return value can be used on any Python object.

OS.unlink(filename) or OS.remove(filename)

This is a file that includes a set of various functions and statements that can be added to an application. They are basically of two types:

• Built-in Modules
• User-defined Modules

This is an environment variable used to import a variable and check for the presence of variables present in different directories.

A package is a collection of different related modules. It normally contains a file with the name init . py.

Creating a module in Python is fairly simple.

1. First, open a text editor and create a new file.
2. Add the code you want to include in the module. You can include various functions and classes, as well as global variables.
3. Save the file with a .py extension (e.g. myModule.py).
4. Import the module using the import statement.
5. Use the module's functions and classes in your program.

This is the small anonymous function used in Python as an inline function. An example of lambda function is:
lambda arguments : expression

In Python, the memory is managed using the Python Memory Manager. The manager allocates memory in the form of a private heap space dedicated to Python. All objects are now stored in this Hype and due to its private feature, it is restricted from the programmer.

These are reserved words with special meanings used to define types of variables. However, they cannot be used for function names or variables. Examples of keywords are: Break, And, Or, If, Elif, For, While, etc.

Yes, it is a case-sensitive language.

Literals are used to represent fixed values for primitive data types in a Python source code.

This is the conversion of one data from one type to another.

The dir() function can be accessed from the Python interpreter, and it is used to access built-in functions of modules and packages. It is used to display the defined symbols.

They can be removed using the remove() or pop() function.

Yes. It is still valid and such a function will return a None object. This is because the end of a function is defined by the block of code that is executed and not the explicit keyword.

They can be used to enclose a string that has a mix of single and double or used when spanning multiple lines.

The role of the init method is to initialize the values of instance members for objects.

Example:

The lower () function, is used to convert string to lowercase

Example:

The split method is used to separate strings in Python

Example:

This is a block that is preceded by the try keyword. The try blocks are used to execute a task, and if any errors occur while the execution, then what should happen is declared in except.

Generators are ways of implementing an effective representation of iterators and it is the only normal function that provides expression in the function. Thus, this enables Python developers to create iterators in a quick and clean way.

We can simply do this:

A built-in function named reverse() is used in Python to reverse lists.

Example:

Ways to do this include:
By joining = combining them on a common column
By stacking two dataframes vertically
By stacking two dataframes horizontally

Some of the new features in the Python 3.11.1 version are:

• Fine-Grained Error Locations in Tracebacks
• Support for Parsing TOML in the Standard Library
• Introduce task groups to asyncio
• Up to 10-60% faster than Python 3.10

PIP represents Python Installer Package. It is a command-line tool used for installing different modules in Python.

It is used to free up unwanted resources and clear up waste before invoking the garbage collector.

The override modifier is used for overriding a base class function within the child class while the new modifier is used to inform the compiler to use the new implementation and not the base class function.

In Python, an empty class is a class that does not have any members defined within it. To create this in Python, we can use the pass keyword.

Of course, yes. It can be called if it is a static method in the base class.

Parent members in a child class can be accessed in Python by using the super() keyword. This method allows the child class to access the parent class's methods and attributes.

Pandas is an open-sourced library used in data manipulation when high performance is required. It is multidimensional data and was derived from the phrase ‘Panel Data’. It is used for loading, manipulating, preparing, modeling, and analyzing data.

NumPy is a Python-based, versatile, easy-to-use package for processing arrays. It stands for Numerical Python.

NumPy is able to solve problems related to vectorized operations that are difficult for Python lists. Additionally, as the dimensions of a NumPy array grow, it is capable of processing operations up to 30 times faster than Python lists.

By using the numpy.loadtxt() method, which automatically reads the header of the file and footer lines and brings up a comment if applicable.

Reindexing in Pandas refers to the process of creating a new object with the data conformed to a new index.

We use the copy module to copy objects in Python. This can be done by shallow copy or deep copying.

In shallow copying, the copied object creates an exact copy of the values in the original object, while in deep copying, it duplicates the objects referenced by the source object.

Pickling is a serialization process in Python. It is used to serialize objects into the byte system and dump them as a file in a memory.

Unpickling is the deserialization of the byte system to recreate objects stored in the file and loads the object to memory.

Pickling: pickle.dump()

Unpickling: pickle.load()

Type conversion is the process of converting a data type into another data type in Python. Some types of type conversions are listed below:
hex(), set(), list(), tuple(), float(), int(), ord(), etc

Example:

In Python, Polymorphism makes us understand how to perform a task in different ways in Python. It is useful in providing flexibility in task processes. Through polymorphism, a class's objects can invoke another class's methods, allowing for code reuse. Polymorphism also allows subclasses to override the methods of a superclass, allowing for further code reuse. This is especially useful in object-oriented programming, as it allows for inheritance that allows code to be written once and reused multiple times.

It is used to convert the existing case of a string from lowercase to uppercase or vice versa.

Example:

It is used to reverse the order of a sequence or an array

Example:

A SQLite3 command installation is needed to initiate and create the database in Flask. Using Flask, the database can be requested in three ways:

teardown_request() method: This is called in cases where the responses are not assured and the exception is raised.

after_request() method: This is called after requesting the database and also sending the response to the client.

before_request(): This method allows the database to be requested before only without passing arguments.

This is the occurrence of an event when the website is hit with more requests by the client at a time and the cache expires. It can be prevented using the semaphore lock.

Yes. Multiple inheritances are supported in Python because it enables flexibility to inherit multiple base classes in a child class. An example is:

No. Python does not use access specifiers. However, Python has a way of prefixing the method variable, or function by using a single or double underscore to act like the behavior of private and protected access specifiers.

We use the init method to create a constructor in Python and an example is given below:

Example:

The code below can be used for this:

The join() function is used to provide a flexible way to concatenate strings. The join() is a string method that returns a string value.
An example is given below:

This can be done by replacing it with the mean value of the column

df[‘column_name’] =

df[‘column_name’].fillna((df[‘column_name’].mean()))

It is a file automatically created inside each Django project, as a command-line utility that allows users to interact with any Django project in Python in different ways.

The shuffle method is used to randomize the items in an array. The shuffle method randomizes elements in an array each time it is called and results in different outputs.

Example:

The random module is used as the standard module to generate a random number in Python. The method employed is defined as:

import random
random.random

*args in Python allows for a variable number of non-keyworded arguments to be passed to a function, with the operations performed on them defined by the function. On the other hand, **kwargs allows for a variable number of keyworded arguments to be passed to a function, which will perform dictionary operations on them.

A flask is basically minimalistic that behaves like the MVC framework. Therefore, MVC would be best for the flask and an example is given below:

This can be done using the isalnum() method that returns true in case the string has only alphanumeric characters or the match() method from the re (regex) module. But here, we are going to show an example for the isalnum() method:

"dkac1961".isalnum() #Output: True

"qbaz#@12".isalnum() #Output: False

The Python modules are files using the Python code which can be functions, classes, or variables. They are followed by the .py extension and some of them are:

• JSON
• re
• sys
• math
• os
• random
• datetime

PyChecker and Pylint are tools used for static analysis and listing respectively. Pylint helps to check for the module’s coding standards and support the different plugins as to create customized features as per requirements. PyChecker helps to find bugs in the Python source code files and brings to attention the code issues.

When no exception occurs.

The answer will be:

invalid code

Using the StringIO module from the io module to read and then using the Pandas library: