20+ Interview Questions To Ask Remote Python Developers

20+ Interview Questions To Ask Remote Python Developers

20+ Interview Questions To Ask Remote Python Developers

if you are planning to hire a Python developer and are looking for questions to ask remote Python developers then you are at the right place. Continue reading to know more!

Since 2018, there has been a steady increase in the demand for Python, and in an effort to hire the top candidates, businesses are developing some fantastic Python interview questions. The Python TIOBE index has increased from 3.78 to an astounding 15.74, and in addition, it was named the language of the year in 2018 as well as 2020 and 2021!

Ultimately, it constitutes the fundamental technology stack for emerging fields like as artificial intelligence (AI), machine learning (ML), deep learning (DL), data visualization, DevSecOps, data analytics, and data science.

Naturally, the increased demand for Python programming led to a mad scramble for competent Python programmers who understood how to write functions in Python, write programs in Python, and work with data types in Python.

However, in order to make an appropriate hiring decision, you must first screen resumes for ideal Python developers, assess their Python proficiency, and other tasks before moving on to the interview stage.

Employing these recruiting strategies, along with the appropriate set of Python interview questions, will be crucial to identifying the best candidate for your company as companies increase their efforts to address the skills crisis.

Python Interview Questions Some common python interview questions and answers include which program is better for python programming, how important it is to indent in Python, essential features of Python, how to write a function in Python, and other python coding questions.

In light of this, we will go over 21 essential frequently requested Python interview questions, along with Python coding questions and answers, Python programming interview questions, and other topics, to help you achieve your ultimate recruitment objectives for Python developers.

Why Do You Need a Python Interview Question Guide to Hire the Right Talent?

Let us take a time to discuss the reasoning behind the interview questions before diving straight into the Python ones.

After all, you may be eager to learn the significance or applicability of the Python developer interview questions we’re going to cover. The best preparation list any employer or recruiter has ever had is made up of questions on Python programming. It aids in your comprehension of fundamental Python development abilities, and the developer mostly possesses sufficient program writing knowledge.

The following are some of the main arguments in favor of hiring Python engineers for your software company.

We have seen our fair share of often asked Python interview questions in our capacity as talent management professionals. Furthermore, based on our experience, Python interviews—which include Python interview questions and answers—often represent a make-or-break scenario that is crucial to the hiring process.

You are obtaining a high-level summary of each Python developer’s essential capabilities, including their subject-matter expertise, comprehension and articulation skills, personality, and logical and analytical abilities, in addition to their technical and soft skills.

Because of this, making sure you have the appropriate selection of Python interview questions prepared will guarantee that every question you ask is purposeful and well-thought out.

Put simply, Python interview questions maintain the effectiveness and efficiency of your efforts throughout the recruitment cycle by making every interaction count.

Now that you know why it’s important to keep a list of Python interview questions, let’s look at the ones that really matter!

You’ll read on to learn about interview questions for Python at the mid-level, interview questions for experienced candidates, and interview questions for beginners.

Best Questions to Ask During a Python Interview When Hiring

Python interview questions vary from one another. Given that senior and novice Python developers have diverse skill sets, it stands to reason that the interview questions for each would be very different.

In a similar vein, the interview questions for a Python backend developer would differ from those for a front-end developer. Because Python is the most widely used programming language according to the TIOBE index, python tech interview questions include fundamental python questions that will assist the recruiters make the best decision!

As a result, we have divided our collection of the best Python interview questions into three categories: entry-level, mid-level, and senior-level, depending on skill and experience. Let’s examine each one of them individually in light of this.

Entry-Level Python Interview Questions

Those interested in pursuing entry-level Python development roles need to be well-versed in the language’s syntactic structures and their variations.

They should also be fairly knowledgeable in Python functions, data structures, object-oriented programming, data types, and algorithms. In programming, data structures are the fundamental building blocks. Python data structures that are appropriate for the task can optimize both temporal and spatial complexity. Thus, you can use these as the foundation for your Python interview questions.

Ten basic Python interview questions are provided below to help you get started:

#1 What are Some Fundamental Features of Python?

This interview question for Python delves into the fundamentals of the Python programming language. Most likely, it is comparable to the fundamental interview questions and answers for Python.

Among the crucial elements you need to look for in the response are:

Open-Source: Python is available for free download, and since its source code is accessible to everybody, developers are likewise free to distribute it.

Easy to Learn and Read: This language is easy to learn, read, and code since it is developer-friendly and has a straightforward syntax.

Interpreted: Python does not require compilation because it operates line-by-line.

Programming language that is object-oriented is Python. Python differs from the functional programming language in that it has encapsulation, polymorphism, inheritance, classes, and objects.

Python encapsulation made sure that methods and data were wrapped together. Python allows for numerous inheritances as well. In Python, a class can inherit from more than one base class thanks to multiple inheritances. Check out what the following produced.

Example of Multiple Inheritances-

High-Level: Python developers do not need to manage memory or retain track of the system architecture.

Because it is platform-independent, this language is extremely portable.

Integrated: Python can be used in conjunction with C, C++, and other programming languages. This feature also lends it extensibility.

#2 What are Python Modules? Name Some Popular Ones.

Files with executable Python programs are called Python modules. A monolithic piece of code can be made more modular, legible, efficient, and debug-friendly by dividing it into smaller pieces.

Several frequently used Python modules consist of:

  • wxPython, WCK, PyGObject, PMW, and so forth—for graphical user interfaces
  • Databases: SQLAlchemy, KInterbasDB, MySQLdb, Gadfly, etc. (focus: interview questions for Python backend developers)
  • For web development, use tools like Selenium, scrape, Google Maps, requests, pyquery, etc. (focus: Python front-end developer interview questions)
  • For manipulating images and videos, use Python Imaging Library, MoviePy, pyscreenshot, GDmodule, VideoCapture, etc.
  • For sound manipulation, use tools like Mutagen, PyMedia, PMIDI, and PySonic.
  • For data science and mathematical computations, use programs like Numpy, SciPy, Pandas, Matplotlib, etc
  • Use programs like Pygame, PyOpenGL, Pyglet, etc. to create games.
  • You can change the response to this Python developer interview question based on the needs of your project.

#3 Is Python Case-Sensitive?

Indeed, Python handles capital and lowercase characters differently because it is a case-sensitive language. You can find out if your Python developer can distinguish between variable A and variable a by asking them this question during a Python interview.

#4 Python Indentation: Why Is It Important?

More than just a readability or esthetic aspect of Python, indentation is a fundamental idea that, if ignored, will result in a failure message.

Code blocks are divided into four spaces, which aids developers in defining a block inside a class or function.

#5 What is the Use of Break, Continue, and Pass?

This Python interview question will reveal more about the developer’s loop-working skills. The following describes these statements’ main application:

  • Break: Ends the loop and advances to the subsequent sentence.
  • Proceed: Rejects a loop’s following statements and returns control to the top.
  • Pass: Ignores a section of code that is required for syntactical reasons.

#6 How Would You Define Python Literals? Can You Share a Few Examples?

This interview question for Python developers again assesses the language’s foundations. A literal is a straightforward way to convey a value.

Here are a few typical Python literals:

  • String literals: A string of characters or text encircled by one, two, or three quotation marks. Say, “Hello.”
  • Unchangeable numbers that fall into the categories of integer, complex, or float are known as numerical literals. For instance, 5 (integer), 8i (complex), and 3.14 (float).
  • Boolean literals: ‘0’ denoting falsehood and ‘1’ denoting truth
  • Special literals: Indicates the absence of creation for a specific field. Say, “None”

#7 Can You Explain What a Namespace is?

The naming scheme that Python uses to guarantee that each object has a unique name is referred to as namespace. It is used in conjunction with the Python dictionary.

In Python, some popular namespaces are:

  • The names of the imported modules that are currently in use are stored in the global namespace. It is created when the module is added and removed at the end of the script.
  • Local namespace: It contains the function’s local names. It ends with the function and is called when a function is called.
  • Built-in functions and exceptions are present in the built-in namespace.

#8 What is the Difference Between Python Scope and Namespace in Python

In Python, the notion of scope and the concept of namespace are interdependent. A Python scope, as you have learnt so far, determines where a name appears in your Python program.

Python scopes function as object-to-name dictionaries. The term “namespace” refers to these dictionaries in common usage. These are the theoretical methods that Python employs for name storage.

The module namespace contains names that are stored at the top level of the module. Stated differently, they are stored in the module’s. dict__ attribute.

Examine the results of the following:

#9 Define the Interpreted Language

Line by line, an interpretive programming language runs its code.  Interpreted programming languages include Python, Javascript, R, PHP, and Ruby.

Programs developed in an interpreted language do not require compilation; they run straight from the source code.

#10 Define Scope in Python.

In Python, each object has an own scope. A section of code in Python where an object is still relevant is called a scope.

Namespaces provide each object in a program a distinct identity. With these namespaces, however, you can use their objects without any prefixes because of their declared scope.

Here are some instances of Python scope that are generated while the code is running:

  • Local scope is the name given to a local Python scope that is accessible in the current function.
  • The objects that have been accessible from the beginning of the code execution are referred to as a global Python scope.
  • A section The global objects of the current module that are available within the program are referred to as the Python scope.
  • Every built-in name in the program is covered by an outermost scope.
  • When hiring Python engineers, these kinds of questions can really help you connect with the most qualified applicants.

Mid-Level Python Interview Questions

A mid-level Python developer will have some practical exposure to Python and its modules as well as some experience with Python.

In light of the profile you are hiring against, you can select the mid-level Python questions and answers accordingly.

These seven mid-level Python interview questions might help you get started. 

#11 What Do You Understand by PYTHONPATH?

Using the environment variable PYTHONPATH, developers can add (and manage) additional folders without placing them in the global default location.

To do this, it adds new directories to the Python program’s sys.path directory list so that modules and packages can be found there.

#12 Have You Used the Re Module?Which three primary functions does it offer?

Three primary functions make up the built-in module Re (Regular Expression, or RegEx), which aids in expression matching. These are the following:

  • sub(): It assesses patterns and calls a replace function for each regex match.
  • subn() performs similar operations as sub(), but it also returns a tuple containing the new string and a count of all substitutions made overall.
  • split(): It splits the string along the specified separator and produces regex matches. 

This is a very useful interview question for Python if you need to build search patterns for text data extraction.

#13 In Python, What Do You Mean by Iterators?

Iterators are objects, such as lists, sets, tuples, and dicts, that contain countable values that are iterable. This implies that it will remember its state at different points while you navigate through the various settings.

It utilizes the next() method to iterate to the next element after being initialized using iter(). By returning the StopIteration exception, object__next__() ends the iteration.

#14 Python Lists vs. NumPy Arrays – What Do You Prefer?

A Python list is an arranged, modifiable collection enclosed in square brackets. Both homogeneous and heterogeneous lists are possible.

It can be nested to provide N dimensions, but it is by default one-dimensional. Benefits like concatenation, item insertion, deletion, and adding are included. 

A Python package called NumPy, sometimes known as NumPy array, facilitates the usage of arrays in complex mathematical operations.

It can be used to generate homogenous N-dimensional arrays by default. It has several Python variables, methods, and functions built in for simple matrix computing.

The candidate should indicate a preference for NumPy arrays in their response to this Python interview question because they are significantly faster, more effective, and need less code.

#15 Can You Explain Monkey Patching in Python?

The term “monkey patching” describes the dynamic, run-time modification of a class or module that modifies the behavior of the code. 

#16 Please Point Out How Flask, Django, and Pyramid Differ.

Three very well-known Python libraries are Flask, Django, and Pyramid. The following are some talking points that should be included in the response to this Python interview question:

  • Large-scale Python frameworks like Django and Pyramid have many needs, but Flask is a micro-framework.
  • While Django and Pyramid are often used to build more complicated systems, Flask is typically used to generate smaller apps.
  • Compared to Django, Pyramid is significantly more configurable.
  • Model-view-controller (MVC) architecture is the foundation of Django, which also comes with an ORM.

#17 Have You Used Python Documentation Strings? 

This interview question for a Python developer will provide some insight into the candidate’s coding style. Since Python is an interpreted language, developers must become familiar with Python strings, data types, and code. We are going to talk about Python strings.

In essence, comments that are added to modules, classes, functions, and methods are known as Python documentation strings, or docstrings. Instead of using hashtags, they utilize triple quotes and are not completed.

Adherence to optimal Python development methods is demonstrated by the utilization of Python documentation strings. 

#18 Explain Pickling and Unpickling in Python.

Pickling is the process of serializing Python objects into a string (or any other format) for network transmission or storage persistence.

The process of reintegrating pickled string into its original form is called unpickling.

#19 Compared to Java, How is Exception Handling Differently in Python?

Python uses a try-except method that enables programmers to see errors in their code without stopping it from running.

In certain instances, it might even offer solutions to the issue. Try-except-finally and Try-except-else are the two variants of try-except that Python uses.

#20 Describe the Python Function Writing Process.

Python developers can write functions by doing the following steps:

  • To declare a function, type its name on the keyboard after def.
  • Enter the arguments in the function’s open and closed parentheses, then finish with a colon.
  • Include the statements in the program that will run when the function is called.

#21 How Would You Programmatically Check the Python Version in Use?

The sys module allows the developer to verify the Python version. This would be coded as follows:

bring in Sys

sys.version print

#22 How Can You Generate Random Numbers in Python?

Numerous functions for generating random numbers are supported by Python, including:

  • The function random() yields a floating-point value between 0 and 1.
  • The function uniform (X, Y) produces a floating point value between X and Y.
  • The function Randint (X, Y) yields a random integer between X and Y.

#23 Can You Differentiate Between Wheels and Eggs?

Even though this Python interview question may seem strange to the uninitiated, a proficient Python developer would seize the chance to clarify how Wheel and Egg package formats avoid the need to compile install artifacts.

The following are the main variations between the two:

  • The wheel is a typical guideline for Python developers and is more recent.
  • Egg is used for distribution and installation, whereas the wheel is utilized for packing (distribution).
  • Unlike egg standards, wheel requirements have been versioned.
  • While Egg uses egg and does not have an official PEP, Wheel is required to comply with PEP-376.details.
  • While Egg’s naming conventions are more lax, Wheel’s are more extensive.

#24 What is PEP8? Do You Think it is Worth Following?

A Python Enhancement Proposal, or PEP, is a document that lists the most recent major features of Python that have been added together with suggested best practices. The most recent PEP document, PEP 693, was published in May 2022.


You can make well-informed recruiting judgments by using these questions to assess a remote Python developer’s technical expertise, problem-solving skills, and aptitude for remote work.

You can choose an accomplished full-stack developer from Appic Softwares to work on your project. Our full-stack engineers have extensive experience working on projects all over the world and are exceptionally competent in soft skills.

If you decide to work with them, you may provide your project with excellent development professionals.

So why the reluctance?

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