Python Coding Questions: The Resources and the Challenges

Company hiring managers and engineering department executives in charge of coding interviews for technical talent will be well-acquainted with Python. Python, of course, is a highly popular programming language. It is dynamic and viewed as exceptionally easy to use, with simple syntax. In short, this language is easy to get up and running on almost any machine. At runtime, Python flags code that does not make sense as it runs.

It is a leading programming language at Intel, IBM, NASA, Pixar, Netflix, Facebook, J.P. Morgan Chase, Spotify, and other massive tech companies. YouTube is mostly written in Python, as are Reddit, Pinterest, and Instagram.

For those reasons, Python will be the favorite language of many computer engineering candidates. And, even if they mostly use Java or JavaScript, most senior engineers likely will be able to use Python.

There is a wealth of Python coding questions for interviews reported by the companies named above, suggested by software engineers, or already collected into online coding tests free or by subscription.

Here is an example of questions from one of the many lists of Python coding questions and answers compiled on GitHub:

  • What is the difference between deep and shallow copy?
  • Write a program to find out the name of an object in Python.
  • How does the string get converted to a number?
  • What is the function of negative index?
  • Explain delegation in Python.
  • What is the function of “self”?
  • How is “self” explicitly defined in a method?
  • What is the procedure to extract values from the object used in Python?
  • How [is]…global value mutation used for thread-safety?
  • What are the steps required to make a script executable on Unix?
  • Write a program to read and write the binary data using Python.
  • What is the process to run sub processes with pipes that connect both input and output?
  • What are the different ways to generate random numbers?
  • Write a program to show the singleton pattern used in Python.

If you’re looking for another Python coding interview cheat sheet, here are a few examples of lists of Python interview questions:

Python programming interview questions

Each company’s interviewing process is somewhat different and will favor different types of questions. A technical phone interview cannot test technical skill in coding, including in Python, and using Python to define and solve problems. But the telephone interviewer will typically go through the most frequently asked Python interview questions to assess the candidate’s knowledge of Python vocabulary and ability to explain terms clearly. That will be true of the in-person interview as well, unless there is a white board feature of the interview—which is not a favorite of many candidates.

Online coding interview tests can assess writing code and applying it to tasks. Lists of questions for both types of interviews—technical knowledge and coding—are available specifically for Python.

Here are some of the most frequently asked Python interview questions:

  • What is the difference between list and tuples in Python?
  • What are the key features of Python?
  • What type of language is Python?
  • How is Python an interpreted language?
  • What is pep 8?
  • How is memory managed in Python?
  • What is namespace in Python?
  • What is PYTHON PATH?
  • What are Python modules?
  • What are local variables and global variables in Python?

For more Python programming examples, a truly massive compendium is Computer Science 1000: Part #7 Programming in Python, a 65-page PDF.

Python programs for practice

Thanks to Python’s popularity and the roster of huge tech companies that use it, job candidates can find unlimited opportunity to build skills with Python programs for practice and prepare for job interviews with some cool Python programs.

PYnative: Python Programming is a site for learning the language with a code editor. It arranges its questions into exercise groups on specific Python topics, where the learner needs to answer different Python programming questions and solve challenges.

All the exercises have been tested on Python 3, and each has 10 to 20 questions with a solution for every question. The learner practices these exercises on an online code editor.  Here are examples of the exercise: Basic exercise for beginners, Python input and output exercise, Python loop exercise, Python functions exercise, Python string exercise, Python data structure exercise, and a dozen more.

Below are sample exercises from the Python Input and Output Exercise. Some exercises are incomplete here; on the site, they are accompanied by additional information or tools.

  • Accept two numbers from the user and calculate multiplication.
  • Display “My Name Is James” as “My**Name**Is**James” using output formatting of a print() function.
  • Convert decimal number to octal using print() output formatting.
  • Display float number with 2 decimal places using print().
  • Accept a list of 5 float numbers as an input from the user.
  • Write all content of a given file into a new file by skipping line number 5.
  • Accept any three string from one input() call.
  • Format the following data using a string.format() method.
  • How to check file is empty or not.
  • Read line number 4 from the following file.

Python interview questions for experienced professionals

Any compilation of interview questions intended to assess technical skills, whether by questioning or coding, must begin with the intended role and the skill level required in that role.

When creating and refining our online coding challenges, we focus on the essential positions required on a typical software engineering development team:

  • Mid/Senior Fullstack Engineer
  • Junior/Mid Fullstack Engineer
  • Engineering Manager
  • SRE/DevOps Engineer
  • Mid/Senior Frontend Engineer
  • Junior/Mid Frontend Engineer
  • Mid/Senior Backend Engineer
  • Junior/Mid Backend Engineer
  • Mid/Senior Generalist Engineer

Engineering roles are defined by the expected level of technical skill. Some lists of interviewing questions on the internet take cognizance of skill level, dividing questions into “beginner,” “junior,” and “senior.” You might even find specific Python interview questions for 5 years experience.

Unfortunately, if the online coding test is too “junior” for the position, then too many applicants qualify. If the test is unrealistic about technical skill levels, then the risk is that the best candidates will view the company’s expectations as unrealistic or its understanding of skill levels as flawed. At Woven, we view our online coding challenges as successful if the skills of the candidate are assessed against the highest realistic standard—but also if the coding challenges are fair. Today, more than 90 percent of candidates complete Woven’s technical assessment, including experienced engineers.

Cracking Python interview questions on programming

“Cracking the Code” style interviews can feel like they’re tricking the candidate into failing. They use Python tricky interview questions like:

  • What kinds of classifiers did you use for your projects?
  • Why did you choose OpenCV for your project on gender and age detection? What helped you make the decision?
  • What ratio did you choose to divide your dataset into training and testing sets?
  • Why did you use config.py for this project on breast cancer classification?
  • How was your experience with the XGBClassifier?
  • What challenges did you face in your best Python projects?
  • What do you know about palindromes? Can you implement one in Python?
  • What do you mean by *args and **kwargs?
  • What is a closure in Python?
  • Are these statements optimal? If not, optimize them.

This makes candidates anxious, which hurts underrepresented groups the most. But what if there’s a better way? What if you gave candidates a chance to showcase their skills? There’s a good chance some candidates who stumbled through trick questions will surprise you with their skill in a more realistic work environment.

Python coding interview questions and answers

A company seeking the best assessment tool for screening candidates for computer science positions must be aware of the challenge of assessing technical skills. What is required to directly assess technical skills such as coding? To obtain objective evidence of those skills being applied? The proof is in the demonstration of the skill in use.

As this reality has reshaped the search for technical talent, the coding interview has come front and center in interviewing computer science engineering candidates. The coding interview in broadest terms sets tasks that the candidate tackles as part of the interview.

The traditional in-person interview of candidates has met the “coding” challenge by asking candidates, on the spot, to take on coding tasks on a white board. We already know that whiteboarding has serious drawbacks. Can we test a candidate’s real-life ability to focus on a coding challenge when the candidate is under the immense pressure of a job interview?

Woven online coding challenges

Woven wants to fix the interview mess caused by technical assessments that aim to trick good candidates into disqualification. That’s the best way to give teams like yours the best chance of accomplishing your mission. The world needs more diverse teams shipping meaningful products. We’re proud to play a small role in helping others.

We have pursued a holistic approach to the pivotal challenge of assessing and hiring the best technical talent for company development teams.

  • The challenges that a job candidate will face, if hired, will be to exercise technical problem-solving skills, not just code.
  • The job candidate will succeed on a team only with competence in technical collaboration.
  • The candidate will require core computer engineering skills in debugging, computer architecture, and systems thinking.
  • The candidate will be expected to fill a role (for example, Frontend Developer) at a specified level such as junior, mid, or senior.

When the required problem-solving skills have been objectively and comparatively tested, the results deserve equally nuanced scoring and assessment. Our network of certified engineers evaluate all tests (with at least two independent assessments) to report on recommendations.

We also provide individual engineering feedback to the candidates who complete Woven’s challenges. They receive an objective report on their performance as compared with other candidates.

In a universe of internet sites with every selection and categorization of Python questions and answers, computer science interview questions, testing, and preparation, Woven stands for these values:

  • Asynchronous assessments based on real engineering work are the right alternative to whiteboarding for assessing computer technical skills.
  • Real engineering work is more than code. It involves problem-solving skills like debugging, architecture, and technical collaboration.
  • The technical vetting service should map to the engineering role and expected level of competence.
  • Bias can be drastically reduced by casting a wide net and then using skills assessment to filter for quality instead of subjective evaluations.
  • Competent humans working with rubrics and machines is the optimal path for measuring problem-solving skills.
  • Creating an assessment that’s worthy of experienced engineers is good for the engineering teams who wish to hire them.

If you’re ready to try Woven’s technical assessment platform for seeking technical talent, sign up for a free trial and take a work simulation to see actual results and analysis.