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Infosys · Python Developer

Infosys Python Developer Interview Questions (2026): process, questions and answers

Updated 25 October 2026 · prep guide

The Infosys Python Developer interview usually tests core Python, web frameworks, data handling and problem solving. Use this guide to review concise answers, practice scenario responses and plan your final study sprint.

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How the Infosys Python Developer interview usually works

  1. application review: Candidates often receive a short call to confirm resume details
  2. technical screen: Usually a coding round on a shared editor covering algorithms and Python basics
  3. deep dive interview: Often includes OOP, Django/Flask, pandas and SQL questions
  4. HR round: Typically focuses on teamwork, communication and career goals
  5. final decision: A summary call to discuss offer and next steps

Technical questions and answers

How does Python manage memory for objects?

Python uses a private heap for object storage and a reference counting mechanism; when count drops to zero the garbage collector frees memory. The cyclic GC runs periodically to clean reference cycles that reference counting alone cannot resolve.

What is a generator and how does it differ from a regular function?

A generator uses the yield keyword to produce a sequence lazily, returning one value at a time and preserving state between calls. A regular function runs to completion and returns a single value, consuming memory for the whole result.

Explain list comprehension and give an example that filters even numbers.

List comprehension creates a new list in a single expression. Example: [x for x in numbers if x%2==0] builds a list of even numbers from numbers without an explicit loop.

What is the purpose of __init__ versus __new__ in a class?

__new__ creates the instance and returns it; it runs before the object exists. __init__ initializes the already created instance’s attributes. Most custom classes only need __init__, while __new__ is used for immutable types or metaprogramming.

How does Flask handle request routing?

Flask maps URL patterns to view functions using the @app.route decorator. When a request matches a pattern, Flask calls the associated function, builds a response object and returns it to the client.

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What is middleware in Django and when would you use it?

Middleware is a lightweight plugin that processes request and response objects globally. Use it for cross‑cutting concerns such as authentication, logging, or modifying headers before view functions handle the request.

Describe how you would implement pagination in a REST API.

Accept page and size query parameters, calculate offset = (page-1)*size, retrieve size records with LIMIT and OFFSET in SQL, and include total count and next/previous links in the JSON response.

How can you merge two pandas DataFrames on a common column while keeping all rows from the left DataFrame?

Use pd.merge(left_df, right_df, on='key', how='left'). This performs a left join, preserving every row from left_df and adding matching columns from right_df where keys exist.

What is a parameterized query and why is it important?

A parameterized query separates SQL code from data values, using placeholders like %s or ?. It prevents SQL injection, improves query plan reuse, and often yields better performance.

How does asyncio.run() differ from creating an event loop manually?

asyncio.run(coro) creates a new event loop, runs the coroutine until completion, and closes the loop automatically. Manually creating a loop gives more control, allowing multiple coroutines to be scheduled or reusing the loop across calls.

Scenario questions

A client needs a Flask endpoint that receives a CSV file, validates data, and stores clean rows in a database. How would you design it?

Explain steps: use request.files to read the file, load it with pandas, apply validation rules, log rejected rows, use a parameterized INSERT for clean rows, and return a JSON summary with counts of processed and failed rows.

You notice a performance bottleneck in a Django view that makes multiple external API calls. What would you do?

Suggest async HTTP client or background task queue, cache frequent responses, profile the view with Django Debug Toolbar, and refactor the view to launch calls concurrently using asyncio.gather or Celery workers.

During a code review, a teammate’s function uses a mutable default argument. How do you address it?

Point out that mutable defaults persist across calls, causing unexpected state. Recommend changing the signature to def func(arg=None): if arg is None: arg = [] and add a brief explanation in the review comment.

HR and behavioural questions

Tell us about a time you had to learn a new technology quickly for a project.

Use STAR: Situation, short project deadline, Task, needed Flask for a microservice, Action, followed official docs, built a small prototype, asked peers, wrote tests, Result, delivered on time and received client praise.

Describe a conflict you faced in a team and how you resolved it.

State the conflict over coding standards, explain you organized a meeting, listened to concerns, proposed a shared style guide using pylint, and the team adopted it, improving code consistency.

How do you prioritize multiple tasks when deadlines overlap?

Mention assessing business impact, breaking work into smaller pieces, using a Kanban board, communicating with stakeholders about trade‑offs, and focusing first on high‑value items while tracking progress.

Why do you want to work at Infosys and how do you see yourself contributing?

Highlight Infosys’s global client base, emphasis on digital transformation, your experience with Python‑based data pipelines, and your plan to drive efficiency in client solutions by applying best practices in code quality and automation.

Your last 48 hours before the interview

  1. Review the 10 technical answers aloud and note any gaps
  2. Write a short Flask endpoint that reads a CSV and returns JSON, then run it
  3. Practice merging pandas DataFrames with a sample dataset
  4. Do a timed coding problem that uses generators and list comprehensions
  5. Re‑read the three scenario questions and rehearse key points
  6. Prepare STAR stories for the four behavioural prompts and record a brief mock interview

Common mistakes to avoid

Frequently asked questions

How many interview rounds are typical for a Python role at Infosys?

Candidates often report a short phone screen, one or two technical rounds and an HR discussion, but the exact number can vary by location and team.

Do I need to bring a portfolio of projects?

It helps to have a few relevant projects ready, especially ones that showcase web development or data processing with Python, as interviewers may ask you to discuss them.

Will there be a live coding platform?

Most technical screens use a shared editor or online IDE where you write and run code in real time, so practice coding without IDE shortcuts.

What soft skills does Infosys value for developers?

Communication, teamwork, adaptability and a client‑focused mindset are frequently mentioned, so be ready to give examples that illustrate these qualities.

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This is an independent preparation guide based on commonly reported interview patterns. The process varies by team, location and year. Interview AI Helper is not affiliated with Infosys.

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