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Sure Pavan, here’s a list of commonly asked general Python questions specifically tailored for DevOps/SRE interviews — designed to be practical, conversational, and focused on real-world usage rather than deep software engineering theory.

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🐍 Python – General Q&A for DevOps/SRE Interviews

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🔹 1. How do you use Python in your day-to-day DevOps/SRE tasks?

Answer: I use Python to automate tasks like log rotation, server health checks, API calls, AWS automation using boto3, and writing custom CLI tools or alerting scripts.

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🔹 2. What’s the difference between a list and a dictionary in Python?

Answer:

  • List: Ordered, indexed, stores values

  • Dict: Unordered (before 3.7), stores key-value pairs Dict is best for configuration or lookup operations.

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🔹 3. How do you handle errors in Python scripts?

Answer: Using try-except blocks:

try:
    risky_function()
except Exception as e:
    print(f"Error: {e}")

For automation, I log errors or trigger alerts.

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🔹 4. What libraries do you commonly use in your Python scripts?

Answer:

  • os, subprocess – for shell & file operations

  • boto3 – AWS automation

  • requests – REST APIs

  • yaml, json – config handling

  • psutil – system monitoring

  • argparse – CLI inputs

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🔹 5. How do you schedule a Python script?

Answer:

  • Use cron (crontab -e) for scheduling

  • For scripts, I often use schedule or APScheduler libraries in long-running jobs

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🔹 6. What is argparse used for?

Answer: It’s used to parse command-line arguments for Python scripts. Example:

import argparse  
parser = argparse.ArgumentParser()  
parser.add_argument("--env")  
args = parser.parse_args()

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🔹 7. How do you execute a Linux command from Python?

Answer:

import subprocess  
output = subprocess.check_output(["df", "-h"])

Used for tasks like disk space checks or reboots.

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🔹 8. How do you parse JSON or YAML config files in Python?

Answer:

import json  
with open("config.json") as f:
    data = json.load(f)

For YAML:

import yaml  
yaml.safe_load(open("config.yaml"))

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🔹 9. How do you monitor system metrics like CPU or memory in Python?

Answer: With psutil:

import psutil  
psutil.cpu_percent()  
psutil.virtual_memory()

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🔹 10. How do you debug a Python script?

Answer: I use:

  • print() statements for quick checks

  • pdb module for step-by-step debugging

  • IDE debuggers (VS Code/PyCharm)

  • Logs with the logging module

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🔹 11. How do you handle large log files in Python?

Answer: Use file streaming:

with open("log.txt") as f:
    for line in f:
        process(line)

Prevents loading large files entirely into memory.

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🔹 12. What is the use of with statement in Python?

Answer: Used for resource management — automatically closes files/sockets:

with open("file.txt") as f:
    data = f.read()

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🔹 13. How do you check if a file or directory exists?

Answer:

import os  
os.path.exists("/etc/passwd")

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🔹 14. How do you write logs in Python scripts?

Answer:

import logging  
logging.basicConfig(filename='app.log', level=logging.INFO)
logging.info("Script started")

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🔹 15. What’s the difference between == and is in Python?

Answer:

  • == checks value

  • is checks object identity Example:

a = [1]; b = a  
a == b → True  
a is b → True

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🔹 16. How do you make your Python script executable on Linux?

Answer:

  • Add shebang: #!/usr/bin/env python3 at top

  • Make executable: chmod +x script.py

  • Run: ./script.py

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🔹 17. How do you read environment variables in Python?

Answer:

import os  
db_user = os.getenv("DB_USER")

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🔹 18. How do you create a simple REST API in Python?

Answer: Using Flask:

from flask import Flask  
app = Flask(__name__)  
@app.route("/health")  
def health(): return {"status": "ok"}  
app.run()

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🔹 19. What is the purpose of requirements.txt?

Answer: It lists all the packages your Python app depends on. Install with:

pip install -r requirements.txt

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🔹 20. How do you write a basic unit test in Python?

Answer:

import unittest  
class TestApp(unittest.TestCase):  
    def test_add(self):  
        self.assertEqual(1+1, 2)

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✅ Bonus: Python Automation Ideas for DevOps

Task
Script Example

AWS backup via boto3

Automate S3 snapshot uploads

Disk usage alerts

Check psutil.disk_usage()

Service health checker

Ping & alert if unreachable

Log parsing/alerting

Parse /var/log/syslog

Slack alerts for failures

Use requests.post() to webhook

Would you like:

  • 📄 A printable cheat sheet PDF

  • 🧪 Hands-on Python automation projects

  • 🧵 Reel or carousel post content using this

Let me know, Pavan — I can also create topic-wise sets for requests, boto3, yaml, or argparse specifically!

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Here you go, Pavan — a list of theory-based Python questions commonly asked to DevOps/SRE professionals. These questions help interviewers assess your core understanding of Python beyond just scripting — perfect for explaining your thought process confidently.

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🧠 Python Theory Q&A for DevOps/SRE Interviews

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🔸 1. What is Python, and why is it popular for DevOps/SRE work?

Answer: Python is a high-level, interpreted language known for its readability and simplicity. It’s widely used in DevOps for automation, configuration management, monitoring, scripting, and integrating with APIs or cloud SDKs (like boto3 for AWS).

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🔸 2. What is the difference between a list and a tuple?

Answer:

  • list is mutable (can change), slower, uses more memory

  • tuple is immutable (cannot change), faster, safer for fixed data Example:

a = [1, 2]; a[0] = 5  # valid
b = (1, 2); b[0] = 5  # error

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🔸 3. **What are *args and kwargs in Python functions?

Answer:

  • *args: allows passing variable number of positional arguments

  • **kwargs: allows passing variable number of keyword arguments Used for flexible function design.

def f(*args, **kwargs):
    print(args, kwargs)

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🔸 4. What is the difference between Python 2 and Python 3?

Answer: Python 3 introduced:

  • print() as a function

  • Better Unicode support

  • Division differences (/ vs //) Python 2 is deprecated as of Jan 2020.

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🔸 5. What are Python virtual environments? Why are they important?

Answer: venv creates isolated environments to manage dependencies per project. Prevents conflicts between system-wide and app-specific Python packages.

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🔸 6. What is a Python dictionary, and how is it used?

Answer: A dictionary (dict) is a key-value store used for structured data. Example:

data = {"name": "pavan", "role": "devops"}

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🔸 7. What are decorators in Python?

Answer: Decorators are functions that modify other functions. Useful for logging, authentication, retries, etc.

@my_decorator
def my_function():
    pass

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🔸 8. What is a lambda function in Python?

Answer: Anonymous one-liner function.

add = lambda x, y: x + y

Useful in short transformations or with map, filter.

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🔸 9. What’s the difference between is and == in Python?

Answer:

  • is: compares identity (memory location)

  • ==: compares values

a = [1]; b = a; a is b → True  
a == b → True

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🔸 10. What are modules and packages in Python?

Answer:

  • Module: a .py file

  • Package: directory with __init__.py, contains multiple modules They help organize reusable code.

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🔸 11. What is exception handling in Python?

Answer: Used to catch and handle runtime errors:

try:
    risky_code()
except Exception as e:
    print(e)
finally:
    cleanup()

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🔸 12. What is list comprehension in Python?

Answer: A concise way to create lists:

squares = [x*x for x in range(5)]

Cleaner and faster than using for loops.

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🔸 13. What are Python data types you commonly use in DevOps scripts?

Answer:

  • str, int, list, dict, bool, tuple, set Most configs use dict, file reading uses str, API calls use json (dict).

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🔸 14. What is the difference between global and nonlocal?

Answer:

  • global: refers to variables at module level

  • nonlocal: refers to variables in enclosing function scope

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🔸 15. What is the difference between shallow copy and deep copy?

Answer:

  • Shallow copy copies references

  • Deep copy copies full object recursively Use copy module:

from copy import deepcopy

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🔸 16. What is the use of __init__.py?

Answer: Marks a directory as a Python package. Also used to initialize or pre-load modules.

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🔸 17. How is Python used in monitoring/logging pipelines?

Answer: Used with:

  • APIs (send alerts to Slack, Discord)

  • Log parsing (grep-like with regex)

  • Metric collection with psutil, prometheus_client

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🔸 18. What is the Global Interpreter Lock (GIL)?

Answer: A mechanism in CPython that prevents multiple native threads from executing Python bytecodes in parallel. Limits true multithreading but async/multiprocessing are workarounds.

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🔸 19. What are Python’s memory management features?

Answer:

  • Automatic garbage collection

  • Reference counting

  • Cyclic GC for unreachable objects

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🔸 20. What are common libraries used in DevOps tasks?

Answer:

Purpose
Library

REST API

requests

OS interaction

os, shutil

Cloud automation

boto3, azure

Config mgmt

json, yaml

Scheduling

schedule, croniter

Regex parsing

re

Monitoring

psutil, prometheus_client

Would you like:

  • 📘 A full PDF cheat sheet

  • 🧪 Sample theory + hands-on mix questions

  • 🎯 A mock quiz to practice before interviews

  • 📽️ Reels/shorts script ideas for Python interview tips

Let me know how you’d like to use this, Pavan — we can turn this into a full Python for DevOps Interview Series too!

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