Python Automation and Data Processing for DevOps
Automate infrastructure tasks and process data with Python scripts.
About This Assessment
Python is the second most in-demand programming language globally and essential for DevOps, data engineering, and automation roles. With AI/ML and automation driving 45% of business priorities in 2026, companies need to verify candidates can write production-grade Python scripts for real-world automation—not just solve algorithm puzzles. This assessment validates practical scripting ability in high-volume hiring scenarios.
What Candidates Will Do
Write a Python script to parse log files (e.g., Apache/Nginx access logs) and extract metrics like top IPs, status codes, error rates
Automate a system administration task: manage files, monitor disk usage, or backup/restore directories with error handling
Process structured data (JSON/CSV) from an API or file: filter, transform, aggregate, and output results
Interact with a database or REST API using Python libraries (requests, psycopg2, pymongo) to fetch and manipulate data
Write unit tests for the scripts using pytest
Automated Grading
Verify Python scripts execute without errors, parse files correctly and produce expected output (validate JSON/CSV structure, metric calculations), automate tasks create/modify system files as intended, API/database interactions retrieve and process data correctly, scripts handle edge cases (missing files, network errors), code follows Python best practices (PEP 8, exception handling, logging), unit tests pass and cover key functions
Environment
Ubuntu 22.04 VM with Python 3.11+, pip, common libraries (requests, pandas, pytest, psycopg2, pymongo), sample log files and datasets, PostgreSQL or MongoDB running locally, Git
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$99.00