Campaign health checks
Use small scripts to compare spend, pacing, delivery, and win-rate anomalies before they become support tickets.
AdTech Learning Hub
Python for AdTech
Python is one of the easiest ways to turn AdTech learning into real operational leverage: faster QA, cleaner API inspection, better KPI checks, and repeatable troubleshooting utilities.
Practical Value
Where Python helps in AdTech work
API payload inspection
Read JSON responses, validate required keys, and convert messy response objects into cleaner internal summaries.
Report cleanup and KPI math
Automate repetitive spreadsheet work like CTR, eCPM, fill rate, pacing gap, and discrepancy checks.
Log and troubleshooting utilities
Search request IDs, timestamps, VAST errors, or HTTP response patterns faster than doing it manually line by line.
Working Pattern
A simple Python workflow for operators
How most useful scripts start
- Pull data from API, CSV, or database.
- Validate the fields you actually need.
- Transform raw data into a simple troubleshooting view.
- Output something useful: summary table, CSV, JSON, or alert-ready result.
Skills worth building
- Reading JSON payloads and nested objects
- Calling REST APIs and handling auth
- Working with CSV and tabular data
- Connecting Python to MySQL safely
- Writing reusable troubleshooting scripts
- Turning scripts into cleaner internal tools
Mini Projects
Good Python builds for this portfolio
KPI calculator
Read impressions, clicks, revenue, and requests from CSV, then calculate CTR, eCPM, and fill rate in one pass.
VAST response checker
Validate whether XML exists, media files are present, trackers are populated, and wrapper chains look healthy.
OpenRTB request parser
Extract `imp`, `site` or `app`, `device`, privacy flags, schain fields, and deal IDs into a readable summary.
Delivery anomaly monitor
Compare yesterday vs today for spend, fill, win rate, and completion rate, then flag abnormal drops.