I need a small, self-contained automation that, once a day, pulls fresh data from YouTube, checks which of the newest uploads is currently leading on raw view count, and hands me a clean result file. What the workflow should do • Scrape or query the YouTube Data API for the most recent videos (the source can be a list of channel IDs, a playlist, or a search term that I’ll supply). • Parse the response, store key fields (video ID, title, publish time, current views) and compare them so the script flags whichever item has the highest view total at the time of the run. • Output the winner plus a simple CSV/JSON table of everything fetched, ready for quick import into Sheets or Excel. Scope of the analysis Outperformance is defined strictly by view count—no engagement-rate or watch-time calculations are required right now, but the code should be written clearly enough that I can add those metrics later if needed. Run schedule The job triggers once every 24 hours. A straightforward cron entry, Windows Task Scheduler step, or GitHub Actions workflow file is enough; just document the setup. Tech preferences Python with the YouTube Data API v3, Requests, pandas, and cron are what I have in mind, but Node.js with Axios or any comparable stack is fine so long as it stays lightweight and well-commented. Acceptance criteria The automation runs without manual input, writes the day’s winner and full dataset to disk, and logs any API errors so I can spot quota issues quickly.