{
  "id": 18202519,
  "title": "Metadata CSVs, Upload Ledgers, and Covers: The Four Scripts Behind 39 Products",
  "url": "https://urgent.news/2026/11/04/metadata-csvs-upload-ledgers-and-covers-the-four-scripts-behind-39",
  "topic": "tech",
  "section": "Tech",
  "published": "2026-11-04T23:12:39.000Z",
  "source": {
    "name": "Dev.to",
    "slug": "dev-to",
    "url": "https://dev.to/revanzart/metadata-csvs-upload-ledgers-and-covers-the-four-scripts-behind-39-products-11ld"
  },
  "original_language": "en",
  "account": "Four scripts form the backbone of a production pipeline behind 39 products. These scripts prevent errors like duplicate uploads and ensure each product adheres to platform-specific requirements. The first script, make_metadata.py, generates metadata CSV files tailored to each platform's specifications. A second script, upload_tracker.py, logs assets as they move through the pipeline to avoid double-posting. md2pdf.py converts Markdown documents into sellable products by formatting, tables, lists, and links. Lastly, pack_product.py packages products into a zip file with a cover and thumbnail image. The entire system runs on minimal hardware requirements and relies heavily on Python's standard library to maintain simplicity and stability.",
  "summary": "Last October I ran my batch upload twice. Same folder, same command, eleven hours apart. I had forgotten which assets I had already submitted to Adobe Stock, so I re-ran the whole thing. Adobe's review caught the duplicates and my account got a warning. That warning is the reason upload_tracker.py exists. This post is about the four scripts that keep my pipeline from making that kind of mistake…",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}