How make_metadata.py Writes the Exact Column Headers Each Stock Platform Demands

Описание и применение

Скрипт make_metadata.py генерирует CSV с точными заголовками, требуемыми платформами, устраняя ошибки заголовков, которые приводят к отклонению всех файлов в пакетной загрузке.

Задача

A batch of 240 Adobe Stock CSV files was rejected because one header column was misspelled, causing the entire upload to fail.

Результат

The pipeline processes 240 assets in seconds, with metadata generation never being a bottleneck, and avoids costly re‑uploads caused by header errors.

Рабочий процесс

• 1. Run make_metadata.py with platform, output, and extension options to generate a CSV with the correct header. 2. (Optional) Provide titles.json to replace default title‑casing and add keywords. 3. Use upload_tracker.py to record pending and completed uploads, preventing double‑posting. 4. Submit the CSV to the stock platform.
• 5. If rejected, edit titles.json and regenerate CSV before resubmission.

Доказательства

I lost a whole afternoon last month to a rejected Adobe Stock CSV. 240 files, ready to go, all rejected in seconds with a header error.

Источник

The script has the three headers hard-coded. There is no template file to edit, no config to misconfigure.

Источник

I got the headers right by checking them against real uploads, not documentation alone, because documentation drifts and the upload parser does not.

Источник

upload_tracker.py is a plain standard-library ledger. Before uploading, you check what is actually left.

Источник

This pipeline runs on a 1 vCPU, 2 GB RAM server with no GPU.

Источник