Why Wrong CSV Headers Get Your Vector Uploads Rejected, And The Script That Fixes All Three Platforms

Описание и применение

Автоматизация генерации CSV‑файлов для Adobe Stock, Vecteezy и Dreamstime устраняет ошибки заголовков и дублирование загрузок, позволяя работать на небольшом сервере.

Задача

Hand‑built CSVs for vector uploads often contain header typos or mismatched schemas, causing entire batches to be rejected by Adobe Stock, Vecteezy, or Dreamstime.

Результат

The automation reduced rejections, eliminated duplicate uploads, and allowed the entire pipeline to run on a 1 vCPU, 2 GB server.

Рабочий процесс

• 1. Store asset metadata (titles, keywords) in a JSON file.
• 2. Run python make_metadata.py ./my-assets --platform <platform> --out <csv> --ext .jpg for each platform to generate the correct CSV.
• 3. Use python upload_tracker.py pending items.txt to list pending uploads.
• 4. After successful upload, mark items as done in the ledger to prevent re‑posting.
• 5. Optionally, run PDF rendering and packaging scripts as needed.

Доказательства

I had 60 vectors ready for Adobe Stock. I built the CSV by hand, copied the column names from a blog post, uploaded, and got the rejection email within minutes.

Источник

Adobe Stock wants a 5-column CSV. Vecteezy wants 4 columns. Dreamstime wants 15.

Источник

The command looks like this: python make_metadata.py ./my-assets --platform adobe --out metadata.csv --ext .jpg

Источник

The metadata script and the tracker use only the Python standard library, no pip install at all.

Источник