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

说明与用途

make_metadata.py 生成符合股票平台要求的精确列标题的 CSV，消除导致整个批量被拒绝的标题错误。

问题

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

结果

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

工作流

• 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.

证据

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.

来源

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

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

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

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

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