Why 'Build a System, Not a Product' Is the Only Advice That Scales

说明与用途

自动化生成 CSV 元数据、避免重复上传并打包文件为专业包，减少了手工工作并提升了在库存平台上的列表质量。

问题

Manual CSV metadata creation and duplicate uploads caused frequent rejections and wasted hours when submitting assets to stock platforms.

结果

Automation reduced manual hours from two hours per batch to seconds, eliminated header typos, prevented duplicate submissions, and produced professional‑looking product packages that improved listing quality.

工作流

• 1. Organize assets in project/assets/
• 2. Run make_metadata.py to generate platform‑specific CSVs
• 3. Use upload_tracker.py to track posted items and avoid duplicates
• 4. Run pack_product.py to bundle files, render cover and thumbnail, and create PDFs
• 5. Submit the generated ZIPs to stock platforms

证据

I built the CSV by hand in a spreadsheet, pasted it into the uploader, and got a rejection in under a minute. Wrong header row.

来源

I stopped hand‑building CSVs and wrote make_metadata.py. It takes a folder of files and writes the exact header each platform demands, nothing more.

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upload_tracker.py is a tiny ledger that remembers what I have already posted. Before any batch run I check pending to see what is actually left.

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pack_product.py bundles the files, renders the cover and thumbnail, and drops everything into a _system folder.

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The whole pipeline runs on 1 vCPU and 2 GB RAM. No GPU.

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