How I Turn One Idea Into a Repeatable Product Pipeline (No GPU)

说明与用途

一个由四个 Python 脚本组成的自动化管道消除了重复上传，确保元数据合规，将 Markdown 转换为样式化 PDF，并打包数字产品，能够在单个 vCPU、2 GB RAM、无 GPU 的环境下运行。

问题

Duplicate uploads and metadata errors caused account flags and rejected batches when uploading vector assets to Adobe, Vecteezy, and Dreamstime.

结果

Automated pipeline eliminated duplicate uploads, ensured metadata compliance, produced styled PDFs, and packaged products efficiently on minimal hardware.

工作流

• Create folder layout with assets/, output/, ready‑to‑submit/, packs/, research/, scripts/
• Run make_metadata.py to generate platform‑specific CSV headers
• Use upload_tracker.py to record and prevent duplicate uploads
• Convert Markdown docs to styled PDFs with md2pdf.py
• Package assets, cover, and thumbnail into a zip with pack_product.py
• Track upload status and repeat for each product

证据

Adobe, Vecteezy and Dreamstime each reject a wrong CSV header instantly. Not the file, the header.

来源

I once uploaded the same 12 vectors twice in one afternoon. Same folder, same batch script, one coffee too many. The metadata had matching titles, so the platform flagged the account for duplicate submission.

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All four scripts fit in one idea of a pipeline. I used them to package 39 products, 856 MB of output, on a single vCPU with 2 GB of RAM and no GPU.

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