From Prompt To Packaged Product In Under An Hour: The Four Scripts That Made 39 Stock Assets

说明与用途

四个脚本自动化了元数据创建、上传跟踪、文档转换和打包，使作者能够在一台1 vCPU、2 GB RAM的服务器上，在一小时内准备好39个可上传的资产。

问题

Uploading 39 finished assets to stock channels failed due to CSV header mismatches and risk of double‑posting, preventing the assets from being listed.

结果

The four scripts automated metadata creation, upload tracking, document conversion, and packaging, enabling the author to produce 39 ready‑to‑upload stock assets in under an hour on a 1 vCPU, 2 GB RAM server.

工作流

• Run python make_metadata.py to generate a CSV with the exact header for the chosen platform.
• Use python upload_tracker.py to list pending items and mark items as done after upload.
• Convert markdown documents to PDFs with python md2pdf.py.
• Package assets and generate covers with python pack_product.py.
• Upload the resulting ZIP to the stock channel.
• Maintain a folder layout with assets/, output/, packs/, research/, and scripts/.
• Use a single‑core server with memory‑management practices such as gc.collect() and single‑process rendering.

证据

Adobe wants 5 columns. Vecteezy wants 4. Dreamstime wants 15.

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The double‑posting fix was the simplest script of the four.

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Half my products are documents: guides, pattern sheets, license notes.

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The last script bundles everything. pack_product.py zips the files and renders a cover at 1280×720 plus a thumbnail at 600×600.

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The whole thing ran on 1 vCPU and 2 GB RAM, so a few habits carried the load: One process at a time. Never fan out image jobs in parallel on a 1-core box.

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