Python UI-ME – Bringing life to Python functions

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I built python-uime, a simple tool that lets your Python functions say “make elegant UI forms out of me.” Add a single @ui_enabled decorator and UI-Me library instantly generates a clean web control panel for your script — with forms for each argument, type-inferred inputs, grouped tabs, global variable setters, rich JSON output. It is like a toned down version of python click-web. Or like Swagger UI, but for your Python functions, built entirely with vanilla HTML/CSS/JS + a small Flask server. No React, no design systems, no heavy front-end stack. - Automatically maps function arguments - Works with regular python functions - It is UI first, and not CLI first - Supports json and nested objects as inputs and responses.

Visit product View on Hacker NewsNov 24, 2025

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Indie HackersFits the IH revenue-focused audience · Strong signals: supports · Missing: reddit linkedin, podcasting, created

75%75% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Product HuntOn track for Day 1 leaderboard · Strong signals: single · Missing: mac, agents, macos

72%72% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

43%43% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

42%42% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

35%35% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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