Plonk – Spotlight Search style Python interpreter

Hacker News

I've just released Plonk, a Spotlight Search style Python interpreter interface for macOS. As someone who often uses Spotlight Search for quick calculations, I was left yearning for more - a way of quickly running snippets of code and bridge the gap between a calculator and a full on script. Plonk solves that problem by dropping you in to a persistent Python interpreter with a global hotkey. The `%copy` command can be used to dump the previous output to the clipboard, or `%copy <expr>` to dump the output of a specific expression/variable. Plonk plugs into system Python by default, but is also compatible with virtualenvs or uv projects. Source and package are available via GitHub: https://github.com/JosephRedfern/plonk

Visit product View on Hacker NewsMay 25, 2026

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

61%61% 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: mac, macos, code · Missing: agents, agent, cursor

52%52% 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: just released, io · Missing: https docs, excited, exist

48%48% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

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

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

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

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

13%13% 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

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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