Py

Python but with Module Import Policies

Hacker News

Python but with Module Import Policies

Hello all, Very excited to share an early stage project of mine! Over the last year I've been reading about software supply chain attacks and their consequences. Suffice to say, I'm paranoid! I've dabbled in a few tools such as Panoptisch( https://news.ycombinator.com/item?id=33926782 ) but wanted to take this even further. I came across Deno's permission model which restricted access to APIs like network, file system, shell and ffi and wanted to take this idea to another language. Possibly as my final project at university. Since I love Python, it made sense to try messing around with CPython. I'm quite satisfied (at the moment) with the result and thought about sharing it with the community for some feedback. Looking forward to your thoughts and for the inevitable pwn of the implementation :)

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Indie HackersFits the IH revenue-focused audience · Strong signals: para · Missing: supports, reddit linkedin, podcasting
82%82% 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: model, new, apis · Missing: mac, agents, macos
61%61% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: excited, ide, io · Missing: https docs, just released, exist
57%57% 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 · Strong signals: para · Missing: mobile apps, ios, personal
27%27% 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
25%25% 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
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.

Incorrect prediction on native model

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