Hookdns (for Python devs)- Because /etc./hosts is not always an option

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Hi, The aim of this Python library is to let you define (or override) DNS resolution directly in your code. No need to modify the hosts file or use an external DNS resolver. I created this library as a toy project a few years ago, mainly to learn how to use GitHub Actions (not really for what the library itself does). I never really shared it before because I don't use it myself, but since a few people have used it, I thought: why not share it with more people if it might be useful to someone, probably for testing purposes? I'd be happy if it can be helpful to any of you. cle.

Visit product View on Hacker NewsJul 29, 2025

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

65%65% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

45%45% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Strong signals: created · Missing: supports, reddit linkedin, podcasting

44%44% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

40%40% 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: host · Missing: plus, platform, intuitive

29%29% 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

15%15% 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.

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