ZakuChess, an open source web game built with Django, htmx and Tailwind

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A while ago I started this side project to test if I could build a rich User Interface that would have about the same level of responsiveness than a "SPA-like" app, but using only htmx[1]... I still have plenty of stuff in my roadmap, but today it's in a playable state and I thought it could be interesting to share it - as it may be a nice demonstration of a relatively rich user interface powered by htmx :-) --> https://zakuchess.com As for the stack: it's built mostly with Django, htmx and Tailwind CSS. It uses a SQLite database, and is hosted (for free) at Fly. The characters' graphics come from the open source game Battle For Wesnoth. I'm afraid my skills in terms of design are rather suboptimal, so the quality of the design is... well, let's just say it's playable ahah The whole thing is open source: https://github.com/olivierphi/zakuchess#readme Apart from the source code itself, the repo's README also gives a bit more details about the various packages I used. 1. htmx: https://htmx.org/

Visit product View on Hacker NewsMar 9, 2024

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

84%84% 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.

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

76%76% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: open source, ide, io · Missing: https docs, excited, just released

75%75% 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, interface · Missing: plus, platform, intuitive

47%47% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

38%38% 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

11%11% 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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