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A Search Engine for High Protein Recipes and Meal Planner

Hacker News

A Search Engine for High Protein Recipes and Meal Planner

Hey folks, I've built this little recipe search engine to scratch my own itch and wanted to share it in case others find it helpful as well. I track what I eat every day to make sure I'm moving towards my goals (whether that be building muscle or cutting fat), but I usually end up defaulting to the standard 'bro meals' like chicken, rice, and vegetables since I'm usually too lazy to find recipes with good macros. So I built this web app focused on recipes and their nutrition. It scrapes the recipes from a bunch of different recipe sites and food bloggers (those that I've found that have nutrition labels). Then I've done some basic data processing and I've filtered out all the recipes that didn't meet the minimum protein ratio so that all the recipes that show up in the results have at least a decent amount of protein. This was a fun project to build. I used Go for both the web app itself and for the crawler. For the interactivity, I'm using HTMX and a little bit of plain JS. And for the database I'm using Sqlite. All-in-all it has been working pretty well. I tried to keep the architecture as simple as possible so I can leave it running forever with minimal maintenance. If you track your meals and also struggle to find good recipes, I hope you find this useful!

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
79%79% 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.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
70%70% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntOn track for Day 1 leaderboard · Strong signals: mac, activity, using · Missing: agents, macos, agent
62%62% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · 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
42%42% 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
16%16% 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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