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I started my first Open source project – Firebase cheatsheet/doc

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I started my first Open source project – Firebase cheatsheet/doc

I often found myself frustrated while looking up Firebase JavaScript SDK documentation and not finding what I needed quickly, so I decided to create this little cheat sheet. Currently, it only covers Firestore client and server-side CRUD requests. I will add new topics soon, like storage, auth, setup, and cloud functions. Feel free to contribute it is Open source

Visit productView on Hacker NewsOct 12, 2024
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Actual performance

1points
Did not reach leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: new, open · Missing: mac, agents, macos
83%83% 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
54%54% 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: open source, ide, io · Missing: https docs, excited, just released
49%49% 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 · Missing: mobile apps, ios, personal
43%43% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: soon · Missing: plus, platform, intuitive
33%33% 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
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
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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