An API to store balances and transactions

Hacker News

Hey everyone! I'm Rob and I want to share what I've built - a solid ledger behind simple API: https://decimals.app The ledger is a key piece of any financial system and is easy to get the design wrong, resulting in troubles for making sure money movements are adding up. I took a lot of inspiration from good designs from Square, Uber, and others for the scalability and security aspects. And on the usability side, I applied many concepts from the Ledger CLI, making it very easy to use. I'm really happy I get to show this to you all, thank you for reading about it! Please let me know your thoughts and questions in the comments (The sample code on the landing page is not working, I'm fixing it). [1] https://www.ledger-cli.org/ [2] https://www.youtube.com/watch?v=iN6mhI5hFt4 [3] https://developer.squareup.com/blog/books-an-immutable-doubl... [5] https://docs.decimals.app

Visit product View on Hacker NewsMay 29, 2020

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

74%74% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

66%66% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

54%54% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

41%41% 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

35%35% 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.

Correct prediction on native model

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