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Added Supporting Function by Patreon to Pixela

Hacker News

Added Supporting Function by Patreon to Pixela

I previously (last October) developed an API service called Pixela https://pixe.la/ and announced it here.(At that time, I didn't know the "SHOW HN" rule, so it didn't get talked about much.) It is a API service for generating GitHub-like graphs. https://news.ycombinator.com/item?id=18289947 https://medium.com/@a.know.dev/pixela-a-service-for-generati... I have been improving since then. Today I am announcing the addition of supporting function by Patreon to Pixela. https://github.com/a-know/Pixela/releases/tag/v1.11.0 If you register for Pixela support by Patreon https://www.patreon.com/pixe_la , you will receive an email with `thanks-code`. Set that code up in your Pixela account and you'll get a few limited features. I would like you to check the details here https://github.com/a-know/Pixela/wiki/How-to-support-Pixela-... , but at the moment I have the following offers: - On the following pages, a badge will be displayed on the username. - [Detail page of each graph]( https://docs.pixe.la/entry/get-graph-html ) - [Graph list page]( https://docs.pixe.la/entry/get-graph-list-html ) - The `isSecret` property of `Graph` is available, which is a parameter to turn off the display of graph on the [graph list page]( https://docs.pixe.la/entry/get-graph-list-html ). By the way, this integration between Patreon and Pixela was made possible by Patreon Webhook. I love developing Web services as a hobby. I am pleased with the compatibility with Patreon. Please try Pixela https://pixe.la/ !!

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Actual performance

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Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Strong signals: para · Missing: supports, reddit linkedin, podcasting
83%83% 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
62%62% 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 · Strong signals: way, para · Missing: mobile apps, ios, personal
46%46% 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
36%36% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: user, new, email · Missing: mac, agents, macos
28%28% predicted probability of success on Product Hunt, 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
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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