A

A just another Cron alternative but with much more capabilities

Hacker News

A just another Cron alternative but with much more capabilities

I have created a Cron alternative that runs DAGs (Directed acyclic graph) defined in a simple YAML format. Why not Airflow? Airflow and other similar tools are powerful and valuable, but in most cases, they require writing code to manage workflows. Our ETL pipeline is already hundreds of thousands of lines of complex code in Perl and shell scripts. Adding another layer of Python on top of this would make it difficult to maintain. Instead, we needed a more lightweight solution. So we developed Dagu, which requires no coding, and is easy-to-use and self-contained, making it ideal for smaller projects with fewer people.

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Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Strong signals: created · Missing: supports, reddit linkedin, podcasting
80%80% 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.
Product HuntOn track for Day 1 leaderboard · Strong signals: coding, code · Missing: mac, agents, macos
75%75% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: lua, ide, pipe · Missing: https docs, excited, just released
72%72% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive
53%53% 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
36%36% 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
12%12% 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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