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Dagu v1.13.0

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Dagu v1.13.0

Dagu is a lightweight workflow engine that replaces Cron. It comes with a full-featured Web UI. It allows you to define dependencies between commands as a DAG in declarative YAML format. Features: - Install by only a single binary - Zero dependencies - No database is required - Built-in Web UI and API Details: https://dagu.readthedocs.io/en/latest/web_interface.html Quickstart: https://dagu.readthedocs.io/en/latest/quickstart.html New features: 1. Added run and params field Now you can modularize DAGs. You can run another DAG from a DAG by specifying the name: ```yaml steps: - name: running sub_dag run: sub_dag params: "FOO=BAR" ``` 2. Accept JSON list to specify command and args You can make the DAG to be more readable by using list notation for specifying complex arguments to a command: ```yaml steps: - name: step1 description: print current time command: [python, "-c", "import sys; print(sys.argv)", "argument"] ```

Visit productView on Hacker NewsMay 26, 2024
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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: new, single, using · Missing: mac, agents, macos
78%78% 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: para · Missing: supports, reddit linkedin, podcasting
68%68% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
60%60% 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: para · Missing: mobile apps, ios, personal
38%38% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: interface · 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
20%20% 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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