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I'm building TaskWeave, a typesafe task orchestrator

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I'm building TaskWeave, a typesafe task orchestrator

Hi, I'm building a task orchestrator library with the ability to specify dependencies between task and with an ability to pass return value into the next task. So something like following is possible: 1. Task1 executes its operation and returns 5 2. Task2 depends on Task1 and retrieve the value returned by Task1, that is 5. 3. Task2 executes its operation and uses the value from Task1. The tasks also type safe, so there's no need for runtime type casting. I'm looking for feedback and ideas, I was thinking to add branching and loop, but I would love to hear your thoughts. You can find it here: https://github.com/spicyPoke/TaskWeave

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Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
46%46% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
43%43% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released
42%42% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntUnlikely to reach the leaderboard · Strong signals: tasks · Missing: mac, agents, macos
40%40% 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
38%38% 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
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

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