Write Github Actions Workflows in Typescript Rather Than YAML

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Hey HN, I just released github-actions-workflow-ts, an NPM package that allows you to write GitHub Actions workflows in Typescript rather than YAML. The package then generates GH Actions workflow YAML files from your Typescript code. Why? - Type safety - Code re-usability: package and reuse common jobs and steps across different workflows. - Imperative edge: Utilize control flow to control the generation of different kinds of workflows easily. Essentially, I realized that as I write larger and more complicated GH Actions workflows in YAML, they become less readable and thus more prone to errors and harder to maintain/refactor. You can try it out on Replit (free but requires an account to fork my examples and run them yourself). Fork it and run the build command in the shell: - Simple Example: https://replit.com/@EmmanuelKyeyune/github-actions-workflow-... - Advanced Example: https://replit.com/@EmmanuelKyeyune/github-actions-workflow-... Read the accompanying blog post here: https://emmanuelnk.hashnode.dev/simplifying-github-actions-w... Please check it out. I'm open to any feedback as I march towards the first stable 1.0.0 release. Thanks

Visit product View on Hacker NewsAug 30, 2023

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

79%79% 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: code, open · Missing: mac, agents, macos

72%72% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: just released, io · Missing: https docs, excited, exist

33%33% 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 · Missing: mobile apps, ios, personal

32%32% 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

26%26% 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

21%21% 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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