Version updated for https://github.com/emilymclean/pkl-java-action to version v2.2.8. This action is used across all versions by ? repositories. Go to the GitHub Marketplace to find the latest changes. Action Summary The pkl-java-action GitHub Action automates the generation of Java source code from Pkl model files. It simplifies the process of converting Pkl files into Java bindings, eliminating manual coding and ensuring consistency. This action is particularly useful for workflows that require automated handling of Pkl models in Java-based projects.

Version updated for https://github.com/emilymclean/pkl-kotlin-action to version v2.0.11. This action is used across all versions by ? repositories. Go to the GitHub Marketplace to find the latest changes. Action Summary The pkl-kotlin-action GitHub Action automates the generation of Kotlin source code from Pkl model files. It streamlines the process of converting Pkl files into Kotlin bindings, solving the need for manual code generation and ensuring consistent and efficient output. This action is particularly useful for developers working with Pkl models in Kotlin projects.

Version updated for https://github.com/emilymclean/pkl-swift-action to version v2.0.12. This action is used across all versions by ? repositories. Go to the GitHub Marketplace to find the latest changes. Action Summary The pkl-swift-action GitHub Action automates the generation of Swift source code from Pkl model files. It simplifies the process of converting Pkl data into reusable Swift bindings, saving time and reducing manual coding efforts. Key capabilities include processing multiple Pkl files and specifying output locations for the generated code.

Version updated for https://github.com/emilymclean/pkldoc-action to version v2.0.10. This action is used across all versions by ? repositories. Go to the GitHub Marketplace to find the latest changes. Action Summary The pkldoc-action GitHub Action automates the generation of PklDoc documentation for Pkl modules by processing specified .pkl files and outputting the results to a designated folder. It simplifies the creation of structured documentation for serialized Python objects, saving developers time and ensuring consistency in documentation workflows.