Introduction to Pkl, a programming language designed for generating configuration files.
Addresses limitations of static languages and general-purpose languages for configuration purposes.
Provides safety by catching validation errors before deployment.
Scales from simple to complex use-cases.
Enhanced with capabilities borrowed from general-purpose languages.
Familiar syntax and easy learning curve.
Built-in validation using type annotations.
Ability to publish packages and import them as dependencies in a project.
Language bindings for Swift, Go, Java, and Kotlin.
Editor support for IntelliJ, VS Code, and Neovim.
Addresses limitations of static languages and general-purpose languages for configuration purposes.
Provides safety by catching validation errors before deployment.
Scales from simple to complex use-cases.
Enhanced with capabilities borrowed from general-purpose languages.
Familiar syntax and easy learning curve.
Built-in validation using type annotations.
Ability to publish packages and import them as dependencies in a project.
Language bindings for Swift, Go, Java, and Kotlin.
Editor support for IntelliJ, VS Code, and Neovim.
Creating a JSON Schema for existing YAML values
We can infer a schema from existing YAML values and use it as a starting point when writing a new schema. The steps are:
Convert your values YAML file to JSON on https://www.json2yaml.com/
Paste the JSON on https://www.jsonschema.net/ and click on "Infer Schema"
Paste the schema into the values.schema.json file
W
We can infer a schema from existing YAML values and use it as a starting point when writing a new schema. The steps are:
Convert your values YAML file to JSON on https://www.json2yaml.com/
Paste the JSON on https://www.jsonschema.net/ and click on "Infer Schema"
Paste the schema into the values.schema.json file
W
