Tags: yaml*

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  1. yq is a command-line tool that processes YAML, XML, and TOML files by converting them to JSON and using jq for further processing. It supports various options for preserving YAML tags and styles, and can be used as a module for in-place edits.

    2025-03-05 Tags: , , , , , , , by klotz
  2. The article discusses the use of jq, xq, and yq tools for processing JSON, XML, and YAML data from the command line. It includes examples of how to use these tools to extract and manipulate data, as well as converting GPX files to CSV format.

    2025-03-04 Tags: , , , , , , , by klotz
  3. The article presents ten lesser-known but highly useful GitHub Actions that can enhance workflow automation, focusing on tasks like YAML validation, markdown link checking, auto-assignment of PRs, commit message linting, dependency caching, Slack notifications, license compliance checking, PR size labeling, security scanning, and Jira integration.

  4. ninja-bear is a tool that keeps language-specific configs in sync across distributed systems using a language-neutral YAML configuration.

    2024-10-31 Tags: , , , by klotz
  5. Google Gemini simplifies creating advanced home automations with its script editor and YAML language, making it user-friendly for non-technical users. Learn how to use Gemini for smart home automation.

  6. Conor Barber explores the evolution of infrastructure from YAML configurations to pipelines-as-code, focusing on modern CI/CD systems like GitHub Actions, GitLab, and CircleCI. The presentation was given at QCon San Francisco 2023, discussing how moving away from YAML can improve scalability, cost efficiency, and developer experience.

  7. it complies to lisp

    2024-03-11 Tags: , , , by klotz
  8. 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.

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