This repository implements a GitHub Action (`actions/setup-java`) that installs a Java JDK or JRE in CI environments. It supports 17+ distributions (Adoptium Temurin, Azul Zulu, Microsoft, Amazon Corretto, GraalVM, Liberica, etc.) and resolves versions from user input, version files (`.java-version`, `.tool-versions`, `.sdkmanrc`), or the `latest` alias. The action also sets up dependency caching for Maven, Gradle, and sbt, generates Maven settings.xml with server credentials and GPG signing profiles, and handles Maven toolchains.xml merging across workflow steps. It includes signature verification (GPG) for Temurin and Microsoft distributions and checksum verification for downloaded archives. The architecture is modular: a factory pattern lazily loads distribution-specific installer classes (each extending an abstract `JavaBase`), which handle version resolution, download, extraction, and tool-cache registration. A separate cache system (JDK binary cache, dependency cache, and resolution cache) uses GitHub Actions cache primitives with configurable retention. The codebase is written in TypeScript and heavily leverages the `@actions/*` toolkit. Tests mock all external dependencies and use static JSON fixtures to simulate vendor APIs. The action is deployed as compiled bundles in `dist/` and is actively maintained with comprehensive CI workflows for e2e testing across OS, architecture, and distribution variants. The core value of this repository is its reliability and breadth of support: it automates the brittle process of Java version management in CI, handles edge cases like early-access builds, floating version tags, and platform-specific package types (jdk+fx, jdk+jmods, etc.). The caching and retry logic reduce pipeline execution time and failure rates. While tightly integrated with GitHub Actions, several internal modules (retrying HTTP client, checksum verification, XML escaping) are isolated enough for potential extraction into other TypeScript projects.
Kapitan is a configuration-as-code CLI tool that renders infrastructure manifests (Kubernetes, Terraform, Docker, etc.) from a hierarchical YAML inventory and pluggable template engines (Jsonnet, Jinja2, Kadet, Helm, Kustomize, CUE). It manages secrets via references (GPG, cloud KMS, Vault, base64), fetches remote dependencies (Git, HTTP, OCI, Helm charts), and supports multiple inventory backends (Reclass, OmegaConf). The compilation pipeline is inventory-driven: targets define classes and parameters, which are deep-merged and interpolated, then passed to input-type compilers that produce deterministic output files. The architecture is modular—separate packages for inputs, inventory backends, secrets/references, and dependency management—all orchestrated by the `kapitan compile` CLI command. It is not a data research project; it is a production-grade infrastructure tool with a large test suite, CI/CD, and documented extension points.
dotdrop is a command-line tool for managing dotfiles across multiple hosts using profiles, Jinja2 templating, actions, and transformations. It stores dotfiles in a Git repository and deploys them to target systems, allowing different configurations per host or environment. The architecture is modular: separate Python modules handle each operation (install, compare, update, import, remove, uninstall), with a central dispatcher in `dotdrop.py`. Configuration is defined in YAML (or optionally TOML) files that specify dotfiles, profiles, variables, actions, and transformations. Key entry points are the CLI subcommands invoked via `dotdrop <command>`. Data flows involve parsing the config, aggregating imported configs and variables, then executing file operations (copy, symlink, diff) with optional template rendering and shell commands. External dependencies include Jinja2, docopt, PyYAML, and optional libraries for TOML support and system detection. The codebase is well-tested with both Python unit tests and a large suite of Bash integration tests, and it is distributed via PyPI, Homebrew, AUR, Snap, and other channels.