Open Source Crystal Software Development Software for Linux

Amber makes building web applications fast, simple, and enjoyable. Get started with blazing-fast performance. Amber provides the bare metal performance of the Crystal Language. It provides productivity and happiness through a powerful CLI and familiar design patterns seen in Kemal, Rails, Phoenix and other popular frameworks. Use code generation and scaffolding features to rapidly build prototypes. Amber is licensed under the MIT license, which makes it perfect for use in commercial applications. Instead of having to plan where things go, Amber comes with a set of conventions to guide you in developing your application. Tools are built-in to prevent and mitigate common attacks against web applications. Minimize the risk of SQL injection, form tampering, cross-site request forgery, and several other attacks. Crystal is a type safe, compiled language inspired by the simplicity of Ruby.

Lucky is a web framework written in Crystal. It helps you work quickly, catch bugs at compile time, and deliver blazing-fast responses. Lucky is extremely fast and uses very little memory. You and your users will love the extra dose of speed. Authentication, asset management, CORS, database ORM, and more can all be included when creating a new Lucky project. Instead of finding bugs in QA or in production, Lucky is designed to catch as many bugs as possible at compile time. Lucky uses Action classes for handling HTTP requests and responses. The classes map the routes and parameters it handles to a response block. Lucky can generate these classes for you with ’lucky gen.action`. Using a class per action provides very solid automatic error detection, as well as the generation of routing, path, and link helpers and methods.

Amethyst is currently undergoing a re-write from the ground up. We'll be releasing the public roadmap soon. Amethyst is a web framework written in the Crystal language. The goals of Amethyst are to be extremely fast and to provide agility in application development, much like Rails.

Lightning fast, super simple web framework. Support all REST verbs. By default Kemal gzips most files, skipping only very small files, or those which don’t benefit from zipping. Websocket support. Request/Response context, easy parameter handling. Middleware support. Built-in JSON support. Built-in static file serving. Built-in view templating via ECR. Documentation. Before filters are evaluated before each request within the same context as the routes. They can modify the request and response. Since Crystal does not allow using variables in macro literals, you need to generate another helper macro to make the code easier to read and write. You can add many blocks to the same verb/path combination by calling it multiple times they will be called in the same order they were defined. Browser redirects are simple as well. Simply call env.redirect in the route’s corresponding block.

Code-style linter for Crystal. A single-celled animal that catches food and moves about by extending fingerlike projections of protoplasm. Ameba is a static code analysis tool for the Crystal language. It enforces a consistent Crystal code style, and also catches code smells and wrong code constructions. Ameba allows you to dig deeper into an issue, by showing you details about the issue and the reasoning behind it being reported. Starting from 0.31.0 Crystal supports parallelism. It allows running linting in parallel too. The default configuration file is .ameba.yml. It allows configuring rule properties, disabling specific rules and excludes sources from the rules.

This is a CLI tool to quickly create and manage Kubernetes clusters in Hetzner Cloud using the lightweight Kubernetes distribution k3s from Rancher. Hetzner Cloud is an awesome cloud provider which offers a truly great service with the best performance/cost ratio in the market. With Hetzner's Cloud Controller Manager and CSI driver you can provision load balancers and persistent volumes very easily. k3s is my favorite Kubernetes distribution now because it uses much less memory and CPU, leaving more resources to workloads. It is also super quick to deploy because it's a single binary. Using this tool, creating a highly available k3s cluster with 3 masters for the control plane and 3 worker nodes takes a few minutes only. The tool assigns the label cluster to each server it creates for static node pools (this doesn't apply to autoscaled node pools), with the cluster name you specify in the config file, as the value.

Crystalline is an implementation of the Language Server Protocol written in and for the Crystal Language. It aims to provide limited language features (like go-to, autocompletion, syntax and semantic checking) and ease development with any compatible code editor. Crystalline is not as extensive in terms of features as other Language Servers but still provides very convenient tools. Code Diagnostics. Syntax and semantic checks on save. Limited Autocompletion. List (depending on the target) method definitions, macros or module/class/struct names or symbols available in the current context. A whole document or a text selection. By clicking on a symbol with the Cmd or Ctrl key pressed (editor/platform dependent). Hovering should display (when possible) either a variable type, a function definition signature or the expanded macro.

irs is a command-line application that downloads audio and metadata in order to package an mp3 with both. Extensible, the user can download individual songs, entire albums, or playlists from Spotify. Note that the binaries right now have only been tested on WSL. They should run on most Linux distros, and OS X, but if they don't please make an issue. At it's core irs downloads individual songs. It does this by interfacing with the Spotify API, grabbing metadata, and then searching Youtube for a video containing the song's audio. It will download the video using youtube-dl, extract the audio using ffmpeg, and then pack the audio and metadata together into an MP3. From the core, it has been extended to download the index of albums and playlists through the Spotify API, and then iteratively use the method described for downloading each song.