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Cequre

Cequre

Cequre Backends

| (0) | Free
Language support for .cequre files
Installation
Launch VS Code Quick Open (Ctrl+P), paste the following command, and press enter.
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Cequre Language Server & VS Code Extension

Welcome to the official VS Code extension for the Cequre DSL. This extension provides a rich development experience for building schema-first applications powered by the Cequre backend framework.

Features

  • Syntax Highlighting: Full syntactic colorization for .cequre files to make your schema and routing logic easy to read.
  • Smart Autocomplete: Intelligent suggestions for:
    • Global blocks (e.g., collection, config, global)
    • Property keys within configuration scopes (e.g., core, security, auth)
    • Field types and definitions (e.g., string, relationship, date, object)
    • Decorators and directives (e.g., @unique, @default(), @encrypt)
    • Access control rules (read, create, update, delete, etc.)
  • Real-time Diagnostics: Immediate semantic feedback and error highlighting while you type. Invalid types or schema conflicts are caught in the editor before you compile.
  • Auto-formatting: Format your .cequre documents seamlessly using VS Code's built-in format on save or format document commands.

Installation

  1. Install this extension from the Visual Studio Code Marketplace.
  2. Open any .cequre file within your project workspace. The Cequre Language Server will initialize automatically and attach to the file.

Usage

Simply write your backend architecture in .cequre syntax!

config {
  core {
    api {
      prefix: "/api";
    }
  }
}

collection users {
  fields {
    email: text @unique;
    password: password;
    role: select @default("user");
  }
  access {
    read: true;
    create: true;
  }
}

Contributing

If you'd like to contribute, report bugs, or request features, please visit our GitHub repository: Cequre Open Source.

Note: This extension bundles its own local Language Server Protocol (LSP) implementation tied to the @cequrebackends/cequre-cli compiler for accurate semantic feedback.

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