rst-language-server 0.2.0

Features

Autocompletion of title adornments

Installation

RST Language Server is available as a package on PyPI and can be installed via pip:

$ pip install --user rst-language-server

Usage with Kate

Using RST Language Server with Kate requires the LSP Client Plugin. Once the plugin is activated in the settings a new settings symbol named LSP-Client appears. Click on the section, select the User Server Settings tab and paste the following server configuration.

{
    "servers": {
        "rst": {
            "command": ["rst-ls", "--client-insert-text-interpretation=false"],
            "highlightingModeRegex": "^reStructuredText$"
        }
    }
}

This will start RST Language Server when opening any file that is configured to use the reStructuredText syntax highlighting.

Usage with Neovim

There are numerous ways to use Language Servers in with Neovim. This setup configuration assumes that you use nvim-lspconfig.

To registers RST Language Server with nvim-lspconfig, add the following lua code before requiring lspconfig and calling the corresponding setup function of the language server:

-- Register rst-ls with lspconfig
local configs = require "lspconfig/configs"
local util = require "lspconfig/util"

configs.rst_language_server = {
  default_config = {
    cmd = { "rst-ls" },
    filetypes = { "rst" },
    root_dir = util.path.dirname,
  },
  docs = {
    description = [[
https://github.com/digitalernachschub/rst-language-server
Server implementation of the Language Server Protocol for reStructuredText.
]],
    default_config = {
      root_dir = [[root_pattern(".git")]],
    },
  },
}

Note that this setup currently requires Neovim Nightly (0.6).

Is my editor supported?

RST Language Server can be used with any text editor that implements a Language Client. See this list of Language Client implementations.

Development configuration with Kate

The RST Language Server is executed as a subprocess of the Language Client. Therefore, if we want to see log output in Kate we need to write the logs to a file using the –log-file command line option. We also set the log level to debug in order to view the JSON-RPC messages exchanged between client and server. Lastly, we configure the root (i.e. the working directory of the executed command) to the directory where our source code lives in and use poetry run to execute the code in the Git repository:

{
    "servers": {
        "rst": {
            "command": ["poetry", "run", "rst-ls", "--log-file=/tmp/rst-ls.log", "--log-level=debug", "--client-insert-text-interpretation=false"],
            "root": "/path/to/rst-language-server-repo",
            "highlightingModeRegex": "^reStructuredText$"
        }
    }
}