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Komodo documentation uses Vuepress.

Setup:

Prerequisites:

  • nodejs
  • yarn

Tip:

If you prefer using Docker, installation of nodejs and yarn is not required. See below for Docker instructions.

  • Fork the repository
  • Clone the repository
  • cd into the directory cd developer-docs/

Install packages & dependencies

yarn install

Start Editing

yarn docs:dev

HTML output is displayed at http://localhost:8080

Edit the markdown files in the directory docs and save the file.

If the changes are not reflected at http://localhost:8080 right away, refresh the page.

Exit the dev mode by using CTRL + C in the same terminal yarn docs:dev has been run.

Issuing the build command while the above dev command is active might cause the build to fail with errors.

Build

yarn docs:build

The html files are available in developer-docs/docs/.vuepress/dist/

Deploy

To deploy to gh-pages at https://<USERNAME>.github.io/developer-docs

./deploy.sh

The above script uses your git <USERNAME> from the global git configuration of your system.

Using Docker:

You can use Docker to reliably produce a developer environment that won't conflict with any of your existing projects.

Prerequisites: Install Docker and Docker Compose on your system

  • Clone the repository

  • cd into the directory cd developer-docs/

  • To start developing, simply issue docker-compose up in a terminal to launch the container

  • Then do docker exec -ti komodo_docs /bin/sh in another terminal to access a terminal inside the container. Now simply follow the instructions detailed in the above Start Editing and Build sections.

  • To exit from the terminal from the container use the exit command.

  • Use CTRL + C in the terminal docker-compose up has been done to stop the container.

  • To deploy using docker, use the command ./deploy_docker.sh. This script deploys to your own fork; the webpages are now located at the following address: https://<USERNAME>.github.io/developer-docs

  • When used for the first time, Docker might take some time to download the required data and build an image. Subsequent usage will be faster.

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