Installation & Configuration

Quick Install: Running in Docker

You can run Lakesuperior in Docker for a hands-off quickstart.

Docker is a containerization platform that allows you to run services in lightweight virtual machine environments without having to worry about installing all of the prerequisites on your host machine.

  1. Install the correct Docker Community Edition for your operating system.
  2. Clone the Lakesuperior git repository: git clone --recurse-submodules https://github.com/scossu/lakesuperior.git
  3. cd into repo folder
  4. Run docker-compose up

Lakesuperior should now be available at http://localhost:8000/.

The provided Docker configuration includes persistent storage as a self-container Docker volume, meaning your data will persist between runs. If you want to clear the decks, simply run docker-compose down -v.

Manual Install (a bit less quick, a bit more power)

Note: These instructions have been tested on Linux. They may work on Darwin with little modification, and possibly on Windows with some modifications. Feedback is welcome.

Dependencies

  1. Python 3.6 or greater.
  2. A message broker supporting the STOMP protocol. For testing and evaluation purposes, CoilMQ is included with the dependencies and should be automatically installed.

Installation steps

Start in an empty project folder. If you are feeling lazy you can copy and paste the lines below in your console.

python3 -m venv venv
source venv/bin/activate
pip install lakesuperior
# Start the message broker. If you have another
# queue manager listening to port 61613 you can either configure a
# different port on the application configuration, or use the existing
# message queue.
coilmq&
# Bootstrap the repo
lsup-admin bootstrap # Confirm manually
# Run the thing
fcrepo

Test if it works:

curl http://localhost:8000/ldp/

Advanced Install

A “developer mode” install is detailed in the Development Setup section.

Configuration

The app should run for testing and evaluation purposes without any further configuration. All the application data are stored by default in the data directory of the Python package.

This setup is not recommended for anything more than a quick look at the application. If more complex interaction is needed, or upgrades to the package are foreseen, it is strongly advised to set up proper locations for configuration and data.

To change the default configuration you need to:

  1. Copy the etc.default folder to a separate location
  2. Set the configuration folder location in the environment: export FCREPO_CONFIG_DIR=<your config dir location> (you can add this line at the end of your virtualenv activate script)
  3. Configure the application
  4. Bootstrap the app or copy the original data folders to the new location if any loction options changed
  5. (Re)start the server: fcrepo

The configuration options are documented in the files.

One thing worth noting is that some locations can be specified as relative paths. These paths will be relative to the data_dir location specified in the application.yml file.

If data_dir is empty, as it is in the default configuration, it defaults to the data directory inside the Python package. This is the option that one may want to change before anything else.

Production deployment

If you like fried repositories for lunch, deploy before 11AM.