GLAM Server

This is the Python backend for GLAM. You can find the frontend at GlamGeoVis/GlamGeoMap.

Requirements

Requires clusterer service to run (growing-glyphs#py4j).

Docker

• This repository contains a Dockerfile that can be used to create a Docker image. The provided nginx configuration file in config/nginx.conf.template provides three endpoints, running on port 8000:
  • Trove backend endpoint /trove
  • Risse backend endpoint /risse
  • All other requests will be forwarded to STATIC_FILES_URL, this is where the files for the frontend can be found (eg. /index.html will forward to {STATIC_FILES_URL}/index.html. This setting can be found in Dockerfile, and is by default configured to an Amazon S3 bucket where the current build of the GlamGeoVis/GlamGeoMap master branch is automatically deployed.

How to run

You can run either using Docker, or using a local python environment.

Docker

• Make sure STATIC_FILES_URL in Dockerfile is set to the frontend files' location (your local deployment of GlamGeoVis/GlamGeoMap or Amazon S3).
• Build the image docker build . -t glam_server.
• Run and bind to a local port eg. docker run -it --name glam_server -p 127.0.0.1:8888:8000 glam_server.
• Server is now running at http://localhost:8888.

Local python

• Use python3
• Make a virtual environment.
• Install dependencies pip install -r requirements.txt.
• Set environmental variable GLAM_DATA_FILE to the data filename eg. glammap-risse-dump-authors.csv (if not set, the script will try to open glammap-risse-dump-authors.csv by default).
• Run using python server.py.
• Note that unlike the Docker setup, this will only serve a single API backend (so either Trove or Risse) on port 8000.