Atlas of lighting is an interactive mapping tool in which the user can combine, isolate or cross-reference both quantitative and qualitative datasets. Atlas of Lighting is a joint project between Philips, MIT Center for Advanced Urbanism and MIT Civic Data Design Lab.

This application is written using a distributed microservices architecture and a CI/CD development setup using docker containers, and it needs to run four services including a web application with nodejs, a postgres databse, a nginx web server, and a service for database migration works called data_services. These will be managed by docker-compose, and are deployed on docker cloud.

###Why the setup? Microservices architecture highly increases the scalability of the application, meaning not only additional services (for example to handle the authentications, etc.) but also makes the application reusable (for example the database could be used as part of other projects).

#####Environment Setup for Mac

This application uses Docker and containers technology. If you don't already have Docker installed, you can do so using one of the following:

• Docker for Mac
• Docker Toolbox

Further instructions on how to test if Docker is correctly installed and troubleshooting instructions are available on Docker's website.

#####Environment Setup for Windows

This application uses Docker and containers technology. If you don't already have Docker installed, you can do so using one of the following:

• Docker for Windows (for Windows 10)
• Docker Toolbox (for Windows 8.1 or earlier)

Further instructions on how to test if Docker is correctly installed and troubleshooting instructions are available on Docker's website.

After cloning from github and in terminal cd in the directory and run docker-compose up -d --build to build and run the application. Make sure they are up and running with docker-compose ps.

If you using docker for windows you should be able to see the app using just localhost for the address, if not and you are using older versions of docker such as docker-toolbox, you need to get the ip using: docker-machine ip default. You will still need to do database migration and populate it with data from the csv files. For that I made a service called data_services which is a flask app with custom migration methods. Run the following commands in terminal (note that atlaslighting_dataservices_1 is the name of the service the docker-compose ps command returns and might be different in your machine if you changed the folder name):

docker exec -it atlaslighting_dataservices_1 rm -rf migrations
docker exec -it atlaslighting_dataservices_1 python manage.py create_db
docker exec -it atlaslighting_dataservices_1 python manage.py db init
docker exec -it atlaslighting_dataservices_1 python manage.py db migrate
docker exec -it atlaslighting_dataservices_1 python manage.py db upgrade
docker exec -it atlaslighting_dataservices_1 python manage.py populate

please note that the stand alone setup of the app won't have the web server, and database components

This app is written for a *NIX environment only, all commands are run in terminal. You need Nodejs and npm for package management.
In Mac, you can install npm using Homebrew– Install Homebrew if you don't have it from their webpage.
After brew installed, in your terminal:

brew install npm

For development, we will need to have a distributed version control system set up. See this short intro for general information on git.

First, fork this repository to your Github account. You can do this by clicking on Fork on the project's Github page at https://github.com/civic-data-design-lab/atlas-lighting.git.

After Forking to your account, Clone the repository to your local machine by:

git clone <your-github-repository>

Point into the project folder in terminal:

cd atlas-lighting

Install the project dependencies with npm.

npm install

Install bower for front-end packages.

npm install -g bower

Then

bower install

After installing all dependencies using npm, and bower, the local application environment should all set up to serve the application on your local host. Run the node server with:

npm start

Check out the application live on localhost:8080 in your browser.