Index Builder

This is a nice little interactive survey using completely randomized data in which users can:

• create unique usernames
• select factors by giving them a weight, pro/anti direction & supporting reasons
• lock-in selections in order to see what kind of index your combination of factors have built
• compare performance of your index against some default indexes as well as other users
• an admin user can:
  • view interesting breakdowns of all factor selections made by users as well as make these breakdowns available for users to see
  • archive off user selections for further future analysis and to reset the app for another round of users

Demo

Live demo (choose any username you'd like): index-builder

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system. Once you've checked out this project you must make sure you have the following installed:

Include instructions on setting up virtualenv

To get up and running perform the following: pip install -r requirements.txt

In order to install scipy I had to run the following: sudo apt-get install gfortran libopenblas-dev liblapack-dev python-dev pip install scipy==0.15.1 easy_install numpy==1.9.2 easy_install pandas==0.16.2

You'll need node, npm & yarn installed yarn install npm run build

Prerequisites

• pip
• easy_install
• virtualenv
• node
• npm
• yarn

Installing

Setting up your virtual environment

1) mkdir -p ~/pyenvs
2) virtualenv ~/pyenvs/index_builder
3) source ~/pyenvs/index_build/bin/activate
4) pip install -r requirements.txt
5) sudo apt-get install gfortran libopenblas-dev liblapack-dev python-dev (assuming you're running linux)
6) pip install scipy==0.15.1
7) easy_install numpy==1.9.2
8) easy_install pandas==0.16.2

Building the javascript

1) yarn install
2) npm run build

Running the Flask back-end

python index_builder/server.py --HOST 0.0.0.0 --PORT 8080 --AUTH true

Running the Flask back-end with gunicorn

gunicorn server:app --config gunicorn_config.py --bind 0.0.0.0:8080 -w 8 -t 120 --limit-request-line 8190 --log-file=- --access-logfile ~/stdout --error-logfile ~/stderr  --log-level=info

Building the javascript files in "watch" mode (this is good for development so it will hot swap changes)

npm run watch

Running the tests

Python tests

python setup.py test

All JS tests

npm run test

Specific JS tests

TEST=static/__tests__/factor_viewer/*-test.jsx npm run test-file

JS coverage report

npm run test-with-coverage

JS Duplication report

npm run report-duplicate-code

JS formatting

npm run format

JS linting

npm run lint -s

Deployment

You can run this application on a larger scale using gunicorn

export AUTH=true (if you want authentication turned on)
gunicorn server:app --config gunicorn_config.py --bind 0.0.0.0:8080 -w 8 -t 120 --limit-request-line 8190 --log-file=- --access-logfile ~/stdout --error-logfile ~/stderr  --log-level=info

TBA: notes on docker deployment

Built With

• Flask - The back-end web framework used
• jinja - Core HTML templating
• yarn - JS Dependency Management
• Webpack - JS Bundler
• React - Core JS library our components are built on

Authors

• Andrew Schonfeld - Initial work - plutoplate

See also the list of contributors who participated in this project.

License

This project is licensed under the MIT License - see the LICENSE.md file for details

Acknowledgments

• Wilfred Hughes was truly an inspiration and a driving force behind many of the solutions to initial infrastructure headaches