Crowdsource Platform - Crowdresearch HCI Stanford

This is a Django 1.8 app using a Postgres database that can be deployed to Heroku.

Setup

If you are on Windows or encounter issues with these instructions, please try the instructions in the Setup with Vagrant section.

Install Postgres and create a new database:

bash> psql
psql> CREATE DATABASE crowdsource_dev ENCODING 'UTF8';

Create a local_settings.py file in the project root folder and configure it to connect to the Postgres database:

DATABASES = {
    "default": {
        "ENGINE": "django.db.backends.postgresql_psycopg2",
        "NAME": "crowdsource_dev"
    }
}

Source the virtual environment, install dependencies, and migrate the database:

bash> source venv/bin/activate
bash> pip install -r requirements.txt
bash> python manage.py makemigrations oauth2_provider
bash> python manage.py migrate
bash> python manage.py makemigrations
bash> python manage.py migrate

#users who do not have migrations please run the following commands
bash> python manage.py makemigrations crowdsourcing
bash> python manage.py migrate --fake-initial

bash>brew install node  #use other ways if you don't have brew
bash>npm install -g bower
bash>bower install
bash>cd staticfiles

If you encounter an error angular-route.js 404, do this:

bash> bower cache clean
bash> rm -fr staticfiles/bower_components
bash> bower install

If there are no errors, you are ready to run the app from your local server:

bash> python manage.py runserver

Where can I get data:

1. Current file: following data supports tasksearch, task,ranking

   bash> python manage.py loaddata fixtures/neilTaskRankingData.json

OPTIONAL 2) Ranking Dataset (>800 records already included in #1)

bash> python manage.py loaddata fixtures/neilCrowdsourcingRankingData.json

3. Optional to dump data from environment to the file bash> python manage.py dumpdata crowdsourcing > fixtures/neilCrowdsourcingRankingData.json

4. How to generate data dynamically with autofixture

   bash> python manage.py loadtestdata AppName.Model:NUMBER OF RECORDS
   Example: bash> python manage.py loadtestdata crowdsourcing.UserCountry:15

User Interface:

Setup with Vagrant

This approach might be useful if you're on Windows or have trouble setting up postgres, python, nodejs, git, etc. It will run the server in a virtual machine.

First install Virtualbox Vagrant and Git

Clone this repo to get the code:

git clone https://github.com/crowdresearch/crowdsource-platform.git
cd crowdsource-platform

Then run the command:

vagrant up

This will set up an Ubuntu VM, install prerequisites, create databases, and start the machine. Then run:

vagrant ssh

This will now give you a shell in your virtual machine. It will automatically cd to /home/vagrant/crowdsource-platform where the code is (this is a shared folder with the host machine)

Now you can run the server:

python manage.py runserver [::]:8000

And you can visit the website by going to http://localhost:8000 in your web browser.

On subsequent runs, you only need to run:

vagrant up
vagrant ssh
python manage.py runserver [::]:8000