Bikewatch

Visualize bike data in munich

Dependencies

Python3 + virtualenv
npm
bower
PostgreSQL 9.2+
Redis
PostGIS

Setup

git clone https://github.com/codeformunich/bikewatch
cd bikewatch
virtualenv -p python3 .
pip install -r requirements.txt
python manage.py bower install

Now you have to configure the database connection and connection for Redis. Edit this in mvgrad/settings.py:

DATABASES = {
    'default': {
        'ENGINE': 'django.contrib.gis.db.backends.postgis',
        'NAME': 'dbname',
        'USER': 'dbuser',
        'PASSWORD': 'dbpassword',
        'HOST': 'localhost',
    }
}

CELERY_BROKER_URL = 'redis://:redispw@localhost:6379/0'

Then you should crate the database and activate the PostGIS extension:

python manage.py migrate

psql <db name>
CREATE EXTENSION postgis;

Now you have to start the Celery worker (this is a asynchronous task worker):

celery -A mvgrad worker -c 2 --loglevel=info

Before using the software, we have to create the cache:

python manage.py generate_available_dates_cache

Finally you can start the development server:

python manage.py runserver

Maybe these install instructions for PostGIS are helpful: https://docs.djangoproject.com/en/1.10/ref/contrib/gis/install/

Working with the data

We use the data from https://data.robbi5.com/nextbike-mvgrad/.

To import the XML files use this command:

python manage.py import *.xml

To calculate the data for the "Routes of Bikes" for one day, run this:

python manage.py generate_path <year> <month> <day>

After every change in the dataset (after one of the commands above):

python manage.py generate_available_dates_cache