Visualize bike data in munich
- Python3 + virtualenv
- npm
- bower
- PostgreSQL 9.2+
- Redis
- PostGIS
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/
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