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Example Project - GTFS Explorer

This project lets you explore GTFS data in a web interface. It should demonstrate how to use django-multi-gtfs in your own projects.

Requirements

The Dockerize project requires Docker and docker-compose.

Running the project locally requires a spatially-enabled database server. This project uses spatiallite by default. You'll need to install the spatialite tools on your system.

If you want to use an alternate database (e.g. PostGIS), you'll need to install its requirements, and adjust the configuration.

Configuration

This project uses python-decouple and dj-database-url to load settings from the environment, an .ini file, or a .env file. For example, to use PostGIS database multigtfs on host postgis.example.com with username user and password password, you could create this .env file in the explore folder:

DATABASE_URL=postgis://user:[email protected]/multigtfs

See exploreproj/settings.py for other parameters that can be overriden.

Running with Docker

  1. Add one or more feeds to import to the folder feeds/import. If you need a feed, pick one from https://transitfeeds.com.
  2. Initialize the containers with docker-compose up. This runs several steps:
    • Initializes a PostgreSQL database server with PostGIS extensions
    • Creates a database explore
    • Adds PostGIS extensions to explore
    • Runs initial Django migrations to setup the database tables
    • Creates a superuser admin with password password
    • Loads any feeds found in feeds/input
    • Runs the web server
  3. When the message Development server is running at http://0.0.0.0:8000/ is displayed, you can view the site at http://localhost:8000 .

To stop Docker, use Ctrl-C. You can also run in the background with docker-compose up -d.

Feeds are only imported the first time you start the project. To load additional feeds:

  1. Place the feed in feeds/import.
  2. Run docker-compose up -d to run the containers in the background
  3. Run docker-compose exec web bash to start a bash shell
  4. Run ./manage.py importgtfs /feeds/import/name_of_feed.zip

Local Installation

If you have a spatial database available, you can run the project locally.

$ cd /path/to/explore
$ mkvirtualenv explore             # Create a virtual environment
$ pip install -r requirements.txt  # Install Django, etc.
$ ./manage.py syncdb               # Create db.sqlite3, superuser
$ ./manage.py migrate              # Add multigtfs tables
$ ./manage.py runserver            # Run on http://localhost:8000

Detailed installation instructions

The following steps have been used to install the example project onto a clean Ubuntu (virtual) machine. The only prerequisite is that Python 2.7 is installed.

Step 1 - Install operating system dependencies

sudo apt-get install -y git python-pip python-virtualenv spatialite-bin gdal-bin

Step 2 - Download copy of multigtfs from git into project folder (assume home directory)

cd ~/
git clone https://github.com/tulsawebdevs/django-multi-gtfs.git

Step 3 - Navigate to example project folder and create python virtual environment (myenv) for example project (use command "deactivate" to deactivate virtualenv).

# Navigate to example project folder
cd django-multi-gtfs/examples/explore

# Create and activate new virtual environment (myenv). 
# Use "deactivate" to deactivate virtualenv.
virtualenv --always-copy myenv
source myenv/bin/activate

Step 4 - Install example project dependencies (django etc)

pip install -r requirements.txt

Step 5 - Setup multigtfs application/database etc.

# Create db.sqlite3, superuser. Enter "yes" to create superuser and 
# then enter username and password when prompted (you can leave email address blank)
./manage.py syncdb

# Create multigtfs tables in database
./manage.py migrate

Step 6 - Example project now installed, run development server to test. Note I have used 0.0.0.0:8000 so can can access from any computer on network (not use host). This is necessary if running in a virtual machine (along with appropriate network settiings/port forwarding, for example in my virtual machine Vagrantfile I use config.vm.network "public_network" to allow access from other machines)

./manage.py runserver 0.0.0.0:8000

Done. The multigtfs server should now be running. Open your favourite web browser and enter the following to access the application (use appropriate IP address if browser not on same machine, you can use ifconfig in Ubuntu to get IP address).

http://localhost:8000

At this stage there are no GTFS feeds defined so lets add one. Return to the command line and enter Control-C to stop the server. The following steps download the latest Wellington Metlink GTFS feed from http://www.gtfs-data-exchange.com/.

# Download a GTFS feed
wget -O wellington-metlink-latest.zip http://www.gtfs-data-exchange.com/agency/metlink/latest.zip

# Import into GTFS
./manage.py importgtfs --name "Wellington Metlink latest" wellington-metlink-latest.zip

# Delete download
rm wellington-metlink-latest.zip

Note that the importgtfs process will take some time (above feed took about 10 minutes). When complete start the multigtfs server again and the new feed should now be available.