Every Stop

This is a Twitter bot which tweets a Google Street View image of every single bus stop for Hong Kong. But it could tweet any Open Street Map node that you provide it.

Data

You'll need to know where the bus stops are in order to populate the database. Examples include Open Street Map or GTFS data feeds.

Open Street Map

For areas where Open Street Map has good coverage, Overpass Turbo will let you extract data as geojson.

For Hong Kong the query looks like:

[out:json][timeout:25];
// gather results
(
  // query part for: “highway=bus_stop and "ref:hkbus"=*”
  node["highway"="bus_stop"]["ref:hkbus"]({{bbox}});
  way["highway"="bus_stop"]["ref:hkbus"]({{bbox}});
  relation["highway"="bus_stop"]["ref:hkbus"]({{bbox}});
);
// print results
out body;
>;
out skel qt;

More generically, a search for bus stops within an area defined by a relation ID might look like:

[out:json][timeout:250];

rel(1842114);
map_to_area -> .a;
(
node(area.a)[highway=bus_stop];
  way(area.a)[highway=bus_stop];
  relation(area.a)[highway=bus_stop];
);

out body;
>;
out skel qt;

Place the resulting export.json file in this directory.

If you are bringing a geojson file from elsewhere then know that we expect each geojson element to include a name, id, latitude and longitude.

Run import_geojson.py to create an sqlite database containing this data. You can now delete the export.json file.

GTFS

Transitland aggregates thousands of GTFS feeds across the world. Individual transit operators are liable for the quality of this data. Whilst all the data listed is ostensibly open data, there's no clear licensing for some feeds.

If you know the name of the operator then you can search by that, otherwise you can browse the world map.

Once you have found a GTFS zip file, extract stops.txt into this directory and then run python import_gtfs.py to load the data into the sqlite database stops.db.

Environment Variables

The application reads credential data from environment variables. You can export these however you like, but the simplest option when testing locally is to copy env_template to .env in this directory and then edit it.

Visit the Google Street View Image API page and click get a key. Make sure that your account and key has street view enabled. Once you have the key, place it in the .env file.

Usage

Both Twitter and Mastodon versions update the stops.db file, so you can only run one. You should use a cross-posting service if you want the same posts to appear in both, and it is easier to do this in the Mastodon to Twitter direction.

Basic validation

python3 everystop.py will perform any database migrations required and fetch a random bus stop, saving the image to sv.jpg and printing out the details of the stop

This will hit the Google API, so will cost money if you have the credentials configured correctly. But it will not update the database to set the stop as being visited.

Twitter

Visit the Twitter Developers page and create an app. Fill in the credentials in the .env file.

python3 twitter_poster.py

Mastodon

You'll need to first edit mastodon_register.py to specify your instance base url along with your email and password.

Then you can run python mastodon_register.py to create some secret files, and then python mastodon_poster.py to actually post.

Dependencies

• Python 3.6+
• pip3 install -r requirements.txt for everything else

Thanks

• Heavily inspired by Everylot Bot but written from scratch for modern Python