gtfsblocks
is a Python package that pieces together GTFS feed data to assemble individual vehicle blocks and compile relevant data from various tables. The code was originally developed to analyze transit bus electrification, but the functionality can be helpful to other applications as well. The package was predominantly built off of the GTFS processing code from ebusopt
.
Some core functions include:
- Reading static GTFS tables into Pandas
DataFrame
objects and performing a bit of basic validation that necessary columns are populated while dropping what isn't needed. - Parsing the
calendar.txt
andcalendar_dates.txt
files to identify the activeservice_id
values on each day of service. - Merging together trip-level data from different GTFS tables for easy manipulation and analysis. For example:
- Adding trip start and end times from
stop_times.txt
- Adding trip start and end locations from
shapes.txt
- Esimating deadhead distances between consecutive trips based on these coordinates
- Adding trip distances calculated from the lat/lon coordinates in
shapes.txt
- Adding trip start and end times from
See this gist for an overview of core functionality as well as the example usage below. Documentation is a work in progress.
gtfsblocks
is installable via pip
:
pip install gtfsblocks
It's easy to read in a GTFS feed with gtfsblocks
. Just supply the path to the directory where unzipped GTFS files are housed:
from gtfsblocks import Feed
gtfs = Feed.from_dir('/path/to/your/data')
This will load all relevant files into memory as Pandas DataFrames. Future releases may take advantage of partridge
for better memory management.
From here, you can access predictably named tables like gtfs.trips_df
or gtfs.stop_times_df
, or call various methods on Feed
to perform some transformations and aggregations for you.
# Get a Pandas Series of the number of trips per day in the scope of these files
trips_per_day = gtfs.get_n_trips_per_day()
# Filter down trips.txt to just those happening on a particular day
test_date = '2/25/25'
day_trips = gtfs.get_trips_from_date(test_date)
from gtfsblocks import filter_blocks_by_route
routes = ['D Line', 'E Line']
route_trips = filter_blocks_by_route(
trips=day_trips,
routes=routes,
route_method=route_method,
route_column='route_short_name'
)
# Add all trip data columns (e.g. locations and distances)
route_trips = gtfs.add_trip_data(route_trips, test_date)
from gtfsblocks import add_deadhead
trips_with_dh = add_deadhead(route_trips)
from gtfsblocks import plot_trips_and_terminals
fig = plot_trips_and_terminals(
trips_df=route_trips,
shapes_df=gtfs.shapes_df
)