gtfspy
is a Python package for analyzing public transport timetable data provided in the General Transit Feed Specification, GTFS, -format.
pip install gtfspy
Windows should work, but has not been tested or and may not be supported as much. Please report problems.
Windows users may need to install Shapely library first. Download Shapely wheel and then run:
pip install wheel
pip install {path to the Shapely wheel file on your PC}
If you come across the Microsoft Visual C++ 14.0 is required
error, you may need to download the latest Microsoft Visual C++ Build Tools.
You can download it from here.
After that, continue with:
pip install gtfspy
Use this if you want to be able to edit gtfspy
's source code.
git clone git@github.com:CxAalto/gtfspy.git
cd gtfspy/
pip install -r requirements.txt # install any requirements
nosetests . # run tests
Remember to also add the gtfspy
directory to your PYTHONPATH
environment variable.
We welcome contributions as GitHub pull requests. In your pull request, please also add yourself as a contributor in the list below.
This library is not yet stabilised, and new features are being developed. Thus code organization and interfaces may change at a fast pace. More precise versioning scheme will be decided upon later.
View the changelog.
Manuel Rios (marz7002)
Nils Haglund
Michaela Ockova (evelyn9191)
You?
This source code of this project licensed under the MIT License - see the LICENSE.txt file for details.
The OpenStreetMap data (.osm.pbf file(s) under examples/data) is licenced under the Open Data Commons Open Database License (ODbL) by the OpenStreetMap Foundation (OSMF).
The GTFS data used for the examples is provided by the City of Kuopio (Finland), and have been downloaded from http://bussit.kuopio.fi/gtfs/gtfs.zip [data licensed under CC-BY 4.0].
If you use this Python package for scientific purposes, please cite our paper
Rainer Kujala, Christoffer Weckström, Miloš N. Mladenović, Jari Saramäki, Travel times and transfers in public transport: Comprehensive accessibility analysis based on Pareto-optimal journeys, In Computers, Environment and Urban Systems, Volume 67, 2018, Pages 41-54, ISSN 0198-9715, https://doi.org/10.1016/j.compenvurbsys.2017.08.012.
If you have any problems using gtfspy
please create an issue in GitHub.
If you have any questions regarding gtfspy
, feel free to send the package maintainers (see above) an e-mail!