Skip to main content

PyRaptor

Python implementation of RAPTOR and McRAPTOR using GTFS data. Tested on Dutch GTFS data.

This repository contains four applications:

  1. pyraptor/gtfs/timetable.py - Extract the timetable information for one operator from a GTFS dataset and write it to an optimized format for querying with RAPTOR.
  2. pyraptor/query_raptor.py - Get the best journey for a given origin, destination and desired departure time using RAPTOR
  3. pyraptor/query_range_raptor.py - Get a list of the best journeys to all destinations for a given origin and desired departure time window using RAPTOR
  4. pyraptor/query_mcraptor.py - Get a list of the Pareto-optimal journeys to all destinations for a given origin and a departure time using McRAPTOR
  5. pyraptor/query_range_mcraptor.py - Get a list of Pareto-optimal journeys to all destinations for a given origin and a departure time window using McRAPTOR

Installation

Install from PyPi using pip install pyraptor or clone this repository and install from source using pip.

Example usage

1. Create timetable from GTFS

python pyraptor/gtfs/timetable.py -d "20211201" -a NS --icd

2. Run (range) queries on timetable

Quering on the timetable to get the best journeys can be done using several implementations.

RAPTOR query

RAPTOR returns a single journey with the earliest arrival time given the query time.

Examples

python pyraptor/query_raptor.py -or "Arnhem Zuid" -d "Oosterbeek" -t "08:30:00"

python pyraptor/query_raptor.py -or "Breda" -d "Amsterdam Centraal" -t "08:30:00"

rRAPTOR query

rRAPTOR returns a set of best journeys with a given query time range. Journeys that are dominated by other journeys in the time range are removed.

Examples

python pyraptor/query_range_raptor.py -or "Arnhem Zuid" -d "Oosterbeek" -st "08:00:00" -et "08:30:00"

python pyraptor/query_range_raptor.py -or "Breda" -d "Amsterdam Centraal" -st "08:00:00" -et "08:30:00"

McRaptor query

McRaptor returns a set of Pareto-optimal journeys given multiple criterions, i.e. earliest arrival time, fare and number of trips.

Examples

python pyraptor/query_mcraptor.py -or "Breda" -d "Amsterdam Centraal" -t "08:30:00"

python pyraptor/query_mcraptor.py -or "Vlissingen" -d "Akkrum" -t "08:30:00"

python pyraptor/query_mcraptor.py -or "Obdam" -d "Akkrum" -t "08:30:00" -r 7

rMcRaptor query

Range version of McRaptor, i.e. it returns a set of Pareto-optimal journeys within a departure time window.

Examples

python pyraptor/query_range_mcraptor.py -or "Breda" -d "Amsterdam Centraal" -st "08:15:00" -et "08:30:00"

python pyraptor/query_range_mcraptor.py -or "Vlissingen" -d "Akkrum" -st "08:15:00" -et "08:30:00"

python pyraptor/query_range_mcraptor.py -or "Obdam" -d "Akkrum" -st "08:00:00" -et "09:00:00"

Notes

  • The current version doesn't implement target pruning as we are interested in efficiently querying all targets/destinations after running RAPTOR algorithm.

References

Round-Based Public Transit Routing, Microsoft.com, Daniel Delling et al

Raptor, another journey planning algorithm, Linus Norton

Dutch GTFS feed, Transit Feeds

Metadata

Release files for pyraptor 1.3.10

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for pyraptor 1.3.10
File Size Uploaded
pyraptor-1.3.10.tar.gz 20.2 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for pyraptor 1.3.10
File Interpreter ABI Platform
pyraptor-1.3.10-py3-none-any.whl Python 3 none any Details

Total release size: 47.2 kB

Release files / pyraptor-1.3.10.tar.gz

Download URL pyraptor-1.3.10.tar.gz
Size 20.2 kB
Tags Source
SHA-256 checksum
How to use checksums
7c4602e0cdbea3e8c5f34f8b1c3715a06bc296c44719b33e2e1fc3783596e2ea
BLAKE2b-256 checksum
How to use checksums
6881b0c1ba4019c992a7e703c127139e6bd6832e814dcfcc9deb0506c09b9269
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.8.0 pkginfo/1.8.3 readme-renderer/35.0 requests/2.28.1 requests-toolbelt/0.9.1 urllib3/1.26.10 tqdm/4.64.0 importlib-metadata/4.12.0 keyring/23.7.0 rfc3986/2.0.0 colorama/0.4.5 CPython/3.8.13

Release files / pyraptor-1.3.10-py3-none-any.whl

Download URL pyraptor-1.3.10-py3-none-any.whl
Size 26.9 kB
Tags Python 3
SHA-256 checksum
How to use checksums
b4acf62a921b8d3a0bec45ab20d366a85296192fbde0789a814143b6ab5d1da1
BLAKE2b-256 checksum
How to use checksums
26c57d7a52d38092c2115484a87ac7c73134751b6c28633c55ab9e3c85a43170
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.8.0 pkginfo/1.8.3 readme-renderer/35.0 requests/2.28.1 requests-toolbelt/0.9.1 urllib3/1.26.10 tqdm/4.64.0 importlib-metadata/4.12.0 keyring/23.7.0 rfc3986/2.0.0 colorama/0.4.5 CPython/3.8.13

Release history Release notifications | RSS feed

This release

1.3.10 This release

2 release files

1.3.9

2 release files

1.3.8

2 release files

1.3.7

2 release files

1.3.6

2 release files

1.3.5

2 release files

1.3.4

2 release files

1.3.3

2 release files

1.3.2

2 release files

1.3.1

2 release files

1.3.0

2 release files

1.2.0

2 release files

1.1.0

2 release files

1.0.2

2 release files

1.0.1

2 release files

1.0.0

2 release files

0.3.0

2 release files

0.2.2

2 release files

0.2.1

2 release files

0.2.0

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page