Python library for network analysis
Project Links
Meta
Author: UrbanSim Inc.
Classifiers
Programming Language
- Python :: 3.6
- Python :: 3.7
- Python :: 3.8
- Python :: 3.9
- Python :: 3.10
- Python :: 3.11
License
- OSI Approved :: GNU Affero General Public License v3
Pandana is a Python library for network analysis that uses contraction hierarchies to calculate super-fast travel accessibility metrics and shortest paths. The numerical code is in C++.
0.7
Jul 26, 2023
0.6.1
Mar 17, 2021
0.6
Nov 23, 2020
0.5.1
Aug 06, 2020
0.5
Jul 28, 2020
0.4.4
Sep 04, 2019
0.4.3
Aug 28, 2019
0.4.2
Aug 09, 2019
0.4.1
Sep 05, 2018
0.4.0.1
Jul 06, 2017
0.4.0
Nov 06, 2017
0.3.0
Apr 05, 2017
0.2.1
Oct 29, 2015
0.2.0
Oct 29, 2015
0.1.2
Nov 10, 2014
0.1.1
Nov 07, 2014
0.1
Aug 27, 2014
Wheel compatibility matrix
| Platform | CPython 3.8 | CPython 3.9 | CPython 3.10 | CPython 3.11 |
|---|---|---|---|---|
| macosx_10_9_x86_64 | ||||
| macosx_11_0_arm64 | ||||
| manylinux2014_x86_64 | ||||
| manylinux_2_17_x86_64 | ||||
| win_amd64 |
Files in release
pandana-0.7-cp310-cp310-macosx_10_9_x86_64.whl (156.2KiB)
pandana-0.7-cp310-cp310-macosx_11_0_arm64.whl (147.0KiB)
pandana-0.7-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.9MiB)
pandana-0.7-cp310-cp310-win_amd64.whl (138.3KiB)
pandana-0.7-cp311-cp311-macosx_10_9_x86_64.whl (156.7KiB)
pandana-0.7-cp311-cp311-macosx_11_0_arm64.whl (147.4KiB)
pandana-0.7-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.0MiB)
pandana-0.7-cp311-cp311-win_amd64.whl (138.7KiB)
pandana-0.7-cp38-cp38-macosx_10_9_x86_64.whl (172.8KiB)
pandana-0.7-cp38-cp38-macosx_11_0_arm64.whl (164.0KiB)
pandana-0.7-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.0MiB)
pandana-0.7-cp38-cp38-win_amd64.whl (139.3KiB)
pandana-0.7-cp39-cp39-macosx_10_9_x86_64.whl (157.1KiB)
pandana-0.7-cp39-cp39-macosx_11_0_arm64.whl (148.0KiB)
pandana-0.7-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.0MiB)
pandana-0.7-cp39-cp39-win_amd64.whl (138.9KiB)
pandana-0.7.tar.gz (288.1KiB)
Extras:
None
Dependencies:
numpy
(>=1.8)
pandas
(>=0.17)
requests
(>=2.0)
scikit-learn
(>=0.18)
tables
(>=3.1)