Skip to main content

A 100% personal route optimizer in a known environment based on experience.

Project description

https://mybinder.org/badge_logo.svg https://github.com/eumiro/pygohome/workflows/CI/badge.svg https://img.shields.io/pypi/v/pygohome.svg https://img.shields.io/pypi/pyversions/pygohome.svg https://img.shields.io/github/license/eumiro/pygohome

pygohome: Python, Let’s Go Home. Quickly.

pygohome is a 100% personal route optimizer in a known environment based on experience.

You walk/ride/drive frequently between known locations (home, work, school, shops, family, friends, …) using different routes, but would like to know the optimal route, that should take you the least time possible? pygohome uses your recorded GPS tracks to build a route network of your world with estimation on how long you need to get from A to B using the mean of transport of your choice.

How it works

You track all your trips

A simple GPS track with 1 or 2 seconds interval works well. Just walk/ride/drive as you are used to, stop at lights, don’t speed. You may start tracking before you leave and stop it after you arrive.

You identify your points of interest (and crossroads)

pygohome does not use any map data, so you’ll have to help it. First, you identify all points of interest (home, work, school, shop, family, friends, pub, club, beach, …) and name them.

In the current version, you’ll also have to identify all forks and crossroads where your individual GPS tracks cross, split, or join.

You let pygohome build your world

It will build a route network with your nodes (named POIs and identified intersections) and edges (automatically generated lists of timedeltas you needed to get between the nodes).

You can find the fastest route from A to B

You can choose anywhere between “I’m feeling lucky” (i.e. Sunday 7am, sunny) and “I’d like to make sure I get there in time” (i.e. Friday 5pm, blizzard).

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pygohome-0.2.1.tar.gz (10.4 kB view details)

Uploaded Source

Built Distribution

pygohome-0.2.1-py3-none-any.whl (9.4 kB view details)

Uploaded Python 3

File details

Details for the file pygohome-0.2.1.tar.gz.

File metadata

  • Download URL: pygohome-0.2.1.tar.gz
  • Upload date:
  • Size: 10.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.3.0 pkginfo/1.6.1 requests/2.25.1 setuptools/49.2.1 requests-toolbelt/0.9.1 tqdm/4.54.1 CPython/3.9.0

File hashes

Hashes for pygohome-0.2.1.tar.gz
Algorithm Hash digest
SHA256 eeb4d807b6b1920580340284baabc4bd72c4b80142f34b4717941c332bdc8aec
MD5 6873c915fa7c655a513281ad50e2a275
BLAKE2b-256 9c599ea26d371c374af6664c6517d916eeed5d3251f2484c9c0c09531527acd0

See more details on using hashes here.

File details

Details for the file pygohome-0.2.1-py3-none-any.whl.

File metadata

  • Download URL: pygohome-0.2.1-py3-none-any.whl
  • Upload date:
  • Size: 9.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.3.0 pkginfo/1.6.1 requests/2.25.1 setuptools/49.2.1 requests-toolbelt/0.9.1 tqdm/4.54.1 CPython/3.9.0

File hashes

Hashes for pygohome-0.2.1-py3-none-any.whl
Algorithm Hash digest
SHA256 f332c7d2a94ccbad5eea98d337a105cd1067e844801e9294a073ec1854a1a85a
MD5 13a43d3ef6712ac2e3a3a8796015c427
BLAKE2b-256 df1e5e0614c7834bb4721453bedf2f9948e7125ae0f1163b940b85dc850acc25

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page