Awesome Open Source
Awesome Open Source

Haversine Build Status

Calculate the distance (in various units) between two points on Earth using their latitude and longitude.


$ pip install haversine


Calculate the distance between Lyon and Paris

from haversine import haversine, Unit

lyon = (45.7597, 4.8422) # (lat, lon)
paris = (48.8567, 2.3508)

haversine(lyon, paris)
>> 392.2172595594006  # in kilometers

haversine(lyon, paris, unit=Unit.MILES)
>> 243.71201856934454  # in miles

# you can also use the string abbreviation for units:
haversine(lyon, paris, unit='mi')
>> 243.71201856934454  # in miles

haversine(lyon, paris, unit=Unit.NAUTICAL_MILES)
>> 211.78037755311516  # in nautical miles

The haversine.Unit enum contains all supported units:

import haversine



(<Unit.FEET: 'ft'>, <Unit.INCHES: 'in'>, <Unit.KILOMETERS: 'km'>,
 <Unit.METERS: 'm'>, <Unit.MILES: 'mi'>, <Unit.NAUTICAL_MILES: 'nmi'>)

Performance optimisation for distances between all points in two vectors

You will need to add numpy in order to gain performance with vectors.

You can then do this:

from haversine import haversine_vector, Unit

lyon = (45.7597, 4.8422) # (lat, lon)
paris = (48.8567, 2.3508)
new_york = (40.7033962, -74.2351462)

haversine_vector([lyon, lyon], [paris, new_york], Unit.KILOMETERS)

>> array([ 392.21725956, 6163.43638211])

It is generally slower to use haversine_vector to get distance between two points, but can be really fast to compare distances between two vectors.

Combine matrix

You can generate a matrix of all combinations between coordinates in different vectors by setting comb parameter as True.

from haversine import haversine_vector, Unit

lyon = (45.7597, 4.8422) # (lat, lon)
london = (51.509865, -0.118092)
paris = (48.8567, 2.3508)
new_york = (40.7033962, -74.2351462)

haversine_vector([lyon, london], [paris, new_york], Unit.KILOMETERS, comb=True)

>> array([[ 392.21725956,  343.37455271],
 	  [6163.43638211, 5586.48447423]])

The output array from the example above returns the following table:

Paris New York
Lyon Lyon <-> Paris Lyon <-> New York
London London <-> Paris London <-> New York

By definition, if you have a vector a with n elements, and a vector b with m elements. The result matrix M would be $n x m$ and a element M[i,j] from the matrix would be the distance between the ith coordinate from vector a and jth coordinate with vector b.


Clone the project.

Install pipenv.

Run pipenv install --dev

Launch test with pipenv run pytest

Get A Weekly Email With Trending Projects For These Topics
No Spam. Unsubscribe easily at any time.
python (50,856
distance (31
earth (22

Find Open Source By Browsing 7,000 Topics Across 59 Categories