Geospatial Indexing Example

This example shows how to create and use a GEO2D index in PyMongo. To create a spherical (earth-like) geospatial index use GEOSPHERE instead.

See also

The MongoDB documentation on Geospatial Indexes.

Creating a Geospatial Index

Creating a geospatial index in pymongo is easy:

>>> from pymongo import MongoClient, GEO2D
>>> db = MongoClient().geo_example
>>> db.places.create_index([("loc", GEO2D)])
'loc_2d'

Inserting Places

Locations in MongoDB are represented using either embedded documents or lists where the first two elements are coordinates. Here, we’ll insert a couple of example locations:

>>> result = db.places.insert_many(
...     [{"loc": [2, 5]}, {"loc": [30, 5]}, {"loc": [1, 2]}, {"loc": [4, 4]}]
... )
>>> result.inserted_ids
[ObjectId('...'), ObjectId('...'), ObjectId('...'), ObjectId('...')]

Note

If specifying latitude and longitude coordinates in GEOSPHERE, list the longitude first and then latitude.

Querying

Using the geospatial index we can find documents near another point:

>>> import pprint
>>> for doc in db.places.find({"loc": {"$near": [3, 6]}}).limit(3):
...     pprint.pprint(doc)
...
{'_id': ObjectId('...'), 'loc': [2, 5]}
{'_id': ObjectId('...'), 'loc': [4, 4]}
{'_id': ObjectId('...'), 'loc': [1, 2]}

Note

If using pymongo.GEOSPHERE, using $nearSphere is recommended.

The $maxDistance operator requires the use of SON:

>>> from bson.son import SON
>>> query = {"loc": SON([("$near", [3, 6]), ("$maxDistance", 100)])}
>>> for doc in db.places.find(query).limit(3):
...     pprint.pprint(doc)
...
{'_id': ObjectId('...'), 'loc': [2, 5]}
{'_id': ObjectId('...'), 'loc': [4, 4]}
{'_id': ObjectId('...'), 'loc': [1, 2]}

It’s also possible to query for all items within a given rectangle (specified by lower-left and upper-right coordinates):

>>> query = {"loc": {"$within": {"$box": [[2, 2], [5, 6]]}}}
>>> for doc in db.places.find(query).sort("_id"):
...     pprint.pprint(doc)
...
{'_id': ObjectId('...'), 'loc': [2, 5]}
{'_id': ObjectId('...'), 'loc': [4, 4]}

Or circle (specified by center point and radius):

>>> query = {"loc": {"$within": {"$center": [[0, 0], 6]}}}
>>> for doc in db.places.find(query).sort("_id"):
...     pprint.pprint(doc)
...
{'_id': ObjectId('...'), 'loc': [2, 5]}
{'_id': ObjectId('...'), 'loc': [1, 2]}
{'_id': ObjectId('...'), 'loc': [4, 4]}

geoNear queries are also supported using SON:

>>> from bson.son import SON
>>> db.command(SON([('geoNear', 'places'), ('near', [1, 2])]))
{'ok': 1.0, 'stats': ...}

Warning

Starting in MongoDB version 4.0, MongoDB deprecates the geoNear command. Use one of the following operations instead.

  • $geoNear - aggregation stage.

  • $near - query operator.

  • $nearSphere - query operator.