Geospatial Indexing Example

See also

The MongoDB documentation on

Creating a geospatial index in pymongo is easy:

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

Note

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

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

Note

The $maxDistance operator requires the use of :

>>> 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)
...
{u'_id': ObjectId('...'), u'loc': [2, 5]}
{u'_id': ObjectId('...'), u'loc': [4, 4]}
{u'_id': ObjectId('...'), u'loc': [1, 2]}

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

Or circle (specified by center point and radius):

>>> for doc in db.places.find(query).sort('_id'):
...   pprint.pprint(doc)
...
{u'_id': ObjectId('...'), u'loc': [2, 5]}
{u'_id': ObjectId('...'), u'loc': [1, 2]}
{u'_id': ObjectId('...'), u'loc': [4, 4]}

geoNear queries are also supported using :

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

$geoNear - aggregation stage.
$near - query operator.