CODEWITHSUNDEEP
pythonmongodbgeolocationmongodb-query
Tony Roczz
Tony Roczz

Reputation: 2398

How to find locations near a given location

I am trying to create a Bounding Box (or a circle) for the given latitude and longitude with some distance(or radius) using Python3.

I have gone through the previous solutions for this problem but I am having some doubt on how it works. There are some variables like halfsideinKm and some degree to radian and radian to degree conversion and I am unable to understand what are those conversions for and how it works.

Given lat and long finding binding box

Geocoding calculate bounding box

I have a database collection Locations(in MongoDB) which holds the lat and long.

My Requirement is if I enter a lat and long I want to have the list of Places(from my mongodb) which lie inside of the Bounding Box region(with a distance of say 20 Km).

Can anyone provide me with a solution for this problem or some explanation on how those codes work?

Can this be achieved using geopy?(because it says something about great circle distance calculation)

Database values

{
  "place_id":"151142295",
  "osm_type":"relation",
  "osm_id":"65606",
  "lat":"51.5073219",
  "lon":"-0.1276474",
  "display_name":"London, Greater London, England, United Kingdom",
  "class":"place",
  "type":"city",
  "importance":0.9754895765402
},
{
  "place_id":"4566287",
  "osm_type":"node",
  "osm_id":"485248691",
  "lat":"42.988097",
  "lon":"-81.2460295",
  "display_name":"London, Ontario, Canada",
  "class":"place",
  "type":"city",
  "importance":0.6515723047601
}

(just a sample of how data is stored in my db)

Upvotes: 0

Views: 2401

Answers (1)

Blakes Seven
Blakes Seven

Reputation: 50406

The very "first" thing you must do is change how you are storing your data if you intend to use geospatial queries with MongoDB. You have the option of legacy coordinate pairs or GeoJSON format. But your current storage with "lat" and "long" in separate fields and also as "strings" will not work.

Here is a schema fix for your collection, written for the mongo shell because this should be a one off operation. I'm advising on GeoJSON, as it is generally compatible with quite a few libraries, and all distances returned are in kilometers rather than radians.

var bulk = db.collection.initializeUnorderedBulkOp(),
    count = 0;

db.collection.find().forEach(function(doc) {
   bulk.find({ "_id": doc._id }).updateOne({
       "$set": {
           "location": {
               "type": "Point",
               "coordinates": [parseFloat(doc.lon),parseFloat(doc.lat)]
           }        
       },
       "$unset": { "lat": "", "lon": "" }
   });
   count++;

   if ( count % 1000 == 0 ) {
       bulk.execute();
       bulk = db.collection.initializeUnorderedBulkOp();
   }
});

if ( count % 1000 !=0 )
   bulk.execute();

Now the data is fixed and compatible with an index, create the index. What makes sense here with GeoJSON data is a "2sphere" index:

db.collection.createIndex({ "location": "2dsphere" })

Now you are ready to query. Sticking with the shell as the python syntax is identical and I don't know your library calls:

db.collection.find({
    "location": {
        "$nearSphere": {
            "$geometry": {
                "type": "Point",
                "coordinates": [lon,lat]
            },
            "$maxDistance": distance
        }
    }
})

This query uses $nearSphere which will calculate properly on distance based on the curvature of the earth, ideal for real location data. Your three variables there are the "longitude", "latitude" ( in that order ) in the coordinates array and the "distance" under $maxDistance that you want to find things within that radius.

This is a very simple query procedure once your data is suitable and the required geospatial index is in place.

No need for messy calculations in your client, as the server does all the work.

The links to the relevant documentation parts are all included for your reference. Read them and learn more about geospatial queries with MongoDB.

Upvotes: 2

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