Step 2: Set Your Location(s)

Select how you'd like to query our nationwide dataset using one of our supported geo-types


"city" [string] + "state" [string]

  • "city" requires "state" to also be provided
{
  "size": 10,
  "absentee_owner": true,
  "city": "Richmond",
  "state": "VA"
}

"state" [string]

  • MUST be a 2 digit state code, all caps
  • some states are too large to fully paginate through past the 500,000 cap without at least a few filters being applied
  • some exceptions exist like assumables, foreclosures, and judgments where it makes sense to filter at the state level
{
  "size": 10,
  "absentee_owner": true,
  "state": "VA"
}

"county" [string] + "state"

"county" requires "state" to also be provide

{
  "size": 10,
  "absentee_owner": true,
  "county": "Henrico",
  "state": "VA"
}

"zip" [string] or [array]

  • no "state" is required
{
  "zip": "22205",
  "absentee_owner": true
}

or

{
  "zip": ["22205", "23857", "95687", "20008"], 
  "absentee_owner": true
}

Support Multiple Geos in One Query with Compound Queries

  • stack multiple cities or counties
  • mix and match different types of geos together
{
  "absentee_owner": true,
  "and": [ { "or": [ { "city": "Richmond", "state": "VA" }, { "zip": "22205" }, { "county": "Brunswick", "state": "VA" } ] } ]
  
}


Search Radius search

There are only a few key components to performing your first Property Search based on Current Location or some other arbitrary geo-point in the US. For best results, please make sure any latitudes or longitudes are at least 6 digits of precision (aka Zip9 Precision)

You'll need:

  • "latitude" (double/float or string representation thereof)
  • "longitude" (double/float or string representation thereof)
  • "radius" (between 0.1-100 [in miles])
  • "address" or "id" are also allowed to be passed instead of "latitude" / "longitude" along with "radius" as the center point of your search

Code sample for query "Find properties within 5 miles of location point provided that have 2-4 beds and 2-5 baths"

{
  "size": 10,
  "latitude": "-86.32762085355883",
  "longitude": "35.42300740560803",
  "radius": 5,
  "beds_min": 2,
  "beds_max": 4,
  "baths_min": 2,
  "baths_max": 5
}

"polygon" search

All you need is a list of latitude and longitude points (aka coordinates) to get started.

For the polygon geo-points, you can use string or double (floats also accepted) representations for the actual point values. Integers will not be accepted, so make sure to include at least 6 digits of precision.

{
  	"size": 100,
  	"count": false,
    "polygon": [
        {
            "lon": "-86.32762085355883",
            "lat": "35.42300740560803"
        },
        {
            "lon": "-86.43359069901402",
            "lat": "35.19184584103132"
        },
        {
            "lon": "-86.0572016901352",
            "lat": "35.15490990082178"
        },
        {
            "lon": "-86.00921468169653",
            "lat": "35.45088715765438"
        },
        {
            "lon": "-86.32762085355883",
            "lat": "35.42300740560803"
        }
  ]
}

"multi_polygon"

For multi-polygon searches, the input looks similar, but it consists of an array of polygon objects, instead of an array of geo-point objects.

{
  "size": 100,
  "count": false,
  "multi_polygon": [
    [
      {
        "lon": "-86.32762085355883",
        "lat": "35.42300740560803"
      },
      {
        "lon": "-86.43359069901402",
        "lat": "35.19184584103132"
      },
      {
        "lon": "-86.0572016901352",
        "lat": "35.15490990082178"
      },
      {
        "lon": "-86.00921468169653",
        "lat": "35.45088715765438"
      },
      {
        "lon": "-86.32762085355883",
        "lat": "35.42300740560803"
      }
    ],
    [
      {
        "lon": "-87.32762085355883",
        "lat": "36.42300740560803"
      },
      {
        "lon": "-87.43359069901402",
        "lat": "36.19184584103132"
      },
      {
        "lon": "-87.0572016901352",
        "lat": "36.15490990082178"
      },
      {
        "lon": "-87.00921468169653",
        "lat": "36.45088715765438"
      },
      {
        "lon": "-87.32762085355883",
        "lat": "36.42300740560803"
      }
    ]
  ]
}