Use Google Maps Grid-Based Market Saturation Scanner with Python

Cover a bounding box, circle, or custom polygon with a search grid to collect every business Google Maps exposes for a query, well beyond the usual 120-result cap on a single search.

1. Choose the data you need

Review the published README for supported collection modes, examples, and limits. The recipe below uses the current published input definition.

2. Prepare a source-based input

This JSON contains published prefills and required-field defaults. Review every value for your task before running it; it is not a promise of successful collection.

{
  "boundingBox": {
    "east": -73.97,
    "north": 40.77,
    "south": 40.73,
    "west": -74.01
  },
  "deduplicateResults": true,
  "enrichDetails": false,
  "maxPagesPerCell": 13,
  "maxPlacesPerCell": 5,
  "maxTotalResults": 5,
  "searchQuery": "coffee shops",
  "zoomLevel": 15
}

Download input.example.json and save your reviewed copy as input.json.

Field	Type	Required	Description
`searchQuery`	string	required	Type of business to search for (e.g., 'pharmacy', 'restaurant', 'dentist').
`locationName`	string	optional	Name of a public Google Maps location (e.g., 'Brooklyn, NY'). Google resolves its real center anonymously, then the actor scans the user-controlled radiusKm around it. Use boundingBox or GeoJSON for exact boundaries.
`boundingBox`	object	optional	Geographic bounding box defining the scan area. Provide north/south/east/west coordinates.
`circleCenter`	object	optional	Center point for a circular scan area. Use with radiusKm.
`radiusKm`	number	optional	Radius in kilometers for circular scan area (used with circleCenter or locationName).
`customGeolocation`	object	optional	Custom GeoJSON Polygon defining the scan boundary.
`zoomLevel`	integer	optional	Controls grid cell granularity. Higher = smaller cells, more thorough coverage.
`maxPlacesPerCell`	integer	optional	Maximum businesses to collect from each grid cell (1–260; Google's ranked window for one cell reaches roughly 136–213 places).
`maxPagesPerCell`	integer	optional	How many 20-result pages to read per cell. Deeper pages surface more businesses — page 1 finds about 20% of a cell's places, page 9 finds all of them.
`maxTotalResults`	integer	optional	Maximum total businesses to extract across all cells. Stops scanning when reached.
`deduplicateResults`	boolean	optional	Remove duplicate businesses that appear in multiple adjacent grid cells.
`enrichDetails`	boolean	optional	Open each place's page for extra fields (price level, Plus Code, photo sample, rating histogram, open/closed status). Slower; leave off for large exports since listing fields are always collected.
`minRating`	number	optional	Only include businesses with a rating at or above this value (1.0–5.0). Leave empty to include all.
`language`	string	optional	Language for Google Maps interface and results.

3. Start an Actor run

Set APIFY_TOKEN in your environment. Python 3.10 or newer is sufficient; this recipe uses no third-party packages.

Execution may incur charges. Review current pricing on Apify. The request asks for a 120-second timeout and a charge limit; these settings are subject to Apify’s pricing and do not guarantee an all-inclusive spending cap.

import json
import os
import urllib.request

# Save the schema-derived example as input.json; review and edit it first.
with open("input.json", encoding="utf-8") as stream:
    actor_input = json.load(stream)

token = os.environ["APIFY_TOKEN"]
request = urllib.request.Request(
    "https://api.apify.com/v2/acts/lEvpsUsigS536O8Wg/runs?timeout=120&maxTotalChargeUsd=0.50",
    data=json.dumps(actor_input).encode("utf-8"),
    headers={"Authorization": "Bearer " + token, "Content-Type": "application/json"},
    method="POST",
)
# This starts a potentially billable run. Do not automatically retry this POST.
with urllib.request.urlopen(request, timeout=40) as response:
    run = json.load(response)["data"]
print("Run ID:", run["id"])
print("Status:", run["status"])
# Inspect and download results in Apify Console once the run succeeds.

4. Inspect the actual results

Open the run in Apify Console and wait for a successful completion. Use the published output schema to locate results and the dataset schema to understand declared views. Missing or optional record fields must not be treated as guaranteed values.

Questions before you run

Which inputs are required?

The published required fields are searchQuery

What does this guide verify?

The fields, prefills, and schema links are rendered from the published build. This is a usage recipe, not a paid live extraction test. Source availability and collection results can vary.

What if the run request times out?

Check Apify Console before retrying. The first request may already have created a run. Do not automatically repeat a run-creation POST.

Open on Apify Full Actor reference

Generated from source build qAmn3PoCcJy3rIf24 and its README and schemas. Source changes regenerate this guide; no third-party editorial claims are inferred.