Get data from Google Places that the official Google Maps Places API does not provide.
The official Google Maps Places API is the best option for most use cases.
But unlike the Google Maps Places API, the crawler can provide:
- Popular place times histogram (no data for that in official API)
- Place reviews (up to 5 reviews from official API)
- Place photos (up to 10 photos from official API)
If you want to run the actor on Apify platform, you need to have at least a few proxy IPs to avoid blocking from Google. You can use proxy IPs pool on Apify proxy trial or you can subscribe to one of Apify subscription plan. It is recommended to run the actor with at least 8GB memory. On Apify platform with 8GB memory you can get:
- 100 google place details for 4 compute units
- 100 google place details with images and reviews for 10 compute units - the usage really depends on how many images and reviews specific places have
Follow guide on actor detail page to see how it works.
Example input:
{
"searchString": "pubs near prague",
"lat": "50.0860729",
"lng": "14.4135326",
"zoom": 10
}
On this input actor searches places on this start url: https://www.google.com/maps/search/pubs+near+prague/@50.0860729,14.4135326,10z
searchString
- String will be search on Google maps. It is possible fill Google Place ID in formatplace_id:ChIJp4JiUCNP0xQR1JaSjpW_Hms
.proxyConfig
- Apify proxy configurationlat
- Use it with combination with longitude and zoom to set up viewport to search on.lng
- Use it with combination with latitude and zoom to set up viewport to search on.zoom
- Viewport zoom, e.g zoom: 10 -> https://www.google.com/maps/@50.0860729,14.4135326,10z vs zoom: 1 -> https://www.google.com/maps/@50.0860729,14.4135326,10zmaxCrawledPlaces
- Limit places you want to get from crawler
You can exclude some attributes from results using input parameters. It can help to speed up crawling.
You need to set the attribute to false
.
includeReviews
includeImages
includeHistogram
includeOpeningHours
includePeopleAlsoSearch
Once the actor finishes, it outputs results to actor default dataset.
Example results item:
{
"title": "Scotiabank",
"placeId": "ChIJZTZXgbEcdkgRI5fp8iVqzl8",
"totalScore": 3.7,
"categoryName": "Bank",
"address": "201 Bishopsgate, London EC2M 3NS, UK",
"plusCode": "GWCC+75 City of London, London, UK",
"popularTimesHistogram": {
"Su": [],
"Mo": [
{
"hour": 6,
"occupancyPercent": 0
},
{
"hour": 7,
"occupancyPercent": 0
},
{
"hour": 8,
"occupancyPercent": 0
},
{
"hour": 9,
"occupancyPercent": 75
},
{
"hour": 10,
"occupancyPercent": 73
},
{
"hour": 11,
"occupancyPercent": 60
},
{
"hour": 12,
"occupancyPercent": 57
},
{
"hour": 13,
"occupancyPercent": 56
},
{
"hour": 14,
"occupancyPercent": 56
},
{
"hour": 15,
"occupancyPercent": 57
},
{
"hour": 16,
"occupancyPercent": 50
},
{
"hour": 17,
"occupancyPercent": 33
},
{
"hour": 18,
"occupancyPercent": 14
},
{
"hour": 19,
"occupancyPercent": 4
},
{
"hour": 20,
"occupancyPercent": 1
},
{
"hour": 21,
"occupancyPercent": 0
},
{
"hour": 22,
"occupancyPercent": 0
},
{
"hour": 23,
"occupancyPercent": 0
}
],
...
},
"reviews": [
{
"name": "NELLORE BALA NAVEEN REDDY",
"text": "nice bank in london",
"stars": "5 stars",
"publishAt": "2 months ago",
"likesCount": "",
"responseFromOwnerText": ""
},
...
],
"reviewsCount": 6,
"imageUrls": [
"https://lh5.googleusercontent.com/p/AF1QipPvm-rzo7_mlLRmctQwDJV6agVGHZMUJYLinU_t=s508-k-no",
...
],
"url": "https://www.google.com/maps/place/Scotiabank/@51.5258542,-0.335595,11z/data=!4m8!1m2!2m1!1sbanks+london!3m4!1s0x48761cb181573665:0x5fce6a25f2e99723!8m2!3d51.5206306!4d-0.0795672"
}