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Google Maps Scraper

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Google Maps Scraper

Google Maps Scraper

compass/crawler-google-places
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No credit card required

Extract data from thousands of Google Maps locations and businesses. Get Google Maps data including reviews, reviewer details, images, contact info, opening hours, location, prices & more. Export scraped data, run the scraper via API, schedule and monitor runs, or integrate with other tools.

You can access the Google Maps Scraper programmatically from your own Python applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in Integrations settings in Apify Console.

1from apify_client import ApifyClient
2
3# Initialize the ApifyClient with your Apify API token
4# Replace '<YOUR_API_TOKEN>' with your token.
5client = ApifyClient("<YOUR_API_TOKEN>")
6
7# Prepare the Actor input
8run_input = {
9    "searchStringsArray": ["restaurant"],
10    "locationQuery": "New York, USA",
11    "language": "en",
12    "maxImages": 1,
13    "maxReviews": 0,
14    "maxQuestions": 0,
15    "countryCode": "",
16    "allPlacesNoSearchAction": "",
17}
18
19# Run the Actor and wait for it to finish
20run = client.actor("compass/crawler-google-places").call(run_input=run_input)
21
22# Fetch and print Actor results from the run's dataset (if there are any)
23print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
24for item in client.dataset(run["defaultDatasetId"]).iterate_items():
25    print(item)
26
27# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

📍 Google Maps Scraper API in Python

The Apify API client for Python is the official library that allows you to use Google Maps Scraper API in Python, providing convenience functions and automatic retries on errors.

Install the apify-client

pip install apify-client

Other API clients include:

Developer
Maintained by Apify

Actor Metrics

  • 4.2k monthly users

  • 852 bookmarks

  • 98% runs succeeded

  • 4.7 days response time

  • Created in Nov 2018

  • Modified 17 hours ago

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