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5 Best Google Maps Crawlers in 2022

Tuesday, February 15, 2022

Even when you are not driving around, Google Maps has a lot to offer. Most notably, Google Maps is definitely a great source to check out if you are looking for local leads or business data. You can get business information such as phone numbers, websites, addresses, hours, reviews, addresses, zip codes, latitude, longitude, and more. 

 

Last time we ranked the Top 20 Web Crawling Tools to Scrape the Websites Quickly, and today we will review the 5 best Google Maps crawlers out there and catch a glimpse of their features. There are numerous ways to create Google Maps crawlers. Try the following and see which one best suits your data needs!

 

 

1. Places API from Google Maps Platform

Yes, Google Maps Platform provides an official Places API for developers! It's one of the best ways to gather places data from Google Maps, and developers are able to get up-to-date information about millions of locations using HTTP requests via the API.

To use the Places API, you should first set up an account and create your own API key. The Places API is not free and uses a pay-as-you-go pricing model. Nevertheless, the data fields provided by the Places API are limited, and thus you may not get all the data you need.

 

2. Octoparse

Octoparse is a free web scraping tool for non-programmers with which you can build crawlers to scrape data. Using drags and drops, you can easily build a workflow that scrapes the information you need from any website. 

What is really neat about Octoparse is that it has quite a number of pre-built web scraping templates dedicated exclusively to Google Maps. You can literally get a spreadsheet with business names, phone numbers, addresses, websites, ratings, and more within minutes. Simply enter keywords or URLs in the templates and Octoparse will start to scrape data automatically. 

 

goole map scraping template

 

 

Crawlers created with Octoparse can be run both on local machines and in the Cloud. The free version is good for downloading up to 10,000 lines of data. If you download the latest version, you can try out their data auto-detect algorithm to build your own crawler within seconds.

  

 

 

3. Python Framework or Library

You can make use of powerful Python Frameworks or Libraries such as Scrapy and Beautiful Soup to customize your crawler and scrape exactly what you want. To be specific, Scrapy is a framework that is used to download, clean, store data from the web pages, and has a lot of built-in code to save you time while BeautifulSoup is a library that helps programmers quickly extract data from web pages.

In this way, you have to write codes yourself to build the crawler and deal with everything. Therefore, only those programmers who master web scraping are competent in this project.

 

4. Open-source Projects on GitHub

Some projects for crawling Google Maps can be found on GitHub such as this project written in Node.js. There are plenty of good open-source projects which have already been created by others, so let's not re-invent the wheels.

Even if you don't need to write most of the codes yourself, you still need to know the rudiments and write some codes to run the script, making it difficult for those who know little about coding. The quantity and quality of your dataset are highly dependent on the open-source project on GitHub, which lacks maintenance. Also, the output can only be a .txt file, and thus if you want a large scale of data, it may not be the best way for you to get data.

 

 

5. Web Scraper

Web Scraper is the most popular web scraping extension. Download the Google Chrome browser and install the extension Web Scraper and you can start to use it. You don't have to write codes or download software to scrape data, a Chrome extension will be enough for most cases.

 

However, the extension is not that powerful when handling complex structures of web pages or scraping some heavy data.

 

Artículo en español: Los 5 Mejores Rastreadores de Google Maps en 2022

También puede leer artículos de web scraping en el sitio web oficial

Author: Yvonne

 

 

 

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