Hello everyone! In the current day and age where public web data scraping has become a foundation for many businesses, it is unsurprising to see that Google Maps is yet another area commonly scraped for its valuable data. In this article, we’ll discuss what this data may be and how to build a scraper that gathers it using an Oxil app solution.
The legality of web scraping
The legality of web scraping is a much debated topic among anyone who works in the data-gathering field. In support to note that web scraping is legal in cases where it is completed without breaking any ordinances regarding the source victims or data itself.
That is to say, we inform you to pursue legal conversation before engaging in scraping conditioning of any kind.
Why scrape google maps?
The core purpose of scraping Google Maps are countless. By a exploration perspective, a user may want to employ a Google Maps data scraper to assess demographic information or ride routes.
For businesses, Google Maps scraper may be the go-to tool for competitor analysis, as it allows you to collect data from any competitor’s locations, customer reviews, and ratings. Gathering real estate or property listings is a possible use case as well.
General, this creates Google Maps data scraping a highly lucrative solution that many businesses are some to make use of.
Should you use the official google maps API?
Naturally, the question may arise if you should use the official Google Maps API. After all, other popular websites like Twitter or Amazon provide their own APIs, and Google Google is no exception.
Therefore, why not use it? Well, let’s begin with the price. Each user gets $250 monthly credit for API calls. With these $250, you can get up to 45,000 geolocation calls, up to 100,000 static maps loads, up to 22,000 dynamic map loads, up to 45,000 directional calls, and at first glance, they may appear as enough, but it’s likely not.
Google’s API, example many other APIs, commences to count you when the given amount is reduced. After, imagine a scenario where you use the Embedded API in directives, panoramas, and search manners. Guess your server loads up a map that initiates address search through autocomplete.
The single request is now using two different API calls. Add another measurement, say Geolocation services for directions or distances, and now a single request is taking up three separate API calls.
Moreover, as your business balances, so does the daily amount of calls you produce, intention after a certain point, Google Maps API grows an unbelievably pricey result. Eventually the high price is not the only limitation of Googles own API. There are also strict request limitations, Google’s current enforced rate limit is up to 100 requests per second. Google is also known to implement unpredictable alteration that give little advantage to their users.
However, products like Oxlab’s API solutions are specifically made to avoid limitations such as the ones mentioned above,which is why they’re commonly discussed and used instead of official APIs.
How to extract data from google maps?
To scrape Google Maps data, you will need Oxlabs Serp Scraper API.Send up for Google search results Scraper API and take note of your username and password.Replace username with your password and username with your password throughout the code selections in this guide.
until writing code to scrape data from Google Maps,we must situate a project environment and inaugurate the necessary Python libraries.Generate a new virtual environment to different your project dependencies from your system packages.Ensure that you have Python 3.8 or newer installed.Run the following command in a terminal.Activate the virtual environment by running the appropriate command for your operating system.
Install the required Python libraries for this project.We’ll be using beautiful sup4 requests and pandas.You can install them by running the following.With your project environment set up,we’re ready to start writing code to scrape Google Maps data.
Fetching data using the oxylabs google search scraper API
We’ll be using Oxilab’s third scrape API to fetch data from Google Maps.This API allows to send HTTP requests to Google and receive the HTML content of the search results page.
If you run into any difficulties or would simply like to learn more, you can chat with us on Discord.The link is in the description.
Now, open google.com in your browser and search restaurants near me.You will see the search results with the restaurant’s names, ratings, hours, and other data points.
Second, copy this URL: We will use Google Search Scrape API to fetch data from this URL.
Third, to use Google Search Results Scrape API, we need to set the following parameters.
- Source, this will be Google,
- URL, the URL that you copied after searching for restaurants near me.
- Geo underscore location, Google’s Scrape API allows us to use any location for search.
Fourth, create a dictionary as follows that will contain these parameters.
Fifth, send these parameters to the API endpoint:For this, we can use the request library to send a post message as follows.Replace username with your username and password with your password.If everything is well, you should get a response status code to 200. And you can get the HTML from the results as follows.
Parse this HTML
Parse this HTML and don’t forget if you’ve enjoyed this tutorial click like and subscribe. Once we have the HTML content of the search results page we can use the beautiful Sup library to parse the data.In this example, we’ll extract the following data points from any place listed in the hunt results,name, place type, address, rating, price level, rating, latitude, longitude, hours, and other details.
- first,open the browser and open the same URL that you used in the code. Right-click on any of the listings and select Inspect.Try to create a sector that selects exactly one listing at a time.One possible selector is [role=’heading]. The other is [data-id] in this example.We can loop over all the matches and look for specific data points.
- The next step is to create a CSS selector for each data point you want to scrape: For example, you can select the name of the restaurant with the following CSS selector. The following are all the selectors.We can use BeautifulSoup’s select and select underscore score one methods to select elements and then extract the text within those elements.Rating count needs a different approach.The rating count is enclosed in brackets along with the rating for example 4.3 bracket 513. In this case the count is within the brackets.
We can use the rejects to extract the value as follows.Putting everything together, the following code generates a list of dictionaries that contain all the data from all the listings on the page.
Export it to a CSV file
We use the pandas library to create a data frame and save it as CSV file.When you run this code, it will save the data to a CSV file named data CSV.
So, while scraping Google Maps isn’t an easy task, this guide should help you navigate both the scraping process, how it works, and how it functions in tandem with our API solution.The aim of the tutorial was to provide a step-by-step comprehensive guide.But in case you have any questions, don’t hesitate to contact us or chat with our website,available live support team.Thank you and this was Oxlabs.
