The Yellow Pages Scraper allows you to search by city or zip code, and search by a number of different criteria such as searching businesses by distance, rating or by name. There’s the option to use multiple proxies, or to search with a delay to emulate human behavior.
Yellowpages.com Web Scraper written in Python and LXML to extract business details available based on a particular category and location.
If you would like to know more about this scraper you can check it out at the blog post 'How to Scrape Business Details from Yellow Pages using Python and LXML' - https://www.scrapehero.com/how-to-scrape-business-details-from-yellowpages-com-using-python-and-lxml/
Getting Started
These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.
Fields to Extract
This yellow pages scraper can extract the fields below:
- Rank
- Business Name
- Phone Number
- Business Page
- Category
- Website
- Rating
- Street name
- Locality
- Region
- Zipcode
- URL
Prerequisites
For this web scraping tutorial using Python 3, we will need some packages for downloading and parsing the HTML.Below are the package requirements:
- lxml
- requests
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Installation
PIP to install the following packages in Python (https://pip.pypa.io/en/stable/installing/)
Python Requests, to make requests and download the HTML content of the pages (http://docs.python-requests.org/en/master/user/install/)
Python LXML, for parsing the HTML Tree Structure using Xpaths (Learn how to install that here – http://lxml.de/installation.html)
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Running the scraper
We would execute the code with the script name followed by the positional arguments keyword and place. Here is an exampleto find the business details for restaurants in Boston. MA.
Sample Output
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This will create a csv file: