Food Ordering Scraper (DoorDash, UberEats, Grubhub)
Get real-time data of delivery orders on DoorDash, Uber Eats, and Grubhub.
PROBLEM
STATEMENT
Our client needed merchant-side data of orders coming to restaurants through 3 major ordering companies (DoorDash, Uber Eats, and Grubhub). We were required to implement a smart algorithm to retrieve such a huge volume of information and prevent blocking, duplication, and other problems.
SOLUTION
We implemented the proprietary algorithm of Data Prism to extract the data in real-time. We used several proxies to ensure that the scraper works continuously and achieves a success rate of over 98%. The data was stored in Big Query and was used to generate useful business insights (through data analysis) for the client.
Input
Access to all the restaurants listed on DoorDash, Uber Eats, and Grubhub.
Output
Real-time data about delivery orders is stored in Big Query for further analysis.
Tools &
Technologies
Python (Scrapy)
Proxy Services (Zyte, Brightdata, ScrapeNinja, ScraperAPI, WebScrapingAPI)
