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Showing posts from July, 2021

How to Scrape Data Foods Around Jakarta Using Selenium Zomato?

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  Thinking about what type of foods as well as drinks The Big Durian can offer? Let’s extract it using Selenium! Jakarta has now entered in the 8th month of COVID-19 pandemic as well as from a way things are standing right now, this not providing any better. Their government has imposed on-as well as-off social restrictions within the city. People are advised to stay-at-home as well as work-from-home, non-important industry are suggested to be temporarily closed and that’s comprising the dessert parlors or restaurants you love! When social restrictions are on, ‘eating out’ gets stopped completely. We can purchase the ingredients and cook them ourselves. That’s called the ‘to cook’ alternative. In the ‘not to cook’ alternative you can purchase takeaway food or order food online. Being a Jakartan that tries very hard for not contributing to the new cases within the city, we at times, order food online, thanks a lot to the growth of food-delivery apps like GrabFood or GoFood, which are si

How to Scrape Zomato Listings Using BeautifulSoup and Python?

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  Amongst the biggest apps of  Web Scraping  is within scraping restaurants listings from different websites. It might be to create aggregators, monitor prices, or offer superior UX on the top of available hotel booking sites. We will see how a simple script can do that. We will utilize BeautifulSoup for scraping information as well as retrieve hotels data on Zomato. To begin with, the given code is boilerplate and we require to get Zomato search result pages and set BeautifulSoup for helping us utilize CSS selectors for asking the pages for important data. # -*- coding: utf-8 -*- from bs4 import BeautifulSoup import requests headers = {'User-Agent':'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_2) AppleWebKit/601.3.9 (KHTML, like Gecko) Version/9.0.2 Safari/601.3.9'} url = 'https://www.zomato.com/ncr/restaurants/pizza' response=requests.get(url,headers=headers) soup=BeautifulSoup(response.content,'lxml') #print(soup.select('[data-lid]')) for item

How Does Extracted Food Delivery Data Help You Find More Business In The Food Industry?

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  The food delivery niche is projected to reach around $127 billion in 2021 end as well as the revenue gets expected to surge at $192 billion in 2025. These platforms as well as apps are having thousands of listings for food restaurants and also are used through millions of customers. Food chains, as well as restaurants, are benefiting from big data analytics to understand consumers’ preferences and tastes. Nowadays, you can use data scraping to collect data from various food data apps for adjusting prices, improve marketing strategies, and more. If you need to advance your restaurant or food delivery business, then food delivery scraping is the best solution that can help you get closer to your goals. How Food Data Scraping Can Help You? Web data scraping is the method of scraping huge amounts of information from targeted websites or apps. Due to the race in various restaurants, food aggregator apps, as well as related businesses, are increasing constantly. So, food delivery companies