Foodspark - Food Data & insights

  The progressive app is developed which will assist people having diabetes to search for the information on the food they consume. Initially, the database will only have a few numbers of food items. Developing the App Axios, Fuse, Icons8, Pluralize, and Vue is some of the open-source projects used to create the app. Netlify is in charge of hosting the entire thing. There are three components at action here: The information A simple lambda function powers the backend search API The attractive user interface on the front end The Information You can initiate by writing a strictly formatted ‘database’ using JSON. It will look like this: The Back-End Once you have the data structure, you can start building API. Thanks to Pluralize and Fuse, the search is rather straightforward. You can start by importing the dependencies... You can see that, in addition to Pluralize and Fuse, it is also possible to import the data. After that, you can build a search engine based on the data. When users sea

  Scrimper is a software that will assist students and other individuals in locating the cost-effective supermarket store for their grocery shopping. To accomplish so, the script web-scrapes via the online inventories of numerous stores to extract the necessary information, which is then stored as a CSV file. This information is sorted to provide the lowest supermarket as well as the final pricing. As a team comprised primarily of students, we are all aware that life is costly. We discovered that food and grocery shopping account for the majority of variable expenses. It's inconvenient to visit many stores in search of the best deal on each commodity or to save money by surviving on bread and water. This is why we set out to create a web scraping tool that will scrape the cheapest supermarket grocery store location for all of your needs. Our purpose is also to assist those in need who do not have the financial means to spend a lot of money on meals. Our first idea was to build a pl

  TripAdvisor reviews provide a wealth of information on airline and hotel costs that might help you grow your business. It also contains a wealth of information about major travel locations, hotels, and restaurants. You can use web scraping to automatically collect information from TripAdvisor reviews if you want to extract and use all of this information. Web scraping is the act of employing automated bots to collect data from a website's HTML version and delivering it in Excel or CSV format so you can process, analyze, and utilize it. Data scraping  reviews from TripAdvisor is the most effective data collection approach currently accessible, and it will considerably improve your capacity to synthesis, organize, and analyze existing patterns in the hospitality business. Why TripAdvisor Reviews are Necessary? How many TripAdvisor reviews are there? TripAdvisor has nearly 884 million reviews on hotels, lodgings, and other services as of 2020. As a result, TripAdvisor evaluations ma

  Introduction Restaurant business has become an aggressive battlefield where you require to be active all the time for satisfying guest expectations as well as outperform the competitors. As good and ready-to-eat food is always in demand, more and more restaurants are opening but not all get the anticipated response from the customer. So, many restaurants face bankruptcy, financial losses, as well as they are forced to close their business. Restaurants have to make the best food and also serve it proficiently to the customers. Simultaneously, they must talk with the customers regarding their menus and how they are serving the food. So, you can say that making a responsive site and doing online marketing is important for their success. Web scraping can be used in almost all spheres and is not restricted to any particular field. Therefore, if you require  restaurant data scraping  for building a professional site, a web scraping tool will be perfect to scrape detailed facts, figures, an