The Sapo Galp Fast API is not currently available on the RapidAPI marketplace.
Click "Request this API on RapidAPI" to let us know if you would like to access to this API.
Meanwhile, you can check out the top APIs that currently available for developers.
Sapo Galp Fast API Search Results & Alternatives
This API provides you with tools to find nutrition and diet data for generic foods, packaged foods and restaurant meals. In addition it employs NLP (Natural Language Processing) which allows for extraction of food entities from unstructured text. Covered Use Cases: Search for a food by keyword, food name or UPC/Barcode Sourcing of nutrition facts for a given food, including: macro and micro nutrients, allergen labels, lifestyle and health labels Search for a food by given nutrient quantity for 28 nutrients Seach for foods within a given brand With the build in food-logging context it allows for NLP requests for chat bots and natural language calorie counters
-SportMonks API- Looking for better and reliable Football Data? More Leagues(1.000+)? Faster Livescores (>15 faster)? And more available Odds and Stats? Check https://sportmonks.com/football-api With this SportMonks Football Pro API we offer 900+ Leagues and the fastest real-time Livescores in the market with a rich set of other features like (live)Odds, Statistics, Line-ups, Standings and many more features. For example our Livescores are often faster than TV and often >15 seconds(!!) faster compared to other suppliers. With more than 14.000 registered users we we can say we are the go-to party for Fast en Reliable Football Data. When you want your business idea to succeed, go for quality Football Data, and not the cheapest supplier. More info: https://sportmonks.com/football-api | | Docs: https://www.sportmonks.com/docs/football/2.0/
Related APIs in Category: eCommerce
This is an API to check a website to determine if it's an online ecommerce store. We do this in a few ways -- first we check to see if it matches common e-commerce store platforms (ie. Shopify, Magento, etc). Next we check the page text to see if we can determine it has characteristics of an online store. Finally we parse the DOM, looking for clues to see if it links to the server that has a e-commerce backend.