🌟 Maximize the Potential of a Well-Planned GraphQL Schema: Elevate Your Project! 🌟
Looking to elevate your project? Discover the game-changing benefits of a well-planned GraphQL schema. 🚀
In modern API development, GraphQL has revolutionized flexibility, efficiency, and scalability. A meticulously crafted schema lies at the core of every successful GraphQL implementation, enabling seamless data querying and manipulation. 💡
Explore the key advantages of a well-planned GraphQL schema for your project:
❤️🔥 Precisely define data requirements for each API call. GraphQL's query language empowers clients to request specific data, reducing over-fetching and network traffic This control ensures lightning-fast responses and a superior user experience.
❤️🔥 Act as a contract between frontend and backend teams, providing clear guidelines for data exchange. Developers can work independently on components, without waiting for API modifications. This decoupling accelerates development and project delivery.
❤️🔥 Anticipate future data requirements by easily adding, modifying, and deprecating with a well-designed schema. This saves development time and prevents disruptive changes down the line, making your project adaptable and future-proof.
❤️🔥 GraphQL's self-documenting nature serves as a comprehensive source of truth, eliminating ambiguity. Developers can effortlessly explore and understand data and relationships, boosting productivity and code quality.
❤️🔥 GraphQL's ability to batch and aggregate data from multiple sources optimizes backend operations By intelligently combining and caching data, you can enhance application performance, delivering lightning-fast experiences to users.
Embrace the power of a well-planned GraphQL schema to transform your project and unlock endless possibilities. Optimize data fetching, simplify development workflows, future-proof your application, enhance developer experience, and improve performance. 💪
try GraphQL Editor now!
GraphQL Editor is recommended for software developers working with GraphQL who are looking for an intuitive and interactive way to design, understand, and collaborate on their GraphQL schemas. It is particularly beneficial for teams that value real-time collaboration and need tools that help in visualizing and documenting APIs.
Scrapy is recommended for developers, data scientists, and businesses that need to gather data from websites efficiently. It's particularly useful for projects involving data aggregation, market research, competitive analysis, and monitoring pricing changes across various platforms.
Based on our record, Scrapy seems to be a lot more popular than GraphQl Editor. While we know about 97 links to Scrapy, we've tracked only 6 mentions of GraphQl Editor. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Aside from the ones mentioned graphql editor has a bunch of features that are helpful for testing like a click-out creator and a built-in mock backend for testing queries. Source: over 2 years ago
I may be wrong, but something like graphqleditor is geared more towards setting up GraphQL API/server, in Supabase case, it's database - Postgres, is the server/API. Source: about 3 years ago
I've tried graphqleditor.com but I can't get my my supabase API url to connect [mysupabaseurl].supabase.co/graphql/v1. Source: about 3 years ago
Https://graphqleditor.com/ New version is available here. Source: over 3 years ago
Make your schema and code to that. Here's a tool to help visualize. I've personally never found it useful, but maybe that's just me. Https://graphqleditor.com/. Source: over 3 years ago
One might ask, what about Scrapy? I'll be honest: I don't really keep up with their updates. But I haven't heard about Zyte doing anything to bypass TLS fingerprinting. So out of the box Scrapy will also be blocked, but nothing is stopping you from using curl_cffi in your Scrapy Spider. - Source: dev.to / 10 months ago
Install scrapy (Offical website) either using pip or conda (Follow for detailed instructions):. - Source: dev.to / 11 months ago
Using Scrapy I fetched the data needed (activities and attendance). Scrapy handled authentication using a form request in a very simple way:. - Source: dev.to / 12 months ago
Scrapy is an open-source Python-based web scraping framework that extracts data from websites. With Scrapy, you create spiders, which are autonomous scripts to download and process web content. The limitation of Scrapy is that it does not work very well with JavaScript rendered websites, as it was designed for static HTML pages. We will do a comparison later in the article about this. - Source: dev.to / about 1 year ago
While there is no specific library for SERP, there are some web scraping libraries that can do the Google Search Page Ranking. One of them which is quite famous is Scrapy - It is a fast high-level web crawling and web scraping framework, used to crawl websites and extract structured data from their pages. It offers rich developer community support and has been used by more than 50+ projects. - Source: dev.to / over 1 year ago
Stellate.co - Everything you need to run your GraphQL API at scale
Apify - Apify is a web scraping and automation platform that can turn any website into an API.
GraphQL Playground - GraphQL IDE for better development workflows
ParseHub - ParseHub is a free web scraping tool. With our advanced web scraper, extracting data is as easy as clicking the data you need.
Hasura - Hasura is an open platform to build scalable app backends, offering a built-in database, search, user-management and more.
Octoparse - Octoparse provides easy web scraping for anyone. Our advanced web crawler, allows users to turn web pages into structured spreadsheets within clicks.