Godspeed Systems’ Post

Effortlessly Format JSON with Teasoft's JSON Formatter. Welcome to Teasoft's JSON Formatter, your ultimate tool for effortlessly formatting JSON data. Whether you're cleaning up API responses, debugging JSON files, or improving readability, our formatter ensures that your JSON is well-structured and easy to work with. Benefits: 1. Quick and Precise Formatting 2. User-Friendly Interface 3. Supports JSON Formatting 4. No Installation Required 5. Free to Use 6. Instant Results Format your JSON data with ease using Teasoft's JSON Formatter: https://lnkd.in/g_2xtgyv [ Teasoft JSON Formatter ]. Whether for software development, data analysis, or educational purposes, our tool provides the efficiency and convenience you need. Explore Teasoft's JSON Formatter capabilities on our website today. #JSONformatting #Teasoft #JSONformatter #effortless #codingtools #developerlife #JSONlove #simplifycoding #JSONformat #codingmadeeasy #JSONtools #JSONsyntax #codinghacks #JSONformattingmadeeasy #TeasoftJSON

Unveiling the API Showdown: GraphQL vs. REST! 😁 Explore their unique strengths and limitations to make informed choices for your projects. Whether you prefer REST's simplicity or crave GraphQL's flexibility, we've got you covered. Let's dive into the API landscape and choose the best fit for your development journey. ✅ #apis #graphql #restapis #development #wadic

Today we are releasing Parsera API — a powerful tool that allows developers to extract data from any website with ease and scalability. Just provide a URL and a description of the data you need, and you’ll receive structured results right from the page. This launch feels like the right time to share the story behind Parsera. As a developer, I often found myself in situations where I needed to pull data from websites. Every time I needed data from a site, I had to dig through convoluted HTML and stitch together something workable. Earlier this year, I hit this wall again while trying to collect leads from multiple sites into one simple table. I was disappointed to realize that despite all the advancements in LLMs, I still had to manually code a scraper. That frustration led to the idea of Parsera. After a few weeks of experimenting, it became clear that LLMs applied to web data extraction is a fascinating challenge. Before diving deep into advanced extraction, I shared a simple yet effective version with the open-source community. It didn’t take long before people started sharing it. Seeing the people’s excitement about the solution made me realize how much this problem resonated with others. That wave of support encouraged me to continue building, leading to today’s launch of the scalable Parsera API. So, check out Parsera and stay tuned for new cool features!

Who said observability tools are just about the UI? Excited to announce some major updates for Sifflet’s technical users: We’re bringing Sifflet’s data observability capabilities directly into your everyday workflows and the tools you use the most — your CI/CD pipelines, your infrastructure-as-code setup, and even your local development environment. As part of our Sifflet Everywhere vision, we'll always strive to deliver Sifflet's observability and metadata wherever (and whenever) it’s needed — and today our focus is on three key areas: - CI workflows for GitHub & GitLab to catch issues before they reach production. - Everything-as-Code: Data-Quality-as-Code (DQaC) v2, an official Terraform provider, and expanded Sifflet APIs. - Local Development: Sifflet right within your dbt projects and a supercharged Sifflet CLI. Yes, we’re bringing Sifflet Everywhere—right into your dev tools and pipelines, with more exciting updates on the way! Check out the blog post for more details and reach out to schedule a demo. #dataobservability #dataquality #dataengineering #analyticsengineering https://lnkd.in/efC_isRW

What is this shiny new thing called TypeSpec? Today, on the blog, Chris Wood gives us a breakdown of this new open-source API description format and how it helps API-first development.

Want to build a data platform and consider Airbyte Low-code CDK or dltHub's new REST API Source toolkit to build many custom data ingestions? Check out our comparison with a practical case study: https://lnkd.in/gqQgAJqF

Often, people ask "How does Airbyte compare to dltHub?" 🤷 ✨Here✨, we discuss the strengths and weaknesses of Airbyte's Low-Code CDK vs. dltHub's REST API Source toolkit. In a practical case study, we implement a Zoom connector pulling webinar and meeting data and discuss: - features: custom authorization and error handling - implementation: Python vs. YAML vs. GUI - execution: platform vs. library What would you choose for your data platform in 2024?

While dltHub is releasing new features, Willi Müller took the time to compare the creation (and I would say also the maintenance) of an API extraction using the dlt REST API source and Airbyte low-code CDK. The post guides you through the implementation process showing how to do it and the differences step by step. If you want to use dlt to extract data from an API and there isn't an already existing verified source, this is a must read. If you are just curious about the outcome, well, it's less code, more features, and you can run it whenever you want. Which one? Oh...

Do you use Airbyte and wondering how dlt's REST API connector compares? Untitled Data Company did a comparison between the 2, check it out below. In my book, the comparison is not even necessary - do you use python? then use python. Don't use python? then be dependent on what others can do for you.

🚀 API protocols you need to know! A shoutout to Ivan Novikov for the inspiration behind this content. 👀 Check it out and don't forget to follow Muhammad Saif for more tech tips, tricks, and insights! #APIProtocols #WebDevelopment #RESTAPI #GraphQL #BackendEngineering #SoftwareDevelopment #CodingCommunity #LearnToCode #TechInsights #DeveloperJourney