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Myth: GraphQL, the query language is designed to let clients perform arbitrary queries https://lnkd.in/gPScBhDZ

Wanted to share something cool from our Data Insights team. We recently hit a roadblock with file generation in our GraphQL API, but we found a solution that really works! I’ve put together a quick article on what we struggled with and how we fixed it. If you’re into GraphQL, this could be super helpful. Check it out here: https://lnkd.in/dT_MErrF #GraphQL #API

Hidden features of FetchXml @kire_devs_hacks https://bit.ly/3S9qqzv #Dataverse #FetchXML #PowerPlatform

GraphQL is a query language and specifications for APIs that enable clients to request specific data, promoting efficiency and flexibility in data retrieval. In this article, you will know: -What GraphQL is -The problem GraphQL solves -The difference in using HTTP methods in REST API vrs query and mutation in GraphQL API to fetch and manipulate data. -How to define the shape of the data to query using Schema - How to query and mutate data on a GraphQL server using ApolloSandbox https://lnkd.in/dVZezz9J GraphQL Foundation Apollo GraphQL.

finally made the web scraper capable of scraping data from multiple URL's, challenge here is mainly I'm returning URL's in batches and want each batch to get scraped separately to not run into memory issues. I'm able to scrape in batches of URL, in this demo I've reduced my features/columns for better visibility. The URL's per batch get scraped sequentially and not all links have same schema internally . the next and final challenge is to make the operation of scraping per batch of URL's Async significantly reducing the time this takes , if not its very hard to scrape a 1000 links with bs4 which is my goal, the beauty of this code is each time I run it URL's returned are different hence each time I run into some errors lol Again tagging those who inspire me to be better and post regularly on LinkedIn Sunny Savita Boktiar Ahmed Bappy Krish Naik sudhanshu kumar #webscraping #data #datascience #dataengineering #deeplearning

📡 Data extraction is an important process for organizations, as it allows them to gather data from diverse sources. This enables the transformation of raw data into actionable insights. Web scraping tools aid in efficient data extraction from websites, significantly reducing the time and effort required for manual data collection. Scraper API is a leading web scraping solution available for developers. However, Zenscrape is another web scraping solution that can be considered the best alternative to Scraper API. Let's compare Zenscrape API and Scraper API and provide the main differences between these two tools.▶️ https://bit.ly/48sgfMM - - - #API #websites #webscrapping #zenscrape #data #extraction #techtrends

Drizly Data Scraping https://lnkd.in/gu4RHy6M 📧 Email us: [email protected] Get accurate, timely data with Drizly data scraping by WebScrapingExpert.com. Our advanced techniques ensure comprehensive extraction of prices, product details, and availability. Gain competitive insights efficiently. Trust our expertise for seamless, reliable web scraping solutions tailored to your needs. #Drizly #DrizlyScraping #DrizlyDataScraping #DrizlyWebScraping #DrizlyWineScraping #DrizlyWinePriceScraping #DrizlyDataScraping #DrizlyScraper #DrizlyDataScraper #DrizlyExtraction #DrizlyDataExtraction

Elastic’s newest query language deserves closer attention. A “new foundational technology" says #CPO Ken Exner of the company's new ES|QL, a unified query language and engine for #logs, #metrics, #traces etc. "We wanted to create something that could also work on #unstructureddata ,like logs; to be able to pull different datasets, do aggregations on them, create new fields on the fly, be able to do maths operations, do a bunch of different capabilities across disparate datasets at blazing fast speed..." Read the full interview, delivered in partnership with #Elastic 👉 https://lnkd.in/e-UfPMpJ

🚀 Drowning in data? Tangled in templates? 🚀 The Ultimate Showdown : JSON, Jinja and YAML Are you confused about the differences between JSON, Jinja, and YAML? Do you struggle to choose the right tool for your data templating needs? In the below article, we'll break down the unique strengths and weaknesses of each technology, so you can make informed decisions about when to use them. Link : https://lnkd.in/dpKs7z58

FetchXML has quietly been updated over the years with some great new features. Being able to compare multiple values across tables is a huge win for doing any kind of efficient querying.