@pnp/queryable
Advanced tools
The SharePoint Patterns and Practices client side libraries were created to help enable developers to do their best work, without worrying about the exact REST api details. Built with feedback from the community they represent a way to simplify your day-to-day dev cycle while relying on tested and proven patterns.
Please use http://aka.ms/community/home for the latest updates around the whole Microsoft 365 and Power Platform Community(PnP) initiative.
This code is managed within the main pnp repo, please report issues and submit pull requests there.
Please see the public site for package documentation.
This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.
THIS CODE IS PROVIDED AS IS WITHOUT WARRANTY OF ANY KIND, EITHER EXPRESS OR IMPLIED, INCLUDING ANY IMPLIED WARRANTIES OF FITNESS FOR A PARTICULAR PURPOSE, MERCHANTABILITY, OR NON-INFRINGEMENT.
FAQs
pnp - provides shared odata functionality and base classes
The npm package @pnp/queryable receives a total of 17,225 weekly downloads. As such, @pnp/queryable popularity was classified as popular.
We found that @pnp/queryable demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 10 open source maintainers collaborating on the project.
Did you know?
Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.
Research
The Socket Threat Research Team uncovered malicious NuGet packages typosquatting the popular Nethereum project to steal wallet keys.
Product
A single platform for static analysis, secrets detection, container scanning, and CVE checks—built on trusted open source tools, ready to run out of the box.
Product
Socket is launching experimental protection for the Hugging Face ecosystem, scanning for malware and malicious payload injections inside model files to prevent silent AI supply chain attacks.
