Showing 41-60 of 1,604,815 packages
client for the SlideRule on-demand science data processing service
Triggered after the completion of a request initiated through an action button or API, such as after adding, updating, deleting data, or "submit to workflow". Suitable for data processing, sending notifications, etc., after actions are completed.
Zero-dependency machine learning, AI, and data processing library for modern JavaScript
Clubs Data Processing Framework
In-Process, In-Memory & File-Based Relational Data Processing with SQLite, BetterSQLite3
Distributed calculation / data processing system. Run computation/jobs on 1000+ cores
dataPipe is a data processing and data analytics library for JavaScript. Inspired by LINQ (C#) and Pandas (Python)
RobinPath - A lightweight, fast, and easy-to-use scripting language for automation and data processing.
Collection of data processing tools and experiments. Designed for use with aurelia/node.js
Universal text normalization utilities for NLP, search, and data processing
A lightweight streaming operations library for JS that provides a flexible pipeline-based approach to data processing. StreamOps leverages generators and async generators to create efficient data processing pipelines with built-in support for parallel pro
An interactive front-end toolkit simplifying JSON, YAML, TOML, and XML data. Visualize, edit, convert formats, and perform real-time data manipulations. Empower your data-driven apps with user-friendly data processing and interactive visualization.
Backing data processing types for compcon - total rewrite of existing code from the official project
Node graph editor framework focused on data processing using Unity UIElements and C# 4.7
a data stream for async data processing
Simple data processing with decorators
the complete solution for node.js command-line programs
A simple multi-core task scheduler that works well with promises. Great for doing parallel data processing.
JSON data processing in flow
Data Pipelines help Data Engineers develop, deploy, run, and manage data processing workloads (called 'Data Job')