paularmstrong/normalizrArchived

Gron is a command line utility that transforms nested JSON data into a flat list of path-value assignments. This process converts hierarchical structures into line-based statements, mapping every leaf value to its absolute path to make the data compatible with standard text-processing tools. The tool allows for the bidirectional transformation of data, enabling the reconstruction of original nested JSON objects from flattened path assignments. It can ingest JSON from local files, standard input, or remote URLs, with the ability to route network traffic through proxy servers. The utility supp

dlt is a Python data ingestion tool and ETL pipeline framework designed to fetch data from diverse sources and persist it into structured destinations. It functions as a schema inference engine that automatically detects data types and flattens nested JSON structures into relational tables, moving data from sources to lakehouses, warehouses, or vector databases. The project distinguishes itself through AI-powered pipeline generation, using large language models to scaffold extraction code and connectors for REST APIs. It also supports multimodal vector storage and specialized population of ve

CloudQuery is a cloud infrastructure ETL tool and multi-cloud data pipeline designed to collect, synchronize, and normalize resource metadata from various cloud providers and SaaS platforms. It functions as a centralized asset inventory manager and security posture manager, extracting configuration and state data into relational databases, data lakes, or data warehouses. The system distinguishes itself by transforming complex, nested cloud API responses into flat relational tables, enabling the use of standard SQL for asset querying and analysis. It employs a modular plugin system for data ex

This project is a comprehensive educational resource and fullstack tutorial for GraphQL development. It provides instructional content and guides focused on designing schemas, implementing servers, and managing the end-to-end workflow of building production-ready applications. The material covers the conceptual differences between graph-based data structures and traditional API architectures. It includes a dedicated security course and guides for client integration, teaching users how to fetch data, manage application state, and apply protection measures to secure API endpoints. The scope of