Awesome GitHub RepositoriesSQL Formatters

Chat2DB is an AI-powered SQL client and multi-database management GUI. It serves as a centralized graphical interface for administering diverse relational and non-relational database engines, integrating large language models to transform natural language prompts into executable SQL statements and application code. The tool utilizes schema-aware prompt engineering to inject database metadata into AI requests, ensuring generated queries match the actual schema. It also functions as an AI data reporting tool, using artificial intelligence to create dashboards and visual reports directly from da

This project is a comprehensive, curated directory of static analysis, linting, and security scanning utilities. It serves as a central resource for developers to discover, compare, and select tools based on specific programming languages, licensing models, and integration requirements. The directory distinguishes itself by providing deep metadata for each listed utility, including community-driven popularity rankings, maintenance status, and deployment methods. By aggregating these tools into a single searchable index, it enables teams to identify solutions for enforcing coding standards, ma

SQLFluff is a multi-dialect SQL linter, formatter, and style guide enforcer. It functions as a parser and analyzer that converts SQL scripts into structured trees to validate syntax, identify logical components, and enforce consistent capitalization, aliasing, and layout conventions across various database dialects. The system is specifically designed to handle templated SQL, providing the ability to analyze, parse, and lint files containing macros or placeholders. It uses dummy-parameter rendering and source mapping to validate the style and correctness of dynamic code before it is rendered

Azure Data Studio is a cross-platform SQL database management IDE used for writing queries, managing schemas, and administering relational databases. It functions as a comprehensive environment for relational database management, providing a structured interface for executing SQL queries and browsing database objects. The platform is distinguished by its interactive data notebooks, which combine executable code cells, narrative text, and visualizations for data analysis. It also includes specialized tools for database migration, allowing users to assess and transfer schemas and data from on-p

Spotless est un orchestrateur de formatage multi-langage et un plugin Gradle qui automatise le style de code sur divers langages de programmation au sein d'un pipeline de build unique. Il fonctionne comme un coordinateur pour plusieurs formateurs tiers, un outil de linting de style de code et un système pour insérer et mettre à jour des en-têtes de licence standardisés. Le projet se distingue par une application du style intégrée à git, utilisant des hooks de pré-push et des références git pour appliquer le formatage uniquement aux fichiers ou lignes modifiés. Il prend en charge des configurations de build partagées, permettant aux règles de formatage d'être distribuées et chargées sur plusieurs projets via des artefacts distants pour maintenir une source unique de vérité. L'outil couvre un large éventail de capacités, notamment la transformation de texte de code source via des expressions régulières et des patchs JSON, la gestion des imports et la standardisation des espaces blancs. Il s'intègre avec un large éventail de binaires et d'outils externes pour des langages tels que Java, Python, Kotlin, C++, Go et TypeScript. Une fonctionnalité supplémentaire inclut la vérification du formatage pour assurer l'idempotence et l'optimisation incrémentale pour ignorer les fichiers inchangés.

This project is a Language Server Protocol implementation for PostgreSQL that provides autocompletion, syntax diagnostics, and type checking for SQL and PL/pgSQL. It functions as a database schema validator and a static analysis engine designed to detect security vulnerabilities, performance bottlenecks, and dangerous migration patterns in database scripts. The server differentiates itself by using live database connections to provide schema-aware intelligence, allowing it to verify that tables, columns, and data types actually exist. It performs static analysis on procedural functions to det