53 dépôts
Extensions for defining specialized data formats and types within database schemas and ORM layers.
Distinguishing note: Focuses on schema-level type extensions rather than generic database management or query building.
Explore 53 awesome GitHub repositories matching data & databases · Custom Data Types. Refine with filters or upvote what's useful.
v2ray-core is a network proxy framework and custom proxy engine designed for censorship circumvention. It functions as a traffic routing platform that directs network data between inbound and outbound connections to access blocked content and services. The system employs a modular architecture using pluggable protocol handlers and a chain-based connection pipeline to transform and forward network traffic. It provides secure tunneling infrastructure to establish encrypted connections and uses a rule-based routing system to direct data between protocols and destinations. The framework includes
Maps internal runtime data structures to serialized configuration formats for system initialization.
Sequelize is an object-relational mapping library that provides a unified interface for managing relational data through code. By implementing the Active Record pattern, it maps database tables to application objects, allowing developers to perform standard create, read, update, and delete operations using high-level method calls. The library abstracts complex database interactions by translating these calls into optimized, engine-specific SQL statements, ensuring consistent behavior across different database systems. The project distinguishes itself through a comprehensive suite of tools for
Sequelize enables defining specialized data formats by extending base functionality when standard options do not meet specific database requirements.
PostgreSQL is an object-relational database management system designed for the persistent storage and retrieval of structured information. It functions as an ACID-compliant database server, utilizing standard query language protocols to maintain data consistency and reliability across large-scale application datasets. The system distinguishes itself through an extensible architecture that allows for the definition of custom data types, operators, and indexing methods. It employs multi-version concurrency control to enable simultaneous read and write operations without blocking, supported by a
Allows definition of custom data types, operators, and indexing methods to support specialized data structures.
Faker is a Python library designed to generate realistic synthetic data for software testing, database prototyping, and privacy-preserving anonymization. It provides a comprehensive suite of tools to create diverse information types, including personal identities, financial records, geographic locations, and technical system metadata, allowing developers to populate environments with mock data that mimics real-world structures. The library is built on a modular provider architecture that supports dynamic method dispatch, enabling users to extend functionality by registering custom data genera
Enables the addition of custom data types or specialized formats by defining new providers.
Blender is a professional 3D creation suite designed for modeling, animation, rendering, and video editing. It functions as an open-source 3D engine that provides a comprehensive framework for procedural geometry, physics simulation, and high-quality visual output. The platform is built upon a foundational architecture that utilizes data-block-based memory management and a dependency-graph-based evaluation system to handle complex scene transformations and geometry updates. The software distinguishes itself through a highly modular, node-based procedural architecture that allows users to cons
Blender defines new datablock types through a standardized interface of callbacks to replace centralized switch statements and hardcoded logic.
Nim is a statically typed, compiled systems programming language designed for high performance and cross-platform development. It translates high-level source code into C, C++, or JavaScript, allowing developers to produce efficient native binaries or web-compatible scripts from a single codebase. The language emphasizes a clean, indentation-based syntax that simplifies code hierarchy while maintaining the power of a full-featured systems language. What distinguishes Nim is its robust metaprogramming framework, which allows developers to inspect, modify, and generate code structures during th
Enables defining custom data types using objects, tuples, and enumerations for type-safe modeling.
This project provides a comprehensive implementation of the AT Protocol, serving as a framework for building decentralized social networking applications. It enables the creation of distributed data repositories where users maintain cryptographic ownership of their identity and content, allowing for portable accounts that can be migrated between independent servers without central authority intervention. The platform distinguishes itself by decoupling content hosting from discovery through modular algorithmic curation. Users can select third-party services to filter and organize their feeds,
Defines and transmits specialized message formats to share unique content types across the network.
pybind11 is a header-only C++ binding library that exposes C++ functions and classes as Python modules. It serves as a language bridge, mapping native types, inheritance hierarchies, and lambda functions into compatible Python objects to enable high-performance native code execution. The library includes specialized integration for NumPy arrays, utilizing buffer protocols to bind native C++ data without copying memory. It provides a toolkit for mapping C++ standard library data structures and smart pointers into the Python environment while maintaining cross-language memory management. The p
Implements mappings that transform specialized C++ data structures into portable formats for efficient storage.
Presto is a distributed SQL query engine designed for high-performance analytical processing across heterogeneous data sources. It functions as a data federation platform and massively parallel processing engine, allowing users to execute interactive queries against diverse storage systems without requiring data migration. By mapping remote metadata and structures to a unified relational namespace, it enables seamless cross-platform analysis through a standard SQL interface. The engine distinguishes itself through a pluggable connector architecture and a shared-nothing distributed processing
Implements new data types to support specialized data structures or formats not natively provided by the core engine.
Grav is a flat-file content management system that eliminates the need for a traditional database by storing site content and configuration in human-readable Markdown and YAML files. Built as a modular PHP web framework, it uses a hierarchical page routing system where the physical directory structure directly determines the site's URL paths. The platform is distinguished by its event-driven plugin architecture and a command-line interface that prioritizes system administration, deployment, and maintenance tasks. It utilizes a blueprint-driven system to generate administrative forms from stru
Enables the definition of structured data objects for flexible content management.
JupyterLab is a web-based development environment designed for interactive data science, collaborative research, and computational notebook authoring. It provides a unified workspace where users can execute code, manage computational kernels, and create documents that integrate live code, rich data visualizations, and narrative text. The platform is built on a modular architecture that supports extensive customization through a plugin system. This framework allows for the dynamic loading of extensions, enabling users to define custom file viewers, interface themes, and keyboard shortcuts. By
Registers custom file formats and associated viewers to allow interaction with specialized data files.
Gel is an object-relational database system that models data as a graph of interconnected objects. By utilizing a strongly typed schema, it enables complex relational queries and polymorphic data structures without the need for traditional join tables. The system integrates native vector storage and similarity search operators, allowing it to function as both a relational and a vector database for semantic data retrieval. The platform distinguishes itself through a comprehensive suite of developer-centric automation tools. It features a declarative migration system that tracks and versions sc
Creates custom data types by adding constraints or annotations to existing scalars to enforce specific business logic or validation.
This project is a curated collection of programming exercises designed to build proficiency in numerical computing and data manipulation. It provides a structured learning path for mastering multidimensional array operations, vectorized arithmetic, and statistical analysis. The repository focuses on developing practical expertise in array-based workflows, emphasizing techniques such as memory management, efficient data processing, and the replacement of explicit loops with vectorized operations. Users engage with hands-on challenges that cover the full lifecycle of numerical data, from initia
Constructs structured arrays with user-defined fields to represent complex data records.
Dask est un framework de calcul parallèle et un planificateur de tâches distribué conçu pour mettre à l'échelle les flux de travail de science des données Python, des machines uniques aux grands clusters. Il fonctionne comme un gestionnaire de ressources de cluster qui orchestre la logique computationnelle en représentant les tâches et leurs dépendances sous forme de graphes acycliques dirigés. Cette architecture permet au système d'automatiser la distribution des charges de travail sur le matériel disponible tout en gérant des exigences d'exécution complexes. Le projet se distingue par un moteur d'évaluation paresseuse qui diffère les opérations sur les données jusqu'à ce qu'elles soient explicitement demandées, permettant une optimisation globale du graphe et une allocation efficace des ressources. Il intègre le déversement de données conscient de la mémoire pour éviter les plantages du système lors du traitement de jeux de données dépassant la mémoire disponible, et il utilise la fusion de graphes de tâches pour combiner des séquences d'opérations en étapes d'exécution uniques, minimisant la surcharge de planification et la communication entre nœuds. La plateforme fournit une surface de capacités complète pour l'analyse de données à grande échelle, incluant le support pour l'apprentissage automatique distribué, l'intégration du calcul haute performance et le traitement de données parallèle. Elle offre des outils étendus pour la gestion du cycle de vie des clusters, le profilage des performances et la surveillance en temps réel de l'exécution des tâches. Les utilisateurs peuvent déployer ces environnements sur diverses infrastructures, incluant le matériel local, les fournisseurs cloud, les systèmes conteneurisés et les clusters de calcul haute performance.
Integrates third-party data types into parallel workflows by registering them so the system can correctly track metadata and handle operations.
SQLAlchemy is a comprehensive Python SQL toolkit and object-relational mapper that provides a full suite of tools for interacting with relational databases. It serves as a foundational layer for database connectivity, offering both a high-level object-oriented interface for data persistence and a programmatic SQL expression language for constructing complex, dialect-agnostic queries. The project distinguishes itself through its sophisticated unit of work persistence, which coordinates atomic transactions and tracks object state changes to minimize redundant database operations. It provides a
Extends the type system by creating user-defined types to handle specialized data serialization, validation, or database-specific operator logic.
This project is a framework for the efficient serialization and deserialization of data structures. It provides a unified, macro-based interface that automates the conversion of complex internal objects into standardized formats and reconstructs them from raw input streams or buffers. By leveraging compile-time code generation, the library minimizes manual implementation overhead while ensuring consistent logic across diverse data types. The framework distinguishes itself through a format-agnostic data model and a visitor-based parsing architecture that decouples data structures from specific
Maps internal data structures to specific output representations through custom method implementations.
Doctrine ORM is a PHP object-relational mapper that connects application objects to relational database tables. It uses the data mapper and identity map patterns to decouple the in-memory object model from the database schema, allowing developers to manage data persistence without writing manual SQL. The project features a dedicated object-oriented query language and programmatic builder for retrieving data based on entities rather than tables. It implements a unit-of-work system to track object changes during a request and synchronize them via atomic transactions. The capability surface inc
Provides a system for defining and using custom data types to map non-standard database columns to objects.
go-swagger is a toolkit for working with Swagger/OpenAPI 2.0 specifications in Go. It generates server, client, and CLI code from a specification document, and can also produce a specification by scanning annotated Go source code. The project includes a static validation engine that checks documents against the schema and project-specific rules, and a specification transformation pipeline that resolves, flattens, and merges documents. The toolkit generates both client and server code from the same specification, ensuring consistency in request and response handling. It also produces a command
Allows overriding default templates and injecting vendor extensions to customize generated code.
This project is a PostgreSQL client library and SQL query builder for JavaScript and TypeScript. It provides a low-level database driver and connection manager to handle database sessions, along with a logical replication client for monitoring real-time changes. The library distinguishes itself with a high-performance bulk data streamer that utilizes the database copy command for importing and exporting large datasets. It also implements a logical replication protocol to facilitate real-time database synchronization through change subscriptions and channel-based notifications. The toolset co
Provides a system to map database identifiers to objects using custom serialization and parsing functions.
The mongo-go-driver is a Go library for building applications that integrate with a MongoDB document store. It enables the storage and retrieval of flexible document data by providing a bridge between Go backends and the database. The driver implements specialized capabilities for semantic vector search, allowing the handling and execution of high-dimensional vector data for similarity-based retrieval. It also supports full-text search via linguistic analysis and programmatic search index management. The project covers a broad range of database operations, including document-based CRUD, bulk
Provides configuration options for mapping Go data types to BSON binary formats.