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22 repositorios

Awesome GitHub RepositoriesStructured Data Records

Syntax and structures for representing key-value data objects.

Distinguishing note: Focuses on shell-native data representation rather than general database records.

Explore 22 awesome GitHub repositories matching data & databases · Structured Data Records. Refine with filters or upvote what's useful.

Awesome Structured Data Records GitHub Repositories

Encuentra los mejores repositorios con IA.Buscaremos los repositorios que mejor coincidan usando IA.
  • nushell/nushellAvatar de nushell

    nushell/nushell

    39,743Ver en GitHub↗

    Nushell is a cross-platform shell and programming language designed to treat all input and output as structured data rather than raw text streams. By enforcing data types and command signatures, it provides a consistent environment for building robust, pipeline-oriented workflows. The shell allows users to chain commands that pass structured objects between stages, enabling complex data processing and automation tasks that remain predictable across different operating systems. What distinguishes the project is its focus on interactive data exploration and modular extensibility. Users can quer

    Provides syntax for creating structured key-value data objects.

    Rustnushellrustshell
    Ver en GitHub↗39,743
  • redis/go-redisAvatar de redis

    redis/go-redis

    22,159Ver en GitHub↗

    This project is a feature-rich Go client library designed for interacting with Redis. It serves as a comprehensive interface for managing remote data stores, enabling developers to execute standard database commands, handle complex data structures, and perform asynchronous operations within Go applications. The library distinguishes itself through its support for advanced Redis capabilities, including connection pooling, pipelining, and transactional integrity. It provides specialized primitives for managing distributed clusters, including automated topology updates and request routing to sha

    Organizes data into collections of field-value pairs or hierarchical JSON objects for flexible, schema-like storage.

    Gogogolangredis
    Ver en GitHub↗22,159
  • toml-lang/tomlAvatar de toml-lang

    toml-lang/toml

    20,525Ver en GitHub↗

    TOML is a configuration file format designed for human readability and unambiguous mapping to hash tables. It serves as a standardized language for structured data, enabling consistent parsing and data exchange across diverse programming environments. The format distinguishes itself through a strict type-system specification that ensures data is interpreted identically regardless of the implementation. It utilizes a line-oriented lexical structure that supports both hierarchical organization through bracketed sections and compact inline embedding for nested objects. This approach allows for t

    Defines a hierarchical syntax for structured configuration data that maps directly to hash tables and arrays.

    Ver en GitHub↗20,525
  • camel-ai/camelAvatar de camel-ai

    camel-ai/camel

    17,253Ver en GitHub↗

    This project is a comprehensive framework for building and managing autonomous agent systems. It provides a unified architecture for orchestrating multi-agent societies, where specialized agents collaborate through roleplay to decompose and solve complex tasks. The system integrates language models with external environments, enabling agents to perform real-world actions through a standardized tool-calling abstraction layer. The framework distinguishes itself through its focus on iterative reasoning and data reliability. It employs automated feedback loops to refine agent outputs and self-eva

    Organizes information into standardized records containing questions, answers, and reasoning to support agent training.

    Pythonagentai-societiesartificial-intelligence
    Ver en GitHub↗17,253
  • fluent/fluentdAvatar de fluent

    fluent/fluentd

    13,554Ver en GitHub↗

    Fluentd is a unified logging layer and distributed event router that collects, parses, and routes log data from diverse sources to various storage backends. It functions as a log forwarding agent and pipeline orchestrator, transforming raw unstructured log strings into formatted objects using structured log parsing. The project utilizes a plugin-based pipeline architecture to route data through independent input, filter, and output stages. It differentiates itself through tag-based event routing, which uses regular expression patterns to direct specific data streams to their intended destinat

    Modifies event content by parsing fields, filtering records via grep, or changing record structures.

    Ruby
    Ver en GitHub↗13,554
  • vibrantlabsai/ragasAvatar de vibrantlabsai

    vibrantlabsai/ragas

    12,659Ver en GitHub↗

    Ragas is an evaluation framework designed to measure the performance of retrieval-augmented generation pipelines and autonomous agent workflows. It provides a comprehensive suite of tools for benchmarking system outputs, utilizing language models as automated judges to score performance against defined rubrics and reference data. By standardizing inputs, retrieved contexts, and generated responses into a unified schema, the project enables consistent analysis across complex AI applications. The framework distinguishes itself through its ability to generate synthetic test datasets from existin

    Structures input data and expected outcomes for question answering and agent conversations to enable automated testing.

    Pythonevaluationllmllmops
    Ver en GitHub↗12,659
  • gcanti/fp-tsAvatar de gcanti

    gcanti/fp-ts

    11,523Ver en GitHub↗

    fp-ts is a TypeScript library that brings pure functional programming patterns to the language through algebraic data types, type class abstractions, and composable combinators. It provides foundational data types like Option for optional values, Either for typed error handling, and Task for lazy asynchronous computations, all designed to make invalid states unrepresentable and side effects explicit. The library is built on category theory concepts, offering type classes such as Functor, Applicative, Monad, Semigroup, and Monoid with lawful instances for common data structures. The library di

    Ships computed field additions for incremental record construction within functorial contexts.

    TypeScriptalgebraic-data-typesfunctional-programmingtypescript
    Ver en GitHub↗11,523
  • apple/pklAvatar de apple

    apple/pkl

    11,429Ver en GitHub↗

    Pkl is a configuration-as-code language used to define, validate, and generate structured configuration files. It functions as a type-safe configuration generator that enforces data integrity through a strongly-typed schema, ensuring configuration values meet defined constraints and types during evaluation. The project distinguishes itself by acting as both a configuration file generator and a binding generator. It transforms high-level programmable definitions into static formats such as JSON, YAML, or XML, and produces language-specific source code to synchronize settings and provide type s

    Provides a programmable syntax for defining hierarchical settings and parameters with built-in logic and variables.

    Javaconfigconfigurationdata
    Ver en GitHub↗11,429
  • emdash-cms/emdashAvatar de emdash-cms

    emdash-cms/emdash

    10,887Ver en GitHub↗

    EmDash is an open-source content management system built on Astro that combines a visual admin panel with a plugin-driven architecture and server-side rendering. It provides a complete content management system with structured content modeling, a rich text editor using Portable Text format, and a TypeScript API for type-safe content queries. The system supports authentication through passkeys, OAuth 2.1, and external providers, with role-based access control and fine-grained permission scopes. What distinguishes EmDash is its plugin development framework, which supports both native plugins ru

    Adds new fields to content collection schemas with type, constraints, validation, and translatability settings.

    TypeScriptastrocmsemdash
    Ver en GitHub↗10,887
  • wandb/wandbAvatar de wandb

    wandb/wandb

    10,844Ver en GitHub↗

    Wandb is a centralized platform for machine learning experiment tracking, model registry management, and workflow orchestration. It provides a comprehensive suite of tools for logging, visualizing, and versioning training metrics, model artifacts, and hyperparameter sweeps to ensure reproducibility across development cycles. The platform also functions as an observability tool for large language model applications, enabling the tracing of execution steps, token usage, and reasoning processes. The project distinguishes itself through its event-driven automation capabilities, which allow users

    Records tabular data and metrics during training runs to serve as sources for custom analysis panels.

    Pythonaicollaborationdata-science
    Ver en GitHub↗10,844
  • apify/crawlee-pythonAvatar de apify

    apify/crawlee-python

    8,097Ver en GitHub↗

    Crawlee-python is a web crawling framework for building scalable scrapers using Python. It serves as a comprehensive tool for web scraping automation, providing a system to extract structured data from websites using both lightweight HTTP requests and headless browser automation. The framework is distinguished by its anti-bot evasion capabilities, which include browser fingerprint impersonation and tiered proxy rotation to bypass detection systems and solve challenges such as Cloudflare. It also incorporates artificial intelligence for autonomous website navigation and schema-based data extra

    Processes raw scraped data through user-defined functions to clean, format, or restructure record content.

    Pythonapifyautomationbeautifulsoup
    Ver en GitHub↗8,097
  • norvig/paip-lispAvatar de norvig

    norvig/paip-lisp

    7,465Ver en GitHub↗

    This project is a comprehensive Lisp AI implementation library that provides reference implementations for various artificial intelligence paradigms and symbolic algorithms. It functions as a multi-purpose toolkit containing a logic programming engine, a natural language processing suite, and a symbolic mathematics toolkit. The library is distinguished by its diverse architectural frameworks, including a Prolog-style execution engine that uses unification and goal-driven backtracking, and a system for simulating human decision-making through expert system shells and certainty factors. It also

    Defines structure types with named slots and automatically generates corresponding constructor and accessor functions.

    Common Lisp
    Ver en GitHub↗7,465
  • deepstreamio/deepstream.ioAvatar de deepstreamIO

    deepstreamIO/deepstream.io

    7,183Ver en GitHub↗

    deepstream.io is an open-source realtime server that synchronizes JSON records, events, and remote procedure calls across clients and backend services. It functions as a realtime data sync server, event pub/sub server, record database server, and RPC server, all within a single platform. The server authenticates and authorizes every message using multiple strategies including JWT, HTTP, and file-based credentials, with a declarative permission language controlling access to records, events, and RPCs at a granular level. The platform distinguishes itself through its combination of realtime dat

    Sets, gets, and subscribes to changes on full records or specific nested JSON paths.

    TypeScriptauthenticationdatasyncdeepstream
    Ver en GitHub↗7,183
  • tokio-rs/tracingAvatar de tokio-rs

    tokio-rs/tracing

    6,750Ver en GitHub↗

    This project is a structured tracing framework for Rust that serves as an async-aware instrumentation library and telemetry data collector. It provides a structured logging facade and the tools necessary to record, filter, and route event-based diagnostic data from both standard applications and embedded systems. The framework distinguishes itself through a core implementation that supports bare-metal and no-standard-library environments without requiring a dynamic memory allocator. It specifically handles the complexities of asynchronous workflows by propagating diagnostic contexts across fu

    Writes several structured data points to an active span in one operation using pre-declared fields.

    Rustdiagnosticslogginglogging-and-metrics
    Ver en GitHub↗6,750
  • unisonweb/unisonAvatar de unisonweb

    unisonweb/unison

    6,487Ver en GitHub↗

    Provides immutable field modification by applying functions to record fields.

    Haskellhacktoberfesthaskellprogramming-language
    Ver en GitHub↗6,487
  • apache/pinotAvatar de apache

    apache/pinot

    6,098Ver en GitHub↗

    Pinot is a distributed, columnar analytical database designed for high-concurrency, low-latency query processing. It functions as a real-time OLAP datastore, enabling interactive, user-facing analytics by ingesting and querying massive datasets from both streaming and batch sources. The system architecture relies on a centralized controller for cluster coordination and a distributed segment-based storage model to ensure horizontal scalability. The platform distinguishes itself through a hybrid ingestion pipeline that unifies real-time event streams and historical batch data into a single quer

    Applies transformation functions to records after upsert merges to ensure data consistency.

    Java
    Ver en GitHub↗6,098
  • dhall-lang/dhall-langAvatar de dhall-lang

    dhall-lang/dhall-lang

    4,458Ver en GitHub↗

    Dhall es un lenguaje de configuración con tipado fuerte diseñado para crear archivos de configuración programables que garantizan su terminación. Es un lenguaje no completo según Turing que utiliza un sistema de tipos estricto para asegurar la corrección y prevenir bucles infinitos durante la evaluación. El proyecto funciona como un motor de configuración determinista y herramienta de marshalling, convirtiendo expresiones programables en formatos estáticos como JSON, YAML y Bash. Se distingue por su enfoque en la seguridad e integridad, utilizando hashing semántico para fijar importaciones remotas y aplicando políticas de origen para prevenir la exfiltración de datos. Sus capacidades cubren una amplia superficie de gestión de configuración, incluyendo el uso de funciones polimórficas, tipos de unión y completado de registros para reducir la redundancia. Proporciona herramientas para la validación de esquemas, resolución de expresiones remotas y una implementación del Language Server Protocol para la integración con editores. El lenguaje proporciona una interfaz de línea de comandos y un REPL para evaluar expresiones y verificar la igualdad.

    Integrates the type-safe configuration language directly into other applications for internal data definition.

    Dhallconfiguration-languagedhall
    Ver en GitHub↗4,458
  • rails/jbuilderAvatar de rails

    rails/jbuilder

    4,414Ver en GitHub↗

    Jbuilder es un motor de plantillas y constructor de JSON para Ruby que proporciona un lenguaje de dominio específico (DSL) para generar objetos JSON estructurados. Sirve como un helper de vista para transformar datos a formato JSON utilizando lógica, condicionales y bucles. El proyecto permite la construcción de estructuras de datos complejas mediante el uso de parciales y objetos anidados para mantener la modularidad. Incluye capacidades para la transformación de claves en tiempo de ejecución, permitiendo convertir las claves de atributos entre diferentes convenciones de nomenclatura como snake case y camel case. El sistema admite la estructuración dinámica de JSON con la capacidad de definir claves en tiempo de ejecución y gestionar la salida de valores nulos. También proporciona un mecanismo para cachear fragmentos de JSON renderizados para reducir el procesamiento repetitivo.

    Supports assigning attribute names and structure keys at runtime using variables instead of static symbols.

    Ruby
    Ver en GitHub↗4,414
  • balancap/ssd-tensorflowAvatar de balancap

    balancap/SSD-Tensorflow

    4,103Ver en GitHub↗

    Este proyecto es un framework de detección de objetos de TensorFlow diseñado para entrenar y desplegar modelos Single Shot MultiBox Detector (SSD). Proporciona un toolkit de entrenamiento de redes neuronales para implementar la arquitectura SSD para lograr la localización de objetos en imágenes y videos en tiempo real. El framework incluye un pipeline de datos dedicado para transformar datasets de detección de objetos en formatos de registro binario para aumentar la velocidad y el rendimiento del entrenamiento. También cuenta con utilidades para convertir pesos de modelos entre diferentes formatos de checkpoint para facilitar la reutilización de redes preentrenadas. El sistema cubre una amplia gama de capacidades, incluyendo ajuste fino de modelos en datasets personalizados, entrenamiento de detección de objetos y evaluación de precisión a través de la medición de métricas de precisión y recall.

    Provides a dedicated pipeline for transforming object detection datasets into binary record formats for faster training.

    Jupyter Notebookdeep-learningobject-detectionssd
    Ver en GitHub↗4,103
  • brightmart/albert_zhAvatar de brightmart

    brightmart/albert_zh

    3,982Ver en GitHub↗

    This project is an implementation of the ALBERT language model architecture, providing a framework for training and evaluating transformer-based text classifiers and similarity models. It specifically includes pre-trained assets and tools optimized for generating semantic embeddings and representations of Chinese text. The framework distinguishes itself through tools for converting heavy language model checkpoints into lightweight formats to enable low-latency inference on mobile devices. It utilizes specific weight reduction techniques, including cross-parameter sharing and factorized embedd

    Ships utilities to transform raw text files into optimized binary record formats for efficient training.

    Pythonalbertbertchinese-corpus
    Ver en GitHub↗3,982
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Explorar subetiquetas

  • Batch Field RecordingCapabilities for writing multiple structured data points to a diagnostic span in a single operation. **Distinct from Structured Data Records:** Focuses on the atomic recording of multiple fields in a telemetry span, not general data record syntax.
  • Configuration Languages1 sub-etiquetaSyntax specifications for defining hierarchical settings and parameters in plain text files. **Distinct from Structured Data Records:** Distinct from Structured Data Records: focuses on human-authored configuration files rather than general-purpose data records.
  • Dataset Record StructuresStandardized record formats for organizing questions, answers, and reasoning metadata. **Distinct from Structured Data Records:** Focuses on dataset-specific record organization, distinct from general key-value data objects.
  • Dynamic Record Generators2 sub-etiquetasTools that generate constructors and accessors for custom structure types with named slots. **Distinct from Structured Data Records:** Focuses on the generation of API functions for records rather than just the data representation.
  • Nested Path Reads and WritesSets, gets, and subscribes to changes on a full record or a specific nested path within its JSON structure. **Distinct from Structured Data Records:** Distinct from Structured Data Records: focuses on reading and writing specific nested paths within JSON structures, not just key-value data objects.
  • Record Transformers4 sub-etiquetasUtilities for modifying the internal structure or content of data records. **Distinct from Structured Data Records:** Distinct from structured records themselves, this focuses on the active modification and filtering of the records.