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29 repositorios

Awesome GitHub RepositoriesData Extraction

Tools and techniques for isolating and retrieving specific data points from larger, often unstructured, source datasets.

Explore 29 awesome GitHub repositories matching data & databases · Data Extraction. Refine with filters or upvote what's useful.

Awesome Data Extraction GitHub Repositories

Encuentra los mejores repositorios con IA.Buscaremos los repositorios que mejor coincidan usando IA.
  • browser-use/browser-useAvatar de browser-use

    browser-use/browser-use

    100,229Ver en GitHub↗

    Browser-use is a framework for building autonomous agents that navigate, interact with, and extract data from web interfaces using natural language instructions. By acting as an orchestration layer between large language models and browser automation protocols, it enables the execution of complex, multi-step workflows without relying on brittle selectors. The system functions as a headless browser controller, providing a programmatic interface to manage browser instances and execute granular interactions. The project distinguishes itself through its ability to translate high-level intent into

    Converts unstructured web content into clean, typed, and organized data formats through automated extraction routines.

    Pythonai-agentsai-toolsbrowser-automation
    Ver en GitHub↗100,229
  • unclecode/crawl4aiAvatar de unclecode

    unclecode/crawl4ai

    68,644Ver en GitHub↗

    Crawl4AI is an AI-powered web crawling and data extraction engine designed to transform complex web content into structured formats. It functions as a headless browser orchestrator, enabling the navigation of dynamic websites, the execution of custom scripts, and the capture of visual assets like screenshots and PDFs. By integrating language models directly into the extraction workflow, the system converts raw HTML into clean, structured data or Markdown files optimized for downstream ingestion. The platform distinguishes itself through a distributed, self-hosted infrastructure that manages l

    Converts unstructured web content into clean, organized schemas using path selectors and language model interpretation.

    Python
    Ver en GitHub↗68,644
  • scrapy/scrapyAvatar de scrapy

    scrapy/scrapy

    62,274Ver en GitHub↗

    Scrapy is a comprehensive framework designed for automated web data extraction and large-scale crawling. It operates on an asynchronous, event-driven engine that manages non-blocking network requests and data processing tasks, allowing for the efficient retrieval of structured information from web documents using path-based selectors. The system distinguishes itself through a highly modular architecture that supports complex data collection workflows. Users can implement custom middleware and signal handlers to intercept and modify request flows, while a priority-based scheduler manages concu

    Converts unstructured web content into clean, typed, and organized data formats using defined extraction logic.

    Pythoncrawlercrawlingframework
    Ver en GitHub↗62,274
  • docling-project/doclingAvatar de docling-project

    docling-project/docling

    61,674Ver en GitHub↗

    Docling is a modular framework designed for document parsing, layout analysis, and structured data extraction. It transforms unstructured files and web content into a unified, hierarchical data model that preserves the spatial and semantic relationships between text, tables, images, and layout elements. By normalizing diverse input formats into a consistent internal representation, the library enables uniform processing across various document types. The project distinguishes itself through a schema-driven approach that maps document regions to strongly-typed objects, ensuring data accuracy t

    Extracts information from unstructured sources by applying schemas to identify and organize content into clean, typed data formats.

    Pythonaiconvertdocument-parser
    Ver en GitHub↗61,674
  • soimort/you-getAvatar de soimort

    soimort/you-get

    56,839Ver en GitHub↗

    This project is a command-line utility designed to fetch video, audio, and image content from a wide range of web platforms. It functions by parsing page metadata and utilizing modular, site-specific scripts to extract direct media stream URLs from complex web structures, enabling the local archiving of digital media for offline use. The tool distinguishes itself through its ability to handle authenticated content, allowing users to inject browser-stored session cookies to access restricted or private media. It also supports real-time media streaming by piping remote content directly into ext

    Extracts raw file locations and structured metadata from web pages for integration into external workflows.

    Python
    Ver en GitHub↗56,839
  • iawia002/annieAvatar de iawia002

    iawia002/annie

    31,414Ver en GitHub↗

    Annie is a command-line video downloader and web video extraction library written in Go. It functions as a concurrent media downloader designed to fetch video files and playlists from websites via URLs. The tool distinguishes itself through a proxy-aware network layer that supports SOCKS5 and HTTP proxies to bypass regional content restrictions. It also incorporates session cookie integration and referrer spoofing to facilitate the download of authenticated or age-gated content. The project provides capabilities for bulk media acquisition, including batch downloading from text files and extr

    Extracts and prints technical resource metadata of videos in JSON format.

    Go
    Ver en GitHub↗31,414
  • swiftyjson/swiftyjsonAvatar de SwiftyJSON

    SwiftyJSON/SwiftyJSON

    22,951Ver en GitHub↗

    SwiftyJSON is a Swift JSON parsing library and data wrapper designed to simplify the reading and manipulation of JSON structures. It provides a toolkit for converting raw JSON strings into structured formats without requiring manual type casting or optional chaining for every value. The library focuses on simplifying nested data extraction through subscript-based value access and recursive data resolution. It ensures optional-safe value retrieval by returning default empty values instead of crashing when encountering missing keys or out-of-bounds array indices. The project includes capabilit

    Facilitates the extraction of specific values from complex, nested JSON hierarchies.

    Swift
    Ver en GitHub↗22,951
  • forem/foremAvatar de forem

    forem/forem

    22,726Ver en GitHub↗

    Forem is an open-source platform designed for building and managing technical communities. It functions as a social publishing engine that enables members to share long-form content, participate in threaded discussions, and engage through social interactions. The platform provides tools for organizations to maintain branded profiles, host community hackathons, and facilitate collaborative learning through structured educational tracks. Beyond its social features, Forem integrates advanced capabilities for AI agent workflow orchestration and codebase knowledge graphing. It allows developers to

    Converts web content into structured formats like markdown or JSON for agent data ingestion.

    Rubycommunitydiscussionfeedback
    Ver en GitHub↗22,726
  • vonng/ddiaAvatar de Vonng

    Vonng/ddia

    22,648Ver en GitHub↗

    This project serves as a comprehensive technical reference for the architecture and design of data-intensive applications. It provides a structured analysis of the fundamental principles required to build reliable, scalable, and maintainable software systems, covering the core trade-offs inherent in modern data infrastructure. The repository explores the mechanics of distributed data management, including strategies for replication, partitioning, and achieving consensus across multiple nodes. It details the design of storage engines, indexing techniques, and transaction management models, whi

    Automates the extraction and transformation of data from source systems into analytical warehouses.

    Pythonbookdatabaseddia
    Ver en GitHub↗22,648
  • alibaba/dataxAvatar de alibaba

    alibaba/DataX

    17,241Ver en GitHub↗

    DataX is a distributed data integration framework and plugin-based ETL tool designed for synchronizing large datasets between heterogeneous sources and destinations. It functions as a JDBC data migration engine and offline synchronization tool, enabling the movement of data between relational databases, NoSQL stores, and object storage. The system utilizes a plugin-based connector architecture that decouples reader and writer logic, allowing it to map and transform data types across different storage engines using a standardized internal representation. This design supports heterogeneous data

    Provides core tools for isolating and retrieving specific data points from relational database sources.

    Java
    Ver en GitHub↗17,241
  • idank/explainshellAvatar de idank

    idank/explainshell

    14,084Ver en GitHub↗

    ExplainShell is a shell command explainer and syntax analyzer that matches command line arguments to manual page documentation. It functions as a man page parser and documentation extraction tool, converting roff-formatted manual pages into a structured database of command options and metadata. The project uses a combination of large language models and roff-macro parsing to identify specific line ranges that define flags and arguments. It employs a command syntax analyzer to deconstruct shell commands into tokens, which are then mapped against documented entries to provide plain language exp

    Ships a utility to identify differences between newly extracted documentation data and existing records.

    Python
    Ver en GitHub↗14,084
  • devttys0/binwalkAvatar de devttys0

    devttys0/binwalk

    14,048Ver en GitHub↗

    Binwalk is a firmware analysis tool and binary data carver used to identify and extract embedded files and data segments from binary images. It functions as an embedded file extractor and data entropy analyzer to retrieve fragments from binary blobs when original file system structures are missing. The tool employs signature-based pattern matching and linear byte-stream scanning to detect known byte sequences and isolate hidden files. It uses sliding-window entropy analysis to locate regions of a file that are compressed or encrypted. The system supports recursive file carving, utilizing heu

    Retrieves specific files and data segments from binary blobs using known signatures and boundaries.

    Rust
    Ver en GitHub↗14,048
  • dask/daskAvatar de dask

    dask/dask

    13,746Ver en GitHub↗

    Dask es un framework de computación paralela y un programador de tareas distribuido diseñado para escalar flujos de trabajo de ciencia de datos en Python desde máquinas individuales hasta grandes clústeres. Funciona como un gestor de recursos de clúster que orquesta la lógica computacional representando las tareas y sus dependencias como grafos acíclicos dirigidos. Esta arquitectura permite al sistema automatizar la distribución de cargas de trabajo a través del hardware disponible mientras gestiona requisitos de ejecución complejos. El proyecto se distingue por un motor de evaluación perezosa que difiere las operaciones de datos hasta que se solicitan explícitamente, permitiendo la optimización global del grafo y una asignación eficiente de recursos. Incorpora el volcado de datos consciente de la memoria para evitar fallos del sistema al procesar conjuntos de datos que exceden la memoria disponible, y utiliza la fusión de grafos de tareas para combinar secuencias de operaciones en pasos de ejecución únicos, minimizando la sobrecarga de programación y la comunicación entre nodos. La plataforma proporciona una superficie de capacidades integral para el análisis de datos a gran escala, incluyendo soporte para aprendizaje automático distribuido, integración de computación de alto rendimiento y procesamiento de datos en paralelo. Ofrece herramientas extensas para la gestión del ciclo de vida del clúster, perfilado de rendimiento y monitoreo en tiempo real de la ejecución de tareas. Los usuarios pueden desplegar estos entornos en diversas infraestructuras, incluyendo hardware local, proveedores de nube, sistemas en contenedores y clústeres de computación de alto rendimiento.

    Provides methods to extract specific temporal units like microseconds or seconds from datetime data within distributed dataframes.

    Pythondasknumpypandas
    Ver en GitHub↗13,746
  • t8rin/imagetoolboxAvatar de T8RIN

    T8RIN/ImageToolbox

    11,746Ver en GitHub↗

    ImageToolbox is an open-source Android application designed for comprehensive image manipulation and batch processing. It provides a toolkit for performing advanced visual edits, including background removal, geometric transformations, and the application of complex filter chains to prepare image assets. The application distinguishes itself through a modular, pipeline-based architecture that allows for the integration of new processing algorithms as isolated plugins. It leverages native hardware acceleration to handle intensive pixel manipulation tasks and supports asynchronous execution to m

    Extracts data from visual files including text via OCR, color palettes, and embedded media information.

    Kotlinaiandroidbackground-removal
    Ver en GitHub↗11,746
  • mamedev/mameAvatar de mamedev

    mamedev/mame

    9,929Ver en GitHub↗

    MAME is a vintage hardware emulation platform designed to recreate the circuitry of arcade games, computers, and consoles to run original software on modern devices. It functions as a retro gaming preservation framework for managing, verifying, and archiving ROM sets and disk images to ensure long-term software accessibility. The project features a system debugging tool for inspecting emulated memory, CPU registers, and execution flow via breakpoints and disassembly. It also includes a Lua-based automation layer that exposes core system state and hardware controls for custom behavior and anal

    Decompresses data from compressed hunk (CHD) images back into original raw or disk formats.

    C++
    Ver en GitHub↗9,929
  • json-path/jsonpathAvatar de json-path

    json-path/JsonPath

    9,423Ver en GitHub↗

    JsonPath is a Java library designed for querying and manipulating JSON documents using the JsonPath expression language. It functions as a query engine for extracting and filtering specific data from JSON structures through path-based expressions. The library provides capabilities for transforming JSON documents by modifying values or mapping extracted data into Java objects. It also includes an aggregation library for calculating statistical metrics, such as sums and averages, on numeric arrays. The project handles data extraction through array filtering and numerical aggregation. Performan

    Provides a specialized domain language for querying and extracting specific data points from JSON documents.

    Java
    Ver en GitHub↗9,423
  • apache/jmeterAvatar de apache

    apache/jmeter

    9,233Ver en GitHub↗

    Apache JMeter is a Java-based performance testing tool and multi-protocol traffic simulator used to analyze the stability and scalability of servers and networks. It functions as a distributed load testing framework that coordinates remote worker nodes from a single controller to generate high volumes of concurrent traffic. The project is distinguished by its ability to simulate traffic across diverse backend systems, including HTTP, JDBC, LDAP, JMS, FTP, and TCP. It provides a headless command-line interface for automated execution and a reporting system that transforms raw sample logs into

    Parses information from structured or unstructured responses to correlate data between sequential network requests.

    Javajavaperformancetest
    Ver en GitHub↗9,233
  • dusty-nv/jetson-inferenceAvatar de dusty-nv

    dusty-nv/jetson-inference

    8,734Ver en GitHub↗

    jetson-inference is a set of libraries and tools for executing optimized deep learning models on embedded GPU hardware. Its primary purpose is to enable real-time computer vision and AI inference at the edge with low latency and high throughput. The project distinguishes itself through high-performance streaming analytics and the ability to execute concurrent AI pipelines on auto-grade silicon. It provides specialized support for multi-sensor stream processing, utilizing zero-copy data transport to load camera frames directly into GPU memory. The codebase covers a broad surface of capabiliti

    Ingests large volumes of unstructured data to extract text, graphs, charts, and tables for retrieval systems.

    C++caffecomputer-visiondeep-learning
    Ver en GitHub↗8,734
  • kean/nukeAvatar de kean

    kean/Nuke

    8,600Ver en GitHub↗

    Nuke is an image loading system designed to fetch, cache, and render images and short video clips within a user interface. It functions as an asset caching engine and a resumable download manager to handle the retrieval of remote media files. The framework includes a request priority manager to coordinate duplicate requests and order loading based on visual importance. It employs an image prefetching strategy to load visuals into memory before they are required and uses an LRU asset cache to reduce network traffic. The system covers broader capabilities in traffic management and data storage

    Transforms compressed image files into viewable raw pixel formats for display.

    Swift
    Ver en GitHub↗8,600
  • 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

    Saves scraped information into specified datasets in machine-readable formats for further analysis.

    Pythonapifyautomationbeautifulsoup
    Ver en GitHub↗8,097
Ant.12Siguiente
  1. Home
  2. Data & Databases
  3. Data Engineering and Infrastructure
  4. Data Extraction & Ingestion
  5. Data Extraction

Explorar subetiquetas

  • Clinical Chart ExtractionRetrieval of patient-specific clinical observations and charted data from healthcare records. **Distinct from Data Extraction:** Distinct from general Data Extraction: specifically targets medical chart data such as ventilator settings and mental status.
  • Clinical Measurement ExtractionRetrieval of specific physiological and clinical measurements from electronic health records. **Distinct from Data Extraction:** Specializes general data extraction to retrieve clinical metrics like blood pressure and BMI from healthcare records.
  • Compressed Hunk CompressionCompression of raw media and hard disks into the standardized compressed hunk (CHD) format. **Distinct from Compressed Image Extraction:** Focuses on the creation/compression of CHD files, whereas the sibling focuses on extraction.
  • Compressed Image ExtractionDecompression of specialized image formats into raw binary or disk formats. **Distinct from Data Extraction:** Distinct from general data extraction: specifically targets the decompression of compressed hunk images (CHD).
  • Database-Specific ExtractionsRetrieval of structured data from a specific database engine. **Distinct from Data Extraction:** Distinct from Data Extraction: specializes the extraction process for a specific database implementation like OceanBase.
  • Datetime Component ExtractorsUtilities for retrieving specific temporal units from datetime data in distributed collections. **Distinct from Data Extraction:** Focuses on temporal component extraction from distributed dataframes, distinct from general data extraction.
  • Extraction DiffingTools for comparing different versions or sources of extracted data to ensure accuracy. **Distinct from Data Extraction:** Distinct from Data Extraction: focuses on comparing results rather than the act of retrieving data.
  • JSONPath Extraction2 sub-etiquetasUtilities for retrieving specific data points from JSON structures using the JSONPath query language. **Distinct from Data Extraction:** Specializes general data extraction to the specific JSONPath syntax and JSON formatted responses.
  • Object Hierarchy QueryingEvaluating path expressions against live Java object hierarchies instead of JSON strings. **Distinct from JSONPath Extraction:** Distinct from JSONPath Extraction: queries Java beans directly rather than parsing JSON text.
  • Resource Metadata ExtractorsTools that retrieve raw file locations or structured metadata from web pages for external integration.
  • Schema-Driven ExtractorsTools that map document regions to typed objects based on predefined templates.
  • Selector-Based ExtractorsTools using path-based query languages to map content into structured objects.
  • StructuredTools that convert unstructured web or document content into clean, typed, and organized data formats.
  • TriageIsolating emergency department assessment and acuity data from medical records. **Distinct from Data Extraction:** Specializes general data extraction specifically for emergency triage and acuity levels.