16 repositorios
Utilities for retrieving typed data from specific database columns by index or name.
Distinct from Value Extraction: Existing candidates focus on lineage or schema definitions, not the runtime extraction of values from result sets.
Explore 16 awesome GitHub repositories matching data & databases · Column Value Extraction. Refine with filters or upvote what's useful.
fmdb is an object-oriented SQLite database library and persistence layer for native macOS and iOS environments. It provides an Objective-C wrapper that encapsulates the low-level C API, allowing applications to manage local relational data storage and embedded database connections through a high-level interface. The library focuses on thread-safe database access by synchronizing operations across multiple threads using serialized queues to prevent data corruption and race conditions. It includes specialized capabilities for secure local storage, such as database encryption and the management
Retrieves data from specific columns by index or name as strings, integers, or binary data.
LanceDB is a vector database and columnar data store designed to function as a versioned dataset manager and vector search engine. It serves as a high-performance backend for indexing and retrieving high-dimensional embeddings, providing the foundation for machine learning data pipelines. The system distinguishes itself through a combination of cloud-native object storage and immutable version tracking, allowing for data time-travel and reproducible AI experiments. It integrates hybrid search capabilities, merging dense vector similarity with BM25 full-text search and SQL-like scalar filters
Creates new data columns by transforming existing values through SQL expressions or external data merges.
AllAboutBugBounty is a curated collection of bug bounty techniques and payloads for web application security testing. It serves as a reference resource covering common web vulnerabilities and exploitation methods for security researchers, providing a structured approach to identifying and exploiting web application security flaws in bug bounty programs. The repository covers a wide range of attack categories including authentication bypass, cross-site scripting injection, server-side request forgery, web cache poisoning, and business logic abuse. It includes techniques for bypassing access co
Documents enumerating database schemas through injection techniques for targeted exploitation.
collect.js is a dependency-free JavaScript library that provides a fluent, chainable interface for manipulating arrays and objects. It mirrors the Laravel Collection API, offering a consistent set of methods for data transformation across JavaScript and Laravel backend environments. The library stores collection data as plain arrays internally and supports fluent method chaining, where each method returns a new collection instance. The library distinguishes itself by closely replicating the Laravel Collection API in JavaScript, mapping each PHP method to an equivalent JavaScript implementatio
Calculates sum, average, median, mode, min, or max across all items or a specified key.
Ibis is a portable Python dataframe library and multi-backend query engine that provides a unified interface for executing data transformations across diverse compute engines. It functions as a Python SQL expression compiler and dialect transpiler, allowing users to define data logic once and execute it across cloud warehouses, embedded databases, and distributed clusters without rewriting code. The project distinguishes itself through a database backend abstraction that decouples transformation logic from the underlying execution engine. It enables polyglot data workflows by mixing raw SQL s
Computes summary statistics like mean, max, min, and sum across columns or groups.
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
Captures record headers, keys, and timestamps as queryable columns within the destination table for deeper analysis.
CodeIgniter is a PHP web framework built on the Model-View-Controller pattern, designed for building full-stack web applications. It provides a lightweight toolkit with minimal configuration, organizing application logic into controllers, models, and views for clean separation of concerns. The framework includes a fluent query builder for constructing SQL statements programmatically, PSR-4 autoloading with namespace mapping, and a service-based dependency injection container for managing shared class instances. The framework distinguishes itself through its comprehensive set of built-in tools
Returns an indexed array of values from a single specified column across matching rows.
Computes and displays summary statistics like sum, average, min, median, or max from a query column.
Daft is a distributed dataframe library and multimodal data processor designed to handle large-scale structured and unstructured data. It functions as a vectorized execution engine that processes tables alongside images, audio, and video, utilizing a unified schema to manage diverse data types. The project distinguishes itself by combining distributed data engineering with large-scale AI inference. It provides an AI data pipeline for batch-optimizing model prompts and generating high-dimensional text embeddings, while utilizing zero-copy memory sharing to execute custom Python functions witho
Calculates summary statistics like sums and averages across multiple columns for a single row.
dtale es una cuadrícula interactiva basada en web y visualizador para dataframes de pandas, diseñado como una herramienta de análisis de datos exploratorio. Proporciona una interfaz basada en navegador para analizar estructuras de datos tabulares, permitiendo a los usuarios calcular estadísticas, detectar valores atípicos y calcular correlaciones sin escribir código manual. El proyecto funciona como un visor de datos integrado que puede integrarse en aplicaciones web a través de iframes o rutas personalizadas, con soporte específico para Django, Flask y Streamlit. Permite la exploración de conjuntos de datos a través de una combinación de una cuadrícula de datos interactiva y una biblioteca de visualización de datos capaz de generar histogramas, diagramas de caja y gráficos de dispersión 3D. La plataforma cubre una amplia gama de capacidades de gestión y análisis de datos, incluyendo limpieza de datos tabulares, remodelación y filtrado interactivo. Incluye herramientas de observabilidad para el análisis de datos faltantes, cálculo de correlación y puntuación de poder predictivo. Para la gestión de sesiones, admite el seguimiento de múltiples instancias y la persistencia del estado en procesos de trabajo concurrentes. La interfaz está protegida por autenticación de nombre de usuario y contraseña y admite la ingesta de datos desde archivos delimitados, hojas de cálculo y almacenes de datos ArcticDB.
Generates box plots, histograms, and value counts to describe the distribution of data columns.
Goravel es un scaffold de desarrollo y framework completo para construir aplicaciones web, APIs REST y servicios gRPC utilizando el lenguaje de programación Go. Implementa una arquitectura modelo-vista-controlador y proporciona un kit de herramientas integral para servidores y clientes de llamadas a procedimientos remotos de alto rendimiento. El framework se distingue por su extenso ecosistema integrado, que incluye un mapeador objeto-relacional fluido para la gestión de bases de datos y un kit de herramientas de interfaz de línea de comandos dedicado para la automatización administrativa y el scaffolding de proyectos. Cuenta con una abstracción de servicios basada en controladores que permite a los desarrolladores intercambiar backends de almacenamiento, caché y sesiones sin alterar la lógica de la aplicación. La plataforma cubre una amplia superficie de capacidades de aplicación, incluyendo el procesamiento de tareas asíncronas con colas distribuidas, gestión de identidad segura mediante autenticación basada en tokens y una capa de seguridad robusta con cifrado y control de acceso. También proporciona herramientas para la localización de contenido, renderizado de plantillas e infraestructura de pruebas automatizada con mocking de dependencias.
Provides utilities to extract specific database column values into Go slices.
H2 es un sistema de gestión de bases de datos relacionales compatible con JDBC, escrito en Java. Funciona como una base de datos SQL embebible que puede ejecutarse directamente dentro de un proceso de aplicación para eliminar la latencia de red, o como una base de datos en memoria para almacenamiento volátil de alto rendimiento. También incluye una consola basada en web para ejecutar comandos SQL y administrar esquemas. El sistema se caracteriza por sus modos de despliegue flexibles, incluyendo un modo servidor independiente para acceso remoto TCP/IP y un modo mixto para conectividad local y remota simultánea. Cuenta con una capa de emulación de dialectos y modos de compatibilidad que permiten imitar el comportamiento y la sintaxis de otros sistemas de bases de datos. El motor proporciona un amplio conjunto de capacidades que cubren transacciones ACID con control de concurrencia multiversión, soporte para datos geoespaciales y JSON, y funciones avanzadas de ventana analítica. Incluye herramientas para la preservación de datos mediante copias de seguridad comprimidas, restauración de scripts SQL y gestión de memoria fuera del heap (off-heap) para manejar grandes datasets. La base de datos se integra con aplicaciones utilizando controladores estándar de Java Database Connectivity y URLs de conexión.
Gathers values from multiple rows into a single array with optional ordering during aggregation.
This PHP data collection library is a functional data wrapper and array manipulation framework. It converts arrays, JSON strings, and iterables into chainable collection objects designed for advanced filtering, sorting, and transformation. The library is distinguished by its ability to dynamically extend functionality through the registration of custom methods via closures. It also provides specialized capabilities for hierarchical data modeling, allowing flat datasets with parent-child identifiers to be reconstructed into nested tree structures. The toolkit covers a broad surface of data ma
Computes sum, average, min, max, and frequency counts on collection values.
Tablesaw is a Java dataframe library designed for manipulating, filtering, and aggregating structured data. It serves as a toolkit for statistical analysis, data visualization, and machine learning execution within the Java Virtual Machine. The project provides specialized tools for computing descriptive statistics and generating cross-tabulations. It includes a visualization library for creating histograms and scatter plots, as well as a framework for executing linear regression, clustering, and classification tasks through integration with statistical libraries. The library covers a broad
Computes single summary statistics like mean, median, and standard deviation across a data column.
Xan is a command-line tool and data transformation engine for processing CSV, TSV, and JSONL datasets. It functions as a processor for compressed files, enabling random access and seeking within gzipped and Zstd files, and serves as a converter for specialized bioinformatics data formats. The tool handles large datasets without requiring full memory loads by utilizing stream-based processing. It provides capabilities for merging, sorting, and deduplicating massive files, as well as converting data between various tabular formats. The project covers a broad range of data wrangling and analysi
Loads only requested data columns into memory to reduce the resource footprint when processing wide datasets.
DataFrame is a C++ tabular data library and manipulation engine designed for managing heterogeneous data in contiguous memory. It functions as a statistical analysis framework and time series analysis toolkit, providing the means to store, index, and transform multidimensional datasets. The project distinguishes itself through a high-performance execution model that utilizes column-major storage, SIMD-aligned memory allocation, and a thread-pool for parallel computations. It employs a visitor-based algorithm dispatch system and policy-driven transformations to decouple data processing logic f
Provides column-based aggregation to compute total sums while optionally ignoring missing data.