14 dépôts
Reducing collections of values into single results using cumulative functions.
Distinct from Decentralized Data Aggregators: Candidates were related to decentralized aggregators or A/B testing, not functional reduction
Explore 14 awesome GitHub repositories matching data & databases · Functional Data Aggregation. Refine with filters or upvote what's useful.
Underscore is a JavaScript utility library providing a suite of functional programming and data manipulation helpers. It serves as a framework for transforming data collections, composing functions, managing objects, and performing precise data type validation without modifying core language prototypes. The project includes a functional programming toolkit designed to control function execution timing and behavior through techniques such as debouncing, throttling, and partial application. It also provides a dedicated object manipulation utility for cloning, merging, picking, and omitting prop
Includes aggregation helpers that collapse collections into a single result via a cumulative function.
type-fest is a library of reusable utility types for performing complex transformations and validations on objects, arrays, strings, and numeric ranges in TypeScript. It provides a collection of type definitions designed to handle advanced structural changes and constraints. The project distinguishes itself by offering specialized logic for string literal processing, such as casing transformations and pattern-based modifications, and type-level arithmetic for calculating numeric ranges and absolute values. It also includes utilities for enforcing deep immutability, ensuring union mutual exclu
Checks whether all elements in a list of booleans are true at the type level.
Redis is a high-performance in-memory key-value store that functions as a distributed cache, message broker, and NoSQL database. It provides sub-millisecond read and write access to data stored in RAM and can operate as a vector database for indexing high-dimensional embeddings. The system supports a wide range of data storage and synchronization primitives, including the management of strings, hashes, lists, sets, and JSON documents. It enables real-time data operations through atomic transactions, hybrid persistence using snapshots and append-only logs, and high-availability configurations
Groups indexed documents by fields and applies reduction functions like count, sum, and average on the server.
vxe-table is a high-performance data table component and UI library for Vue, designed for building data-heavy applications. It functions as a virtualized data grid and spreadsheet UI framework capable of rendering millions of rows by mounting only the visible elements of a dataset. The project distinguishes itself through spreadsheet-like functionality, including cell selection, copy-paste support, and the generation of cross-tabulated pivot tables. It also provides specialized tools for managing complex data hierarchies using virtual trees, row grouping, and cell merging. The library covers
Calculates summaries and applies mathematical functions to provide high-level insights from raw tabular data.
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
Reduces collections of dataset entries into a single accumulated result using custom reduction functions.
This is an interactive Python tutorial delivered as a collection of Jupyter notebooks. It is designed as a structured learning path for beginners, teaching fundamental language concepts through a sequence of lessons that combine explanatory text with runnable code cells and embedded practice exercises. Each notebook is a self-contained unit that introduces a topic, demonstrates it with a minimal code example, and then asks the learner to write code themselves, receiving immediate feedback from the browser-based execution environment. The curriculum is built on a progressive concept-stacking mo
Teaches built-in any() and all() functions for boolean aggregation checks.
Hazelcast is a distributed data platform that combines an in-memory data grid with a stream processing engine to support real-time analytics and event-driven applications. It functions as a partitioned, distributed key-value store that replicates data across cluster nodes to provide low-latency access and high availability. The platform also serves as a distributed SQL query engine, allowing users to execute standard SQL statements against both in-memory datasets and external data sources. What distinguishes Hazelcast is its use of a distributed consensus subsystem to maintain strongly consis
Computes distributed functions like sum or max across map entries in parallel.
Arrow is a functional programming library for Kotlin that provides tools for implementing data-oriented programming patterns. It serves as a framework for typed error handling, a concurrency toolkit, and a library for the manipulation of immutable data. The project distinguishes itself through specialized capabilities for managing application failures using explicit types instead of exceptions and implementing resilience patterns such as circuit breakers and retry policies for distributed services. It also provides optics to update and query deeply nested immutable data structures without man
Provides functional reduction and cumulative functions to aggregate sequence data into single results.
smartTable est un composant de grille de données et un framework de vue de table pour Android. Il fonctionne comme une bibliothèque d'interface utilisateur pilotée par annotations qui utilise des marqueurs de classe et de champ pour mapper automatiquement les modèles de données vers des colonnes visuelles et définir les propriétés de table. Le projet se distingue par une intégration profonde avec les feuilles de calcul, fournissant des outils pour importer et exporter des données vers et depuis des fichiers Excel tout en préservant le formatage des cellules, les styles, les couleurs et l'alignement. Il dispose également d'un système de rendu basé sur le canvas qui prend en charge des mises en page de grille complexes avec des cellules fusionnées, des en-têtes figés et le verrouillage de colonnes. La bibliothèque couvre un large éventail de capacités de gestion de données, incluant le tri, l'agrégation et le calcul de statistiques de colonne. Elle gère de grands jeux de données via la pagination virtuelle, les contrôles de zoom et le formatage conditionnel des cellules pour maintenir la lisibilité et la performance. Le framework est implémenté en Java pour les applications Android.
Performs mathematical reduction of table columns into summary values within a dedicated row.
This is an interactive notebook-based course that teaches machine learning from Python fundamentals through deep learning and natural language processing. It uses real datasets and multiple frameworks within a structured, hands-on curriculum that combines concise explanations with executable code cells, built-in datasets, and embedded exercise checkpoints. Learning progresses through data preparation and exploration, classical machine learning workflows, computer vision with convolutional neural networks, and natural language processing with deep learning, all delivered as a cohesive progressi
Provides mathematical reduction of table columns into summary values using group-by operations.
H2 is a JDBC-compliant relational database management system written in Java. It functions as an embeddable SQL database that can run directly within an application process to remove network latency, or as an in-memory database for high-performance volatile storage. It also includes a web-based console for executing SQL commands and administering schemas. The system is characterized by its flexible deployment modes, including a standalone server mode for remote TCP/IP access and a mixed mode for simultaneous local and remote connectivity. It features a dialect emulation layer and compatibilit
Provides built-in logical aggregation functions to determine if any or all expressions in a group are true.
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
Implements mathematical reduction of table columns into summary values to condense large datasets.
This project is a numerical computing library designed for scientific and engineering mathematical operations. It functions as a comprehensive linear algebra framework, a statistical analysis library, and a toolkit for mathematical optimization and numerical integration. The library is distinguished by its provider-based native acceleration, which allows managed code to be swapped for platform-native binary libraries to increase the performance of computationally intensive routines. It also supports a hybrid approach to matrix storage, implementing separate strategies for dense and sparse mat
Summarizes matrix data using functional fold and reduce routines across rows and columns.
Ktorm is a lightweight object-relational mapping framework for Kotlin that provides a type-safe SQL domain-specific language and functional sequence APIs for database interaction. It enables developers to define database schemas and map relational tables to interface-based objects, ensuring that data persistence and retrieval are handled through strongly-typed expressions. The framework distinguishes itself by utilizing a functional, collection-style approach to query construction, allowing developers to chain operations like filtering, sorting, and aggregation using idiomatic language patter
Computes summary statistics like sums, averages, or counts from filtered database records.