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Creation of reusable SQL functions with custom parameters.
Distinct from SQL Function Namespaces: Distinct from SQL Function Namespaces: focuses on the definition of function logic rather than namespace organization.
Explore 14 awesome GitHub repositories matching development tools & productivity · Function Definitions. Refine with filters or upvote what's useful.
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
Creates reusable SQL functions with specified parameters to encapsulate complex logic.
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
Allows the definition of user-defined SQL functions using logic blocks to extend standard query capabilities.
PRQL is a functional, modular data transformation language that serves as a compiler for relational data pipelines. It allows developers to write expressive, pipelined queries that are translated into standard SQL dialects. By abstracting complex data manipulation into a readable, sequential syntax, the project enables the construction of maintainable workflows that remain independent of specific database engines. The language distinguishes itself through a robust compilation infrastructure that performs type validation and relational algebra analysis before generating target-specific code. I
Creates reusable logic blocks using a functional syntax that accepts parameters and returns computed values.
wasm-bindgen este un generator de binding-uri și un strat de interop conceput pentru a mapa tipurile de date și funcțiile peste granița dintre WebAssembly și JavaScript. Funcționează ca o interfață de funcții străine (FFI) care sintetizează boilerplate-ul necesar pentru a permite comunicarea bidirecțională între Rust și runtime-ul browserului. Proiectul generează cod glue și wrapper-e care automatizează conversia tipurilor complexe, permițând funcțiilor Rust să fie exportate ca module JavaScript și API-urilor browserului să fie importate în Rust. Utilizează macro-uri procedurale pentru a defini aceste interfețe și sintetizează binding-urile bazate pe definițiile de tip Rust. Sistemul gestionează memoria prin transmiterea pointerilor în memoria liniară și gestionează schimbul de resurse folosind handle-uri de memorie gestionate de JavaScript. Se bazează pe o convenție de apelare compatibilă cu C ABI pentru a transmite numere întregi primitive și float-uri între modul și host.
Uses procedural macros to annotate Rust functions and types for export to the JavaScript environment.
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
Provides the ability to define custom functions for computing new data features or bucket values based on column data.
VisiData is a terminal-based interactive data analysis tool and browser designed for exploring, filtering, and sorting large tabular datasets. It functions as a structured data inspector that loads and flattens complex formats like JSON, XML, and PCAP into interactive sheets, as well as a terminal file manager for navigating directories and performing staged filesystem operations. The project distinguishes itself by rendering data visualizations, such as scatter plots and histograms, directly in the terminal using Unicode Braille characters. It provides a Python-based data wrangling environme
Allows users to define custom Python functions to calculate specific statistics for grouped data.
Director is a routing library for JavaScript that handles URL and command-line pattern matching across client-side, server-side, and CLI environments. It provides a unified approach to defining routes as nested object literals, where each key maps to a URL segment and its handler, supporting both hash fragment monitoring and the HTML5 History API for browser navigation without page reloads. The library distinguishes itself through its ability to operate in multiple contexts with a single routing paradigm. It supports asynchronous handler queue execution for sequential tasks like authenticatio
Runs route handlers sequentially with async control flow for tasks like authentication or animations.
Acest proiect este o colecție cuprinzătoare de materiale educaționale de programare Python, incluzând tutoriale, exerciții și mostre de cod curate. Acesta servește drept curriculum de învățare și set de instrumente de inginerie software, utilizând Jupyter Notebooks pentru a combina codul executabil cu text educațional descriptiv. Repository-ul oferă ghiduri practice de implementare pentru construirea de aplicații cu modele de limbaj mari, cum ar fi sisteme de generare augmentată prin regăsire (RAG), agenți AI cu stare și fluxuri de lucru de machine learning. Se distinge prin oferirea unei abordări structurate a fluxurilor de lucru de codare agentică, acoperind distilarea ferestrei de context, rutarea modelelor agnostice la furnizor și output-uri structurate impuse prin schemă. Materialele acoperă o gamă largă de capabilități de inginerie software, inclusiv programarea asincronă cu cozi de sarcini distribuite, dezvoltarea de aplicații web cu API-uri REST și fluxuri de lucru de analiză a datelor. Include, de asemenea, resurse pentru stăpânirea designului orientat pe obiecte, implementarea pipeline-urilor CI/CD și aplicarea standardelor profesionale de linting și formatare.
Implements non-blocking HTTP client patterns using asynchronous functions with exponential backoff and type hints.
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
Allows the execution of custom user-defined logic directly on data stored within dataframes.
Arroyo is a high-performance stream processing platform built in Rust. It executes continuous SQL queries on streaming data with event-time semantics, enabling accurate windowed aggregations, joins, and stateful computations on unbounded event streams. The platform uses native Rust execution for high throughput and low latency, with periodic checkpointing for exactly-once fault tolerance and horizontal scaling across distributed workers. The system integrates deeply with Kafka for reading and writing topics with exactly-once delivery and supports change data capture (CDC) from MySQL and Postg
Provides async Rust UDFs for non-blocking I/O operations within stream processing pipelines.
pgx este un framework și o suită de instrumente pentru dezvoltarea de extensii PostgreSQL de înaltă performanță folosind limbajul de programare Rust. Oferă un wrapper API de nivel scăzut pentru a interacționa cu contextele de memorie interne ale bazei de date, sistemele de logare și API-urile de execuție de bază, permițând implementarea de funcționalități și logică personalizată direct în motorul bazei de date. Proiectul se distinge printr-un instrument de build dedicat și o interfață în linia de comandă (CLI) care gestionează ciclul de viață al dezvoltării extensiei, de la inițializarea mediului până la împachetarea binară. Include un mapper de tipuri care traduce structurile de limbaj în tipuri compozite de bază de date și generează automat definițiile SQL corespunzătoare. Framework-ul acoperă o suprafață largă de capabilități, inclusiv maparea funcțiilor definite de utilizator, integrarea protocolului binar și suportul pentru mai multe versiuni de target pentru a asigura compatibilitatea între diferite release-uri de baze de date. De asemenea, oferă wrappere specializate pentru gestionarea memoriei, pentru a manipula pointerii și a preveni scurgerile de memorie în mediul bazei de date.
Maps typed Rust functions to the PostgreSQL internal execution system to create custom functions and triggers.
pgrx is a framework for building and packaging custom PostgreSQL extensions using Rust. It serves as a foreign function interface bridge that maps Rust types and functions to the internal server programming interface of the database. The project provides a specialized toolchain for cross-compilation across different operating systems and target architectures using custom sysroots. It includes a schema generator that automatically translates high-level language structures into SQL definitions and binary protocol mappings. The framework manages memory safety by wrapping database memory context
Annotates Rust functions to register them as PostgreSQL user-defined functions and triggers.
uniffi-rs is a Rust FFI binding generator and multi-language binding tool. It functions as an automated binding scaffolder that creates type-safe foreign function interfaces and native wrappers for Rust libraries in languages such as Swift, Kotlin, and Python. The project provides a system for cross-language interface definition, allowing functions and data structures to be specified in a shared format to ensure consistent API signatures across platforms. It further serves as an FFI memory management layer, handling object lifetimes and thread safety when sharing state between Rust and foreig
Annotates functions and traits with export macros to expose them across FFI without a separate definition file.
Advises using async functions in route handlers to avoid thread pool performance penalties.