7 रिपॉजिटरी
Conversion of asynchronous effect blueprints into continuous streams of values.
Distinct from Stream Processing: Specifically addresses the lifting of functional effects into streams, not general data ingestion architectures.
Explore 7 awesome GitHub repositories matching data & databases · Effect-to-Stream Conversion. Refine with filters or upvote what's useful.
node-fetch एक लाइटवेट HTTP क्लाइंट लाइब्रेरी है जो Node.js के लिए ब्राउज़र-स्टैंडर्ड Fetch API को लागू करती है। यह सर्वर-साइड वातावरण से डेटा प्राप्त करने या भेजने के लिए एसिंक्रोनस नेटवर्क अनुरोध करने के लिए एक प्रॉमिस-आधारित इंटरफ़ेस प्रदान करती है। यह प्रोजेक्ट रिक्वेस्ट और रिस्पॉन्स स्ट्रीमिंग का उपयोग करके मेमोरी-कुशल डेटा हैंडलिंग में माहिर है। यह मेमोरी की कमी (memory exhaustion) को रोकने के लिए नेटिव सिस्टम स्ट्रीम्स के माध्यम से बड़े नेटवर्क पेलोड्स की वृद्धिशील प्रोसेसिंग (incremental processing) की अनुमति देता है। यह लाइब्रेरी DNS और SSL कॉन्फ़िगरेशन के लिए कस्टम HTTP एजेंट्स का उपयोग, एबॉर्ट सिग्नल्स के माध्यम से अनुरोध रद्दीकरण, और विभिन्न कंटेंट एन्कोडिंग व फॉर्म डेटा सबमिशन को संभालने सहित नेटवर्किंग क्षमताओं की एक विस्तृत श्रृंखला को कवर करती है।
Converts raw binary data from the network layer into standard Node.js streams for asynchronous processing.
Fluent Bit is a cloud-native log shipper and unified telemetry collector designed as a resource-efficient data pipeline. It ingests logs, metrics, and traces from multiple sources, processing them in real-time before routing the data to external storage backends. The project functions as a real-time stream processor and OpenTelemetry log processor, capable of transforming and filtering data using SQL and conditional logic. It also acts as a distributed tracing agent that can sample traces to reduce data volume while preserving full request paths. The system provides reliable data delivery th
Converts external text configurations into static array definitions during the build process.
This project is a sample library and implementation guide for using RxJava to manage asynchronous data streams and concurrent tasks in Android applications. It provides a collection of reference implementations for reactive programming, focusing on functional operators to transform and combine asynchronous data flows. The library demonstrates specific Android architectural patterns, such as implementing decoupled event buses for component communication and coordinating parallel network requests. It includes concrete examples of mobile-specific patterns including search input debouncing, list
Implements patterns for converting single-use data sequences into shared streams to allow multiple subscribers.
Bacon.js is a JavaScript functional reactive programming library used for coordinating complex asynchronous data flows. It functions as an observable event stream framework and an asynchronous data flow orchestrator, allowing developers to model events as declarative streams and properties. The library distinguishes itself through its ability to manage reactive state and synchronize timing across multiple sources. It provides specialized mechanisms for atomic state synchronization to prevent glitches in derived properties and offers advanced coordination strategies such as asynchronous stream
Provides a comprehensive set of utilities to generate event streams from DOM events, promises, callbacks, and polling functions.
go-flutter is a runtime and embedding library that enables Flutter applications to run natively on Windows, macOS, and Linux using Go and GLFW. It implements the Flutter Embedding API to render Flutter UIs on desktop platforms, providing a cross-platform desktop runtime that bridges Go and Dart code through standard Flutter method and event channels. The project includes a plugin framework that supports bidirectional communication between Go and Dart, allowing Go code to invoke Dart handlers and expose Go methods for Dart to call, with optional synchronous replies. It also provides event stre
Stream data from Go to Dart whenever an event occurs, using an EventChannel.
KurrentDB is an event-native database designed for event sourcing and event-driven architectures. It stores events as immutable, ordered records in streams, preserving a complete audit trail and enabling temporal queries. The database uses gRPC for all client-server and inter-node communication, providing efficient binary serialization and bidirectional streaming, and supports atomic multi-stream writes that ensure consistency across multiple streams in a single transaction. The database distinguishes itself with a built-in JavaScript projection engine that transforms, filters, and aggregates
Transforms and writes events from source streams into new streams using user-defined JavaScript functions.
R3 is a reactive extensions library and asynchronous data pipeline framework. It provides a system for composing asynchronous data streams, managing reactive state, and coordinating event sequences using observable patterns. The project distinguishes itself with a deterministic testing toolkit that mocks time and frame updates to ensure reproducible unit tests for asynchronous logic. It also includes observability tools for tracking active subscriptions and generating stack traces to identify memory leaks, alongside centralized exception routing for pipeline recovery. The framework covers a
Transforms standard event triggers into reactive streams to compose them with other asynchronous data sequences.