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PapaParse - Fast and powerful CSV (delimited text) parser that gracefully handles large files and malformed input
Fast and powerful CSV parser for the browser that supports web workers and streaming large files. Converts CSV to JSON and JSON to CSV.
csv csv-parser parser parse parsing delimited text data auto-detect comma tab pipe file filereader stream worker workers thread threading multi-threaded jquery-pluginbacon.js - FRP (functional reactive programming) library for Javascript
A small functional reactive programming lib for JavaScript.
bacon.js bacon frp functional reactive programming stream streams eventstream rx rxjs observable reactive-library functional-reactivespeedment - Speedment is a Stream ORM Java Toolkit and Runtime
Read and modify your database using standard Java 8-streams and generated entity classes.
database stream orm code-generator javafx java-ee spring spring-boot database-helper database-library query-librarylevelup - A node.js wrapper for abstract-leveldown compliant stores
If you are upgrading: please see CHANGELOG.md.Fast and simple storage. A Node.js wrapper for abstract-leveldown compliant stores, which follow the characteristics of LevelDB.
leveldb leveldown memdown stream database db store storage jsonnode-s3-client - high level amazon s3 client for node.js
See also the companion CLI tool which is meant to be a drop-in replacement for s3cmd: s3-cli.This contains a reference to the aws-sdk module. It is a valid use case to use both this module and the lower level aws-sdk module in tandem.
amazon s3 sync folder directory retry limit stream async parallel multipart sizeJSONStream - rawStream.pipe(JSONStream.parse()).pipe(streamOfObjects)
The .. operator is the recursive descent operator from JSONPath, which will match a child at any depth (see examples below).If your keys have keys that include . or * etc, use an array instead. ['row', true, /^doc/].
json stream streaming parser async parsingthrough2 - Tiny wrapper around Node streams2 Transform to avoid explicit subclassing noise
Inspired by Dominic Tarr's through in that it's so much easier to make a stream out of a function than it is to set up the prototype chain properly: through(function (chunk) { ... }).Note: As 2.x.x this module starts using Streams3 instead of Stream2. To continue using a Streams2 version use npm install through2@0 to fetch the latest version of 0.x.x. More information about Streams2 vs Streams3 and recommendations see the article Why I don't use Node's core 'stream' module.
stream streams2 through transformsimple-peer - 📡 Simple WebRTC video/voice and data channels
This module works in the browser with browserify.Note: If you're NOT using browserify, then use the included standalone file simplepeer.min.js. This exports a SimplePeer constructor on window.
webrtc p2p nodejs browser data-channels peer-connection data data-channel data-channel-stream peer peer-to-peer stream video voice webrtc-streamstream-handbook - how to write node programs with streams
Now you will have a stream-handbook command that will open this readme file in your $PAGER. Otherwise, you may continue reading this document as you are presently doing.Streams come to us from the earliest days of unix and have proven themselves over the decades as a dependable way to compose large systems out of small components that do one thing well. In unix, streams are implemented by the shell with | pipes. In node, the built-in stream module is used by the core libraries and can also be used by user-space modules. Similar to unix, the node stream module's primary composition operator is called .pipe() and you get a backpressure mechanism for free to throttle writes for slow consumers.
documentation guide handbook stream streamsrapscallion - Asynchronous React VirtualDOM renderer for SSR.
This function returns a Renderer, an interface for rendering your VirtualDOM element. Methods are enumerated below.This function evaluates the React VirtualDOM Element originally provided to the renderer, and returns a Promise that resolves to the component's evaluated HTML string.
react server-side-rendering react-dom asynchronous stream html render ssrRxGo - Reactive Extensions for the Go language.
All contributions are welcome, both in development and documentation! Be sure you check out contributions and roadmap.ReactiveX, or Rx for short, is an API for programming with observable streams. This is a ReactiveX API for the Go language.
reactivex goroutines stream observable-streams observablewebpack-stream - :tropical_drink: Run webpack through a stream interface
Run webpack as a stream to conveniently integrate with gulp. The above will compile src/entry.js into assets with webpack into dist/ with the output filename of [hash].js (webpack generated hash of the build).
gulpplugin webpack streamjava8-tutorial - Modern Java - A Guide to Java 8
This article was originally posted on my blog. Java 8 enables us to add non-abstract method implementations to interfaces by utilizing the default keyword. This feature is also known as virtual extension methods.
java-8 tutorial lambda-expressions stream parallel-streams guide learningstreamjs - Lazy Object Streaming Pipeline for JavaScript
Stream.js is a lightweight (2.6 KB minified, gzipped), intensely tested (700+ assertions, 97% coverage) functional programming library for operating upon collections of in-memory data. It requires EcmaScript 5+, has built-in support for ES6 features and works in all current browsers, Node.js and Java 8 Nashorn. Before explaining how Stream.js works in detail, here's a few real world code samples.
stream streaming-api stream-pipeline functional collection pipeline lazy utils arraybrain.js - 🤖 Neural networks in JavaScript
brain.js is a library of Neural Networks written in JavaScript. 💡 Note: This is a continuation of the harthur/brain repository (which is not maintained anymore). For more details, check out this issue.
neural-network brain recurrent-neural-networks easy-to-use api web nodejs browser convolutional-neural-networks node stream ai artificial-intelligence brainjs brain.js feed-forward classifier neural network neural-networks machine-learning synapse recurrent long-short-term-memory gated-recurrent-unit rnn lstm gruxstream - An extremely intuitive, small, and fast functional reactive stream library for JavaScript
To keep the core of xstream small and simple, less frequently-used methods are available under the xstream/extra directory, and must be imported separately. See EXTRA_DOCS for documentation. XStream has four fundamental types: Stream, Listener, Producer, and MemoryStream.
reactive-programming stream typescript cyclejsgulp - The streaming build system
This file will give you a taste of what gulp does. Node already supports a lot of ES2015, to avoid compatibility problem we suggest to install Babel and rename your gulpfile.js as gulpfile.babel.js.
build stream system make tool asset pipeline series parallel streamingsnappydata - SnappyData - The Spark Database. Stream, Transact, Analyze, Predict in one cluster
Apache Spark is a general purpose parallel computational engine for analytics at scale. At its core, it has a batch design center and is capable of working with disparate data sources. While this provides rich unified access to data, this can also be quite inefficient and expensive. Analytic processing requires massive data sets to be repeatedly copied and data to be reformatted to suit Spark. In many cases, it ultimately fails to deliver the promise of interactive analytic performance. For instance, each time an aggregation is run on a large Cassandra table, it necessitates streaming the entire table into Spark to do the aggregation. Caching within Spark is immutable and results in stale insight. At SnappyData, we take a very different approach. SnappyData fuses a low latency, highly available in-memory transactional database (GemFireXD) into Spark with shared memory management and optimizations. Data in the highly available in-memory store is laid out using the same columnar format as Spark (Tungsten). All query engine operators are significantly more optimized through better vectorization and code generation. The net effect is, an order of magnitude performance improvement when compared to native Spark caching, and more than two orders of magnitude better Spark performance when working with external data sources.
snappydata spark memory-database analytics stream transaction scale
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