```markdown # @push.rocks/smartstream A TypeScript library to simplify the creation and manipulation of Node.js streams, providing utilities for transform, duplex, and readable/writable stream handling while managing backpressure effectively. ## Install To install `@push.rocks/smartstream`, you can use npm or yarn as follows: ```bash npm install @push.rocks/smartstream --save # OR yarn add @push.rocks/smartstream ``` This will add `@push.rocks/smartstream` to your project's dependencies. ## Usage The `@push.rocks/smartstream` module is designed to simplify working with Node.js streams by providing a set of utilities for creating and manipulating streams. This module makes extensive use of TypeScript for improved code quality, readability, and maintenance. ESM syntax is utilized throughout the examples. ### Importing the Module Start by importing the module into your TypeScript file: ```typescript import * as smartstream from '@push.rocks/smartstream'; ``` For a more specific import, you may do the following: ```typescript import { SmartDuplex, StreamWrapper, StreamIntake, createTransformFunction, createPassThrough } from '@push.rocks/smartstream'; ``` ### Creating Basic Transform Streams The module provides utilities for creating transform streams. For example, to create a transform stream that modifies chunks of data, you can use the `createTransformFunction` utility: ```typescript import { createTransformFunction } from '@push.rocks/smartstream'; const upperCaseTransform = createTransformFunction(async (chunk) => { return chunk.toUpperCase(); }); // Usage with pipe readableStream .pipe(upperCaseTransform) .pipe(writableStream); ``` ### Handling Backpressure with SmartDuplex `SmartDuplex` is a powerful part of the `smartstream` module designed to handle backpressure effectively. Here's an example of how to create a `SmartDuplex` stream that processes data and respects the consumer's pace: ```typescript import { SmartDuplex } from '@push.rocks/smartstream'; const processDataDuplex = new SmartDuplex({ async writeFunction(chunk, { push }) { const processedChunk = await processChunk(chunk); // Assume this is a defined asynchronous function push(processedChunk); } }); sourceStream.pipe(processDataDuplex).pipe(destinationStream); ``` ### Combining Multiple Streams `Smartstream` facilitates easy combining of multiple streams into a single pipeline, handling errors and cleanup automatically. Here's how you can combine multiple streams: ```typescript import { StreamWrapper } from '@push.rocks/smartstream'; const combinedStream = new StreamWrapper([ readStream, // Source stream transformStream1, // Transformation transformStream2, // Another transformation writeStream // Destination stream ]); combinedStream.run() .then(() => console.log('Processing completed.')) .catch(err => console.error('An error occurred:', err)); ``` ### Working with StreamIntake `StreamIntake` allows for more dynamic control of the reading process, facilitating scenarios where data is not continuously available: ```typescript import { StreamIntake } from '@push.rocks/smartstream'; const streamIntake = new StreamIntake(); // Dynamically push data into the intake streamIntake.pushData('Hello, World!'); streamIntake.pushData('Another message'); // Signal end when no more data is to be pushed streamIntake.signalEnd(); ``` ### Real-world Scenario: Processing Large Files Consider a scenario where you need to process a large CSV file, transform the data row-by-row, and then write the results to a database or another file. With `smartstream`, you could create a pipe that reads the CSV, processes each row, and handles backpressure, ensuring efficient use of resources. ```typescript import { SmartDuplex, createTransformFunction } from '@push.rocks/smartstream'; import fs from 'fs'; import csvParser from 'csv-parser'; const csvReadTransform = createTransformFunction(async (row) => { // Process row return processedRow; }); fs.createReadStream('path/to/largeFile.csv') .pipe(csvParser()) .pipe(csvReadTransform) .pipe(new SmartDuplex({ async writeFunction(chunk, { push }) { await writeToDatabase(chunk); // Assume this writes to a database } })) .on('finish', () => console.log('File processed successfully.')); ``` This example demonstrates reading a large CSV file, transforming each row with `createTransformFunction`, and using a `SmartDuplex` to manage the processed data flow efficiently, ensuring no data is lost due to backpressure issues. ### Advanced Use Case: Backpressure Handling Effective backpressure handling is crucial when working with streams to avoid overwhelming the downstream consumers. Here’s a comprehensive example that demonstrates handling backpressure in a pipeline with multiple `SmartDuplex` instances: ```typescript import { SmartDuplex } from '@push.rocks/smartstream'; // Define the first SmartDuplex, which writes data slowly to simulate backpressure const slowProcessingStream = new SmartDuplex({ name: 'SlowProcessor', objectMode: true, writeFunction: async (chunk, { push }) => { await new Promise(resolve => setTimeout(resolve, 100)); // Simulated delay console.log('Processed chunk:', chunk); push(chunk); } }); // Define the second SmartDuplex as a fast processor const fastProcessingStream = new SmartDuplex({ name: 'FastProcessor', objectMode: true, writeFunction: async (chunk, { push }) => { console.log('Fast processing chunk:', chunk); push(chunk); } }); // Create a StreamIntake to dynamically handle incoming data const streamIntake = new StreamIntake(); // Chain the streams together and handle the backpressure scenario streamIntake .pipe(fastProcessingStream) .pipe(slowProcessingStream) .pipe(createPassThrough()) // Use Pass-Through to provide intermediary handling .on('data', data => console.log('Final output:', data)) .on('error', error => console.error('Stream encountered an error:', error)); // Simulate data pushing with intervals to observe backpressure handling let counter = 0; const interval = setInterval(() => { if (counter >= 10) { streamIntake.signalEnd(); clearInterval(interval); } else { streamIntake.pushData(`Chunk ${counter}`); counter++; } }, 50); ``` In this advanced use case, a `SlowProcessor` and `FastProcessor` are created using `SmartDuplex`, simulating a situation where one stream is slower than another. The `StreamIntake` dynamically handles incoming chunks of data and the intermediary Pass-Through handles any potential interruptions. ### Transform Streams in Parallel For scenarios where you need to process data in parallel: ```typescript import { SmartDuplex, createTransformFunction } from '@push.rocks/smartstream'; const parallelTransform = createTransformFunction(async (chunk) => { // Parallel Processing const results = await Promise.all(chunk.map(async item => await processItem(item))); return results; }); const streamIntake = new StreamIntake(); streamIntake .pipe(parallelTransform) .pipe(new SmartDuplex({ async writeFunction(chunk, { push }) { console.log('Processed parallel chunk:', chunk); push(chunk); } })) .on('finish', () => console.log('Parallel processing completed.')); // Simulate data pushing streamIntake.pushData([1, 2, 3, 4]); streamIntake.pushData([5, 6, 7, 8]); streamIntake.signalEnd(); ``` ### Error Handling in Stream Pipelines Error handling is an essential part of working with streams. The `StreamWrapper` assists in combining multiple streams while managing errors seamlessly: ```typescript import { StreamWrapper } from '@push.rocks/smartstream'; const faultyStream = new SmartDuplex({ async writeFunction(chunk, { push }) { if (chunk === 'bad data') { throw new Error('Faulty data encountered'); } push(chunk); } }); const readStream = new StreamIntake(); const writeStream = new SmartDuplex({ async writeFunction(chunk) { console.log('Written chunk:', chunk); } }); const combinedStream = new StreamWrapper([readStream, faultyStream, writeStream]); combinedStream.run() .then(() => console.log('Stream processing completed.')) .catch(err => console.error('Stream error:', err.message)); // Push Data readStream.pushData('good data'); readStream.pushData('bad data'); // This will throw an error readStream.pushData('more good data'); readStream.signalEnd(); ``` ### Testing Streams Here's an example test case using the `tap` testing framework to verify the integrity of the `SmartDuplex` from a buffer: ```typescript import { expect, tap } from '@push.rocks/tapbundle'; import { SmartDuplex } from '@push.rocks/smartstream'; tap.test('should create a SmartStream from a Buffer', async () => { const bufferData = Buffer.from('This is a test buffer'); const smartStream = SmartDuplex.fromBuffer(bufferData, {}); let receivedData = Buffer.alloc(0); return new Promise((resolve) => { smartStream.on('data', (chunk: Buffer) => { receivedData = Buffer.concat([receivedData, chunk]); }); smartStream.on('end', () => { expect(receivedData.toString()).toEqual(bufferData.toString()); resolve(); }); }); }); tap.start(); ``` ### Working with Files and Buffers You can easily stream files and buffers with `smartstream`. Here’s a test illustrating reading and writing with file streams using `smartfile` combined with `smartstream` utilities: ```typescript import { tap } from '@push.rocks/tapbundle'; import * as smartfile from '@push.rocks/smartfile'; import { SmartDuplex, StreamWrapper } from '@push.rocks/smartstream'; tap.test('should handle file read and write streams', async () => { const readStream = smartfile.fsStream.createReadStream('./test/assets/readabletext.txt'); const writeStream = smartfile.fsStream.createWriteStream('./test/assets/writabletext.txt'); const transformStream = new SmartDuplex({ async writeFunction(chunk, { push }) { const transformedChunk = chunk.toString().toUpperCase(); push(transformedChunk); } }); const streamWrapper = new StreamWrapper([readStream, transformStream, writeStream]); await streamWrapper.run(); const outputContent = await smartfile.fs.promises.readFile('./test/assets/writabletext.txt', 'utf-8'); console.log('Output Content:', outputContent); }); tap.start(); ``` ### Modular and Scoped Transformations Creating modular and scoped transformations is straightforward with `SmartDuplex`: ```typescript import { SmartDuplex } from '@push.rocks/smartstream'; type DataChunk = { id: number; data: string; }; const transformationStream1 = new SmartDuplex({ async writeFunction(chunk, { push }) { chunk.data = chunk.data.toUpperCase(); push(chunk); } }) const transformationStream2 = new SmartDuplex({ async writeFunction(chunk, { push }) { chunk.data = `${chunk.data} processed with transformation 2`; push(chunk); } }); const initialData: DataChunk[] = [ { id: 1, data: 'first' }, { id: 2, data: 'second' } ]; const intakeStream = new StreamIntake(); intakeStream .pipe(transformationStream1) .pipe(transformationStream2) .on('data', data => console.log('Transformed Data:', data)); initialData.forEach(item => intakeStream.pushData(item)); intakeStream.signalEnd(); ``` By leveraging `SmartDuplex`, `StreamWrapper`, and `StreamIntake`, you can streamline and enhance your data transformation pipelines in Node.js with a clear, efficient, and backpressure-friendly approach. ``` ## License and Legal Information This repository contains open-source code that is licensed under the MIT License. A copy of the MIT License can be found in the [license](license) file within this repository. **Please note:** The MIT License does not grant permission to use the trade names, trademarks, service marks, or product names of the project, except as required for reasonable and customary use in describing the origin of the work and reproducing the content of the NOTICE file. ### Trademarks This project is owned and maintained by Task Venture Capital GmbH. The names and logos associated with Task Venture Capital GmbH and any related products or services are trademarks of Task Venture Capital GmbH and are not included within the scope of the MIT license granted herein. Use of these trademarks must comply with Task Venture Capital GmbH's Trademark Guidelines, and any usage must be approved in writing by Task Venture Capital GmbH. ### Company Information Task Venture Capital GmbH Registered at District court Bremen HRB 35230 HB, Germany For any legal inquiries or if you require further information, please contact us via email at hello@task.vc. By using this repository, you acknowledge that you have read this section, agree to comply with its terms, and understand that the licensing of the code does not imply endorsement by Task Venture Capital GmbH of any derivative works.