clue/reactphp-flux

Flux, the lightweight stream processor to concurrently do many (but not too many) things at once, built on top of ReactPHP.

v1.4.0 2023-04-21 11:40 UTC

This package is auto-updated.

Last update: 2024-04-04 17:27:06 UTC


README

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Flux, the lightweight stream processor to concurrently do many (but not too many) things at once, built on top of ReactPHP.

Let's say you have a large list of users or products that you want to process by individually sending a (RESTful) HTTP API request to some third party API for each record. Estimating each call to take around 0.3s means that having 10000 users processed sequentially, you would have to wait around 50 minutes for all jobs to complete. This works perfectly fine for a small number of operations, but keeping thousands of jobs in memory at once may easily take up all resources on your side. Instead, you can use this library to stream your arbitrarily large input list as individual records to a non-blocking (async) transformation handler. It uses ReactPHP to enable you to concurrently process multiple records at once. You can control the concurrency limit, so that by allowing it to process 10 operations at the same time, you can thus process this large input list around 10 times faster and at the same time you're no longer limited how many records this list may contain (think processing millions of records). This library provides a simple API that is easy to use in order to manage any kind of async operation without having to mess with most of the low-level details. You can use this to throttle multiple HTTP requests, database queries or pretty much any API that already uses Promises.

  • Async execution of operations - Choose how many async operations should be processed at once (concurrently). Process their results as soon as responses come in. The Promise-based design provides a sane interface to working with out of order results.
  • Standard interfaces - Allows easy integration with existing higher-level components by implementing ReactPHP's standard promises and streaming interfaces.
  • Lightweight, SOLID design - Provides a thin abstraction that is just good enough and does not get in your way. Builds on top of well-tested components and well-established concepts instead of reinventing the wheel.
  • Good test coverage - Comes with an automated tests suite and is regularly tested in the real world.

Table of contents

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Quickstart example

Once installed, you can use the following code to process an example user lists by sending a (RESTful) HTTP API request for each user record:

<?php

require __DIR__ . '/vendor/autoload.php';

$browser = new React\Http\Browser();

$concurrency = isset($argv[1]) ? $argv[1] : 3;

// each job should use the browser to GET a certain URL
// limit number of concurrent jobs here
$transformer = new Clue\React\Flux\Transformer($concurrency, function ($user) use ($browser) {
    // skip users that do not have an IP address listed
    if (!isset($user['ip'])) {
        return React\Promise\resolve($user);
    }

    // look up country for this IP
    return $browser->get("https://ipapi.co/$user[ip]/country_name/")->then(
        function (Psr\Http\Message\ResponseInterface $response) use ($user) {
            // response successfully received
            // add country to user array and return updated user
            $user['country'] = (string)$response->getBody();

            return $user;
        }
    );
});

// load a huge number of users to process from NDJSON file
$input = new Clue\React\NDJson\Decoder(
    new React\Stream\ReadableResourceStream(
        fopen(__DIR__ . '/users.ndjson', 'r')
    ),
    true
);

// process all users by piping through transformer
$input->pipe($transformer);

// log transformed output results
$transformer->on('data', function ($user) {
    echo $user['name'] . ' is from ' . $user['country'] . PHP_EOL;
});
$transformer->on('end', function () {
    echo '[DONE]' . PHP_EOL;
});
$transformer->on('error', function (Exception $e) {
    echo 'Error: ' . $e->getMessage() . PHP_EOL;
});

See also the examples.

By changing the $concurrency parameter, you can see how processing this list without concurrency takes near 4s, while using a concurrency setting of 5 takes near just 1s (YMMV obviously).

Usage

Transformer

The Transformer passes all input data through its transformation handler and forwards the resulting output data.

It uses ReactPHP's standard streaming interfaces which allow to process huge inputs without having to store everything in memory at once and instead allows you to efficiently process its input in small chunks. Any data you write to this stream will be passed through its transformation handler which is responsible for processing and transforming this data and also takes care of mangaging streaming throughput and back-pressure.

The transformation handler can be any non-blocking (async) callable that uses promises to signal its eventual results. This callable receives a single data argument as passed to the writable side and must return a promise. A successful fulfillment value will be forwarded to the readable end of the stream, while an unsuccessful rejection value will emit an error event and then close() the stream.

The new Transformer(int $concurrency, callable $handler) call can be used to create a new transformer instance. You can create any number of transformation streams, for example when you want to apply different transformations to different kinds of streams.

The $concurrency parameter sets a new soft limit for the maximum number of jobs to handle concurrently. Finding a good concurrency limit depends on your particular use case. It's common to limit concurrency to a rather small value, as doing more than a dozen of things at once may easily overwhelm the receiving side. Using a 1 value will ensure that all jobs are processed one after another, effectively creating a "waterfall" of jobs. Using a value less than 1 will throw an InvalidArgumentException.

// handle up to 10 jobs concurrently
$transformer = new Transformer(10, $handler);
// handle each job after another without concurrency (waterfall)
$transformer = new Transformer(1, $handler);

The $handler parameter must be a valid callable that accepts your job parameter (the data from its writable side), invokes the appropriate operation and returns a Promise as a placeholder for its future result (which will be made available on its readable side).

// using a Closure as handler is usually recommended
$transformer = new Transformer(10, function ($url) use ($browser) {
    return $browser->get($url);
});
// accepts any callable, so PHP's array notation is also supported
$transformer = new Transformer(10, array($browser, 'get'));

Continue with reading more about promises.

Promises

This library works under the assumption that you want to concurrently handle async operations that use a Promise-based API. You can use this to concurrently run multiple HTTP requests, database queries or pretty much any API that already uses Promises.

For demonstration purposes, the examples in this documentation use ReactPHP's async HTTP client. Its API can be used like this:

$browser = new React\Http\Browser();

$promise = $browser->get($url);

If you wrap this in a Transformer instance as given above, this code will look like this:

$browser = new React\Http\Browser();

$transformer = new Transformer(10, function ($url) use ($browser) {
    return $browser->get($url);
});

$transformer->write($url);

The $transformer instance is a WritableStreaminterface, so that writing to it with write($data) will actually be forwarded as $browser->get($data) as given in the $handler argument (more about this in the following section about streaming).

Each operation is expected to be async (non-blocking), so you may actually invoke multiple handlers concurrently (send multiple requests in parallel). The $handler is responsible for responding to each request with a resolution value, the order is not guaranteed. These operations use a Promise-based interface that makes it easy to react to when an operation is completed (i.e. either successfully fulfilled or rejected with an error):

$transformer = new Transformer(10, function ($url) use ($browser) {
    $promise = $browser->get($url);

    return $promise->then(
        function ($response) {
            var_dump('Result received', $result);

            return json_decode($response->getBody());
        },
        function (Exception $e) {
            echo 'Error: ' . $e->getMessage() . PHP_EOL;

            throw $error;
        }
    );
);

Each operation may take some time to complete, but due to its async nature you can actually start any number of (queued) operations. Once the concurrency limit is reached, this invocation will simply be queued and this stream will signal to the writing side that it should pause writing, thus effectively throttling the writable side (back-pressure). It will automatically start the next operation once another operation is completed and signal to the writable side that is may resume writing. This means that this is handled entirely transparently and you do not need to worry about this concurrency limit yourself.

This example expects URI strings as input, sends a simple HTTP GET request and returns the JSON-decoded HTTP response body. You can transform your fulfillment value to anything that should be made available on the readable end of your stream. Similar logic may be used to filter your input stream, such as skipping certain input values or rejecting it by returning a rejected promise. Accordingly, returning a rejected promise (the equivalent of throwing an Exception) will result in an error event that tries to cancel() all pending operations and then close() the stream.

Timeout

By default, this library does not limit how long a single operation can take, so that the transformation handler may stay pending for a long time. Many use cases involve some kind of "timeout" logic so that an operation is cancelled after a certain threshold is reached.

You can simply use react/promise-timer which helps taking care of this through a simple API.

The resulting code with timeouts applied look something like this:

use React\Promise\Timer;

$transformer = new Transformer(10, function ($uri) use ($browser) {
    return Timer\timeout($browser->get($uri), 2.0);
});

$transformer->write($uri);

The resulting stream can be consumed as usual and the above code will ensure that execution of this operation can not take longer than the given timeout (i.e. after it is actually started).

Please refer to react/promise-timer for more details.

Streaming

The Transformer implements the DuplexStreamInterface and as such allows you to write to its writable input side and to consume from its readable output side. Any data you write to this stream will be passed through its transformation handler which is responsible for processing and transforming this data (see above for more details).

The Transformer takes care of passing data you pass on its writable side to the transformation handler argument and forwarding resulting data to it readable end. Each operation may take some time to complete, but due to its async nature you can actually start any number of (queued) operations. Once the concurrency limit is reached, this invocation will simply be queued and this stream will signal to the writing side that it should pause writing, thus effectively throttling the writable side (back-pressure). It will automatically start the next operation once another operation is completed and signal to the writable side that is may resume writing. This means that this is handled entirely transparently and you do not need to worry about this concurrency limit yourself.

The following examples use an async (non-blocking) transformation handler as given above:

$browser = new React\Http\Browser();

$transformer = new Transformer(10, function ($url) use ($browser) {
    return $browser->get($url);
});

The write(mixed $data): bool method can be used to transform data through the transformation handler like this:

$transformer->on('data', function (ResponseInterface $response) {
    var_dump($response);
});

$transformer->write('http://example.com/');

This handler receives a single data argument as passed to the writable side and must return a promise. A successful fulfillment value will be forwarded to the readable end of the stream, while an unsuccessful rejection value will emit an error event, try to cancel() all pending operations and then close() the stream.

Note that this class makes no assumptions about any data types. Whatever is written to it, will be processed by the transformation handler. Whatever the transformation handler yields will be forwarded to its readable end.

The end(mixed $data = null): void method can be used to soft-close the stream once all transformation handlers are completed. It will close the writable side, wait for all outstanding transformation handlers to complete and then emit an end event and then close() the stream. You may optionally pass a (non-null) $data argument which will be processed just like a write($data) call immediately followed by an end() call.

$transformer->on('data', function (ResponseInterface $response) {
    var_dump($response);
});
$transformer->on('end', function () {
    echo '[DONE]' . PHP_EOL;
});

$transformer->end('http://example.com/');

The close(): void method can be used to forcefully close the stream. It will try to cancel() all pending transformation handlers and then immediately close the stream and emit a close event.

$transformer->on('data', $this->expectCallableNever());
$transformer->on('close', function () {
    echo '[CLOSED]' . PHP_EOL;
});

$transformer->write('http://example.com/');
$transformer->close();

The pipe(WritableStreamInterface $dest): WritableStreamInterface method can be used to forward an input stream into the transformer and/or to forward the resulting output stream to another stream.

$source->pipe($transformer)->pipe($dest);

This piping context is particularly powerful because it will automatically throttle the incoming source stream and wait for the transformation handler to complete before resuming work (back-pressure). Any additional data events will be queued in-memory and resumed as appropriate. As such, it allows you to limit how many operations are processed at once.

Because streams are one of the core abstractions of ReactPHP, a large number of stream implementations are available for many different use cases. For example, this allows you to use the following pseudo code to send an HTTP request for each JSON object in a compressed NDJSON file:

$transformer = new Transformer(10, function ($data) use ($http) {
    return $http->post('https://example.com/?id=' . $data['id'])->then(
        function ($response) use ($data) {
            return array('done' => $data['id']);
        }
    );
});

$source->pipe($gunzip)->pipe($ndjson)->pipe($transformer)->pipe($dest);

$transformer->on('error', function (Exception $e) {
    echo 'Error: ' . $e->getMessage() . PHP_EOL;
});

Keep in mind that the transformation handler may return a rejected promise. In this case, the stream will emit an error event and then close() the stream. If you do not want the stream to end in this case, you explicitly have to handle any rejected promises and return some placeholder value instead, for example like this:

$uploader = new Transformer(10, function ($data) use ($http) {
    return $http->post('https://example.com/?id=' . $data['id'])->then(
        function ($response) use ($data) {
            return array('done' => $data['id']);
        },
        function ($error) use ($data) {
            // HTTP request failed => return dummy indicator
            return array(
                'failed' => $data['id'],
                'reason' => $error->getMessage()
            );
        }
    );
});

all()

The static all(ReadableStreamInterface $input, int $concurrency, callable $handler): PromiseInterface<int,Exception> method can be used to concurrently process all jobs from the input stream through the given $handler.

This is a convenience method which uses the Transformer internally to schedule all jobs from the input stream while limiting concurrency to ensure no more than $concurrency jobs ever run at once. It will return a promise which resolves with the total number of all successful jobs on success.

$browser = new React\Http\Browser();

$promise = Transformer::all($input, 3, function ($data) use ($browser, $url) {
    return $browser->post($url, [], json_encode($data));
});

$promise->then(function ($count) {
    echo 'All ' . $count . ' jobs successful!' . PHP_EOL;
}, function (Exception $e) {
    echo 'Error: ' . $e->getMessage() . PHP_EOL;
});

If either of the jobs fail, it will reject the resulting promise, will close() the input stream and will try to cancel all outstanding jobs. Calling cancel() on the pending promise will close() the input stream and will try to cancel all outstanding jobs. Similarly, if the $input stream emits an error event, it will reject the resulting promise and will try to cancel all outstanding jobs.

The $input parameter must be a ReadableStreamInterface which emits one data event for each job to process. Each element will be passed to the $handler to start one job. The fulfillment value for each job will be ignored, so for best performance it's recommended to not return any excessive data structures. When the stream emits an end or close event, this method will wait for all outstanding jobs to complete and then resolve with the number of successful jobs. If this stream is already closed or does not emit any data events, this method will resolve with a 0 value without processing any jobs.

$input = new ThroughStream();

$promise = Transformer::all($input, 2, $handler);

$input->write('a');
$input->write('b');
$input->write('c');
$input->end();

Because streams are one of the core abstractions of ReactPHP, a large number of stream implementations are available for many different use cases. For example, this allows you to use clue/reactphp-ndjson or clue/reactphp-csv to process large lists of structured input data. See also streaming for more details.

The $concurrency parameter sets a new soft limit for the maximum number of jobs to handle concurrently. Finding a good concurrency limit depends on your particular use case. It's common to limit concurrency to a rather small value, as doing more than a dozen of things at once may easily overwhelm the receiving side. Using a 1 value will ensure that all jobs are processed one after another, effectively creating a "waterfall" of jobs. Using a value less than 1 will reject with an InvalidArgumentException without processing any jobs.

// handle up to 10 jobs concurrently
$promise = Transformer::all($stream, 10, $handler);
// handle each job after another without concurrency (waterfall)
$promise = Transformer::all($stream, 1, $handler);

The $handler parameter must be a valid callable that accepts your job parameter (the data from the $input stream), invokes the appropriate operation and returns a Promise as a placeholder for its future result. The fulfillment value for each job will be ignored, so for best performance it's recommended to not return any excessive data structures. If the given argument is not a valid callable, this method will reject with an InvalidArgumentException without processing any jobs.

// using a Closure as handler is usually recommended
$promise = Transformer::all($stream, 10, function ($url) use ($browser) {
    return $browser->get($url);
});
// accepts any callable, so PHP's array notation is also supported
$promise = Transformer::all($stream, 10, array($browser, 'get'));

Note that this method returns a promise that resolves with the total number of successful operations only if all operations succeed. This is mostly a convenience method that uses the Transformer under the hood. If your input data is small enough to fit into memory (a few dozens or hundreds of operations), you may want to use clue/reactphp-mq instead and keep all operations in memory without using a streaming approach.

any()

The static any(ReadableStreamInterface $input, int $concurrency, callable $handler): PromiseInterface<mixed,Exception> method can be used to concurrently process some jobs from the input stream through the given $handler.

This is a convenience method which uses the Transformer internally to schedule the jobs from the input stream while limiting concurrency to ensure no more than $concurrency jobs ever run at once. It will return a promise which resolves with the first successful resolution value on success.

$browser = new React\Http\Browser();

$promise = Transformer::any($input, 3, function ($data) use ($browser, $url) {
    return $browser->post($url, [], json_encode($data));
});

$promise->then(function (ResponseInterface $response) {
    echo 'First successful job: ' . $response->getBody() . PHP_EOL;
}, function (Exception $e) {
    echo 'Error: ' . $e->getMessage() . PHP_EOL;
});

If the first job succeeds, it will resolve the resulting promise with its resolution value, close() the input stream and will try to cancel all other outstanding jobs.

If either of the jobs fails, it will stay in a pending state and will wait for one of the other jobs to succeed. If all jobs fail, it will reject the resulting promise. Calling cancel() on the pending promise will close() the input stream and will try to cancel all outstanding jobs. Similarly, if the $input stream emits an error event, it will reject the resulting promise and will try to cancel all outstanding jobs.

The $input parameter must be a ReadableStreamInterface which emits one data event for each job to process. Each element will be passed to the $handler to start one job. The fulfillment value for the first successful job will be used to fulfill the resulting promise. When the stream emits an end or close event, this method will wait for all outstanding jobs to complete and then resolve or reject accordingly. If this stream is already closed or does not emit any data events, this method will reject with an UnderflowException without processing any jobs.

$input = new ThroughStream();

$promise = Transformer::any($input, 2, $handler);

$input->write('a');
$input->write('b');
$input->write('c');
$input->end();

Because streams are one of the core abstractions of ReactPHP, a large number of stream implementations are available for many different use cases. For example, this allows you to use clue/reactphp-ndjson or clue/reactphp-csv to process large lists of structured input data. See also streaming for more details.

The $concurrency parameter sets a new soft limit for the maximum number of jobs to handle concurrently. Finding a good concurrency limit depends on your particular use case. It's common to limit concurrency to a rather small value, as doing more than a dozen of things at once may easily overwhelm the receiving side. Using a 1 value will ensure that all jobs are processed one after another, effectively creating a "waterfall" of jobs. Using a value less than 1 will reject with an InvalidArgumentException without processing any jobs.

// handle up to 10 jobs concurrently
$promise = Transformer::any($stream, 10, $handler);
// handle each job after another without concurrency (waterfall)
$promise = Transformer::any($stream, 1, $handler);

The $handler parameter must be a valid callable that accepts your job parameter (the data from the $input stream), invokes the appropriate operation and returns a Promise as a placeholder for its future result. The fulfillment value for the first successful job will be used to fulfill the resulting promise. If the given argument is not a valid callable, this method will reject with an InvalidArgumentException without processing any jobs.

// using a Closure as handler is usually recommended
$promise = Transformer::any($stream, 10, function ($url) use ($browser) {
    return $browser->get($url);
});
// accepts any callable, so PHP's array notation is also supported
$promise = Transformer::any($stream, 10, array($browser, 'get'));

Note that this method returns a promise that resolves with the first successful resolution value only if any operation succeeds. This is mostly a convenience method that uses the Transformer under the hood. If your input data is small enough to fit into memory (a few dozens or hundreds of operations), you may want to use clue/reactphp-mq instead and keep all operations in memory without using a streaming approach.

Install

The recommended way to install this library is through Composer. New to Composer?

This project follows SemVer. This will install the latest supported version:

composer require clue/reactphp-flux:^1.4

See also the CHANGELOG for details about version upgrades.

This project aims to run on any platform and thus does not require any PHP extensions and supports running on legacy PHP 5.3 through current PHP 8+ and HHVM. It's highly recommended to use the latest supported PHP version for this project.

Tests

To run the test suite, you first need to clone this repo and then install all dependencies through Composer:

composer install

To run the test suite, go to the project root and run:

vendor/bin/phpunit

The test suite is set up to always ensure 100% code coverage across all supported environments. If you have the Xdebug extension installed, you can also generate a code coverage report locally like this:

XDEBUG_MODE=coverage vendor/bin/phpunit --coverage-text

License

This project is released under the permissive MIT license.

Did you know that I offer custom development services and issuing invoices for sponsorships of releases and for contributions? Contact me (@clue) for details.

More

  • If you want to learn more about processing streams of data, refer to the documentation of the underlying react/stream component.

  • If you only want to process a few dozens or hundreds of operations, you may want to use clue/reactphp-mq instead and keep all operations in memory without using a streaming approach.

  • If you want to process structured NDJSON files (.ndjson file extension), you may want to use clue/reactphp-ndjson on the input stream before passing the decoded stream to the transformer.

  • If you want to process compressed GZIP files (.gz file extension), you may want to use clue/reactphp-zlib on the compressed input stream before passing the decompressed stream to the decoder (such as NDJSON).