General-purpose collections pipeline

v4.0.1 2020-01-26 21:24 UTC


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Pipeline makes dealing with iterable types as easy as it can be, making it a perfect tool for bespoke data processing pipelines, hence the name. If you ever piped together several bash commands where one command uses output of another in succession, this library does just that but for PHP functions, generators, arrays, and iterators.

Pipeline comes with the most important yet basic building blocks. It boasts methods to map, filter, reduce, zip, and unpack data from arbitrary generators and from all kinds of standard iterators.

This rigorously tested library just works. Pipeline neither defines nor throws any exceptions.


composer require sanmai/pipeline

The latest version requires at least PHP 7.1. There are earlier versions that work under PHP 5.6 and above, but they are not as feature complete.


use function Pipeline\take;

// iterable corresponds to arrays, generators, iterators
// we use an array here simplicity sake
$iterable = range(1, 3);

// wrap the initial iterable with a pipeline
$pipeline = take($iterable);

// join side by side with other iterables of any type
    \range(1, 3),
    map(function () {
        yield 1;
        yield 2;
        yield 3;

// lazily process their elements together
$pipeline->unpack(function (int $a, int $b, int $c) {
    return $a - $b - $c;

// map one value into several more
$pipeline->map(function ($i) {
    yield pow($i, 2);
    yield pow($i, 3);

// simple one-to-one mapper
$pipeline->map(function ($i) {
    return $i - 1;

// map into arrays
$pipeline->map(function ($i) {
    yield [$i, 2];
    yield [$i, 4];

// unpack array into arguments
$pipeline->unpack(function ($i, $j) {
    yield $i * $j;

// one way to filter
$pipeline->map(function ($i) {
    if ($i > 50) {
        yield $i;

// this uses a filtering iterator from SPL under the hood
$pipeline->filter(function ($i) {
    return $i > 100;

// reduce to a single value; can be an array or any value
$value = $pipeline->reduce(function ($carry, $item) {
    // for the sake of convenience the default reducer from the simple
    // pipeline does summation, just like we do here
    return $carry + $item;
}, 0);

// int(104)

API entry points

All entry points always return an instance of a standard pipeline.

Method Details Use with
map() Takes an optional initial callback, where it must not require any arguments. Other than that, works just like an instance method below. use function Pipeline\map;
take() Takes any iterable, including arrays, initializes a standard pipeline with it. use function Pipeline\take;
fromArray() Takes an array, initializes a standard pipeline with it. use function Pipeline\fromArray;
zip() Takes an iterable, and several more, merging them together. use function Pipeline\zip;

Instance methods in a nutshell

Method Details A.K.A.
map() Takes an optional callback that for each input value may return one or yield many. Also takes an initial generator, where it must not require any arguments. Provided no callback does nothing. Also available as a plain function. array_map, Select, SelectMany
zip() Takes a number of iterables, merging them together with the current sequence, if any. array_map(null, ...$array), Python's zip(), transposition
unpack() Unpacks arrays into arguments for a callback. Flattens inputs if no callback provided. flat_map, flatten
filter() Removes elements unless a callback returns true. Removes falsey values if no callback provided. array_filter, Where
reduce() Reduces input values to a single value. Defaults to summation. array_reduce, Aggregate, Sum
toArray() Returns an array with all values. Eagerly executed. dict, ToDictionary
__construct() Can be provided with an optional initial iterator. Used in the take() function from above. Not part of any interface.

Pipeline is an iterator and can be used as any other iterable. Implements JsonSerializable.

Pipeline is a final class. It comes with a pair of interfaces to aid you with composition over inheritance.

In general, Pipeline instances are mutable, meaning every Pipeline-returning method returns the very same Pipeline instance. This gives us great flexibility on trusting someone or something to add processing stages to a Pipeline instance, while also avoiding non-obivius mistakes, raised from a need to strictly follow a fluid interface. E.g. if you add a processing stage, it stays there no matter if you capture the return value or not.


  • Since most callback are lazily evaluated as more data coming in and out, you must consume the results with a plain foreach or use a reduce() to make sure processing happens.

    foreach ($pipeline as $result) {
        // Processing happens only if you consume the results.
        // Want to stop early after few results? Not a problem here!

    Almost nothing will happen unless you use the results. That's the point of lazy evaluation after all!

  • That said, if a non-generator used to seed the pipeline, it will be executed eagerly.

    $pipeline = new \Pipeline\Standard();
    $pipeline->map(function () {
        // will be executed immediately on the spot, unless yield is used
        return $this->veryExpensiveMethod();

    In the above case the pipeline will store an array internally, with which the pipeline will operate eagerly whenever possible. Ergo, when in doubt, use a generator.

    $pipeline->map(function () {
        // will be executed only as needed, when needed
        yield $this->veryExpensiveMethod();
  • Keys for yielded values are being kept as is on a best effort basis, so one must take care when using iterator_to_array() on a pipeline: values with duplicate keys will be discarded with only the last value for a given key being returned.

    $pipeline = \Pipeline\map(function () {
        yield 'foo' => 'bar';
        yield 'foo' => 'baz';
    /* ['foo' => 'baz'] */

    Safer would be to use provided toArray() method. It will return all values regardless of keys used, making sure to discard all keys in the process.

    /* ['bar', 'baz'] */
  • The resulting pipeline is an iterator and should be assumed not rewindable, just like generators it uses.

     $pipeline = \Pipeline\map(function () {
         yield 1;
     $sum = $pipeline->reduce();
     // Won't work the second time though
     // Exception: Cannot traverse an already closed generator

    Although there are some cases where a pipeline can be rewinded and reused just like a regular array, a user should make no assumptions about this behavior as it is not a part of the API compatibility guarantees.

  • Pipeline implements IteratorAggregate which is not the same as Iterator. Where the latter needed, the pipeline can be wrapped with an IteratorIterator:

    $iterator = new \IteratorIterator($pipeline);
    /** @var $iterator \Iterator */
  • Iterating over a pipeline all over again results in undefined behavior. Best to avoid doing this.

Classes and interfaces: overview

  • \Pipeline\Standard is the main user-facing class for the pipeline with sane defaults for most methods.
  • \Pipeline\Principal is an abstract class you may want to extend if you're not satisfied with defaults from the class above. E.g. getIterator() can have different error handling.
  • Interface PrincipalPipeline defines three main functions all pipelines must bear.
  • Interface StandardPipeline defines unpack() from the standard pipeline.

This library is built to last. There's not a single place where an exception is thrown. Never mind any asserts whatsoever.

Class inheritance diagram

  • \Pipeline\Standard extends \Pipeline\Principal and implements StandardPipeline.
  • Abstract \Pipeline\Principal implements PrincipalPipeline.
  • Interface PrincipalPipeline extends StandardPipeline.
  • Interface PrincipalPipeline extends \IteratorAggregate.



Takes an instance of Traversable or none. In the latter case the pipeline must be primed by passing an initial generator to the map method. This method is not part to any interface, as per LSP.


Takes a processing stage in a form of a generator function or a plain mapping function. Provided no callback does nothing.

$pipeline->map(function (Customer $customer) {
    foreach ($customer->allPayments() as $item) {
        yield $item;

Can also take an initial generator, where it must not require any arguments.

$pipeline = new \Pipeline\Standard();
$pipeline->map(function () {
    yield $this->foo;
    yield $this->bar;


An extra variant of map which unpacks arrays into arguments for a callback.

Where with map() you would use:

$pipeline->map(function ($args) {
    list ($a, $b) = $args;

    // and so on

With unpack() these things are done behind the scene for you:

$pipeline->map(function () {
    yield [-1, [10, 20], new DateTime()];
$pipeline->unpack(function ($a, array $b, \DateTime ...$dates) {
    // and so on

You can have all kinds of standard type checks with ease too.

With no callback, the default callback for unpack() will flatten inputs:

$pipeline->map(function () {
    yield [1];
    yield [2, 3];
// [1, 2, 3]


Sequence-joins several iterables together, forming a feed with elements side by side:

$pipeline = take($iterableA);
$pipeline->zip($iterableB, $iterableC);
$pipeline->unpack(function ($elementOfA, $elementOfB, $elementOfC) {
    // ... 

Behavior with iterators with unequal number of elements is undefined.


Takes a filter callback not unlike that of array_filter.

$pipeline->filter(function ($item) {
    return $item->isGood() && $item->amount > 0;

Standard pipeline has a default callback with the same effect as in array_filter: it'll remove all falsy values.


Takes a reducing callback not unlike that of array_reduce with two arguments for the value of the previous iteration and for the current item. As a second argument it can take an inital value.

$total = $pipeline->reduce(function ($curry, $item) {
    return $curry + $item->amount;
}, 0);

Standard pipeline has a default callback that sums all values.


Returns an array with all values from a pipeline. All array keys are ignored to make sure every single value is returned.

// Yields [0 => 1, 1 => 2]
$pipeline = map(function () {
    yield 1;
    yield 2;

// For each value yields [0 => $i + 1, 1 => $i + 2]
$pipeline->map(function ($i) {
    yield $i + 1;
    yield $i + 2;

$result = $pipeline->toArray();
// Since keys are ignored we get:
// [2, 3, 3, 4]

If in the example about one would use iterator_to_array($result) they would get just [3, 4].


A method to conform to the Traversable interface. In case of unprimed \Pipeline\Standard it'll return an empty array iterator, essentially a no-op pipeline. Therefore this should work without errors:

$pipeline = new \Pipeline\Standard();
foreach ($pipeline as $value) {
    // no errors here

This allows to skip type checks for return values if one has no results to return: instead of false or null it is safe to return an unprimed pipeline.


Contributions to documentation and test cases are welcome. Bug reports are welcome too.

API is expected to stay as simple as it is, though.

Use case

Imagine you have a very deep and complex processing chain. Something akin to this obviously contrived example:

foreach ($obj->generator() as $val) {
    if ($val->a || $val->foo() == 3) {
        foreach ($val->bar as $b) {
            if ($b->keys) {
                foreach ($b->keys as $key) {
                    if ($key->name == "foo") {
                        foreach ($b->assoc[$key->id] as $foo) {
                            // ...
                           foreach ($b->uassoc[$key->id] as $foo) {
                               // ...

Now, you naturally want to break this monster down into manageable parts. You think you could do it like this:

$step1 = [];
foreach ($obj->generator() as $val) {
    if ($val->a || $val->foo() == 3) {
        $step1[] = $val->bar;

$step2 = [];
foreach ($step1 as $b) {
    if ($b->keys) {
        $step2[] = $b->keys;

$step3 = [];
foreach ($step2 as $key) {
    if ($key->name == "foo") {
        $step3[] = $b->assoc[$key->id];
        $step3[] = $b->uassoc[$key->id];

$step4 = [];
foreach ($step3 as $foo) {
    // ...

Indeed you made it somewhat simpler to understand, but this is still far from perfect. Three things come to mind:

  1. You lost type information here and there, so no autocomplete suggestions for you.
  2. On every step, every result has to buffer. This not only takes memory space, but you would not see if your algorithm is failing on the last step until you passed all the previous steps. What a bummer!
  3. These separate cycles are nice, but you still can not test them one by one. That's practically impossible without further work.

One may think they can pull the trick with array_map. But there's a catch: you can't easily return more than one value from array_map. No luck here too.

So, how do you solve this problem? Pipeline to the rescue!


With the pipeline, you could split just about any processing chain into a manageable sequence of testable generators or mapping functions. Want to know average shipping delay for these three warehouses for orders made during previous sale? Map matching orders into shipments, exclude unwanted warehouses, map shipments into dates and timings, sum and divide. Done!

Take a single step and write a generator or a function for it:

$this->double = function ($value) {
    return $value * 2;

$this->rowTotal = function (SomeType $value) {
    yield $value->price * $value->quantity;

With type checks and magic of autocomplete! Apply it to the data:

$sourceData = new \ArrayIterator(range(1, 1000)); // can be any type of generator

$pipeline = new \Pipeline\Standard($sourceData);
// any number of times in any sequence

Get results for the first rows immediately.

foreach ($pipeline as $result) {
    echo "$result,";
// immediately starts printing 4,8,12,...

Test with ease:

$this->plusone = function ($value) {
    yield $value;
    yield $value + 1;

$this->assertSame([4, 5], iterator_to_array(call_user_func($this->plusone, 4)));

Pretty neat, eh?

You can even pass on an instance of League\Pipeline to batch-process a collection of values, not just a single value it can usually handle:

$leaguePipeline = (new \League\Pipeline\Pipeline())->pipe(function ($payload) {
    return $payload + 1;
})->pipe(function ($payload) {
    return $payload * 2;

$pipeline = new \Pipeline\Standard(new \ArrayIterator([10, 20, 30]));

foreach ($pipeline as $result) {
    echo "$result,";
// prints 22,42,62,

About collection pipelines in general

About collection pipelines programming pattern by Martin Fowler.

What else is out there:

  • Pipe operator from Hack is about same, only won't work for generators, and not under the regular PHP. See a proposal for a similar operator for JavaScript.

  • Iteration primitives using generators provide functions like array_map and such, but returning lazy generators. You'll need quite some glue to accomplish the same thing Pipeline does out of box.

  • League\Pipeline is good for single values only. Similar name, but very different purpose. Not supposed to work with sequences of values. Each stage may return only one value.

  • Illuminate\Support\Collection a fluent wrapper for working with arrays of data. Can only work with arrays, also immutable, which is kind of expected for an array-only wrapper.

  • Knapsack is a close call. Can take a Traversable as an input, has lazy evaluation. But can't have multiple values produced from a single input. Has lots of utility functions for those who need them: they're out of scope for this project.

  • transducers.php is worth a close look if you're already familiar transducers from Clojure. API is not very PHP-esque. Read as not super friendly. Detailed write-up from the author.

  • Primitives for functional programming in PHP by Lars Strojny et al. is supposed to complement currently exisiting PHP functions, which it does, although it is subject to some of the same shortcomings as are array_map and array_filter. No method chaining.

  • Chain provides a consistent and chainable way to work with arrays in PHP, although for arrays only. No lazy evaluation.

  • Simple pipes with PHP generators by Hugh Grigg. Rationale and explanation for an exceptionally close concept. Probably one can use this library as a drop-in replacement, short of different method names.

  • Submit a PR to add yours.

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