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https://github.com/joboccara/pipes

Pipelines for expressive code on collections in C++
https://github.com/joboccara/pipes

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Pipelines for expressive code on collections in C++

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Pipes are small components for writing expressive code when working on collections. Pipes chain together into a pipeline that receives data from a source, operates on that data, and send the results to a destination.

This is a header-only library, implemented in C++14.

The library is under development and subject to change. Contributions are welcome. You can also [log an issue](https://github.com/joboccara/pipes/issues) if you have a wish for enhancement or if you spot a bug.

# Contents

* [A First Example](#a-first-example)
* [A Second Example](#a-second-example)
* [Doesn't it look like ranges?](#doesnt-it-look-like-ranges)
* [Operating on several collections](#operating-on-several-collections)
* [End pipes](#end-pipes)
* [Easy integration with STL algorithms](#easy-integration-with-stl-algorithms)
* [Streams support](#streams-support)
* [List of available pipes](#list-of-available-pipes)

# A First Example

Here is a simple example of a pipeline made of two pipes: `transform` and `filter`:

```cpp
auto const source = std::vector{0, 1, 2, 3, 4, 5, 6, 7, 8, 9};
auto destination = std::vector{};

source >>= pipes::filter([](int i){ return i % 2 == 0; })
>>= pipes::transform([](int i){ return i * 2; })
>>= pipes::push_back(destination);

// destination contains {0, 4, 8, 12, 16};
```
### What's going on here:
* Each elements of `source` is sent to `filter`.
* Every time `filter` receives a piece of data, it sends its to the next pipe (here, `transform`) only if that piece of data satisfies `filter`'s' predicate.
* `transform` then applies its function on the data its gets and sends the result to the next pipe (here, `pipes::push_back`).
* `pipes::push_back` `push_back`s the data it receives to its `vector` (here, `destination`).

# A Second Example

Here is a more elaborate example with a pipeline that branches out in several directions:

```cpp
A >>= pipes::transform(f)
>>= pipes::filter(p)
>>= pipes::unzip(pipes::push_back(B),
pipes::fork(pipes::push_back(C),
pipes::filter(q) >>= pipes::push_back(D),
pipes::filter(r) >>= pipes::push_back(E));
```

Here, `unzip` takes the `std::pair`s or `std::tuple`s it receives and breaks them down into individual elements. It sends each element to the pipes it takes (here `pipes::push_back` and `fork`).

`fork` takes any number of pipes and sends the data it receives to each of them.

Since data circulates through pipes, real life pipes and plumbing provide a nice analogy (which gave its names to the library). For example, the above pipeline can be graphically represented like this:

# Doesn't it look like ranges?

Pipes sort of look like [ranges](https://github.com/ericniebler/range-v3) adaptors from afar, but those two libraries have very different designs.

Range views are about adapting ranges with view layers, and reading through those layers in lazy mode. Ranges are "pull based", in that components ask for the next value.
Pipes are about sending pieces of data as they come along in a collection through a pipeline, and let them land in a destination. Pipes are "push based", in that components wait for the next value.

Ranges and pipes have overlapping components such as `transform` and `filter`. But pipes do things like ranges can't do, such as `pipes::mux`, `pipes::fork` and `pipes:unzip`, and ranges do things that pipes can't do, like infinite ranges.

It is possible to use ranges and pipes in the same expression though:

```cpp
ranges::view::zip(dadChromosome, momChromosome)
>>= pipes::transform(crossover) // crossover takes and returns a tuple of 2 elements
>>= pipes::unzip(pipes::push_back(gameteChromosome1),
pipes::push_back(gameteChromosome2));
```

# Operating on several collections

The pipes library allows to manipulate several collections at the same time, with the `pipes::mux` helper.
Note that contrary to `range::view::zip`, `pipes::mux` doesn't require to use tuples:

```cpp
auto const input1 = std::vector{1, 2, 3, 4, 5};
auto const input2 = std::vector{10, 20, 30, 40, 50};

auto results = std::vector{};

pipes::mux(input1, input2) >>= pipes::filter ([](int a, int b){ return a + b < 40; })
>>= pipes::transform([](int a, int b) { return a * b; })
>>= pipes::push_back(results);

// results contains {10, 40, 90}
```

## Operating on all the possible combinations between several collections

`pipes::cartesian_product` takes any number of collections, and generates all the possible combinations between the elements of those collections. It sends each combination successively to the next pipe after it.

Like `pipes::mux`, `pipes::cartesian_product` doesn't use tuples but sends the values directly to the next pipe:

```cpp
auto const inputs1 = std::vector{1, 2, 3};
auto const inputs2 = std::vector{"up", "down"};

auto results = std::vector{};

pipes::cartesian_product(inputs1, inputs2)
>>= pipes::transform([](int i, std::string const& s){ return std::to_string(i) + '-' + s; })
>>= pipes::push_back(results);

// results contains {"1-up", "1-down", "2-up", "2-down", "3-up", "3-down"}
```

## Operating on adjacent elements of a collection

`pipes::adjacent` allows to send adjacent pairs of element from a range to a pipeline:

```cpp
auto const input = std::vector{1, 2, 4, 7, 11, 16};

auto results = std::vector{};

pipes::adjacent(input)
>>= pipes::transform([](int a, int b){ return b - a; })
>>= pipes::push_back(results);

// result contains {1, 2, 3, 4, 5};
```

## Operating on all combinations of elements of one collection

`pipes::combinations` sends each possible couple of different elements of a range to a pipeline:

```cpp
auto const inputs = std::vector{ 1, 2, 3, 4, 5 };

auto results = std::vector>{};

pipes::combinations(inputs)
>>= pipes::transform([](int i, int j){ return std::make_pair(i, j); })
>>= pipes::push_back(results);

/*
results contains:
{
{ 1, 2 }, { 1, 3 }, { 1, 4 }, { 1, 5 },
{ 2, 3 }, { 2, 4 }, { 2, 5 },
{ 3, 4 }, { 3, 5 },
{ 4, 5 }
}
/*
```

# End pipes

This library also provides end pipes, which are components that send data to a collection in an elaborate way. For example, the `map_aggregate` pipe receives `std::pair`s and adds them to a map with the following rule:
* if its key is not already in the map, insert the incoming pair in the map,
* otherwise, aggregate the value of the incoming pair with the existing one in the map.

Example:

```cpp
std::map entries = { {1, "a"}, {2, "b"}, {3, "c"}, {4, "d"} };
std::map entries2 = { {2, "b"}, {3, "c"}, {4, "d"}, {5, "e"} };
std::map results;

// results is empty

entries >>= pipes::map_aggregator(results, concatenateStrings);

// the elements of entries have been inserted into results

entries2 >>= pipes::map_aggregator(results, concatenateStrings);

// the new elements of entries2 have been inserter into results, the existing ones have been concatenated with the new values
// results contains { {1, "a"}, {2, "bb"}, {3, "cc"}, {4, "dd"}, {5, "e"} }
```

All components are located in the namespace `pipes`.

# Easy integration with STL algorithms

All pipes can be used as output iterators of STL algorithms:

```cpp
std::set_difference(begin(setA), end(setA),
begin(setB), end(setB),
transform(f) >>= filter(p) >>= map_aggregator(results, addValues));
```

# Streams support

The contents of an input stream can be sent to a pipe by using `read_in_stream`.
The end pipe `to_out_stream` sends data to an output stream.

The following example reads strings from the standard input, transforms them to upper case, and sends them to the standard output:

```cpp
std::cin >>= pipes::read_in_stream{}
>>= pipes::transform(toUpper)
>>= pipes::to_out_stream(std::cout);
```

# List of available pipes

* [General pipes](#general-pipes)
* [`dev_null`](#dev_null)
* [`drop`](#drop)
* [`drop_while`](#drop_while)
* [`filter`](#filter)
* [`fork`](#fork)
* [`partition`](#partition)
* [`read_in_stream`](#read_in_stream)
* [`switch`](#switch)
* [`stride`](#stride)
* [`take`](#take)
* [`tee`](#tee)
* [`transform`](#transform)
* [`unzip`](#unzip)
* [End pipes](#end-pipes-1)
* [`for_each`](#for_each)
* [`map_aggregator`](#map_aggregator)
* [`override`](#override)
* [`push_back`](#push_back)
* [`set_aggregator`](#set_aggregator)
* [`insert`](#insert)
* [`to_out_stream`](#to_out_stream)

## General pipes

### `dev_null`

`dev_null` is a pipe that doesn't do anything with the value it receives. It is useful for selecting only some data coming out of an algorithm that has several outputs.
An example of such algorithm is [`set_segregate`](https://github.com/joboccara/sets):

```cpp
std::set setA = {1, 2, 3, 4, 5};
std::set setB = {3, 4, 5, 6, 7};

std::vector inAOnly;
std::vector inBoth;

sets::set_seggregate(setA, setB,
pipes::push_back(inAOnly),
pipes::push_back(inBoth),
dev_null{});

// inAOnly contains {1, 2}
// inBoth contains {3, 4, 5}
```

### `drop`

`drop` is a pipe that ignores the first N incoming values, and sends on the values after them to the next pipe:

```cpp
auto const input = std::vector{ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10};

auto result = std::vector{};

input >>= pipes::drop(5)
>>= pipes::push_back(result);

// result contains { 6, 7, 8, 9, 10 }
```

### `drop_while`

`drop` is a pipe that ignores the incoming values until they stop satisfying a predicate, and sends on the values after them to the next pipe:

```cpp
auto const input = std::vector{ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10};

auto result = std::vector{};

input >>= pipes::drop_while([](int i){ return i != 6; })
>>= pipes::push_back(result);

// result contains { 6, 7, 8, 9, 10 }
```

### `filter`

`filter` is a pipe that takes a predicate `p` and, when it receives a value `x`, sends the result on to the next pipe iif `p(x)` is `true`.

```cpp
std::vector input = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10};
std::vector results;

input >>= pipes::filter([](int i){ return i % 2 == 0; })
>>= pipes::push_back(results);

// results contains {2, 4, 6, 8, 10}
```

### `fork`

`fork` is a pipe that takes any number of pipes, and sends a copy of the values it receives to each of those pipes.

```cpp
std::vector input = {1, 2, 3, 4, 5};
std::vector results1;
std::vector results2;
std::vector results3;

input >>= pipes::fork(pipes::push_back(results1),
pipes::push_back(results2),
pipes::push_back(results3));

// results1 contains {1, 2, 3, 4, 5}
// results2 contains {1, 2, 3, 4, 5}
// results3 contains {1, 2, 3, 4, 5}
```

### `join`

The `join` pipe receives collection and sends each element of each of those collections to the next pipe:

```cpp
auto const input = std::vector>{ {1, 2}, {3, 4}, {5, 6} };
auto results = std::vector{};

input >>= pipes::join >>= pipes::push_back(results);

// results contain {1, 2, 3, 4, 5, 6}
```

### `partition`

`partition` is a pipe that takes a predicate `p` and two other pipes. When it receives a value `x`, sends the result on to the first pipe iif `p(x)` is `true`, and to the second pipe if `p(x)` is `false`.

```cpp
std::vector input = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10};
std::vector evens;
std::vector odds;

input >>= pipes::partition([](int n){ return n % 2 == 0; },
pipes::push_back(evens),
pipes::push_back(odds));

// evens contains {2, 4, 6, 8, 10}
// odds contains {1, 3, 5, 7, 9}
```

### `read_in_stream`

`read_in_stream` is a template pipe that reads from an input stream. The template parameter indicates what type of data to request from the stream:

```cpp
auto const input = std::string{"1.1 2.2 3.3"};

std::istringstream(input) >>= pipes::read_in_stream{}
>>= pipes::transform([](double d){ return d * 10; })
>>= pipes::push_back(results);

// results contain {11, 22, 33};
```

### `switch`

`switch_` is a pipe that takes several `case_` branches. Each branch contains a predicate and a pipe. When it receives a value, it tries it successively on the predicates of each branch, and sends the value on to the pipe of the first branch where the predicate returns `true`.
The `default_` branch is equivalent to one that takes a predicate that returns always `true`. Having a `default_` branch is not mandatory.

```cpp
std::vector numbers = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10};
std::vector multiplesOf4;
std::vector multiplesOf3;
std::vector rest;

numbers >>= pipes::switch_(pipes::case_([](int n){ return n % 4 == 0; }) >>= pipes::push_back(multiplesOf4),
pipes::case_([](int n){ return n % 3 == 0; }) >>= pipes::push_back(multiplesOf3),
pipes::default_ >>= pipes::push_back(rest) ));

// multiplesOf4 contains {4, 8};
// multiplesOf3 contains {3, 6, 9};
// rest contains {1, 2, 5, 7, 10};
```

### `stride`

`stride` is a pipe that sends every `N`th element starting from the first one. Hence `N-1` elements after every `N`th element are ignored

```cpp
auto const input = std::vector{1, 2, 3, 4, 5, 6, 7, 8, 9, 10};

auto result = std::vector{};

input >>= pipes::stride(3)
>>= pipes::push_back(result);

// result contains {1, 4, 7, 10}
```

### `take`

`take` takes a number `N` and sends to the next pipe the first `N` element that it receives. The elements after it are ignored:

```cpp
auto const input = std::vector{1, 2, 3, 4, 5, 6, 7, 8, 9, 10};

auto result = std::vector{};

input >>= pipes::take(6)
>>= pipes::push_back(result);

// result contains {1, 2, 3, 4, 5, 6}
```

### `take_while`

`take_while` takes a predicate and sends to the next pipe the first values it receives. It stops when one of them doesn't satisfy the predicate:

```cpp
auto const input = std::vector{1, 2, 3, 4, 5, 6, 7, 8, 9, 10};

auto result = std::vector{};

input >>= pipes::take_while([](int i){ return i != 7; })
>>= pipes::push_back(result);

// result contains {1, 2, 3, 4, 5, 6}
```

### `tee`

`tee` is a pipe that takes one other pipe, and sends a copy of the values it receives to each of these pipes before sending them on to the next pipe.
Like the `tee` command on UNIX, this pipe is useful to take a peek at intermediary results.

```cpp
auto const inputs = std::vector{1, 2, 3, 4, 5, 6, 7, 8, 9, 10};
auto intermediaryResults = std::vector{};
auto results = std::vector{};

inputs
>>= pipes::transform([](int i) { return i * 2; })
>>= pipes::tee(pipes::push_back(intermediaryResults))
>>= pipes::filter([](int i){ return i >= 12; })
>>= pipes::push_back(results);

// intermediaryResults contains {2, 4, 6, 8, 10, 12, 14, 16, 18, 20}
// results contains {12, 14, 16, 18, 20}
```

### `transform`

`transform` is a pipe that takes a function `f` and, when it receives a value, applies `f` on it and sends the result on to the next pipe.

```cpp
std::vector input = {1, 2, 3, 4, 5};
std::vector results;

input >>= pipes::transform([](int i) { return i*2; })
>>= pipes::push_back(results);

// results contains {2, 4, 6, 8, 10}
```

### `unzip`

`unzip` is a pipe that takes N other pipes. When it receives a `std::pair` or `std::tuple` of size N (for `std::pair` N is 2), it sends each of its components to the corresponding output pipe:

```cpp
std::map entries = { {1, "one"}, {2, "two"}, {3, "three"}, {4, "four"}, {5, "five"} };
std::vector keys;
std::vector values;

entries >>= pipes::unzip(pipes::push_back(keys),
pipes::push_back(values)));

// keys contains {1, 2, 3, 4, 5};
// values contains {"one", "two", "three", "four", "five"};
```

## End pipes

### `for_each`

`for_each` takes a function (or function object) that sends to the data it receives to that function. One of its usages is to give legacy code that does not use STL containers access to STL algorithms:

```cpp
std::vector input = {1, 2, 3, 4, 5, 6, 7 ,8, 9, 10};

void legacyInsert(int number, DarkLegacyStructure const& thing); // this function inserts into the old non-STL container

DarkLegacyStructure legacyStructure = // ...

std::copy(begin(input), end(input), for_each([&legacyStructure](int number){ legacyInsert(number, legacyStructure); });
```

Read the [full story](https://www.fluentcpp.com/2017/11/24/how-to-use-the-stl-in-legacy-code/) about making legacy code compatible with the STL.

Note that `for_each` goes along with a helper function object, `do_`, that allows to perfom several actions sequentially on the output of the algorithm:

```cpp
std::copy(begin(input), end(input), pipes::for_each(pipes::do_([&](int i){ results1.push_back(i*2);}).
then_([&](int i){ results2.push_back(i+1);}).
then_([&](int i){ results3.push_back(-i);})));

```

### `insert`

In the majority of cases where it is used in algoritms, `std::inserter` forces its user to provide a position. It makes sense for un-sorted containers such as `std::vector`, but for sorted containers such as `std::set` we end up choosing begin or end by default, which doesn't make sense:

```cpp
std::vector v = {1, 3, -4, 2, 7, 10, 8};
std::set results;
std::copy(begin(v), end(v), std::inserter(results, end(results)));
```

`insert` removes this constraint by making the position optional. If no hint is passed, the containers is left to determine the correct position to insert:

```cpp
std::vector v = {1, 3, -4, 2, 7, 10, 8};
std::set results;
std::copy(begin(v), end(v), insert(results));

//results contains { -4, 1, 2, 3, 7, 8, 10 }
```
Read the [full story](https://www.fluentcpp.com/2017/03/17/smart-iterators-for-inserting-into-sorted-container/) about `insert`.

### `map_aggregator`

`map_aggregator` provides the possibility to embark an aggregator function in the inserter iterator, so that new elements whose **key is already present in the map** can be merged with the existent (e.g. have their values added together).

```cpp
std::vector> entries = { {1, "a"}, {2, "b"}, {3, "c"}, {4, "d"} };
std::vector> entries2 = { {2, "b"}, {3, "c"}, {4, "d"}, {5, "e"} };
std::map results;

std::copy(entries.begin(), entries.end(), map_aggregator(results, concatenateStrings));
std::copy(entries2.begin(), entries2.end(), map_aggregator(results, concatenateStrings));

// results contains { {1, "a"}, {2, "bb"}, {3, "cc"}, {4, "dd"}, {5, "e"} }
```

`set_aggreagator` provides a similar functionality for aggregating elements into sets.

Read the [full story](https://www.fluentcpp.com/2017/03/21/smart-iterator-aggregating-new-elements-existing-ones-map-set/) about `map_aggregator` and `set_aggregator`.

### `override`

`override` is the pipe equivalent to calling `begin` on an existing collection. The data that `override` receives overrides the first element of the container, then the next, and so on:

```cpp
std::vector input = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10};
std::vector results = {0, 0, 0, 0, 0, 0, 0, 0, 0, 0};

input >>= pipes::filter([](int i){ return i % 2 == 0; })
>>= pipes::override(results);

// results contains {2, 4, 6, 8, 10, 0, 0, 0, 0, 0};
```

`override` can also write on a specifc data member instead of erasing the complete structure in the outputs:

```cpp
struct P
{
int x = 0;
int y = 0;
};

auto const xs = std::vector{1, 2, 3, 4, 5};
auto results = std::vector

(5);

xs >>= pipes::override(results, &P::x);

// results now contains { {1,0}, {2,0}, {3,0}, {4,0}, {5,0} }
```

`override` can also send data to a specific setter function of the outputs:

```cpp
struct P
{
int x = 0;
int y = 0;

void setX(int aX){ x = aX; }
};

auto const xs = std::vector{1, 2, 3, 4, 5};
auto results = std::vector

(5);

xs >>= pipes::override(results, &P::setX);

// results now contains { {1,0}, {2,0}, {3,0}, {4,0}, {5,0} }
```

### `push_back`

`push_back` is a pipe that is equivalent to `std::back_inserter`. It takes a collection that has a `push_back` member function, such as a `std::vector`, and `push_back`s the values it receives into that collection.

### `set_aggregator`

Like `map_aggregator`, but inserting/aggregating into `std::set`s. Since `std::set` values are `const`, this pipe erases the element and re-inserts the aggregated value into the `std::set`.

```cpp
struct Value
{
int i;
std::string s;
};

bool operator==(Value const& value1, Value const& value2)
{
return value1.i == value2.i && value1.s == value2.s;
}

bool operator<(Value const& value1, Value const& value2)
{
if (value1.i < value2.i) return true;
if (value2.i < value1.i) return false;
return value1.s < value2.s;
}

Value concatenateValues(Value const& value1, Value const& value2)
{
if (value1.i != value2.i) throw std::runtime_error("Incompatible values");
return { value1.i, value1.s + value2.s };
}

int main()
{
std::vector entries = { Value{1, "a"}, Value{2, "b"}, Value{3, "c"}, Value{4, "d"} };
std::vector entries2 = { Value{2, "b"}, Value{3, "c"}, Value{4, "d"}, Value{5, "e"} };
std::set results;

std::copy(entries.begin(), entries.end(), pipes::set_aggregator(results, concatenateValues));
std::copy(entries2.begin(), entries2.end(), pipes::set_aggregator(results, concatenateValues));

// results contain { Value{1, "a"}, Value{2, "bb"}, Value{3, "cc"}, Value{4, "dd"}, Value{5, "e"} }
}
```

### `to_out_stream`

`to_out_stream` takes an output stream and sends incoming to it:

```cpp
auto const input = std::vector{"word1", "word2", "word3"};

input >>= pipes::transform(toUpper)
>>= pipes::to_out_stream(std::cout);

// sends "WORD1WORD2WORD3" to the standard output
```

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