FunctionalPlus 0,0

helps you write concise and readable C++ code.


Build Status (License Boost 1.0)


helps you write concise and readable C++ code.


Great code should mostly be self-documenting, but while using C++ in reality you can find yourself dealing with low-level stuff like iterators or hand-written loops that distract from the actual essence of your code.

FunctionalPlus is a small header-only library supporting you in reducing code noise and in dealing with only one single level of abstraction at a time. By increasing brevity and maintainability of your code it can improve productivity (and fun!) in the long run. It pursues these goals by providing pure and easy-to-use functions that free you from implementing commonly used flows of control over and over again.

Say you have a list of numbers and are interested in the odd ones only.

bool is_odd(int x) { return x % 2 == 1; }

int main()
    typedef vector<int> Ints;
    Ints numbers = { 24, 11, 65, 44, 80, 18, 73, 90, 69, 18 };
    // todo: get odd values from numbers ...

There are different possibilities to attain your goal. Some of them are:

  1. write a (range based) for loop

     Ints odds;
     for (int x : numbers)
         if (is_odd(x))
  2. use std::copy_if from the STL

     Ints odds;
     std::copy_if(std::begin(numbers), std::end(numbers),
             std::back_inserter(odds), is_odd);
  3. use keep_if from FunctionalPlus

     auto odds = fplus::keep_if(is_odd, numbers);

If you think version 3 could be the one most pleasant to work with, you might like FunctionalPlus. And if you still think the hand-written for loop is easier to understand, also consider what would happen if the loop body (i.e. a corresponding lambda function in the call to fplus::keep_if) would be much longer. When reading keep_if you would still immediately know that odds can only contain elements that came from numbers and were selected by some, possibly complicated, predicate. In the for loop case you have no idea what is happening until you read the whole loop body. The loop version probably would need a comment at the top stating what the use of keep_if would tell at first glance.

More examples

Below you find some short examples showing nice things you can do with functions and containers using FunctionalPlus.

The same old song

You can test the content of a container for various properties, e.g.

#include "fplus/fplus.hpp"
#include <iostream>

int main()
    std::list<std::string> things = {"same old", "same old"};
    if (fplus::all_the_same(things))
        std::cout << "All things being equal." << std::endl;

The I in our team

There also are some convenience functions for retrieving properties of containers. For example you can count the occurrences of a character in a string.

#include "fplus/fplus.hpp"
#include <iostream>

int main()
    std::string team = "Our team is great. I love everybody I work with.";
    std::cout << "There actually are this many 'I's in team: " <<
        fplus::count("I", fplus::split_words(team, false)) << std::endl;


There actually are this many 'I's in team: 2

The cutest kitty

Finding the highest rated element in a container is very simple compared to a hand-written version.

#include "fplus/fplus.hpp"
#include <iostream>

struct cat
    std::string name_;
    double softness_;
    double temperature_;
    double size_;
    double roundness_;
    double fur_amount_;

int main()
    auto cuteness = [](const cat& c) -> double
        return c.softness_ * c.temperature_ * c.roundness_ *
            c.fur_amount_ - c.size_;
    std::vector<cat> cats = {
        {"Tigger",   5, 5, 5, 5, 5},
        {"Simba",    2, 9, 9, 2, 7},
        {"Muffin",   9, 4, 2, 8, 6},
        {"Garfield", 6, 5, 7, 9, 5}};

    auto cutest_cat = fplus::maximum_on(cuteness, cats);

    std::cout << cutest_cat.name_ <<
        " is happy and sleepy. *purr* *purr* *purr*" << std::endl;


Muffin is happy and sleepy. *purr* *purr* *purr*

Function composition, binding and map creation

Let’s say you have the following function given.

std::list<int> collatz_seq(int x);

And you want to create an std::map<std::uint64_t, std::string> containing string representations of the Collatz sequences for all numbers below 30. You can implement this nicely in a functional way too.

#include "fplus/fplus.hpp"
#include <iostream>

// std::list<std::uint64_t> collatz_seq(std::uint64_t x) { ... }

int main()
    typedef std::list<int> Ints;

    // [1, 2, 3 ... 29]
    auto numbers = fplus::generate_range<Ints>(1, 30);

    // A function that does [1, 2, 3, 4, 5] -> "[1 => 2 => 3 => 4 => 5]"
    auto show_ints = fplus::bind_1st_of_2(fplus::show_cont_with<Ints>, " => ");

    // A composed function that calculates a Collatz sequence and shows it.
    auto show_collats_seq = fplus::compose(collatz_seq, show_ints);

    // Associate the numbers with the string representation of their sequences.
    auto collatz_dict = fplus::create_map_with(show_collats_seq, numbers);

    // Print some of the sequences.
    std::cout << collatz_dict[13] << std::endl;
    std::cout << collatz_dict[17] << std::endl;


[13 => 40 => 20 => 10 => 5 => 16 => 8 => 4 => 2 => 1]
[17 => 52 => 26 => 13 => 40 => 20 => 10 => 5 => 16 => 8 => 4 => 2 => 1]

The functions shown not only work with default STL containers like std::vector, std::list, std::deque, std::string etc., but also with custom containers providing a similar interface.


The article “Functional programming in C++ with the FunctionalPlus library; today: HackerRank challange Gemstones” provides a smooth introduction into the library by showing how one could develop an elegant solution to a problem using the FunctionalPlus approach.

Type deduction and useful error messages

FunctionalPlus deduces types for you where possible. Let’s take one line of code from the Collatz example:

    auto show_collats_seq = fplus::compose(collatz_seq, show_ints);

collatz_seq is a function taking an uint64_t and returning a list<uint64_t>. show_ints takes a list<uint64_t> and returns a string. Thanks to making use of function_traits written by kennyim it is possible to automatically deduce the expression fplus::compose(collatz_seq, show_ints) being a function taking an uint64_t and returning a string, so you do not have to manually provide type hints to the compiler.

In case you would accidentally pass two functions whose “connecting type” does not match, you will get a nice error message telling you exactly that, because FunctionalPlus uses compile time assertions where feasible to guard you from the sometimes confusingly long error messages compilers like to generate when faced with type errors in function templates.

By changing the way you think about programming from “writing your own loops and nested ifs” to “using and composing small functions” you will first perhaps get more errors at compile time, but this will pay out in having fewer errors at runtime and in spending less time debugging.

Finding the functions you need

If you are looking for a specific FunctionalPlus function you do not know the name of yet, you can of course use the autocomplete feature of your IDE to browse the content of the namespace fplus. But the recommended way is to simply use the FunctionalPlus API search website. You can quickly search by keywords or (curried) function type signatures there.


The basic functions are fast, thanks to C++’s concept of abstraction without overhead. Here are some measurements from the first example, taken on a standard desktop PC, compiled with GCC and the O3 flag.

5000 random numbers, keep odd ones, 20000 consecutive runs accumulated

| Hand-written for loop | std::copy_if | fplus::keep_if |
|               0.632 s |      0.641 s |        0.627 s |

So the compiler seems to do a very good job in optimizing and inlining everything to basically equal machine code performance-wise.

The more complex functions though sometimes could be written in a more optimized way. If you use FunctionalPlus in a performance-critical scenario and profiling shows you need a faster version of a function please let me know or even help improving FunctionalPlus.

Additionally keep in mind that FunctionalPlus always produces copies and never operates in place. Even modern compilers often can not optimize these allocations away in chained calls.. Thanks to working with a multi-paradigm language one easily can combine manually optimized imperative code with fplus functions. Luckily experience (aka. profiling) shows that in most cases the vast majority of code in an application is not relevant for overall performance and memory consumption. So initially focusing on developer productivity and readability of code is a good idea.


A C++11-compatible compiler is needed. The tests run successfully on GCC 4.8, Clang 3.6 and Visual C++ 2015.

You can install FunctionalPlus in one of the following ways:

download manually

Just download/extract FunctionalPlus and tell your compiler to use the include directory.

using cmake

git clone
cd FunctionalPlus
mkdir build
cd build
cmake ..
sudo make install

Building the tests (optional) requires doctest. Unit Tests are disabled by default – they are enabled and executed by:

cmake -DUNITTEST=ON ..
make unittest

using cget

# Setup up toolchain to use c++11
cget init --std=c++11
# Test and install
cget install Dobiasd/FunctionalPlus


The functionality in this library initially grew due to my personal need for it while using C++ on a regular basis. I try my best to make it error free and as comfortable to use as I can. The API still might change in the future. If you have any suggestions, find errors, miss some functions or want to give general feedback/criticism, I’d love to hear from you. Of course, contributions are also very welcome.


Distributed under the Boost Software License, Version 1.0. (See accompanying file LICENSE_1_0.txt or copy at

Related Repositories



helps you write concise and readable C++ code. ...

Top Contributors

Dobiasd offa xtofl CrikeeIP pmalek GustavooPaiva ztdwu pfultz2 thiagobbt