I would like to be able to do something like the following:
struct A {};
template<typename T, typename U> struct B : public A {};
std::unique_ptr<A> chooseB(int i, int j)
{
// return B<T, U> where T and U vary with i and j (0 = int, 1 = double etc.)
}
i and j are not known at compile time. Potentially the list of types could be long enough that just forming a big conditional that enumerates all possible pairs of i and j could be painful.
Is there are nice way to write the chooseB function? I might potentially want to generalize this to more than two template parameters.
Time for some abuse.
We're going to write a function that will figure out which type corresponds to a given index. But we can't return that type - the return type must be known at compile-time. So instead we'll forward that along to a function that we provide. I'll start with the end-result:
std::unique_ptr<A> chooseB(int i, int j)
{
using choices = typelist<int, double>;
return pick_elem<std::unique_ptr<A>>(i, choices{},
[=](auto tag1){
return pick_elem<std::unique_ptr<A>>(j, choices{},
[=](auto tag2) {
using T1 = typename decltype(tag1)::type;
using T2 = typename decltype(tag2)::type;
return std::make_unique<B<T1, T2>>();
});
});
}
pick_elem takes three arguments: the index, the list of choices, and the function to forward along with. So we call it with the first index and call a lambda -- which in turns calls it with the second index and calls another lambda -- which finally makes our B.
You have to explicitly provide the return type to pick_elem<> because it needs to halt recursion somehow and that end-step will need to know what to return. So we start with some convenient metaprogramming helpers:
template <class... > struct typelist {};
template <class T> struct tag { using type = T; };
And then pick_elem is:
template <class R, class F>
R pick_elem(int , typelist<>, F )
{
throw std::runtime_error("wtf");
}
template <class R, class T, class... Ts, class F>
R pick_elem(int i, typelist<T, Ts...>, F f)
{
if (i == 0) {
return f(tag<T>{});
}
else {
return pick_elem<R>(i-1, typelist<Ts...>{}, f);
}
}
This can be generalized to arbitrarily many types by making chooseB variadic itself. In a way, this is actually cleaner than what I had before. chooseB() now additionally takes some non-deducible arguments that are the types we've figured out so far:
template <class... Ts>
std::unique_ptr<A> chooseB()
{
return std::make_unique<B<Ts...>>();
}
template <class... Ts, class Idx, class... Rest>
std::unique_ptr<A> chooseB(Idx i, Rest... rest)
{
using choices = typelist<int, double>;
return pick_elem<std::unique_ptr<A>>(i, choices{},
[=](auto tag){
return chooseB<Ts..., typename decltype(tag)::type>(rest...);
});
}
You can add some safety around this by asserting that the number of arguments is correct.
My pragmatic solution inspired by 0x499602D2 above. This will actually probably work for OK for the problem at hand - but I was interested in more general answers that don't rely on specific enumeration of all possibilities.
struct A
{
virtual ~A() = default;
virtual void printTypes() = 0;
};
template<typename T, typename U>
struct B : public A
{
virtual void printTypes() override
{
std::cout << typeid(T).name() << ", " << typeid(U).name() << std::endl;
}
};
int main()
{
std::map<std::pair<int, int>, std::function<std::unique_ptr<A> ()>> m =
{
{{0, 0}, [](){return std::unique_ptr<A>(new B<int, int>);}},
{{0, 1}, [](){return std::unique_ptr<A>(new B<int, double>);}},
{{1, 0}, [](){return std::unique_ptr<A>(new B<double, int>);}},
{{1, 1}, [](){return std::unique_ptr<A>(new B<double, double>);}}
};
for (int i = 0; i < 2; ++i)
{
for (int j = 0; j < 2; ++j)
{
auto a = m[std::make_pair(i, j)]();
a->printTypes();
}
}
}
You can map both numbers to instantiations of the base class:
#define FWD(x) std::forward<decltype(x)>((x))
auto p=[](auto&&l,auto&&r){return std::make_pair(FWD(l),FWD(r));};
std::unique_ptr<A> chooseB(int i, int j) {
std::map<std::pair<int,int>,std::unique_ptr<A>> m;
m.emplace(p(p(0,0),std::make_unique<B<int,int>>()));
m.emplace(p(p(0,1),std::make_unique<B<int,double>>()));
m.emplace(p(p(1,0),std::make_unique<B<double,int>>()));
m.emplace(p(p(1,1),std::make_unique<B<double,double>>()));
/* and so on for different (i,j) */
return std::move(m[p(i,j)]);
}
If you want to generalize this for more than two parameters, then have the function take a parameter pack (Args&&...) possibly SFINAE-ified to all integers, and use a std::tuple<std::decay_t<Args...>> instead of a pair.
Make a jump table and dispatch.
template<size_t I, class... Ts>
std::unique_ptr<A> do_make() {
using T = std::tuple_element_t<I / sizeof...(Ts), std::tuple<Ts...>>;
using U = std::tuple_element_t<I % sizeof...(Ts), std::tuple<Ts...>>;
return std::make_unique<B<T,U>>();
}
template<class... Ts, size_t...Is>
std::unique_ptr<A> make(size_t i, size_t j, std::index_sequence<Is...>) {
using fptr_t = std::unique_ptr<A> (*)();
static constexpr fptr_t table[] = { do_make<Is, Ts...> ...};
return table[ i * sizeof...(Ts) + j]();
}
template<class... Ts>
std::unique_ptr<A> make(size_t i, size_t j) {
return make<Ts...>(i, j, std::make_index_sequence<sizeof...(Ts) * sizeof...(Ts)>());
}
Related
At work, I ran into a situation where the best type to describe the result returned from a function would be std::variant<uint64_t, uint64_t> - of course, this isn't valid C++, because you can't have two variants of the same type. I could represent this as a std::pair<bool, uint64_t>, or where the first element of the pair is an enum, but this is a special case; a std::variant<uint64_t, uint64_t, bool> isn't so neatly representable, and my functional programming background really made me want Either - so I went to try to implement it, using the Visitor pattern as I have been able to do in other languages without native support for sum types:
template <typename A, typename B, typename C>
class EitherVisitor {
virtual C onLeft(const A& left) = 0;
virtual C onRight(const B& right) = 0;
};
template <typename A, typename B>
class Either {
template <typename C>
virtual C Accept(EitherVisitor<A, B, C> visitor) = 0;
};
template <typename A, typename B>
class Left: Either<A, B> {
private:
A value;
public:
Left(const A& valueIn): value(valueIn) {}
template <typename C>
virtual C Accept(EitherVisitor<A, B, C> visitor) {
return visitor.onLeft(value);
}
};
template <typename A, typename B>
class Right: Either<A, B> {
private:
B value;
public:
Right(const B& valueIn): value(valueIn) {}
template <typename C>
virtual C Accept(EitherVisitor<A, B, C> visitor) {
return visitor.onRight(value);
}
};
C++ rejects this, because the template method Accept cannot be virtual. Is there a workaround to this limitation, that would allow me to correctly represent the fundamental sum type in terms of its f-algebra and catamorphism?
Perhaps the simplest solution is a lightweight wrapper around T for Right and Left?
Basically a strong type alias (could also use Boost's strong typedef)
template<class T>
struct Left
{
T val;
};
template<class T>
struct Right
{
T val;
};
And then we can distinguish between them for visitation:
template<class T, class U>
using Either = std::variant<Left<T>, Right<U>>;
Either<int, int> TrySomething()
{
if (rand() % 2 == 0) // get off my case about rand(), I know it's bad
return Left<int>{0};
else
return Right<int>{0};
}
struct visitor
{
template<class T>
void operator()(const Left<T>& val_wrapper)
{
std::cout << "Success! Value is: " << val_wrapper.val << std::endl;
}
template<class T>
void operator()(const Right<T>& val_wrapper)
{
std::cout << "Failure! Value is: " << val_wrapper.val << std::endl;
}
};
int main()
{
visitor v;
for (size_t i = 0; i < 10; ++i)
{
auto res = TrySomething();
std::visit(v, res);
}
}
Demo
std::variant<X,X> is valid C++.
It is a bit awkward to use, because std::visit doesn't give you the index, and std::get<X> won't work either.
The way you can work around this is to create a variant-of-indexes, which is like a strong enum.
template<std::size_t i>
using index_t = std::integral_constant<std::size_t, i>;
template<std::size_t i>
constexpr index_t<i> index = {};
template<std::size_t...Is>
using number = std::variant< index_t<Is>... >;
namespace helpers {
template<class X>
struct number_helper;
template<std::size_t...Is>
struct number_helper<std::index_sequence<Is...>> {
using type=number<Is...>;
};
}
template<std::size_t N>
using alternative = typename helpers::number_helper<std::make_index_sequence<N>>::type;
we can then extract the alternative from a variant:
namespace helpers {
template<class...Ts, std::size_t...Is, class R=alternative<sizeof...(Ts)>>
constexpr R get_alternative( std::variant<Ts...> const& v, std::index_sequence<Is...> ) {
constexpr R retvals[] = {
R(index<Is>)...
};
return retvals[v.index()];
}
}
template<class...Ts>
constexpr alternative<sizeof...(Ts)> get_alternative( std::variant<Ts...> const& v )
{
return helpers::get_alternative(v, std::make_index_sequence<sizeof...(Ts)>{});
}
so now you have a std::variant<int, int>, you can
auto which = get_alternative( var );
and which is a variant, represented at runtime by an integer which is the index of the active type in var. You can:
std::variant<int, int> var( std::in_place_index_t<1>{}, 7 );
auto which = get_alternative( var );
std::visit( [&var](auto I) {
std::cout << std::get<I>(var) << "\n";
}, get_alternative(var) );
and get access to which of the alternative possibilities in var is active with a compile time constant.
The get_alternative(variant), I find, makes variant<X,X,X> much more usable, and fills in the hole I think you might be running into.
Live example.
Now if you don't need a compile-time index of which one is active, you can just call var.index(), and visit via visit( lambda, var ).
When you construct the variant, you do need the compile time index to do a variant<int, int> var( std::in_place_index_t<0>{}, 7 ). The wording is a bit awkward, because while C++ supports variants of multiples of the same type, it considers them a bit less likely than a "standard" disjoint variant outside of generic code.
But I've used this alternative and get_alternative like code to support functional programming like data glue code before.
I am struggling with an implementation of the Cartesian product for
multiple indices with a given range 0,...,n-1.
The basic idea is to have a function:
cartesian_product<std::size_t range, std::size_t sets>()
with an output array that contains tuples that hold the different products
[(0,..,0), (0,...,1), (0,...,n-1),...., (n-1, ..., n-1)]
An simple example would be the following:
auto result = cartesian_product<3, 2>();
with the output type std::array<std::tuple<int, int>, (3^2)>:
[(0,0), (0,1), (0,2), (1,0), (1,1), (1,2), (2,0), (2,1), (2,2)]
My main problem is that my version of the Cartesian product is slow and creates a stack overflow if you choose to have more than 5 sets. I believe that my code has too many recursions and temporary variables.
My implementation (C++17) can be found here: cartesian_product
#include <stdio.h>
#include <iostream>
#include <tuple>
template<typename T, std::size_t ...is>
constexpr auto flatten_tuple_i(T tuple, std::index_sequence<is...>) {
return std::tuple_cat(std::get<is>(tuple)...);
}
template<typename T>
constexpr auto flatten_tuple(T tuple) {
return flatten_tuple_i(tuple, std::make_index_sequence<std::tuple_size<T>::value>{});
}
template<std::size_t depth, typename T>
constexpr auto recursive_flatten_tuple(T tuple){
if constexpr(depth <= 1){
return tuple;
}else{
return recursive_flatten_tuple<depth-1>(flatten_tuple(tuple));
}
}
template<std::size_t depth, typename T, std::size_t ...is>
constexpr auto wdh(T&& tuple, std::index_sequence<is...>){
if constexpr (depth == 0) {
return tuple;
}else{
//return (wdh<depth-1>(std::tuple_cat(tuple, std::make_tuple(is)),std::make_index_sequence<sizeof...(is)>{})...);
return std::make_tuple(wdh<depth-1>(std::tuple_cat(tuple, std::make_tuple(is)), std::make_index_sequence<sizeof...(is)>{})...);
}
}
template<std::size_t sets, typename T, std::size_t ...is>
constexpr auto to_array(T tuple, std::index_sequence<is...>){
if constexpr (sets == 0){
auto t = (std::make_tuple(std::get<is>(tuple)),...);
std::array<decltype(t), sizeof...(is)> arr = {std::make_tuple(std::get<is>(tuple))...};
//decltype(arr)::foo = 1;
return arr;
}else{
auto t = ((std::get<is>(tuple)),...);
std::array<decltype(t), sizeof...(is)> arr = {std::get<is>(tuple)...};
return arr;
}
}
template<std::size_t sets, std::size_t ...is>
constexpr auto ct_i(std::index_sequence<is...>){
if constexpr (sets == 0){
auto u = std::tuple_cat(wdh<sets>(std::make_tuple(is), std::make_index_sequence<sizeof...(is)>{})...);
auto arr = to_array<sets>(u, std::make_index_sequence<std::tuple_size<decltype(u)>::value>{});
return arr;
}else {
auto u = std::tuple_cat(wdh<sets>(std::make_tuple(is), std::make_index_sequence<sizeof...(is)>{})...);
auto r = recursive_flatten_tuple<sets>(u);
auto d = to_array<sets>(r, std::make_index_sequence<std::tuple_size<decltype(r)>::value>{});
return d;
}
}
template<std::size_t range, std::size_t sets>
constexpr auto cartesian_product(){
static_assert( (range > 0), "lowest input must be cartesian<1,1>" );
static_assert( (sets > 0), "lowest input must be cartesian<1,1>" );
return ct_i<sets-1>(std::make_index_sequence<range>{});
}
int main()
{
constexpr auto crt = cartesian_product<3, 2>();
for(auto&& ele : crt){
std::cout << std::get<0>(ele) << " " << std::get<1>(ele) << std::endl;
}
return 0;
}
Since I was also working on a solution I thought I post it aswell (although very similar to Artyer's answer). Same premise, we replace the tuple with an array and just iterate over the elements, incrementing them one by one.
Note that the power function is broken, so if you need power values <0 or non-integer types you have to fix it.
template <typename It, typename T>
constexpr void setAll(It begin, It end, T value)
{
for (; begin != end; ++begin)
*begin = value;
}
template <typename T, std::size_t I>
constexpr void increment(std::array<T, I>& counter, T max)
{
for (auto idx = I; idx > 0;)
{
--idx;
if (++counter[idx] >= max)
{
setAll(counter.begin() + idx, counter.end(), 0); // because std::fill is not constexpr yet
}
else
{
break;
}
}
}
// std::pow is not constexpr
constexpr auto power = [](auto base, auto power)
{
auto result = base;
while (--power)
result *= base;
return result;
};
template<std::size_t range, std::size_t sets>
constexpr auto cartesian_product()
{
std::array<std::array<int, sets>, power(range, sets)> products{};
std::array<int, sets> currentSet{};
for (auto& product : products)
{
product = currentSet;
increment(currentSet, static_cast<int>(range));
}
return products;
}
int main()
{
constexpr auto crt = cartesian_product<5, 3>();
for (auto&& ele : crt)
{
for (auto val : ele)
std::cout << val << " ";
std::cout << "\n";
}
return 0;
}
Example
With Boost.Mp11, this is... alright, it's not a one-liner, but it's still not so bad:
template <typename... Lists>
using list_product = mp_product<mp_list, Lists...>;
template <typename... Ts>
constexpr auto list_to_tuple(mp_list<Ts...>) {
return std::make_tuple(int(Ts::value)...);
}
template <typename... Ls>
constexpr auto list_to_array(mp_list<Ls...>) {
return std::array{list_to_tuple(Ls{})...};
}
template <size_t R, size_t N>
constexpr auto cartesian_product()
{
using L = mp_repeat_c<mp_list<mp_iota_c<R>>, N>;
return list_to_array(mp_apply<list_product, L>{});
}
With C++20, you can declare the two helper function templates as lambdas inside of cartesian_product, which makes this read nicer (top to bottom instead of bottom to top).
Explanation of what's going on, based on the OP example of cartesian_product<3, 2>:
mp_iota_c<R> gives us the list [0, 1, 2] (but as integral constant types)
mp_repeat_c<mp_list<mp_iota_c<R>>, N> gives us [[0, 1, 2], [0, 1, 2]]. We just repeat the list, but we want a list of lists (hence the extra mp_list in the middle).
mp_apply<list_product, L> does mp_product, which is a cartesian product of all the lists you pass in... sticking the result in an mp_list. This gives you [[0, 0], [0, 1], [0, 2], ..., [2, 2]], but as an mp_list of mp_list of integral constants.
At this point the hard part is over, we just have to convert the result back to an array of tuples. list_to_tuple takes an mp_list of integral constants and turns that into a tuple<int...> with the right values. And list_to_array takes an mp_list of mp_lists of integral constants and turns that into an std::array of tuples.
A slightly different approach using just the single helper function:
template <template <typename...> class L,
typename... Ts, typename F>
constexpr auto unpack(L<Ts...>, F f) {
return f(Ts{}...);
}
template <size_t R, size_t N>
constexpr auto cartesian_product()
{
using P = mp_apply_q<
mp_bind_front<mp_product_q, mp_quote<mp_list>>,
mp_repeat_c<mp_list<mp_iota_c<R>>, N>>;
return unpack(P{},
[](auto... lists){
return std::array{
unpack(lists, [](auto... values){
return std::make_tuple(int(values)...);
})...
};
});
}
This approach is harder to read though, but it's the same algorithm.
You can do this without recursion easily. Notice that each tuple is the digits of numbers from 0 to range ** sets in base range, so you could increment a counter (Or apply to a std::index_sequence) and calculate each value one after the other.
Here's an implementation (That returns a std::array of std::arrays, which works mostly the same as std::tuples as you can get<N>, tuple_size and tuple_element<N> on a std::array, though if you really wanted you can convert them to std::tuples):
#include <cstddef>
#include <array>
namespace detail {
constexpr std::size_t ipow(std::size_t base, std::size_t exponent) noexcept {
std::size_t p = 1;
while (exponent) {
if (exponent % 2 != 0) {
p *= base;
}
exponent /= 2;
base *= base;
}
return p;
}
}
template<std::size_t range, std::size_t sets>
constexpr std::array<std::array<std::size_t, sets>, detail::ipow(range, sets)>
cartesian_product() noexcept {
constexpr std::size_t size = detail::ipow(range, sets);
std::array<std::array<std::size_t, sets>, size> result{};
for (std::size_t i = 0; i < size; ++i) {
std::size_t place = size;
for (std::size_t j = 0; j < sets; ++j) {
place /= range;
result[i][j] = (i / place) % range;
}
}
return result;
}
Here's a test link: https://www.onlinegdb.com/By_X9wbrI
Note that (empty_set)^0 is defined as a set containing an empty set here, but that can be changed by making ipow(0, 0) == 0 instead of 1
I was trying it out just for fun and I ended with pretty much the same idea as #Timo, just with a different format/style.
#include <iostream>
#include <array>
using namespace std;
template<size_t range, size_t sets>
constexpr auto cartesian_product() {
// how many elements = range^sets
constexpr auto size = []() {
size_t x = range;
size_t n = sets;
while(--n != 0) x *= range;
return x;
}();
auto products = array<array<size_t, sets>, size>();
auto counter = array<size_t, sets>{}; // array of zeroes
for (auto &product : products) {
product = counter;
// counter increment and wrapping/carry over
counter.back()++;
for (size_t i = counter.size()-1; i != 0; i--) {
if (counter[i] == range) {
counter[i] = 0;
counter[i-1]++;
}
else break;
}
}
return products;
}
int main() {
auto prods = cartesian_product<3, 6>();
}
I basically have a counter array which I increment manually, like so:
// given cartesian_product<3, 4>
[0, 0, 0, 0]
[0, 0, 0, 1]
[0, 0, 0, 2]
[0, 0, 1, 0] // carry over
...
...
[2, 2, 2, 2]
Pretty much just how you would do it by hand.
Example
If you want it in compile-time, you should only employ compile-time evaluations over compile-time data structures. As #Barry pointed above, using Boost.Mp11 greatly facilitates it. Of course you can do reimplement the relevant fundamental functions in plain C++17 on your own:
#include <iostream>
template<class T> struct Box {
using type = T;
};
template<class... Types> struct List {};
template<class Car, class Cdr> struct Cons;
template<class Car, class Cdr> using ConsT = typename Cons<Car, Cdr>::type;
template<class Car, class... Cdr> struct Cons<Car, List<Cdr...>>: Box<List<Car, Cdr...>> {};
using Nil = List<>;
template<std::size_t i, class L> struct Nth;
template<std::size_t i, class L> using NthT = typename Nth<i, L>::type;
template<std::size_t i, class... Ts> struct Nth<i, List<Ts...>>: std::tuple_element<i, std::tuple<Ts...>> {};
template<class L> struct Head;
template<class L> using HeadT = typename Head<L>::type;
template<class Car, class... Cdr> struct Head<List<Car, Cdr...>>: Box<Car> {};
template<class L> struct Tail;
template<class L> using TailT = typename Tail<L>::type;
template<class Car, class... Cdr> struct Tail<List<Car, Cdr...>>: Box<List<Cdr...>> {};
template<class... Lists> struct Concat;
template<class... Lists> using ConcatT = typename Concat<Lists...>::type;
template<class T, class... Rest> struct Concat<T, Rest...>: Cons<T, ConcatT<Rest...>> {};
template<class Head, class... Tail, class... Rest> struct Concat<List<Head, Tail...>, Rest...>: Cons<Head, ConcatT<List<Tail...>, Rest...>> {};
template<class... Rest> struct Concat<Nil, Rest...>: Concat<Rest...> {};
template<> struct Concat<>: Box<Nil> {};
template<class T, class Subspace> struct Prepend;
template<class T, class Subspace> using PrependT = typename Prepend<T, Subspace>::type;
template<class T, class... Points> struct Prepend<T, List<Points...>>: Box<List<ConsT<T, Points>...>> {};
template<class T> struct Prepend<T, Nil>: Box<List<List<T>>> {};
template<class Range, class Subspace> struct Product;
template<class Range, class Subspace> using ProductT = typename Product<Range, Subspace>::type;
template<class Range, class Subspace> struct Product: Concat<PrependT<HeadT<Range>, Subspace>, ProductT<TailT<Range>, Subspace>> {};
template<class Subspace> struct Product<Nil, Subspace>: Box<Nil> {};
template<std::size_t i> using IntValue = std::integral_constant<std::size_t, i>;
template<class Seq> struct IntegerSequence;
template<class Seq> using IntegerSequenceT = typename IntegerSequence<Seq>::type;
template<std::size_t... is> struct IntegerSequence<std::index_sequence<is...>>: Box<List<IntValue<is>...>> {};
template<std::size_t n> using Range = IntegerSequenceT<std::make_index_sequence<n>>;
template<std::size_t dimensions, std::size_t range> struct CartesianCube;
template<std::size_t dimensions, std::size_t range> using CartesianCubeT = typename CartesianCube<dimensions, range>::type;
template<std::size_t dimensions, std::size_t range> struct CartesianCube: Product<Range<range>, CartesianCubeT<dimensions - 1, range>> {};
template<std::size_t range> struct CartesianCube<0, range>: Box<Nil> {};
template<std::size_t i> std::ostream &operator<<(std::ostream &s, IntValue<i>) {
return s << '<' << i << '>';
}
template<class... Ts> std::ostream &operator<<(std::ostream &s, List<Ts...>);
namespace detail_ {
template<class L, std::size_t... is> std::ostream &printList(std::ostream &s, L, std::index_sequence<is...>) {
return ((s << (is == 0? "" : ", ") << NthT<is, L>{}), ...), s;
}
}
template<class... Ts> std::ostream &operator<<(std::ostream &s, List<Ts...>) {
return detail_::printList(s << "List{", List<Ts...>{}, std::index_sequence_for<Ts...>{}) << '}';
}
int main() {
std::cout << CartesianCubeT<2, 3>{} << '\n';
}
Note that CartesianCubeT here is actually a List of Lists of integral_constants. Once you have those, converting them into run-time values is trivial. Note that cartesian_product does not even have to be a function, since the whole data set is evaluated at compile-time it can be a templated value.
I'm using C++17. I'd like to get an element of a tuple that satisfies some type trait. It would be amazing if the trait could be supplied generically, but I'd be satisfied with a specific function for a certain trait. Usage might look something like this:
auto my_tuple = std::make_tuple { 0.f, 1 };
auto basic = get_if_integral (my_tuple);
auto fancy = get_if<std::is_floating_point> (my_tuple);
std::cout << basic; // '1'
std::cout << fancy; // '0.f'
Ideally this would fail to compile if more than one element satisfies the trait, like std::get (std::tuple).
Here's a surprisingly simple way without using recursion:
template <template <typename...> typename T, typename... Ts>
constexpr int index_of_integral(const T<Ts...>&)
{
const bool a[] = { std::is_integral_v<Ts>... };
for (int i = 0; i < sizeof...(Ts); ++i) if (a[i]) return i;
return -1;
}
template <typename T>
constexpr decltype(auto) get_if_integral(T&& t)
{
return std::get<index_of_integral(t)>(std::forward<T>(t));
}
int main()
{
constexpr auto t = std::make_tuple(3.14, 42, "xyzzy");
static_assert(get_if_integral(t) == 42);
}
It could easily be extended to be parametrized on the trait.
The only things that make it C++17 are the is_integral_v variable template and the single-argument static_assert. Everything else is C++14.
Note that in C++20 the for loop could be replaced with std::find and std::distance.
Ideally it should throw an exception instead of returning -1, but compilers don't seem to like that.
Inspired by this answer.
If I understand correctly what you want... I propose an helper struct gf_h ("get first helper") as follows
template <std::size_t, bool ...>
struct gf_h
{ };
template <std::size_t I, bool ... Bs>
struct gf_h<I, false, Bs...> : public gf_h<I+1u, Bs...>
{ };
template <std::size_t I, bool ... Bs>
struct gf_h<I, true, Bs...> : public std::integral_constant<std::size_t, I>
{ };
and a couple of functions that use it:
template <typename ... Us,
std::size_t I = gf_h<0, std::is_integral<Us>::value...>::value>
auto get_first_integral (std::tuple<Us...> const & t)
{ return std::get<I>(t); }
template <typename ... Us,
std::size_t I = gf_h<0, std::is_floating_point<Us>::value...>::value>
auto get_first_floating (std::tuple<Us...> const & t)
{ return std::get<I>(t); }
Observe that are SFINAE enabled/disabled functions, so are enabled only if there is an integral (or float) value in the tuple
The following is a full compiling example
#include <tuple>
#include <iostream>
template <std::size_t, bool ...>
struct gf_h
{ };
template <std::size_t I, bool ... Bs>
struct gf_h<I, false, Bs...> : public gf_h<I+1u, Bs...>
{ };
template <std::size_t I, bool ... Bs>
struct gf_h<I, true, Bs...> : public std::integral_constant<std::size_t, I>
{ };
template <typename ... Us,
std::size_t I = gf_h<0, std::is_integral<Us>::value...>::value>
auto get_first_integral (std::tuple<Us...> const & t)
{ return std::get<I>(t); }
template <typename ... Us,
std::size_t I = gf_h<0, std::is_floating_point<Us>::value...>::value>
auto get_first_floating (std::tuple<Us...> const & t)
{ return std::get<I>(t); }
int main()
{
auto tup1 = std::make_tuple(3.f, 2., 1, 0);
std::cout << get_first_integral(tup1) << std::endl; // 1
std::cout << get_first_floating(tup1) << std::endl; // 3
auto tup2 = std::make_tuple("abc", 4, 5);
std::cout << get_first_integral(tup2) << std::endl; // 4
// std::cout << get_first_floating(tup2) << std::endl; // error
auto tup3 = std::make_tuple("xyz", 6., 7.f);
// std::cout << get_first_integral(tup3) << std::endl; // error
std::cout << get_first_floating(tup3) << std::endl; // 6
}
Ok, I figured out a way to accomplish this in a way that is not generic over the trait, but that's good enough for my current purpose. Using if constexpr this really doesn't look too bad. I'm sure this isn't hugely idiomatic, but it works for me:
template <std::size_t Idx, typename... Us>
auto& get_if_integral_impl (std::tuple<Us...>& t)
{
static_assert (Idx < std::tuple_size_v<std::tuple<Us...>>,
"No integral elements in this tuple.");
if constexpr (std::is_integral<std::tuple_element_t<Idx, std::tuple<Us...>>>::value)
return std::get<Idx> (t);
else
return get_if_integral_impl<Idx + 1> (t);
}
template<typename... Us>
auto& get_if_integral (std::tuple<Us...>& t)
{
return get_if_integral_impl<0> (t);
}
auto tup = std::make_tuple (3.f, 2., 1, 0);
std::cout << get_if_integral (tup); // '1'
My use case is a little more complex, involving returning the first nested tuple which itself contains another type, but this should convey the basic idea.
I wanted to write a generic sum function like the following one but not in template syntax but in lambda syntax:
template<typename T>
auto Sum(T lastSummand)
{
return lastSummand;
}
template<typename T, typename... Ts>
auto Sum(T firstSummand, Ts... restSummands)
{
return firstSummand + Sum(restSummands...);
}
Because generic lambdas are mapped to templates it should be possible to do something like:
auto sum = [](auto firstSummand, auto... restSummands) { ... };
But I cannot figure out how to do the recursion using lambdas. Searching in this and other locations did not bring forward much.
In C++14 you don't actually need recursion to do that with generic lambdas.
As an example, you can do this:
#include<type_traits>
#include<iostream>
int main() {
auto l = [](auto... values) {
std::common_type_t<decltype(values)...> ret = {};
decltype(ret) _[] = { (ret += values)... };
(void)_;
return ret;
};
auto v = l(0, 0., 5, 4.2);
std::cout << v << std::endl;
}
Return type is given by the std::common_type_t of the given pack.
The rest of the code contains the common pattern usually used while waiting for fold expressions.
In C++17 it will become:
#include<iostream>
int main() {
auto l = [](auto... values) { return (values + ...); };
auto v = l(0, 0., 5, 4.2);
std::cout << v << std::endl;
}
See it on wandbox.
If you want to verify on the fly that given parameters are all of arithmetic types, you can use the bool trick as it follows:
auto l = [](auto... values) {
static_assert(
std::is_same<
std::integer_sequence<bool, true, std::is_arithmetic<decltype(values)>::value...>,
std::integer_sequence<bool, std::is_arithmetic<decltype(values)>::value..., true>
>::value, "!"
);
std::common_type_t<decltype(values)...> ret = {};
decltype(ret) _[] = { (ret += values)... };
(void)_;
return ret;
};
Well, i'm assuming you need a functor-like type to calculate the sum if you're using the lambda. If that's the case then I suppose you could write a small generic class to take the place of that lambda.
template < typename T > struct Sum
{
template < typename U >
T operator () (U v) const noexcept
{
return static_cast< T >(v);
}
template < typename U, typename... Values >
T operator () (U v, Values&&... vs) const noexcept
{
return static_cast< T >(v) + (*this)(std::forward< Values >(vs)...);
}
};
And used as:
auto sum = Sum< int >();
printf("%d\n", sum(23, 4.0, true, 7));
I wrote it in such way that the return type can be specified in advance. But I suppose you could adjust it to make that generic as well.
If this was not your intention then please ignore this answer.
What is currying?
How can currying be done in C++?
Please Explain binders in STL container?
1. What is currying?
Currying simply means a transformation of a function of several arguments to a function of a single argument. This is most easily illustrated using an example:
Take a function f that accepts three arguments:
int
f(int a,std::string b,float c)
{
// do something with a, b, and c
return 0;
}
If we want to call f, we have to provide all of its arguments f(1,"some string",19.7f).
Then a curried version of f, let's call it curried_f=curry(f) only expects a single argument, that corresponds to the first argument of f, namely the argument a. Additionally, f(1,"some string",19.7f) can also be written using the curried version as curried_f(1)("some string")(19.7f). The return value of curried_f(1) on the other hand is just another function, that handles the next argument of f. In the end, we end up with a function or callable curried_f that fulfills the following equality:
curried_f(first_arg)(second_arg)...(last_arg) == f(first_arg,second_arg,...,last_arg).
2. How can currying be achieved in C++?
The following is a little bit more complicated, but works very well for me (using c++11)... It also allows currying of arbitrary degree like so: auto curried=curry(f)(arg1)(arg2)(arg3) and later auto result=curried(arg4)(arg5). Here it goes:
#include <functional>
namespace _dtl {
template <typename FUNCTION> struct
_curry;
// specialization for functions with a single argument
template <typename R,typename T> struct
_curry<std::function<R(T)>> {
using
type = std::function<R(T)>;
const type
result;
_curry(type fun) : result(fun) {}
};
// recursive specialization for functions with more arguments
template <typename R,typename T,typename...Ts> struct
_curry<std::function<R(T,Ts...)>> {
using
remaining_type = typename _curry<std::function<R(Ts...)> >::type;
using
type = std::function<remaining_type(T)>;
const type
result;
_curry(std::function<R(T,Ts...)> fun)
: result (
[=](const T& t) {
return _curry<std::function<R(Ts...)>>(
[=](const Ts&...ts){
return fun(t, ts...);
}
).result;
}
) {}
};
}
template <typename R,typename...Ts> auto
curry(const std::function<R(Ts...)> fun)
-> typename _dtl::_curry<std::function<R(Ts...)>>::type
{
return _dtl::_curry<std::function<R(Ts...)>>(fun).result;
}
template <typename R,typename...Ts> auto
curry(R(* const fun)(Ts...))
-> typename _dtl::_curry<std::function<R(Ts...)>>::type
{
return _dtl::_curry<std::function<R(Ts...)>>(fun).result;
}
#include <iostream>
void
f(std::string a,std::string b,std::string c)
{
std::cout << a << b << c;
}
int
main() {
curry(f)("Hello ")("functional ")("world!");
return 0;
}
View output
OK, as Samer commented, I should add some explanations as to how this works. The actual implementation is done in the _dtl::_curry, while the template functions curry are only convenience wrappers. The implementation is recursive over the arguments of the std::function template argument FUNCTION.
For a function with only a single argument, the result is identical to the original function.
_curry(std::function<R(T,Ts...)> fun)
: result (
[=](const T& t) {
return _curry<std::function<R(Ts...)>>(
[=](const Ts&...ts){
return fun(t, ts...);
}
).result;
}
) {}
Here the tricky thing: For a function with more arguments, we return a lambda whose argument is bound to the first argument to the call to fun. Finally, the remaining currying for the remaining N-1 arguments is delegated to the implementation of _curry<Ts...> with one less template argument.
Update for c++14 / 17:
A new idea to approach the problem of currying just came to me... With the introduction of if constexpr into c++17 (and with the help of void_t to determine if a function is fully curried), things seem to get a lot easier:
template< class, class = std::void_t<> > struct
needs_unapply : std::true_type { };
template< class T > struct
needs_unapply<T, std::void_t<decltype(std::declval<T>()())>> : std::false_type { };
template <typename F> auto
curry(F&& f) {
/// Check if f() is a valid function call. If not we need
/// to curry at least one argument:
if constexpr (needs_unapply<decltype(f)>::value) {
return [=](auto&& x) {
return curry(
[=](auto&&...xs) -> decltype(f(x,xs...)) {
return f(x,xs...);
}
);
};
}
else {
/// If 'f()' is a valid call, just call it, we are done.
return f();
}
}
int
main()
{
auto f = [](auto a, auto b, auto c, auto d) {
return a * b * c * d;
};
return curry(f)(1)(2)(3)(4);
}
See code in action on here. With a similar approach, here is how to curry functions with arbitrary number of arguments.
The same idea seems to work out also in C++14, if we exchange the constexpr if with a template selection depending on the test needs_unapply<decltype(f)>::value:
template <typename F> auto
curry(F&& f);
template <bool> struct
curry_on;
template <> struct
curry_on<false> {
template <typename F> static auto
apply(F&& f) {
return f();
}
};
template <> struct
curry_on<true> {
template <typename F> static auto
apply(F&& f) {
return [=](auto&& x) {
return curry(
[=](auto&&...xs) -> decltype(f(x,xs...)) {
return f(x,xs...);
}
);
};
}
};
template <typename F> auto
curry(F&& f) {
return curry_on<needs_unapply<decltype(f)>::value>::template apply(f);
}
In short, currying takes a function f(x, y) and given a fixed Y, gives a new function g(x) where
g(x) == f(x, Y)
This new function may be called in situations where only one argument is supplied, and passes the call on to the original f function with the fixed Y argument.
The binders in the STL allow you to do this for C++ functions. For example:
#include <functional>
#include <iostream>
#include <vector>
using namespace std;
// declare a binary function object
class adder: public binary_function<int, int, int> {
public:
int operator()(int x, int y) const
{
return x + y;
}
};
int main()
{
// initialise some sample data
vector<int> a, b;
a.push_back(1);
a.push_back(2);
a.push_back(3);
// here we declare a function object f and try it out
adder f;
cout << "f(2, 3) = " << f(2, 3) << endl;
// transform() expects a function with one argument, so we use
// bind2nd to make a new function based on f, that takes one
// argument and adds 5 to it
transform(a.begin(), a.end(), back_inserter(b), bind2nd(f, 5));
// output b to see what we got
cout << "b = [" << endl;
for (vector<int>::iterator i = b.begin(); i != b.end(); ++i) {
cout << " " << *i << endl;
}
cout << "]" << endl;
return 0;
}
Simplifying Gregg's example, using tr1:
#include <functional>
using namespace std;
using namespace std::tr1;
using namespace std::tr1::placeholders;
int f(int, int);
..
int main(){
function<int(int)> g = bind(f, _1, 5); // g(x) == f(x, 5)
function<int(int)> h = bind(f, 2, _1); // h(x) == f(2, x)
function<int(int,int)> j = bind(g, _2); // j(x,y) == g(y)
}
Tr1 functional components allow you to write rich functional-style code in C++. As well, C++0x will allow for in-line lambda functions to do this as well:
int f(int, int);
..
int main(){
auto g = [](int x){ return f(x,5); }; // g(x) == f(x, 5)
auto h = [](int x){ return f(2,x); }; // h(x) == f(2, x)
auto j = [](int x, int y){ return g(y); }; // j(x,y) == g(y)
}
And while C++ doesn't provide the rich side-effect analysis that some functional-oriented programming languages perform, const analysis and C++0x lambda syntax can help:
struct foo{
int x;
int operator()(int y) const {
x = 42; // error! const function can't modify members
}
};
..
int main(){
int x;
auto f = [](int y){ x = 42; }; // error! lambdas don't capture by default.
}
Hope that helps.
Have a look at Boost.Bind which makes the process shown by Greg more versatile:
transform(a.begin(), a.end(), back_inserter(b), bind(f, _1, 5));
This binds 5 to f's second argument.
It’s worth noting that this is not currying (instead, it’s partial application). However, using currying in a general way is hard in C++ (in fact, it only recently became possible at all) and partial application is often used instead.
Other answers nicely explain binders, so I won't repeat that part here. I will only demonstrate how currying and partial application can be done with lambdas in C++0x.
Code example: (Explanation in comments)
#include <iostream>
#include <functional>
using namespace std;
const function<int(int, int)> & simple_add =
[](int a, int b) -> int {
return a + b;
};
const function<function<int(int)>(int)> & curried_add =
[](int a) -> function<int(int)> {
return [a](int b) -> int {
return a + b;
};
};
int main() {
// Demonstrating simple_add
cout << simple_add(4, 5) << endl; // prints 9
// Demonstrating curried_add
cout << curried_add(4)(5) << endl; // prints 9
// Create a partially applied function from curried_add
const auto & add_4 = curried_add(4);
cout << add_4(5) << endl; // prints 9
}
If you're using C++14 it's very easy:
template<typename Function, typename... Arguments>
auto curry(Function function, Arguments... args) {
return [=](auto... rest) {
return function(args..., rest...);
}; // don't forget semicolumn
}
You can then use it like this:
auto add = [](auto x, auto y) { return x + y; }
// curry 4 into add
auto add4 = curry(add, 4);
add4(6); // 10
Some great answers here. I thought I would add my own because it was fun to play around with the concept.
Partial function application: The process of "binding" a function with only some of its parameters, deferring the rest to be filled in later. The result is another function with fewer parameters.
Currying: Is a special form of partial function application where you can only "bind" a single argument at a time. The result is another function with exactly 1 fewer parameter.
The code I'm about to present is partial function application from which currying is possible, but not the only possibility. It offers a few benefits over the above currying implementations (mainly because it's partial function application and not currying, heh).
Applying over an empty function:
auto sum0 = [](){return 0;};
std::cout << partial_apply(sum0)() << std::endl;
Applying multiple arguments at a time:
auto sum10 = [](int a, int b, int c, int d, int e, int f, int g, int h, int i, int j){return a+b+c+d+e+f+g+h+i+j;};
std::cout << partial_apply(sum10)(1)(1,1)(1,1,1)(1,1,1,1) << std::endl; // 10
constexpr support that allows for compile-time static_assert:
static_assert(partial_apply(sum0)() == 0);
A useful error message if you accidentally go too far in providing arguments:
auto sum1 = [](int x){ return x;};
partial_apply(sum1)(1)(1);
error: static_assert failed "Attempting to apply too many arguments!"
Other answers above return lambdas that bind an argument and then return further lambdas. This approach wraps that essential functionality into a callable object. Definitions for operator() allow the internal lambda to be called. Variadic templates allow us to check for someone going too far, and an implicit conversion function to the result type of the function call allows us to print the result or compare the object to a primitive.
Code:
namespace detail{
template<class F>
using is_zero_callable = decltype(std::declval<F>()());
template<class F>
constexpr bool is_zero_callable_v = std::experimental::is_detected_v<is_zero_callable, F>;
}
template<class F>
struct partial_apply_t
{
template<class... Args>
constexpr auto operator()(Args... args)
{
static_assert(sizeof...(args) == 0 || !is_zero_callable, "Attempting to apply too many arguments!");
auto bind_some = [=](auto... rest) -> decltype(myFun(args..., rest...))
{
return myFun(args..., rest...);
};
using bind_t = decltype(bind_some);
return partial_apply_t<bind_t>{bind_some};
}
explicit constexpr partial_apply_t(F fun) : myFun(fun){}
constexpr operator auto()
{
if constexpr (is_zero_callable)
return myFun();
else
return *this; // a callable
}
static constexpr bool is_zero_callable = detail::is_zero_callable_v<F>;
F myFun;
};
Live Demo
A few more notes:
I chose to use is_detected mainly for enjoyment and practice; it serves the same as a normal type trait would here.
There could definitely be more work done to support perfect forwarding for performance reasons
The code is C++17 because it requires for constexpr lambda support in C++17
And it seems that GCC 7.0.1 is not quite there yet, either, so I used Clang 5.0.0
Some tests:
auto sum0 = [](){return 0;};
auto sum1 = [](int x){ return x;};
auto sum2 = [](int x, int y){ return x + y;};
auto sum3 = [](int x, int y, int z){ return x + y + z; };
auto sum10 = [](int a, int b, int c, int d, int e, int f, int g, int h, int i, int j){return a+b+c+d+e+f+g+h+i+j;};
std::cout << partial_apply(sum0)() << std::endl; //0
static_assert(partial_apply(sum0)() == 0, "sum0 should return 0");
std::cout << partial_apply(sum1)(1) << std::endl; // 1
std::cout << partial_apply(sum2)(1)(1) << std::endl; // 2
std::cout << partial_apply(sum3)(1)(1)(1) << std::endl; // 3
static_assert(partial_apply(sum3)(1)(1)(1) == 3, "sum3 should return 3");
std::cout << partial_apply(sum10)(1)(1,1)(1,1,1)(1,1,1,1) << std::endl; // 10
//partial_apply(sum1)(1)(1); // fails static assert
auto partiallyApplied = partial_apply(sum3)(1)(1);
std::function<int(int)> finish_applying = partiallyApplied;
std::cout << std::boolalpha << (finish_applying(1) == 3) << std::endl; // true
auto plus2 = partial_apply(sum3)(1)(1);
std::cout << std::boolalpha << (plus2(1) == 3) << std::endl; // true
std::cout << std::boolalpha << (plus2(3) == 5) << std::endl; // true
Currying is a way of reducing a function that takes multiple arguments into a sequence of nested functions with one argument each:
full = (lambda a, b, c: (a + b + c))
print full (1, 2, 3) # print 6
# Curried style
curried = (lambda a: (lambda b: (lambda c: (a + b + c))))
print curried (1)(2)(3) # print 6
Currying is nice because you can define functions that are simply wrappers around other functions with pre-defined values, and then pass around the simplified functions. C++ STL binders provide an implementation of this in C++.
I implemented currying with variadic templates as well (see Julian's answer). However, I did not make use of recursion or std::function. Note: It uses a number of C++14 features.
The provided example (main function) actually runs at compile time, proving that the currying method does not trump essential optimizations by the compiler.
The code can be found here: https://gist.github.com/Garciat/c7e4bef299ee5c607948
with this helper file: https://gist.github.com/Garciat/cafe27d04cfdff0e891e
The code still needs (a lot of) work, which I may or may not complete soon. Either way, I'm posting this here for future reference.
Posting code in case links die (though they shouldn't):
#include <type_traits>
#include <tuple>
#include <functional>
#include <iostream>
// ---
template <typename FType>
struct function_traits;
template <typename RType, typename... ArgTypes>
struct function_traits<RType(ArgTypes...)> {
using arity = std::integral_constant<size_t, sizeof...(ArgTypes)>;
using result_type = RType;
template <size_t Index>
using arg_type = typename std::tuple_element<Index, std::tuple<ArgTypes...>>::type;
};
// ---
namespace details {
template <typename T>
struct function_type_impl
: function_type_impl<decltype(&T::operator())>
{ };
template <typename RType, typename... ArgTypes>
struct function_type_impl<RType(ArgTypes...)> {
using type = RType(ArgTypes...);
};
template <typename RType, typename... ArgTypes>
struct function_type_impl<RType(*)(ArgTypes...)> {
using type = RType(ArgTypes...);
};
template <typename RType, typename... ArgTypes>
struct function_type_impl<std::function<RType(ArgTypes...)>> {
using type = RType(ArgTypes...);
};
template <typename T, typename RType, typename... ArgTypes>
struct function_type_impl<RType(T::*)(ArgTypes...)> {
using type = RType(ArgTypes...);
};
template <typename T, typename RType, typename... ArgTypes>
struct function_type_impl<RType(T::*)(ArgTypes...) const> {
using type = RType(ArgTypes...);
};
}
template <typename T>
struct function_type
: details::function_type_impl<typename std::remove_cv<typename std::remove_reference<T>::type>::type>
{ };
// ---
template <typename Args, typename Params>
struct apply_args;
template <typename HeadArgs, typename... Args, typename HeadParams, typename... Params>
struct apply_args<std::tuple<HeadArgs, Args...>, std::tuple<HeadParams, Params...>>
: std::enable_if<
std::is_constructible<HeadParams, HeadArgs>::value,
apply_args<std::tuple<Args...>, std::tuple<Params...>>
>::type
{ };
template <typename... Params>
struct apply_args<std::tuple<>, std::tuple<Params...>> {
using type = std::tuple<Params...>;
};
// ---
template <typename TupleType>
struct is_empty_tuple : std::false_type { };
template <>
struct is_empty_tuple<std::tuple<>> : std::true_type { };
// ----
template <typename FType, typename GivenArgs, typename RestArgs>
struct currying;
template <typename FType, typename... GivenArgs, typename... RestArgs>
struct currying<FType, std::tuple<GivenArgs...>, std::tuple<RestArgs...>> {
std::tuple<GivenArgs...> given_args;
FType func;
template <typename Func, typename... GivenArgsReal>
constexpr
currying(Func&& func, GivenArgsReal&&... args) :
given_args(std::forward<GivenArgsReal>(args)...),
func(std::move(func))
{ }
template <typename... Args>
constexpr
auto operator() (Args&&... args) const& {
using ParamsTuple = std::tuple<RestArgs...>;
using ArgsTuple = std::tuple<Args...>;
using RestArgsPrime = typename apply_args<ArgsTuple, ParamsTuple>::type;
using CanExecute = is_empty_tuple<RestArgsPrime>;
return apply(CanExecute{}, std::make_index_sequence<sizeof...(GivenArgs)>{}, std::forward<Args>(args)...);
}
template <typename... Args>
constexpr
auto operator() (Args&&... args) && {
using ParamsTuple = std::tuple<RestArgs...>;
using ArgsTuple = std::tuple<Args...>;
using RestArgsPrime = typename apply_args<ArgsTuple, ParamsTuple>::type;
using CanExecute = is_empty_tuple<RestArgsPrime>;
return std::move(*this).apply(CanExecute{}, std::make_index_sequence<sizeof...(GivenArgs)>{}, std::forward<Args>(args)...);
}
private:
template <typename... Args, size_t... Indices>
constexpr
auto apply(std::false_type, std::index_sequence<Indices...>, Args&&... args) const& {
using ParamsTuple = std::tuple<RestArgs...>;
using ArgsTuple = std::tuple<Args...>;
using RestArgsPrime = typename apply_args<ArgsTuple, ParamsTuple>::type;
using CurryType = currying<FType, std::tuple<GivenArgs..., Args...>, RestArgsPrime>;
return CurryType{ func, std::get<Indices>(given_args)..., std::forward<Args>(args)... };
}
template <typename... Args, size_t... Indices>
constexpr
auto apply(std::false_type, std::index_sequence<Indices...>, Args&&... args) && {
using ParamsTuple = std::tuple<RestArgs...>;
using ArgsTuple = std::tuple<Args...>;
using RestArgsPrime = typename apply_args<ArgsTuple, ParamsTuple>::type;
using CurryType = currying<FType, std::tuple<GivenArgs..., Args...>, RestArgsPrime>;
return CurryType{ std::move(func), std::get<Indices>(std::move(given_args))..., std::forward<Args>(args)... };
}
template <typename... Args, size_t... Indices>
constexpr
auto apply(std::true_type, std::index_sequence<Indices...>, Args&&... args) const& {
return func(std::get<Indices>(given_args)..., std::forward<Args>(args)...);
}
template <typename... Args, size_t... Indices>
constexpr
auto apply(std::true_type, std::index_sequence<Indices...>, Args&&... args) && {
return func(std::get<Indices>(std::move(given_args))..., std::forward<Args>(args)...);
}
};
// ---
template <typename FType, size_t... Indices>
constexpr
auto curry(FType&& func, std::index_sequence<Indices...>) {
using RealFType = typename function_type<FType>::type;
using FTypeTraits = function_traits<RealFType>;
using CurryType = currying<FType, std::tuple<>, std::tuple<typename FTypeTraits::template arg_type<Indices>...>>;
return CurryType{ std::move(func) };
}
template <typename FType>
constexpr
auto curry(FType&& func) {
using RealFType = typename function_type<FType>::type;
using FTypeArity = typename function_traits<RealFType>::arity;
return curry(std::move(func), std::make_index_sequence<FTypeArity::value>{});
}
// ---
int main() {
auto add = curry([](int a, int b) { return a + b; });
std::cout << add(5)(10) << std::endl;
}
These Links are relevant:
The Lambda Calculus page on Wikipedia has a clear example of currying
http://en.wikipedia.org/wiki/Lambda_calculus#Motivation
This paper treats currying in C/C++
http://asg.unige.ch/site/papers/Dami91a.pdf
C++20 provides bind_front for doing currying.
For older C++ version it can be implemented (for single argument) as follows:
template <typename TFunc, typename TArg>
class CurryT
{
private:
TFunc func;
TArg arg ;
public:
template <typename TFunc_, typename TArg_>
CurryT(TFunc_ &&func, TArg_ &&arg)
: func(std::forward<TFunc_>(func))
, arg (std::forward<TArg_ >(arg ))
{}
template <typename... TArgs>
auto operator()(TArgs &&...args) const
-> decltype( func(arg, std::forward<TArgs>(args)...) )
{ return func(arg, std::forward<TArgs>(args)...); }
};
template <typename TFunc, typename TArg>
CurryT<std::decay_t<TFunc>, std::remove_cv_t<TArg>> Curry(TFunc &&func, TArg &&arg)
{ return {std::forward<TFunc>(func), std::forward<TArg>(arg)}; }
https://coliru.stacked-crooked.com/a/82856e39da5fa50d
void Abc(std::string a, int b, int c)
{
std::cerr << a << b << c << std::endl;
}
int main()
{
std::string str = "Hey";
auto c1 = Curry(Abc, str);
std::cerr << "str: " << str << std::endl;
c1(1, 2);
auto c2 = Curry(std::move(c1), 3);
c2(4);
auto c3 = Curry(c2, 5);
c3();
}
Output:
str:
Hey12
Hey34
Hey35
If you use long chains of currying then std::shared_ptr optimization can be used to avoid copying all previous curried parameters to each new carried function.
template <typename TFunc>
class SharedFunc
{
public:
struct Tag{}; // For avoiding shadowing copy/move constructors with the
// templated constructor below which accepts any parameters.
template <typename... TArgs>
SharedFunc(Tag, TArgs &&...args)
: p_func( std::make_shared<TFunc>(std::forward<TArgs>(args)...) )
{}
template <typename... TArgs>
auto operator()(TArgs &&...args) const
-> decltype( (*p_func)(std::forward<TArgs>(args)...) )
{ return (*p_func)(std::forward<TArgs>(args)...); }
private:
std::shared_ptr<TFunc> p_func;
};
template <typename TFunc, typename TArg>
SharedFunc<
CurryT<std::decay_t<TFunc>, std::remove_cv_t<TArg>>
>
CurryShared(TFunc &&func, TArg &&arg)
{
return { {}, std::forward<TFunc>(func), std::forward<TArg>(arg) };
}
https://coliru.stacked-crooked.com/a/6e71f41e1cc5fd5c