At this point, this library is experimental and it is a pure curiosity. No stability of interface or quality of implementation is guaranteed at. Use at your own risks.
Dyno solves the problem of runtime polymorphism better than vanilla C does. It provides a way to define interfaces that can be fulfilled non-intrusively, and it provides a fully customizable way of storing polymorphic objects and dispaching to virtual methods. It does not require inheritance, heap allocation or leaving the comfortable world of value semantics, and it can do so while outperforming vanilla C .
Dyno is pure-library implementation of what's also known as Rust traits,
Go interfaces, Haskell type classes, and virtual concepts. Under the
hood, it uses a C technique known as type erasure, which is the idea
behind std::any
, std::function
and many other useful types.
#include <dyno.hpp>
#include <iostream>
using namespace dyno::literals;
// Define the interface of something that can be drawn
struct Drawable : decltype(dyno::requires(
"draw"_s = dyno::function<void (dyno::T const&, std::ostream&)>
)) { };
// Define how concrete types can fulfill that interface
template <typename T>
auto const dyno::default_concept_map<Drawable, T> = dyno::make_concept_map(
"draw"_s = [](T const& self, std::ostream& out) { self.draw(out); }
);
// Define an object that can hold anything that can be drawn.
struct drawable {
template <typename T>
drawable(T x) : poly_{x} { }
void draw(std::ostream& out) const
{ poly_.virtual_("draw"_s)(poly_, out); }
private:
dyno::poly<Drawable> poly_;
};
struct Square {
void draw(std::ostream& out) const { out << "Square"; }
};
struct Circle {
void draw(std::ostream& out) const { out << "Circle"; }
};
void f(drawable const& d) {
d.draw(std::cout);
}
The library depends on Boost.Hana and Boost.CallableTraits. The unit
tests depend on libawful and the benchmarks on Google Benchmark, but
you don't need them to use the library. For local development, the
dependencies/install.sh
script can be used to install all the
dependencies automatically.
Dyno is a header-only library, so there's nothing to build per-se. Just
add the include/
directory to your compiler's header search path (and make
sure the dependencies are satisfied), and you're good to go. However, there
are unit tests, examples and benchmarks that can be built:
(cd dependencies && ./install.sh) # Install dependencies; will print a path to add to CMAKE_PREFIX_PATH
mkdir build
(cd build && cmake .. -DCMAKE_PREFIX_PATH="${PWD}/../dependencies/install") # Setup the build directory
cmake --build build --target examples # Build and run the examples
cmake --build build --target tests # Build and run the unit tests
cmake --build build --target check # Does both examples and tests
cmake --build build --target benchmarks # Build and run the benchmarks
In programming, the need for manipulating objects with a common interface but with a different dynamic type arises very frequently. C solves this with inheritance:
struct Drawable {
virtual void draw(std::ostream& out) const = 0;
};
struct Square : Drawable {
virtual void draw(std::ostream& out) const override final { ... }
};
struct Circle : Drawable {
virtual void draw(std::ostream& out) const override final { ... }
};
void f(Drawable const* drawable) {
drawable->draw(std::cout);
}
However, this approach has several drawbacks. It is
-
Intrusive
In order forSquare
andCircle
to fulfill theDrawable
interface, they both need to inherit from theDrawable
base class. This requires having the license to modify those classes, which makes inheritance very inextensible. For example, how would you make astd::vector<int>
fulfill theDrawable
interface? You simply can't. -
Incompatible with value semantics
Inheritance requires you to pass polymorphic pointers or references to objects instead of the objects themselves, which plays very badly with the rest of the language and the standard library. For example, how would you copy a vector ofDrawable
s? You'd need to provide a virtualclone()
method, but now you've just messed up your interface. -
Tightly coupled with dynamic storage
Because of the lack of value semantics, we usually end up allocating these polymorphic objects on the heap. This is both horribly inefficient and semantically wrong, since chances are we did not need the dynamic storage duration at all, and a simple stack-allocated object with the usual lifetime would have been enough. -
Slow
95% of the time, we end up calling a virtual method through a polymorphic pointer or reference. That requires three indirections: one for loading the pointer to the vtable inside the object, one for loading the right entry in the vtable, and one for the call to the function pointer. All of this but the indirect call can be avoided.
Unfortunately, this is the choice that C has made for us, and these are the rules that we are bound to when we need dynamic polymorphism. Or is it really?
Dyno solves the problem of runtime polymorphism in C without any of the drawbacks listed above, and many more goodies. It is:
-
Non-intrusive
An interface can be fulfilled by a type without requiring any modification to that type. Heck, a type can even fulfill the same interface in different ways! With Dyno, you can kiss ridiculous class hierarchies goodbye. -
100% based on value semantics
Polymorphic objects can be passed as-is, with their natural value semantics. You need to copy your polymorphic objects? Sure, just make sure they have a copy constructor. You want to make sure they don't get copied? Sure, mark it as deleted. With Dyno, sillyclone()
methods and the proliferation of pointers in APIs are things of the past. -
Not coupled with any specific storage strategy
The way a polymorphic object is stored is really an implementation detail, and it should not interfere with the way you use that object. Dyno gives you complete control over the way your objects are stored. You have a lot of small polymorphic objects? Sure, let's store them on the stack directly and avoid any allocation. Or maybe it makes sense for you to store things on the heap? Sure, go ahead. -
Fast
Storing a pointer to a vtable is just one of many different implementation strategies for performing dynamic dispatch. Dyno gives you complete control over how dynamic dispatch happens, and can in fact beat vtables. You've got a function that gets called in a hot loop? Sure, let's store it in the object directly and skip the indirection through the vtable. The classic vtable scheme works for you? Sure, let's use this and get exactly the same performance as usual vtables.
First, you start by defining a generic interface and giving it a name.
Dyno provides a simple domain specific language to do that. For example,
let's define an interface Drawable
that describes types that can be drawn:
#include <dyno.hpp>
using namespace dyno::literals;
struct Drawable : decltype(dyno::requires(
"draw"_s = dyno::function<void (dyno::T const&, std::ostream&)>
)) { };
This defines Drawable
as representing an interface for anything that has a
function called draw
taking a reference to a const object of any type, and
a std::ostream&
. Dyno calls these interfaces dynamic concepts, since
they describe sets of requirements to be fulfilled by a type (like C concepts).
However, unlike C concepts, these dynamic concepts are used to generate
runtime interfaces, hence the name dynamic. The above definition is basically
equivalent to the following, except we make no statement about whether draw
is a member function or not:
struct Drawable {
virtual void draw(std::ostream&) const = 0;
};
In some sense, the dyno::T const&
parameter used above represents the type of
the (polymorphic) this
pointer that would be passed in case of a traditional
virtual method. When the interface is defined, the next step is to actually
create a type that satisfies this interface. With inheritance, you would write
something like this:
struct Square : Drawable {
virtual void draw(std::ostream& out) const override final {
out << "square" << std::endl;
}
};
With Dyno, the polymorphism is non-intrusive and it is instead provided via what is called a concept map (after C 0x Concept Maps):
struct Square { /* ... */ };
template <>
auto const dyno::concept_map<Drawable, Square> = dyno::make_concept_map(
"draw"_s = [](Square const& square, std::ostream& out) {
out << "square" << std::endl;
}
);
This construct is the specialization of a C 14 variable template named
concept_map
defined in thedyno::
namespace. We then initialize that specialization withdyno::make_concept_map(...)
.
This concept map defines how the type Square
satisfies the Drawable
concept. In a sense, it maps the type Square
to its implementation of
the concept, which motivates the appellation. When a type satisfies the
requirements of a concept, we say that the type models (or is a model of)
that concept. Now that Square
is a model of the Drawable
concept, we'd
like to use a Square
polymorphically as a Drawable
. With traditional
inheritance, we would use a pointer to a base class like this:
void f(Drawable const* d) {
d->draw(std::cout);
}
f(new Square{});
With Dyno, polymorphism and value semantics are compatible, and the way
polymorphic types are passed around can be highly customized. To do this,
we'll need to define a type that can hold anything that's Drawable
. It is
that type, instead of a Drawable*
, that we'll be passing around to and from
polymorphic functions. To help define this wrapper, Dyno provides the
dyno::poly
container, which can hold an arbitrary object satisfying a given
concept. As you will see, dyno::poly
has a dual role: it stores the polymorphic
object and takes care of the dynamic dispatching of methods. All you need to do
is write a thin wrapper over dyno::poly
to give it exactly the desired interface:
struct drawable {
template <typename T>
drawable(T x) : poly_{x} { }
void draw(std::ostream& out) const
{ poly_.virtual_("draw"_s)(poly_, out); }
private:
dyno::poly<Drawable> poly_;
};
Let's break this down. First, we define a member poly_
that is a polymorphic
container for anything that models the Drawable
concept:
dyno::poly<Drawable> poly_;
Then, we define a constructor that allows constructing this container from an
arbitrary type T
:
template <typename T>
drawable(T x) : poly_{x} { }
The unsaid assumption here is that T
actually models the Drawable
concept.
Indeed, when you create a dyno::poly
from an object of type T
, Dyno
will go and look at the concept map defined for Drawable
and T
, if any. If
there's no such concept map, the library will report that we're trying to create
a dyno::poly
from a type that does not support it, and your program won't compile.
Finally, the strangest and most important part of the definition above is that
of the draw
method:
void draw(std::ostream& out) const
{ poly_.virtual_("draw"_s)(poly_, out); }
What happens here is that when .draw
is called on our drawable
object,
we'll actually perform a dynamic dispatch to the implementation of the "draw"
function for the object currently stored in the dyno::poly
, and call that.
Now, to create a function that accepts anything that's Drawable
, no need
to worry about pointers and ownership in your interface anymore:
void f(drawable d) {
d.draw(std::cout);
}
f(Square{});
By the way, if you're thinking that this is all stupid and you should have been using a template, you're right. However, consider the following, where you really do need runtime polymorphism:
drawable get_drawable() {
if (some_user_input())
return Square{};
else
return Circle{};
}
f(get_drawable());
Strictly speaking, you don't need to wrap dyno::poly
, but doing so puts a nice
barrier between Dyno and the rest of your code, which never has to worry
about how your polymorphic layer is implemented. Also, we largely ignored how
dyno::poly
was implemented in the above definition. However, dyno::poly
is
a very powerful policy-based container for polymorphic objects that can be
customized to one's needs for performance. Creating a drawable
wrapper makes
it easy to tweak the implementation strategy used by dyno::poly
for performance
without impacting the rest of your code.
The first aspect that can be customized in a dyno::poly
is the way the object
is stored inside the container. By default, we simply store a pointer to the
actual object, like one would do with inheritance-based polymorphism. However,
this is often not the most efficient implementation, and that's why dyno::poly
allows customizing it. To do so, simply pass a storage policy to dyno::poly
.
For example, let's define our drawable
wrapper so that it tries to store
objects up to 16
bytes on the stack, but then falls back to the heap if the
object is larger:
struct drawable {
template <typename T>
drawable(T x) : poly_{x} { }
void draw(std::ostream& out) const
{ poly_.virtual_("draw"_s)(poly_, out); }
private:
dyno::poly<Drawable, dyno::sbo_storage<16>> poly_;
// ^^^^^^^^^^^^^^^^^^^^^ storage policy
};
Notice that nothing except the policy changed in our definition. That is one
very important tenet of Dyno; these policies are implementation
details, and they should not change the way you write your code. With the
above definition, you can now create drawable
s just like you did before,
and no allocation will happen when the object you're creating the drawable
from fits in 16
bytes. When it does not fit, however, dyno::poly
will allocate
a large enough buffer on the heap.
Let's say you actually never want to do an allocation. No problem, just change
the policy to dyno::local_storage<16>
. If you try to construct a drawable
from an object that's too large to fit in the stack-allocated storage, your
program won't compile. Not only are we saving an allocation, but we're also
saving a pointer indirection every time we access the polymorphic object if
we compare to the traditional inheritance-based approach. By tweaking these
(important) implementation details for you specific use case, you can make
your program much more efficient than with classic inheritance.
Other storage policies are also provided, like dyno::remote_storage
and
dyno::non_owning_storage
. dyno::remote_storage
is the default one, which
always stores a pointer to a heap-allocated object. dyno::non_owning_storage
stores a pointer to an object that already exists, without worrying about
the lifetime of that object. It allows implementing non-owning polymorphic
views over objects, which is very useful.
Custom storage policies can also be created quite easily. See <dyno/storage.hpp>
for details.
When we introduced dyno::poly
, we mentioned that it had two roles; the first
is to store the polymorphic object, and the second one is to perform dynamic
dispatch. Just like the storage can be customized, the way dynamic dispatching
is performed can also be customized using policies. For example, let's define
our drawable
wrapper so that instead of storing a pointer to the vtable, it
instead stores the vtable in the drawable
object itself. This way, we'll
avoid one indirection each time we access a virtual function:
struct drawable {
template <typename T>
drawable(T x) : poly_{x} { }
void draw(std::ostream& out) const
{ poly_.virtual_("draw"_s)(poly_, out); }
private:
using Storage = dyno::sbo_storage<16>; // storage policy
using VTable = dyno::vtable<dyno::local<dyno::everything>>; // vtable policy
dyno::poly<Drawable, Storage, VTable> poly_;
};
Notice that nothing besides the vtable policy needs to change in the definition
of our drawable
type. Furthermore, if we wanted, we could change the storage
policy independently from the vtable policy. With the above, even though we are
saving all indirections, we are paying for it by making our drawable
object
larger (since it needs to hold the vtable locally). This could be prohibitive
if we had many functions in the vtable. Instead, it would make more sense to
store most of the vtable remotely, but only inline those few functions that we
call heavily. Dyno makes it very easy to do so by using Selectors, which
can be used to customize what functions a policy applies to:
struct drawable {
template <typename T>
drawable(T x) : poly_{x} { }
void draw(std::ostream& out) const
{ poly_.virtual_("draw"_s)(poly_, out); }
private:
using Storage = dyno::sbo_storage<16>;
using VTable = dyno::vtable<
dyno::local<dyno::only<decltype("draw"_s)>>,
dyno::remote<dyno::everything_else>
>;
dyno::poly<Drawable, Storage, VTable> poly_;
};
Given this definition, the vtable is actually split in two. The first part is
local to the drawable
object and contains only the draw
method. The second
part is a pointer to a vtable in static storage that holds the remaining methods
(the destructor, for example).
Dyno provides two vtable policies, dyno::local<>
and dyno::remote<>
.
Both of these policies must be customized using a Selector. The selectors
supported by the library are dyno::only<functions...>
, dyno::except<...>
,
and dyno::everything_else
(which can also be spelled dyno::everything
).
When defining a concept, it is often the case that one can provide a default
definition for at least some functions associated to the concept. For example,
by default, it would probably make sense to use a member function named draw
(if any) to implement the abstract "draw"
method of the Drawable
concept.
For this, one can use dyno::default_concept_map
:
template <typename T>
auto const dyno::default_concept_map<Drawable, T> = dyno::make_concept_map(
"draw"_s = [](auto const& t, std::ostream& out) { t.draw(out); }
);
Now, whenever we try to look at how some type T
fulfills the Drawable
concept, we'll fall back to the default concept map if no concept map was
defined. For example, we can create a new type Circle
:
struct Circle {
void draw(std::ostream& out) const {
out << "circle" << std::endl;
}
};
f(Circle{}); // prints "circle"
Circle
is automatically a model of Drawable
, even though we did not
explicitly define a concept map for Circle
. On the other hand, if we
were to define such a concept map, it would have precedence over the
default one:
template <>
auto dyno::concept_map<Drawable, Circle> = dyno::make_concept_map(
"draw"_s = [](Circle const& circle, std::ostream& out) {
out << "triangle" << std::endl;
}
);
f(Circle{}); // prints "triangle"
It is sometimes useful to define a concept map for a complete family of types
all at once. For example, we might want to make std::vector<T>
a model of
Drawable
, but only when T
can be printed to a stream. This is easily
achieved by using this (not so) secret trick:
template <typename T>
auto const dyno::concept_map<Drawable, std::vector<T>, std::void_t<decltype(
std::cout << std::declval<T>()
)>> = dyno::make_concept_map(
"draw"_s = [](std::vector<T> const& v, std::ostream& out) {
for (auto const& x : v)
out << x << ' ';
}
);
f(std::vector<int>{1, 2, 3}) // prints "1 2 3 "
Notice how we do not have to modify
std::vector
at all. How could we do this with classic polymorphism? Answer: no can do.