Fast, orthogonal, open multi-methods. Supersedes yomm11.
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README.md

YOMM2

This is a complete rewrite of YOMM11, which is now deprecated. This library is much better, see here to find out why.

TL;DR

If you are familiar with the concept of open multi-methods, or prefer to learn by reading code, go directly to the synopsis

Open Methods in a Nutshell

Cross-cutting Concerns and the Expression Problem

You have a matrix math library. It deals with all sort of matrices: dense, diagonal, tri-diagonal, etc. Each matrix subtype has a corresponding class in a hierarchy rooted in Matrix.

Now you would like to render Matrix objects as JSON strings. The representation will vary depending on the exact type of the object; for example, if a matrix is a DiagonalMatrix, you only need to store the diagonal - the other elements are all zeroes.

This is an example of a "cross-cutting concern". How do you do it?

It turns out that OOP doesn't offer a good solution to this.

You can stick a pure virtual to_json function in the Matrix base class and override it in the subclasses. It is an easy solution but it has severe drawbacks. It requires you to change the Matrix class and its subclasses, and recompile the library. And now all the applications that use it will contain the to_json functions even if they don't need them, because of the way virtual functions are implemented.

Or you may resort on a "type switch": have the application test for each category and generate the JSON accordingly. This is tedious, error prone and, above all, not extensible. Adding a new matrix subclass requires updating all the type switches. The Visitor pattern also suffers from this flaw.

Wouldn't it be nice if you could add behavior to existing types, just as easily and unintrusively as you can extend existing class hierarchies via derivation? What if you could solve the so-called Expression Problem:

behaviors += types
types += behaviors

This is exactly what Open Methods are all about: solving the Expression Problem.

Let's look at an example.

// -----------------------------------------------------------------------------
// library code

struct matrix {
    virtual ~matrix() {}
    // ...
};

struct dense_matrix    : matrix { /* ... */ };
struct diagonal_matrix : matrix { /* ... */ };

// -----------------------------------------------------------------------------
// application code

#include <yorel/yomm2/cute.hpp>

using yorel::yomm2::virtual_;

register_class(matrix);
register_class(dense_matrix, matrix);
register_class(diagonal_matrix, matrix);

declare_method(string, to_json, (virtual_<const matrix&>));

define_method(string, to_json, (const dense_matrix& m)) {
    return "json for dense matrix...";
}

define_method(string, to_json, (const diagonal_matrix& m)) {
    return "json for diagonal matrix...";
}

int main() {
    yorel::yomm2::update_methods();

    shared_ptr<const matrix> a = make_shared<dense_matrix>();
    shared_ptr<const matrix> b = make_shared<diagonal_matrix>();

    cout << to_json(*a) << "\n"; // json for dense matrix
    cout << to_json(*b) << "\n"; // json for diagonal matrix

    return 0;
}

The declare_method line declares an open method called to_jsonthat takes one virtual argument of type const matrix& and returns a string. The virtual_<> decorator specifies that the argument must be taken into account to select the appropriate specialization. In essence, this is the same thing as having a virtual string to_json() const inside class Matrix - except that the virtual function lives outside of any classes, and you can add as many as you want without modifying the classes.

NOTE: DO NOT specify argument names, i.e. virtual_<const matrix&> arg is not permitted.

The following two define_method ... end_method blocks define two implementations for the to_json method: one for dense matrices, and one for diagonal matrices.

yorel::yomm2::update_methods() must be called before any method is called, and after dynamically loading and unloading shared libraries.

Multiple Dispatch

Methods can have more than one virtual argument. This is handy in certain situations, for example to implement binary operations on matrices:

// -----------------------------------------------------------------------------
// matrix * matrix

declare_method(
    shared_ptr<const matrix>,
    times,
    (virtual_<shared_ptr<const matrix>>, virtual_<shared_ptr<const matrix>>));

// catch-all matrix * matrix -> dense_matrix
define_method(
    shared_ptr<const matrix>,
    times,
    (shared_ptr<const matrix> a, shared_ptr<const matrix> b)) {
    return make_shared<dense_matrix>();
}

// diagonal_matrix * diagonal_matrix -> diagonal_matrix
define_method(
    shared_ptr<const matrix>,
    times,
    (shared_ptr<const diagonal_matrix> a, shared_ptr<const diagonal_matrix> b)) {
    return make_shared<diagonal_matrix>();
}

Performance

Don't worry about it. Open methods are almost as fast as ordinary virtual member functions once you turn on optimization (-O2). With both clang and gcc, dispatching a call to a method with one virtual argument is only 15-30% slower than calling the equivalent virtual member function. If the body of the method does any amount of work, the difference is unnoticeable. See the implementation notes for benchmarks and assembly listings.

Building and Installing

Make sure that you have the following dependencies:

  • a C++17 capable compiler

  • The following Boost libraries: Preprocessor, DynamicBitset, TypeTraits - version 1.65 or above is recommended

  • For tests: Boost.Test version 1.65 or above

  • cmake version 3.5 or above

Clone the repository:

git clone https://github.com/jll63/yomm2.git
cd yomm2

If you want to run the benchmarks, fetch the Google Benchmark submodule:

git submodule init
git submodule update

Create a build directory and run cmake then make:

mkdir build
cd build
cmake ..
make

If you want to run the tests:

cmake .. -DYOMM2_ENABLE_TESTS=1
make && ctest

If you also want to run the benchmarks (and in this case you really want a release build):

cmake .. -DYOMM2_ENABLE_TESTS=1 -DYOMM2_ENABLE_BENCHMARKS=1 -DCMAKE_BUILD_TYPE=Release
make && tests/benchmarks # wow it's fast!

Finally, if you like it and you want to install it:

# either:
sudo make install
# or:
make install DESTDIR=/path/to/my/libs

Going Further

The Reference is here.

The library comes with a series of examples: