Awesome
rpp
Minimal Rust-inspired C++20 STL replacement. Refer to the blog post for details.
Goals:
- Fast Compilation
- Debuggability
- High Performance
- Explicit Code
- Easy Metaprogramming
Integration
To use rpp in your project, run the following command (or manually download the source):
git submodule add https://github.com/TheNumbat/rpp
Then add the following lines to your CMakeLists.txt:
add_subdirectory(rpp)
target_link_libraries($your_target PRIVATE rpp)
target_include_directories($your_target PRIVATE ${RPP_INCLUDE_DIRS})
To use rpp with another build system, add rpp
to your include path, add rpp/rpp/impl/unify.cpp
to the build, and add either rpp/rpp/pos/unify.cpp
or rpp/rpp/w32/unify.cpp
based on your platform.
Platform Support
The following configurations are supported:
OS | Compiler | Arch |
---|---|---|
Windows | MSVC 19.39+ | x64 |
Linux | Clang 17+ | x64, aarch64 |
macOS | Clang 17+ | x64, aarch64 |
Except for MSVC on Windows, the gcc vector extensions (also implemented by clang) are used to emit SIMD operations. On Linux, other architectures should therefore work, but they have not been tested.
Other configurations (GCC, etc.) may be added in the future.
Examples
Logging
#include <rpp/base.h>
using namespace rpp;
i32 main() {
assert(true);
info("Information");
warn("Warning");
die("Fatal error (exits)");
}
Data Structures
#include <rpp/base.h>
#include <rpp/rc.h>
#include <rpp/stack.h>
#include <rpp/heap.h>
#include <rpp/tuple.h>
#include <rpp/variant.h>
using namespace rpp;
i32 main() {
Ref<i32> ref;
Box<i32> box;
Rc<i32> rc;
Arc<i32> arc;
Opt<i32> optional;
Storage<i32> storage;
String<> string;
String_View string_view;
Array<i32, 1> array;
Vec<i32> vec;
Slice<i32> slice;
Stack<i32> stack;
Queue<i32> queue;
Heap<i32> heap;
Map<i32, i32> map;
Pair<i32, i32> pair;
Tuple<i32, i32, i32> tuple;
Variant<i32, f32> variant{0};
Function<i32()> function{[]() { return 0; }};
}
Allocators
#include <rpp/base.h>
using namespace rpp;
i32 main() {
using A = Mallocator<"A">;
using B = Mallocator<"B">;
{
Vec<i32, A> a;
Vec<i32, B> b;
info("A allocated: %", a);
info("B allocated: %", b);
Box<i32, Mpool> pool;
info("Pool allocated: %", pool);
Region(R) {
Vec<i32, Mregion<R>> region{1, 2, 3};
info("Region allocated: %", region);
}
}
Profile::finalize(); // Print statistics and check for leaks
}
Trace
#include <rpp/base.h>
using namespace rpp;
i32 main() {
Profile::begin_frame();
Trace("Section") {
// ...
}
Profile::end_frame();
Profile::iterate_timings([](Thread::Id id, const Profile::Timing_Node& n) {
// ...
});
}
Reflection
#include <rpp/base.h>
using namespace rpp;
struct Foo {
i32 x;
Vec<i32> y;
};
RPP_RECORD(Foo, RPP_FIELD(x), RPP_FIELD(y));
template<Reflectable T>
struct Bar {
T t;
};
template<Reflectable T>
RPP_TEMPLATE_RECORD(Bar, T, RPP_FIELD(t));
i32 main() {
Bar<Foo> bar{Foo{42, Vec<i32>{1, 2, 3}}};
info("bar: %", bar);
}
Thread
#include <rpp/base.h>
#include <rpp/thread.h>
using namespace rpp;
i32 main() {
Thread::set_priority(Thread::Priority::high);
auto future = Thread::spawn([]() {
info("Hello from thread %!", Thread::this_id());
return 0;
});
info("Thread returned: %", future->block());
}
Async
#include <rpp/base.h>
#include <rpp/pool.h>
#include <rpp/asyncio.h>
using namespace rpp;
i32 main() {
Async::Pool<> pool;
auto coro = [](Async::Pool<>& pool) -> Async::Task<i32> {
co_await pool.suspend();
info("Hello from thread %!", Thread::this_id());
co_await Async::wait(pool, 100);
co_return 0;
};
auto task = coro(pool);
info("Task returned: %", task.block());
}
Math
#include <rpp/base.h>
#include <rpp/vmath.h>
#include <rpp/simd.h>
using namespace rpp;
i32 main() {
Vec3 v{0.0f, 1.0f, 0.0f};
Mat4 m = Mat4::translate(v);
info("Translated: %", m * v);
auto simd = SIMD::F32x4::set1(1.0f);
info("Dot product: %", SIMD::F32x4::dp(simd, simd));
}
Build and Run Tests
To build rpp and run the tests, run the following commands:
Windows
Assure MSVC 19.39 and cmake 3.17 (or newer) are installed and in your PATH.
mkdir build
cd build
cmake ..
cmake --build . -DRPP_TEST=ON
ctest -C Debug
For faster parallel builds, you can instead generate ninja build files with cmake -G Ninja ..
.
Linux
Assure clang-17 and cmake 3.17 (or newer) are installed.
mkdir build
cd build
CXX=clang++-17 cmake .. -DRPP_TEST=ON
make -j
ctest -C Debug
For faster parallel builds, you can instead generate ninja build files with cmake -G Ninja ..
.
To-Dos
- Modules
- Async
- scheduler priorities
- scheduler affinity
- scheduler work stealing
- io_uring for Linux file IO
- sockets
- use relaxed atomics on aarch64
- Types
- Result<T,E>
- Map: don't store hashes of integer keys
- Opt: specializations for null representations
- Allocators
- Allow reallocating the topmost stack allocation
- Per-thread pools
- Misc
- Range_Allocator: add second level of linear buckets
- Range_Allocator: reduce overhead