Cap'n Proto VS cppcoro

Yeah I pretty much only use my own alternate container implementations (from KJ[0]), which avoid these footguns, but the result is everyone complains our project is written in Kenton-Language rather than C++ and there's no Stack Overflow for it and we can't hire engineers who know how to write it... oops.

[0] https://github.com/capnproto/capnproto/blob/v2/kjdoc/tour.md

- may massively reduce the latency involved.

Those sharing Cap'n Proto-encoded data may have particular interest. Cap'n Proto (https://capnproto.org) is fantastic at its core task - in-place serialization with zero-copy - and we wanted to make the IPC (inter-process communication) involving capnp-serialized messages be zero-copy, end-to-end.

That said, we paid equal attention to other varieties of payload; it's not limited to capnp-encoded messages. For example there is painless (<-- I hope!) zero-copy transmission of arbitrary combinations of STL-compliant native C++ data structures.

To help determine whether Flow-IPC is relevant to you we wrote an intro blog post. It works through an example, summarizes the available features, and has some performance results. https://www.linode.com/blog/open-source/flow-ipc-introductio...

Of course there's nothing wrong with going straight to the GitHub link and getting into the README and docs.

Currently Flow-IPC is for Linux. (macOS/ARM64 and Windows support could follow soon, depending on demand/contributions.)

FWIW, my C++ toolkit library, KJ, does the same thing.[0]

But presumably you could still write a condition predicate which looks at things which aren't actually part of the mutex-wrapped structure? Or does is the Rust type system able to enforce that the callback can only consider the mutex-wrapped value and values that are constant over the lifetime of the wait? (You need the latter e.g. if you are waiting for the mutex-wrapped value to compare equal to some local variable...)

[0] https://github.com/capnproto/capnproto/blob/e6ad6f919aeb381b...

The second one is to encode data in such a way that you can read it and operate on it directly from the buffer. You write data in a layout that is the same, or easily transformed as types in memory. To do that you usually need to encode with a known schema, only Sized types to efficiently compute fields locations as offsets in the buffer, and you usually represent pointers as offset into the encode. You can look at capnproto protocol for instance https://capnproto.org/

Worked well for Cap'n Proto (the cerealization protocol)! https://capnproto.org/

With all due respect, you read completely wrong.

* The very first use case for which Cap'n Proto was designed was to be the protocol that Sandstorm.io used to talk between sandbox and supervisor -- an explicitly adversarial security scenario.

* The documentation explicitly calls out how implementations should manage resource exhaustion problems like deep recursion depth (stack overflow risk).

* The implementation has been fuzz-tested multiple ways, including as part of Google's oss-fuzz.

* When there are security bugs, I issue advisories like this:

https://github.com/capnproto/capnproto/tree/v2/security-advi...

* The primary aim of the entire project is to be a Capability-Based Security RPC protocol.

I like how they use capability-based security [0] and use Cap'n Proto protocol. This is another technology that is slow to get broad adoption, but has many things going for when compared to e.g. Protocol Buffers (Cap'n Proto is created by the primary author of Protobuf v2, Kenton Varda).

[0] https://sandstorm.io/how-it-works#capabilities

[1] https://capnproto.org

Related but not Rust-specific: FlatBuffers, Cap'n Proto.

PS: Take a look at cppcoro; this might help as well, especially generator<>, if you're looking to generate numbers, and stuff;

This is the only viable implementation.

Kind of sounds like whatever library you were using provided leaky abstractions. Something like cppcoro provides really good abstractions for coroutines, the user really doesn't need to understand why any of it works.

Is there a usecase for copying/serializing such coroutines? If not, I would use the normal C++20 coroutines (cppcoro?).

C++ has the popular CppCoro library. Async_mutex is its equivalent of Tokio::sync::Mutex, providing exclusive access to data shared between tasks.

Because the whole application is running under a single thread there is no need for atomic operations in synchronization primitives(which most of the time requires seq_cst memory order and CMPXCHG which is an expensive instruction in CPU). for example what async_mutex would look like if it knows it's running in a single-threaded scheduler (a non-atomic state variable and waiters queue).

Maybe not old, but I wish cppcoro was still updated. It was such a nice start!

You can get generator<> from https://github.com/lewissbaker/cppcoro

It is possible to compose them more easily than described in the article; Lewis Baker's cppcoro library for example provides a recursive_generator<> type[0] that allows this without using any macros. It's up to the library part of coroutines to make things easy, end users are not expected to write low-level coroutine code themselves.

I wonder about the allocation elision. Return value optimization became mandatory, and some compilers can already elide calls to new/delete and malloc()/free() in normal code, so perhaps it will be possible to guarantee allocation elision in the future in the most used cases.

[0]: https://github.com/lewissbaker/cppcoro#recursive_generatort