FlatBuffers VS function2

I don't work at Cloudflare but follow their work and occasionally work on performance sensitive projects.

If I had to guess, they looked at the landscape a bit like I do and regarded Cap'n Proto, flatbuffers, SBE, etc. as being in one category apart from other data formats like Avro, protobuf, and the like.

So once you're committed to record'ish shaped (rather than columnar like Parquet) data that has an upfront parse time of zero (nominally, there could be marshalling if you transmogrify the field values on read), the list gets pretty short.

https://capnproto.org/news/2014-06-17-capnproto-flatbuffers-... goes into some of the trade-offs here.

Cap'n Proto was originally made for https://sandstorm.io/. That work (which Kenton has presumably done at Cloudflare since he's been employed there) eventually turned into Cloudflare workers.

Another consideration: https://github.com/google/flatbuffers/issues/2#issuecomment-...

Much more in the discussion of this particular issue onGitHub: flatbuffers:Reverse engineering #4258

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

If json files are a concern because of space, you can always look into something like protobuffers or flatbuffers. But whatever you use, you should try to find a solution where you don't have to think about the actual serialization/deserialization of your objects, and can just concentrate on the data.

Or, as an alternative to protobuffers, there's also flatbuffers, which is lighter weight and needs less memory: https://google.github.io/flatbuffers/

As the title suggests, I am considering using Flatbuffers as a way to parse sensor data that has been stored in local datafiles. The project language is python.

Fixed size function wrappers are not only limited and also a waste of space. Use a configurable function wrapper like fu2 with a stack allocator and set small object optimizer capacity to 0.

std::function wasn't cutting it for me, but I ended up going with fu2::function. It comes with a lot of features (almost too many), but the header size and compile times are comparable to , and it fit my needs pretty well.

Thank you, function2 is also used heavily in Idle as a type-erasure backend for continuable that is the primary asynchronous task abstraction.

You can write your own std::function, too, nor is it the only STL type that can take a capturing lambda (std::packaged_task for example).

A capturing lambda is just a class with an operator(). It's complicated to do what std::function does, but fully possible.

In fact, custom std::function replacements have better lambda support than std::function itself. Such as unique_function in https://github.com/Naios/function2 which can handle non-copyable lambdas.