Representation of gridded data via NumPy arrays and views.
The cross-language and schema/IDL support of FlatBuffers.
It can generate typed msgspec.Struct models and read-only FlatBuffers views from .fbs schemas.
Its JSON, MessagePack, and FlatBuffers codecs also support very fast encoding/decoding of Structs containing NumPy arrays (with or without a FlatBuffers schema).
In my benchmarks, msgspec-serde encodes FlatBuffers about 20–22 times faster and decodes them into complete models about 11–13 times faster than the official Python FlatBuffers API.