Though it's not per-tick accurate, accumulate the number of "trades"
(i.e. the "clearing rate" - maybe this is a better name?) per bar
inside the `dolla_vlm` fsp and average and report wmas of this in the
`flow_rates` fsp.
Define the flows table as a class var (thus making it a "global" and/or
actor-local state) which can be accessed by any in process task. Add
`Fsp.get_shm()` to allow accessing output streams by source-token + fsp
routine reference and thus providing inter-fsp low level access to
real-time flows.
In order for fsp routines to be able to look up other "flows" in the
cascade, we need a small registry-table which gives access to a map of
a source stream + an fsp -> an output stream. Eventually we'll also
likely want a dependency (injection) mechanism so that any fsp demanded
can either be dynamically allocated or at the least waited upon before
a consumer tries to access it.
Instead of referencing the remote processing funcs by a `str` name start
embracing the new `@fsp`/`Fsp` API such that wrapped processing
functions are first class APIs.
Summary of the changeset:
- move and load the fsp built-in set in the new `.fsp._api` module
- handle processors ("fsps") which want to yield multiple keyed-values
(interleaved in time) by expecting both history that is keyed and
assigned to the appropriate struct-array field, *and* real-time
`yield`ed value in tuples of the form `tuple[str, float]` such that
any one (async) processing function can deliver multiple outputs from
the same base calculation.
- drop `maybe_mk_fsp_shm()` from UI module
- expect and manage `Fsp` instances (`@fsp` decorated funcs) throughout
the UI code, particularly the `FspAdmin` layer.
Tyler Goodlet
goodboy
Guillermo Rodriguez