- use more compact optional value style with `|`-union
- fix `.flows` typing-only import since we need `MktPair` to be
immediately defined for use on a `msgspec.Struct` field.
- more "tree-like" warning msg in `.validate()` reporting.
Allows opening with `.from_msg(readonly=False)` for write permissions
making underlyig shm arrays readonly. Also, make sure to pop the
`ShmArray` field entries prior to msg-ization, not sure how that worked
with the `Feed.flumes` equivalent..but?
Since it's depended on by `.data` stuff as well as pretty much
everything else, makes more sense to expose it as a top level module
(and maybe eventually as a subpkg as we add to it).
Since there's a growing list of top level mods which are more or less
utils/tools for working with the runtime; begin to move them into a new
subpkg starting with a new `.toolz.debug`.
Start with,
- a new `open_crash_handller()` for doing breakpoints around blocks that
might error.
- move in what was `piker._profile` into `.toolz.profile` and adjust all
importing appropriately.
The list is `open_symcache()`, `get_symcache()`, `SymbologyCache`, and
`Stuct` which seems more or less fine to make part of the public
namespace. Also, make `._timeseries.t_unit` an instance of literal to make
`ruff` happy?
Stash it for now in the (now mutable by default) `.shm_write_opts` and
have the new `Flume._has_vlm: bool` (only set to false internally by
feed layer) which can be read via new public `.has_vlm()` predicate.
Move out the old `.ui/_fsp` helper logic to this flume method.
Might as well try and flip it over to the new type; make appropriate
dict serialization changes in `.to_msg()`. Alias back to `.symbol:
Symbol` with a property.
We need to subtract the first index in the array segment read, not the
first index value in the time-sliced output, to get the correct offset
into the non-absolute (`ShmArray.array` read) array..
Further we **do** need the `&` between the advance indexing conditions
and this adds profiling to see that it is indeed real slow (like 20ms
ish even when using `np.where()`).
Probably means it doesn't need to be a `Flume` method but it's
convenient to expect the caller to pass in the `np.ndarray` with
a `'time'` field instead of a `timeframe: str` arg; also, return the
slice mask instead of the sliced array as output (again allowing the
caller to do any slicing). Also, handle the slice-outside-time-range
case by just returning the entire index range with a `None` mask.
Adjust `Viz.view_data()` to instead do timeframe (for rt vs. hist shm
array) lookup and equiv array slicing with the returned mask.
Tyler Goodlet