Since we only ever want to do incremental y-range calcs based on the
price always skip any tick types emitted by the data daemon which aren't
defined in the fundamental set. Further, toss in a new `debug_n_trade:
bool` toggle which by default turns off all loggin and profiler calls;
if you want to do profiling this has to now be adjusted manually!
Since crypto backends now also may expand an FQME like `xbteur.kraken`
-> `xbteur.spot.kraken` (by filling in the venue token), we need to use
this identifier when looking up per-market order dialogs or submitting
new requests. The simple fix is to simply look up that expanded from
from the `Feed.flumes` table which is always keyed by the `MktPair.fqme:
str` - the expanded form.
This was actually incorrect prior, we were rounding triggered limit
orders with the `.size_tick` value's digits when we should have been
using the `.price_tick` (facepalm). So fix that and compute the rounding
number of digits (as passed to the round(<value>, ndigits=<here>)`
builtin) and store it in the `DarkBook.triggers` tuples so that at
trigger/match time the round call is done *just prior* to msg send to
`brokerd` given the last known live L1 queue price.
Not sure how this lasted so long without complaint (literally since we
added history 1m OHLC it seems; guess it means most backends are pretty
tolerant XD ) but we've been sending 2 cancels per order (dialog) due to
the mirrored lines on each chart: 1s and 1m. This fixes that by
reworking the `OrderMode` methods to be a bit more sane and less
conflated with the graphics (lines) layer.
Deatz:
- add new methods:
- `.oids_from_lines()` line -> oid extraction,
- `.cancel_orders()` which makes the order client cancel requests from
a `oids: list[str]`.
- re-impl `.cancel_all_orders()` and `.cancel_orders_under_cursor()` to
use the above methods thus fixing the original bug B)
Since we want to be able to support user-configurable vnc socketaddrs,
this preps for passing the piker client direct into the vnc hacker
routine so that we can (eventually load) and read the ib brokers config
settings into the client and then read those in the `asyncvnc` task
spawner.
It's been getting setup in the `brokerd` daemon-actor spawn task for
a while now and worker tasks already get a ref to that global log
instance so they don't need to care (in data or trading) task spawn
endpoints.
Also move to the new `open_trade_dialog()` naming for working broker
backends B)
Discovered due to originally having a history loading bug between
btcusdt futes display where the same time series was being loaded into
the graphics system, this avoids the issue where 2 (or more) curves are
measured to have the same dispersion and thus do not get added as unique
entries to the `overlay_table: dict[float, tuple]` during the scaling
phase..
Practically speaking this should never really be a problem if the curves
(and their backing timeseries) are indeed unique but keying the
overlay table by the dispersion and the `Viz` is a minimal performance
hit when looping the sorted table and is a lot nicer then you **do want
to show** duplicate curves then having one overlay just not be ranged
correctly at all XD
Instead of effectively (and poorly) duplicating the trade dialog setup
logic, just use the new helper we exposed in the EMS module B)
Also, handle paper accounts that have no ledger / positions existing.
As part of bringing the brokerd agnostic APIs up to date and modernizing
wrapping CLIs, this adds a new sub-cmd to allow more or less directly
calling the `.get_mkt_info()` broker mod endpoint and dumping the both
the backend specific `Pair`-ish and `.accounting.MktPair` normalized
version to console.
Deatz:
- make the click config's `brokermods` entry a `dict`
- make `.brokers.core.mkt_info()` strip the broker name part from the
input fqme before calling the backend.
Connecting to a `brokerd` daemon's trading dialog via a helper `@acm`
func is handy so that arbitrary trading middleware clients **and** the
ems can setup a trading dialog and, at the least, query existing
position state; this is in fact our immediate need when simply querying
for an account's position status in the `.accounting.cli.ledger` cli.
It's now exposed (for now) as `.clearing._ems.open_brokerd_dialog()` and
is called by the `Router.maybe_open_brokerd_dialog()` for every new
relay allocation or paper-account engine instance.
Changed from the old `store clone` to instead simply load any shm buffer
matching a user provided `FQME: str` pattern; writing to parquet file is
only done if an explicit option flag is passed by user.
Implement new `iter_dfs_from_shms()` generator which allows interatively
loading both 1m and 1s buffers delivering the `Path`, `ShmArray` and
`polars.DataFrame` instances per matching file B)
Also add a todo for a `NativeStorageClient.clear_range()` method.
Also adjust sizing such that the history buffer will backfill the last
six years by default (in 1m OHLC) and the hft buffer will do only 3 days
worth. Also ensure the fsp layer passes the src shm's buffer size when
allocating since the size is now required by allocators in the shm apis.
Avoid unnecessarily re-rendering the wrong (1min OHLC history) chart
and/or other such charts with update tasks listening to the sampler
stream. Instead only redraw in tasks which are updating vizs which match
the actual details of the backfill event.
We can probably also eventually match against a range tuple (emitted in
the msg) and then have the task further only update the formatter layer
unless the range is actually in view?
It's no longer part of the default OHLCV array-buffer schema and just
generally we should be processing and managing **any** non source data
in the FSP subsystem(s) despite it maybe being provided as a default by
some backends.
Explains why stuff always seemed wrong before XD
Previously whenever a time-gappy asset (like a stock due to it's venue
operating hours) was being loaded, we weren't querying for a "durations
worth" of bars and this was causing all sorts of actual gaps in our
data set that shouldn't exist..
Fix that by always attempting to retrieve a min aggregate-time's
worth/duration of bars/datums in the history manager. Actually,
i implemented this in both the feed and api layers for this backend
since it doesn't seem to strictly work just implementing it at the
`Client.bars()` level, not sure why but..
Also, buncha `ruff` linting cleanups and fix the logger nameeee, lel.
Tyler Goodlet