`ChartPlotWidget.curve_width_pxs()` now can be used to get the total
horizontal (x) pixels on screen that are occupied by the current curve
graphics for a given chart. This will be used for downsampling large
data sets to the pixel domain using M4.
Probably the best place to root the profiler since we can get a better
top down view of bottlenecks in the graphics stack.
More,
- add in draft M4 downsampling code (commented) after getting it mostly
working; next step is to move this processing into an FSP subactor.
- always update the vlm chart last y-axis sticky
- set call `.default_view()` just before inf sleep on startup
Obviously determining the x-range from indices was wrong and was the
reason for the incorrect (downsampled) output size XD. Instead correctly
determine the x range and start value from the *values of* the input
x-array. Pretty sure this makes the implementation nearly production
ready.
Relates to #109
All the refs are in the comments and original sample code from infinite
has been reworked to expect the input x/y arrays to already be sliced
(though we can later support passing in the start-end indexes if
desired).
The new routines are `ds_m4()` the python top level API and `_m4()` the
fast `numba` implementation.
- the chart's uppx (units-per-pixel) is > 4 (i.e. zoomed out a lot)
- don't shift the chart (to keep the most recent step in view) if the
last datum isn't in view (aka the user is probably looking at history)
When a bars graphic is zoomed out enough you get a high uppx, datum
units-per-pixel, and there is no point in drawing the 6-lines in each
bar element-graphic if you can't see them on the screen/display device.
Instead here we offer converting to a `FastAppendCurve` which traces
the high-low outline and instead display that when it's impossible to see the
details of bars - approximately when the uppx >= 2.
There is also some draft-commented code in here for downsampling the
outlines as zoom level increases but it's not fully working and should
likely be factored out into a higher level api anyway.
In effort to start getting some graphics speedups as detailed in #109,
this adds a `FastAppendCurve`to every `BarItems` as a `._ds_line` which
is only displayed (instead of the normal mult-line bars curve) when the
"width" of a bar is indistinguishable on screen from a line -> so once
the view coordinates map to > 2 pixels on the display device.
`BarItems.maybe_paint_line()` takes care of this scaling detection logic and is
called by the associated view's `.sigXRangeChanged` signal handler.
The graphics update loop is much easier to grok when all the UI
components which potentially need to be updated on a cycle are arranged
together in a high-level composite namespace, thus this new
`DisplayState` addition. Create and set this state on each
`LinkedSplits` chart set and add a new method `.graphics_cycle()` which
let's a caller trigger a graphics loop update manually. Use this method
in the fsp graphics manager such that a chain can update new history
output even if there is no real-time feed driving the display loop (eg.
when a market is "closed").
As per https://github.com/erdewit/ib_insync/pull/454 the more correct
way to do this is with `.reqContractDetailsAsync()` which we wrap with
`Client.con_deats()` and which works just as well. Further drop all the
`dict`-ifying that was being done in that method and instead always
return `ContractDetails` object in an fqsn-like explicitly keyed `dict`.
ib has a throttle limit for "hft" bars but contained in here is some
hackery using ``xdotool`` to reset data farms auto-magically B)
This copies the working script into the ib backend mod as a routine and
now uses `trio.run_process()` and calls into it from the `get_bars()`
history retriever and then waits for "data re-established" events to be
received from the client before making more history queries.
TL;DR summary of changes:
- relay ib's "system status" events (like for data farm statuses)
as a new "event" msg that can be processed by registers of
`Client.inline_errors()` (though we should probably make a new
method for this).
- add `MethodProxy.status_event()` which allows a proxy user to register
for a particular "system event" (as mentioned above), which puts
a `trio.Event` entry in a small table can be set by an relay task if
there are any detected waiters.
- start a "msg relay task" when opening the method proxy which does
the event setting mentioned above in the background.
- drop the request error handling around the proxy creation, doesn't
seem necessary any more now that we have better error propagation from
`asyncio`.
- add event waiting logic around the data feed reset hackzorin.
- change the order relay task to only log system events for now (though
we need to do some better parsing/logic to get tws-external order
updates to work again..
Found an issue (that was predictably brushed aside XD) where the
`ib_insync.util.df()` helper was changing the timestamps on bars data to
be way off (probably a `pandas.Timestamp` timezone thing?).
Anyway, dropped all that (which will hopefully let us drop `pandas` as
a hard dep) and added a buncha timestamp checking as well as start/end
datetime return values using `pendulum` so that consumer code can know
which "slice" is output.
Also added some WIP code to work around "no history found" request
errors where instead now we try to increment backward another 200
seconds - not sure if this actually correct yet.
Make the throttle error propagate through to `trio` again by adding
`dict`-msg support between the two loops such that errors can be
re-raised on the `trio` side. This is all integrated into the
`MethoProxy` and accompanying result relay task.
Further fix a longer standing issue where sometimes the `ib_insync`
order entry method will raise a weird assertion error because it detects
some internal order-id state issue.. Just ignore those and make relay
back an error to the ems in such cases.
Add a bunch of notes for todos surrounding data feed reset hackery.
To start we only have futes working but this allows both searching
and loading multiple expiries of the same instrument by specifying
different expiries with a `.<expiry>` suffix in the symbol key (eg.
`mnq.globex.20220617`). This also paves the way for options contracts
which will need something similar plus a strike property. This change
set also required a patch to `ib_insync` to allow retrieving multiple
"ambiguous" contracts from the `IB.reqContractDetailsAcync()` method,
see https://github.com/erdewit/ib_insync/pull/454 for further discussion
since the approach here might change.
This patch also includes a lot of serious reworking of some `trio`-`asyncio`
integration to use the newer `tractor.to_asyncio.open_channel_from()`
api and use it (with a relay task) to open a persistent connection with
an in-actor `ib_insync` `Client` mostly for history requests.
Deats,
- annot the module with a `_infect_asyncio: bool` for `tractor` spawning
- add a futes venu list
- support ambiguous futes contracts lookups so that all expiries will
show in search
- support both continuous and specific expiry fute contract
qualification
- allow searching with "fqsn" keys
- don't crash on "data not found" errors in history requests
- move all quotes msg "topic-key" generation (which should now be
a broker-specific fqsn) and per-contract quote processing into
`normalize()`
- set the fqsn key in the symbol info init msg
- use `open_client_proxy()` in bars backfiller endpoint
- include expiry suffix in position update keys
This adds a new client manager-factory: `open_client_proxy()` which uses
the newer `tractor.to_asyncio.open_channel_from()` (and thus the
inter-loop-task-channel style) a `aio_client_method_relay()` and
a re-implemented `MethodProxy` wrapper to allow transparently calling
`asyncio` client methods from `trio` tasks. Use this proxy in the
history backfiller task and add a new (prototype)
`open_history_client()` which will be used in the new storage management
layer. Drop `get_client()` which was the portal wrapping equivalent of
the same proxy but with a one-task-per-call approach. Oh, and
`Client.bars()` can take `datetime`, so let's use it B)
Use fqsn as input to the client-side EMS apis but strip broker-name
stuff before generating and sending `Brokerd*` msgs to each backend for
live order requests (since it's weird for a backend to expect it's own
name, though maybe that could be a sanity check?).
Summary of fqsn use vs. broker native keys:
- client side pps, order requests and general UX for order management
use an fqsn for tracking
- brokerd side order dialogs use the broker-specific symbol which is
usually nearly the same key minus the broker name
- internal dark book and quote feed lookups use the fqsn where possible
In order to support instruments with lifetimes (aka derivatives) we need
generally need special symbol annotations which detail such meta data
(such as `MNQ.GLOBEX.20220717` for daq futes). Further there is really
no reason for the public api for this feed layer to care about getting
a special "brokername" field since generally the data is coming directly
from UIs (eg. search selection) so we might as well accept a fqsn (fully
qualified symbol name) which includes the broker name; for now a suffix
like `'.ib'`. We may change this schema (soon) but this at least gets us
to a point where we expect the full name including broker/provider.
An additional detail: for certain "generic" symbol names (like for
futes) we will pull a so called "front contract" and map this to
a specific fqsn underneath, so there is a double (cached) entry for that
entry such that other consumers can use it the same way if desired.
Some other machinery changes:
- expect the `stream_quotes()` endpoint to deliver it's `.started()` msg
almost immediately since we now need it deliver any fqsn asap (yes
this means the ep should no longer wait on a "live" first quote and
instead deliver what quote data it can right away.
- expect the quotes ohlc sampler task to add in the broker name before
broadcast to remote (actor) consumers since the backend isn't (yet)
expected to do that add in itself.
- obviously we start using all the new fqsn related `Symbol` apis
Move the core ws message handling into `stream_messages()` and call that
from 2 new stream processors: `process_data_feed_msgs()` and
`process_order_msgs()`. Add comments for hints on how to implement the
order msg parsing as well as `pprint` received msgs to console for now.
Since moving to a "god loop" for graphics, we don't really need to have
a dedicated task for updating graphics on new sample increments. The
only UX difference will be that curves won't be updated until an actual new
rt-quote-event triggers the graphics loop -> so we'll have the chart
"jump" to a new position and new curve segments generated only when new
data arrives. This is imo fine since it's just less "idle" updates
where the chart would sit printing the same (last) value every step.
Instead only update the view increment if a new index is detected by
reading shm.
If we ever want this dedicated task update again this commit can be
easily reverted B)
Break up real-time quote feed and history loading into 2 separate tasks
and deliver a client side `data.Feed` as soon as history is loaded
(instead of waiting for a rt quote - the previous logic). If
a symbol doesn't have history then likely the feed shouldn't be loaded
(since presumably client code will need at least "some" datums history
to do anything) and waiting on a real-time quote is dumb, since it'll
hang if the market isn't open XD. If a symbol doesn't have history we
can always write a zero/null array when we run into that case. This also
greatly speeds up feed loading when both history and quotes are available.
TL;DR summary:
- add a `_Feedsbus.start_task()` one-cancel-scope-per-task method for
assisting with (re-)starting and stopping long running persistent
feeds (basically a "one cancels one" style nursery API).
- add a `manage_history()` task which does all history loading (and
eventually real-time writing) which has an independent signal and
start it in a separate task.
- drop the "sample rate per symbol" stuff since client code doesn't really
care when it can just inspect shm indexing/time-steps itself.
- run throttle tasks in the bus nursery thus avoiding cancelling the
underlying sampler task on feed client disconnects.
- don't store a repeated ref the bus nursery's cancel scope..
To avoid the "trigger finger" issue (darks execing before they should
due to a stale last price state, normally when generating a trigger
predicate..) always iterate the loop and update the last known book
price even when no execs/triggered orders are registered.
Tyler Goodlet
goodboy
Konstantine Tsafatinos