Allows starting UI apps and passing the `pikerd` registry socket-addr
args via `--host` or `--port` such that a separate actor tree can be
started by selecting an unused port. This is handy when hacking new
features but while also wishing to run a more stable version of the code
for trading on the same host.
Drop all attempts at rewiring `ViewBox` signals, monkey-patching
relayee handlers, and generally modifying event source public
attributes. Instead take a much simpler approach where the event source
graphics object simply has it's handler dynamically overridden by
a broadcaster function which relays to all consumers using a Python
loop.
The benefits of this much simplified approach include:
- avoiding the tedious and often complex (re)connection of signals between
the source plot and the overlayed consumers.
- requiring zero modification of the public interface of any of the
publisher or consumer `ViewBox`s, no decoration, extra signal
definitions (eg. previous `mouseDragEventRelay` or the like).
- only a single dynamic method override on the event source graphics object
(`ViewBox`) which does the broadcasting work and requires no
modification to handler implementations.
Detailed `.ui._overlay` changes:
- drop `mk_relay_signal()`, `enable_relays()` which removes signal/slot
hacking methodology.
- drop unused `ComposedGridLayout.grid` and `.reverse`, change some
method names: `.insert()` -> `.insert_plotitem()`, `append()` ->
`.append_plotitem()`.
- in `PlotOverlay`, again drop all signal/slot rewiring in
`.add_plotitem()` and instead add our new closure based python-loop in
`broadcast()` routine which is used to override the event-source
object's handler.
- comment out all the auxiliary/want-to-have event source selection
methods for now.
Mainly this involves instantiating our overriden `PlotItem` in a few
places and tweaking type annots. A further detail is that inside
the fsp sub-chart creation code we hide some axes for overlays in the
flows subchart; these were previously somehow hidden implicitly?
Fork out our patch set submitted to upstream in multiple PRs (since they
aren't moving and/or aren't a priority to core) which can be seen in
full from the following diff:
https://github.com/pyqtgraph/pyqtgraph/compare/master...pikers:pyqtgraph:graphics_pin
Move these type extensions into the internal `.ui._pg_overrides` module.
The changes are related to both `pyqtgraph.PlotItem` and `.AxisItem` and
were driven for our need for multi-view overlays (overlaid charts with
optionally synced axis and interaction controls) as documented in the PR
to upstream: https://github.com/pyqtgraph/pyqtgraph/pull/2162
More specifically,
- wrt to `AxisItem` we added lru caching of tick values as per:
https://github.com/pyqtgraph/pyqtgraph/pull/2160.
- wrt to `PlotItem` we adjusted some of the axis management code, namely
adding a standalone `.removeAxis()` and modifying the `.setAxisItems()` logic
to use it in: https://github.com/pyqtgraph/pyqtgraph/pull/2162
as well as some tweaks to `.updateGrid()` to loop through all possible
axes when grid setting.
Details of the original patch to upstream are in:
https://github.com/pyqtgraph/pyqtgraph/pull/2281
Instead of trying to land this we've opted to just copy out that version
of `.debug.Profiler` into our own internals (luckily the class is
entirely self-contained) until such a time when we choose to find
a better dependency as per https://github.com/pikers/piker/issues/337
To make it easier to manually read/decipher long ledger files this adds
`dict` sorting based on record-type-specific (api vs. flex report)
datetime processing prior to ledger file write.
- break up parsers into separate routines for flex and api record
processing.
- add `parse_flex_dt()` for special handling of the weird semicolon
stamps in flex reports.
There never was any underlying db bug, it was a hardcoded timeframe in
the column series write key.. Now we always assert a matching timeframe
in results.
Not only improves startup latency but also avoids a bug where the rt
buffer was being tsdb-history prepended *before* the backfilling of
recent data from the backend was complete resulting in our of order
frames in shm.
Factor the multi-sample-rate region UI connecting into a new helper
`link_views_with_region()` which reads in the shm buffer offsets from
the `Feed` and appropriately connects the fast and slow chart handlers
for the linear region graphics. Add detailed comments writeup for the
inter-sampling transform algebra.
If a history manager raises a `DataUnavailable` just assume the sample
rate isn't supported and that no shm prepends will be done. Further seed
the shm array in such cases as before from the 1m history's last datum.
Also, fix tsdb -> shm back-loading, cancelling tsdb queries when either
no array-data is returned or a frame is delivered which has a start time
no lesser then the least last retrieved. Use strict timeframes for every
`Storage` API call.
Turns out querying for a high freq timeframe (like 1sec) will still
return a lower freq timeframe (like 1Min) SMH, and no idea if it's the
server or the client's fault, so we have to explicitly check the sample
step size and discard lower freq series-results. Do this inside
`Storage.read_ohlcv()` and return an empty `dict` when the wrong time
step is detected from the query result.
Further enforcements,
- both `.load()` and `read_ohlcv()` now require an explicit `timeframe:
int` input to guarantee the time step of the output array.
- drop all calls `.load()` with non-timeframe specific input.
Our default sample periods are 60s (1m) for the history chart and 1s for
the fast chart. This patch adds concurrent loading of both (or more)
different sample period data sets using the existing loading code but
with new support for looping through a passed "timeframe" table which
points to each shm instance.
More detailed adjustments include:
- breaking the "basic" and tsdb loading into 2 new funcs:
`basic_backfill()` and `tsdb_backfill()` the latter of which is run
when the tsdb daemon is discovered.
- adjust the fast shm buffer to offset with one day's worth of 1s so
that only up to a day is backfilled as history in the fast chart.
- adjust bus task starting in `manage_history()` to deliver back the
offset indices for both fast and slow shms and set them on the
`Feed` object as `.izero_hist/rt: int` values:
- allows the chart-UI linked view region handlers to use the offsets
in the view-linking-transform math to index-align the history and
fast chart.
Allows keeping mutex state around data reset requests which (if more
then one are sent) can cause a throttling condition where ib's servers
will get slower and slower to conduct a reconnect. With this you can
have multiple ongoing contract requests without hitting that issue and
we can go back to having a nice 3s timeout on the history queries before
activating the hack.
When a network outage or data feed connection is reset often the
`ib_insync` task will hang until some kind of (internal?) timeout takes
place or, in some (worst) cases it never re-establishes (the event
stream) and thus the backend needs to restart or the live feed will
never resume..
In order to avoid this issue once and for all this patch implements an
additional (extremely simple) task that is started with the real-time
feed and simply waits for any market data reset events; when detected
restarts the `open_aio_quote_stream()` call in a loop using
a surrounding cancel scope.
Been meaning to implement this for ages and it's finally working!
Allows for easier restarts of certain `trio` side tasks without killing
the `asyncio`-side clients; support via flag.
Also fix a bug in `Client.bars()`: we need to return the duration on the
empty bars case..
This allows the history manager to know the decrement size for
`end_dt: datetime` on the next query if a no-data / gap case was
encountered; subtract this in `get_bars()` in such cases. Define the
expected `pendulum.Duration`s in the `.api._samplings` table.
Also add a bit of query latency profiling that we may use later to more
dynamically determine timeout driven data feed resets. Factor the `162`
error cases into a common exception handler block.
When we get a timeout or a `NoData` condition still return a tuple of
empty sequences instead of `None` from `Client.bars()`. Move the
sampling period-duration table to module level.
It doesn't seem to be any slower on our least throttled backend
(binance) and it removes a bunch of hard to get correct frame
re-ordering logic that i'm not sure really ever fully worked XD
Commented some issues we still need to resolve as well.
Manual tinker-testing demonstrated that triggering data resets
completely independent of the frame request gets more throughput and
further, that repeated requests (for the same frame after cancelling on
the `trio`-side) can yield duplicate frame responses. Re-work the
dual-task structure to instead have one task wait indefinitely on the
frame response (and thus not trigger duplicate frames) and the 2nd data
reset task poll for the first task to complete in a poll loop which
terminates when the frame arrives via an event.
Dirty deatz:
- make `get_bars()` take an optional timeout (which will eventually be
dynamically passed from the history mgmt machinery) and move request
logic inside a new `query()` closure meant to be spawned in a task
which sets an event on frame arrival, add data reset poll loop in the
main/parent task, deliver result on nursery completion.
- handle frame request cancelled event case without crash.
- on no-frame result (due to real history gap) hack in a 1 day decrement
case which we need to eventually allow the caller to control likely
based on measured frame rx latency.
- make `wait_on_data_reset()` a predicate without output indicating
reset success as well as `trio.Nursery.start()` compat so that it can
be started in a new task with the started values yielded being
a cancel scope and completion event.
- drop the legacy `backfill_bars()`, not longer used.
Adjust all history query machinery to pass a `timeframe: int` in seconds
and set default of 60 (aka 1m) such that history views from here forward
will be 1m sampled OHLCV. Further when the tsdb is detected as up load
a full 10 years of data if possible on the 1m - backends will eventually
get a config section (`brokers.toml`) that allow user's to tune this.
The `Store.load()`, `.read_ohlcv()` and `.write_ohlcv()` and
`.delete_ts()` now can take a `timeframe: Optional[float]` param which
is used to look up the appropriate sampling period table-key from
`marketstore`.
Allow data feed sub-system to specify the timeframe (aka OHLC sample
period) to the `open_history_client()` delivered history fetching API.
Factor the data keycombo hack into a new routine to be used also from
the history backfiller code when request latency increases; there is
a first draft at trying to use the feed reset to speed up 1m frame
throttling by timing out on the history frame response, but it needs
a lot of fine tuning.
This is a simpler (and oddly more `trio`-nic and/or SC) way to handle
the cancelled-before-acked race for order dialogs. Will allow keeping
the `.req` field as solely an `Order` msg.
When the client is faster then a `brokerd` at submitting and cancelling
an order we run into the case where we need to specify that the EMS
cancels the order-flow as soon as the brokerd's ack arrives. Previously
we were stashing a `BrokerdCancel` msg as the `Status.req` msg (to be
both tested for as a "already cancelled" and sent immediately on ack arrival to
the broker), but for such
cases we can't use that msg to find the fqsn (since only the client side
msgs have it defined) which is required by the new
`Router.client_broadcast()`.
So, Since `Status.req` is supposed to be a client-side flow msg anyway,
and we need the fqsn for client broadcasting, we change this `.req`
value to the client's submitted `Cancel` msg (thus rectifying the
missing `Router.client_broadcast()` fqsn input issue) and build the
`BrokerdCancel` request from that `Cancel` inline in the relay loop
from the `.req: Cancel` status msg lookup.
Further we allow `Cancel` msgs to define an `.account` and adjust the
order mode loop to expect `Cancel` source requests in cancelled status
updates.
Except for paper accounts (in which case we need a trades dialog and
paper engine per symbol to enable simulated clearing) we can rely on the
instrument feed (symbol name) to be the caching key. Utilize
`tractor.trionics.maybe_open_context()` and the new key-as-callable
support in the paper case to ensure we have separate paper clearing
loops per symbol.
Requires https://github.com/goodboy/tractor/pull/329
With the refactor of the dark loop into a daemon task already-open order
relaying from a `brokerd` was broken since no subscribed clients were
registered prior to the relay loop sending status msgs for such existing
live orders. Repair that by adding one more synchronization phase to the
`Router.open_trade_relays()` task: deliver a `client_ready: trio.Event`
which is set by the client task once the client stream has been
established and don't start the `brokerd` order dialog relay loop until
this event is ready.
Further implementation deats:
- factor the `brokerd` relay caching back into it's own `@acm` method:
`maybe_open_brokerd_dialog()` since we do want (but only this) stream
singleton-cached per broker backend.
- spawn all relay tasks on every entry for the moment until we figure
out what we're caching against (any client pre-existing right, which
would mean there's an entry in the `.subscribers` table?)
- rename `_DarkBook` -> `DarkBook` and `DarkBook.orders` -> `.triggers`
This enables "headless" dark order matching and clearing where an `emsd`
daemon subactor can be left running with active dark (or other
algorithmic) orders which will still trigger despite to attached-controlling
ems-client.
Impl details:
- rename/add `Router.maybe_open_trade_relays()` which now does all work
of starting up ems-side long living clearing and relay tasks and the
associated data feed; make is a `Nursery.start()`-able task instead of
an `@acm`.
- drop `open_brokerd_trades_dialog()` and move/factor contents into the
above method.
- add support for a `router.client_broadcast('all', msg)` to wholesale
fan out a msg to all clients.
Establishes a more formalized subscription based fan out pattern to ems
clients who subscribe for order flow for a particular symbol (the fqsn
is the default subscription key for now).
Make `Router.client_broadcast()` take a `sub_key: str` value which
determines the set of clients to forward a message to and drop all such
manually defined broadcast loops from task (func) code. Also add
`.get_subs()` which (hackily) allows getting the set of clients for
a given sub key where any stream that is detected as "closed" is
discarded in the output. Further we simplify to `Router.dialogs:
defaultdict[str, set[tractor.MsgStream]]` and `.subscriptions` as maps
to sets of streams for much easier broadcast management/logic using set
operations inside `.client_broadcast()`.
This patch was originally to fix a bug where new clients who
re-connected to an `emsd` that was running a paper engine were not
getting updates from new fills and/or cancels. It turns out the solution
is more general: now, any client that creates a order dialog will be
subscribing to receive updates on the order flow set mapped for that
symbol/instrument as long as the client has registered for that
particular fqsn with the EMS. This means re-connecting clients as well
as "monitoring" clients can see the same orders, alerts, fills and
clears.
Impl details:
- change all var names spelled as `dialogues` -> `dialogs` to be
murican.
- make `Router.dialogs: dict[str, defaultdict[str, list]]` so that each
dialog id (oid) maps to a set of potential subscribing ems clients.
- add `Router.fqsn2dialogs: dict[str, list[str]]` a map of fqsn entries to
sets of oids.
- adjust all core task code to make appropriate lookups into these 2 new
tables instead of being handed specific client streams as input.
- start the `translate_and_relay_brokerd_events` task as a daemon task
that lives with the particular `TradesRelay` such that dialogs cleared
while no client is connected are still processed.
- rename `TradesRelay.brokerd_dialogue` -> `.brokerd_stream`
- broadcast all status msgs to all subscribed clients in the relay loop.
- always de-reg each client stream from the `Router.dialogs` table on close.
Not sure what exactly happened but it seemed clears weren't working in
some cases without this, also there's no point in spinning the simulated
clearing loop if we're handling a non-clearing tick type.
We haven't been using it for a while and the supposed (remembered)
latency issue on interaction doesn't seem existing after applying the
cache mode. This allows dropping some internal state-logic and generally
simplifying the show-on-hover checks.
Further add `.show_markers()` and `.hide_markers()` as explicit methods
that can be called externally by UI business logic.
Bit of a face palm but obviously `LevelLine.delete()` also removes any
`._marker` from the view which makes it disappear permanently when
moving from non-zero to zero to non-zero positions.. We don't really
need to delete the line since it can be re-used so just remove that
code.
Further this patch removes marker style setting logic from within the
`pp_line()` factory and instead expects the caller to set the correct
"direction" (for long / short) afterward.
- Every time a symbol is switched on chart we need to wait until the
search bar sidepane has been added beside the slow chart before
determining the offset for the pp line's arrow/labels; trigger this in
`GodWidget.load_symbol()` -> required monkeypatching on a
`.mode: OrderMode` to the `.rt_linked` for now..
- Drop the search pane widget removal from the current linked chart,
seems faster?
- On the slow chart override the `LevelMarker.scene_x()` callback to
adjust for the case where no L1 labels are shown beside the y-axis.
Also adds a `GodWidget.resize_all()` helper method which resizes all
sub-widgets and charts to their default ratios and/or parent-widget
dependent defaults using the detected available space on screen. This is
a "default layout" config method that eventually we'll probably want
allow users to customize.
In other words instead of some static view size previously determined by
the accompanying (slow) chart's height, (recursively) calculate the
number of displayed rows and compute the minimal height needed. This
still caps the view at the height of the chart such that the view will
switch to scroll bar mode when too many results are shown and can't all
be fit in the vertical space.
Deats:
- add a ``CompleterView.iter_df_rows()`` which recursively iterates all
rows in depth-first order making it simple to compute the absolute
number of result rows in view and thus the minimal number of pixels to
show all results.
- always pass the height in the `.on_resize()` handler to ensure
triggering the height logic when new results are generated in the
search loop.
Scales the "view" instance that holds search results to the size of the
accompanying "slow chart" for which the search pane is a "sidepane".
A lot of mucking about was required due to resizing of the view
seemingly feeding back into window resizing and further implementing the
sizing logic such that the parent `QSplitter` can be resized as the
user's whim as well.
Details,
- add a `CompleterView._init: bool` which is set once (and only once)
after startup where the first display of the current symbol/feed is
shown allowing and a single *width* padding applied once at startup
to ensure we don't have an awkward line to the right of the longest
result.
- in `.resize_to_results()` only apply a minimum height to the view
using `.setMinimumHeight()` with a down-scaled (`0.91` for now) height
value from input.
- re-implement `CompleterView.show_matches()` to accept and optional
width, heigh tuple and when not supplied pull the slow chart's
dimensions and pass as input to the resize method.
- Make `SearchWidget` x dim sizing policy "fixed".
- register the `SearchWidget` for resize events with god.
- add `.show_only_cache_entries()` for easy results clearing.
- add `.space_dims()` to retrieve slow linked-charts dimensions.
- implement `SearchWidget.on_resize()` which is the caller of all the
previously mentioned resizing routines.
- do resizing and cache entry showing on search loop startup and be sure
to clear to cache when the user selects a symbol-feed with Enter.
It ended up being what'd you expect, races on the accessing shm buffer
data by the UI during the whole "mega-async-startup-everything" phase XD
So we add the following list of ad-hoc startup steps:
- do `.default_view()` on the slow chart after the fast chart is mostly
fully spawned with the intention being to capture the state where the
historical buffer is mostly loaded before sizing the view to the
graphical form of the data.
- resize slow chart sidepanes from the fast chart just before sleeping
forever (and after order mode has booted).
Turns out god widget resizes aren't triggered implicitly by window
resizes, so instead, hook into the window by moving what was our useless
method to that class. Further we explicitly define and declare that our
window has a `.godwidget: GodWidget` and set it up in the bootstrap
phase - in `run_qutractor()` during `trio` guest mode configuration.
Further deatz:
- retype the runtime/bootstrap routines to take a qwidget "type" not an
instance, and drop the whole implicit `.main_widget` stuff.
- delegate into the `GodWidget.on_win_resize()` for any window resize
which then triggers all the custom resize callbacks we already had in
place.
- privatize `ChartnPane.sidepane` so that it can't be mutated willy
nilly without calling `.set_sidepane()`.
- always adjust splitter sizes inside `LinkeSplits.add_plot()`.
More or less moves all the UI related position "nav" logic and graphics
item management into a new `._position.Nav` composite type + api for
high level mgmt of position graphics indicators across multiple charts
(fast and slow).
The slow (history) chart requires it's own y-range checker logic which
needs to be run in 2 cases:
- the last datum is in view and goes outside the previous mx/mn in view
- the chart is incremented a step
Since we need this duplicate logic this patch also factors the incremental
graphics update info "reading" into a new `DisplayState.incr_info()`
method that can be configured to a chart and input state and returns all
relevant "graphics update measure" in a tuple (for now).
Use this method throughout the rest of the display loop for both fast
and slow chart checks and in the `increment_history_view()` slow chart
task.
Use the new `Feed.get_ds_info()` method in a poll loop to definitively
get the inter-chart sampling info and avoid races with shm buffer
backfilling.
Also, factor the history increment closure-task into
`graphics_update_loop()` which will make it clearer how to factor
all the "should we update" logic into some `DisplayState` API.
If you spawn a brokerd set and no `ib` data feed was started (via our
`.data.feed.Feed` api) then there will be no active client loaded and
thus wont' be connected. So in these cases just return nothing, and
I guess we'll figure out real connection failures later?
Add an update call to the display loop to consistently update the last
datum in the history view chart. Compute the inter-chart sampling ratio
and use it to sync the linear region.
Add a first draft of a working `pyqtgraph.LinearRegionItem` link between
a history view chart (+ data set) and the normal real-time "HFT" chart
set.
Add the history view (aka more downsampled data view) chart set to the
rt/hft set's splitter as it's "first widget". Hook up linear region
callbacks to enable syncing between charts including compenstating for
the downsampling rate ration (in this case hardcoded 60 since 1s to 1M,
but we'll actually compute it going forward obvs).
More to come dawgys..
Adds an additional `GodWidget.hist_linked: LinkedSplits` alongside the
renamed `.rt_linked` to enable 2 sets of linked charts with different
sampled data sets/flows. The history set is added without "all the
fixins" for now (i.e. no order mode sidepane or search integration) such
that it is merely a top level chart which shows a much longer term
history and can be added to the UI via embedding the entire history
linked-splits instance into the real-time linked set's splitter.
Further impl deats:
- adjust the `GodWidget._chart_cache: dict[str, tuple]]` to store both
linked split chart sets per symbol so that symbol switching will
continue to work with the added history chart (set).
- rework `.load_symbol()` to operate on both the real-time (HFT) chart
set and the history set.
- rework `LinkedSplits.set_split_sizes()` to compensate for the history
chart and do more detailed height calcs arithmetic to make it appear
by default as a minor sub-chart.
- adjust `LinkedSplits.add_plot()` and `ChartPlotWidget` internals to allow
adding a plot without a sidepane and/or container `ChartnPane`
composite widget by checking for a `sidepane == False` input.
- make `.default_view()` accept a manual y-axis offset kwarg.
- adjust search mode to provide history linked splits to
`.set_chart_symbol()` call.
As part of supporting a "history view" chart which shows downsampled
datums alongside our 1s (or higher) sampled OHLC we need a separate
buffer to store a the slower history from broker backends. This begins
that design by allocating 2 buffers:
- `rt_shm: ShmArray` which maps to a `/dev/shm/` file with `_rt` suffix
- `hist_shm: ShmArray` which maps to a file with `_hist` suffix
Deliver both of these shms back from both `manage_history()` and load
them as `Feed.rt_shm`/`.hist_shm` on the client side.
Impl deats:
- init the rt buffer with the first datum from loaded history and
assign all OHLC values to that row's 'close' and the vlm to 0.
- pass the hist buffer to the backfiller task
- only spawn **one** global sampler array-row increment task per
`brokerd` and pass in the 1s delay which we presume is our lowest
OHLC sample rate for now.
- drop `open_sample_step_stream()` and just move its body contents into
`Feed.index_stream()`
Instead of worrying about the increment period per shm subscription,
just use the value passed as input and presume the caller knows that
only one task is necessary and that the wakeup (sampling) period should
be the shortest that is needed.
It's very unlikely we don't want at least a 1s sampling (both in terms
of task switching cost and general usage) which will eventually ship as
the default "real-time" feed "timeframe". Further, this "fast" increment
sampling task can handle all lower sampling periods (eg. 1m, 5m, 1H)
based on the current implementation just the same.
Also, add a global default sample period as `_defaul_delay_s` for use in
other internal modules.
Clearly, the linter didn't help us here.. but, just pass the
`brokerd` time for now in the `.broker_time` field; we can't get it from
the fill-case incremental updates in the `openOrders` sub. Add some
notes about this and how we might approach for backends with this
limitation.
This fixes a regression added after moving the msg parsing to later in
the order mode startup sequence. The `Allocator` needs to be configured
*to* the initial pos otherwise default settings will show in the UI..
Move the startup config logic from inside `mk_allocator()` to
`PositionTracker.update_from_pp()` and add a flag to allow setting the
`.startup_pp` from the current live one as is needed during initial
load.
In the short case (-ve size) we had a bug where the last sub-slots worth
of exit size would never be limited to zero once the allocator limit pos
size was hit (i.e. you could keep going more -ve on the pos,
exponentially per slot over the limit). It's a simple fix, just
a `max()` around the `l_sub_pp` var used in the next-step-size calc.
Resolves#392
Turns out we were putting too many brokername suffixes in the symbol
field and thus the order mode msg parser wasn't matching the current
asset to said msgs correctly and pps weren't being shown...
This repairs that plus simplifies the order mode initial pos msg loading
to just delegate into `process_trade_msg()` just as is done for
real-time msg updates.
If a setting fails to apply try to log an error msg and revert to the
previous setting by not applying the UI read-update until after the new
`SettingsPane.apply_setting()` call. This prevents crashes when the user
tries to give bad inputs on editable allocator fields.
Previously we only simulated paper engine fills when the data feed
provide L1 queue-levels matched an execution. This patch add further
support for clear-level matches when there are real live clears on the
data feed that are faster/not synced with the L1 (aka usually during
periods of HFT).
The solution was to simply iterate the interleaved paper book entries on
both sides for said tick types and instead yield side-specific predicate
per entry.
Not entirely sure why this all of a sudden became a problem but it seems
price changes on order edits were sometimes resulting in key errors when
modifying paper book entries quickly. This changes the implementation to
not care about matching the last price when keying/popping old orders
and use `bidict`s to more easily pop cleared orders in the paper loop.
When the paper engine is used it seems we can definitely hit races where
order ack msgs arrive close enough to status messages that `trio`
schedules the status processing before the acks. In such cases we want
to be tolerant and not crash but instead warn that we got an
unknown/out-of-order msg.
Quite a simple fix, we just assign the account-specific
`PositionTracker` to the level line's `._on_level_change()` handler
instead of whatever the current `OrderMode.current_pp` is set to.
Further this adds proper pane switching support such that when a user
modifies an order line from an account which is not the currently
selected one, the settings pane is changed to reflect the
account and thus corresponding position info for that account and
instrument B)
We were overwriting the existing loaded orders list in the per client
loop (lul) so move the def above all that.
Comment out the "try-to-cancel-inactive-orders-via-task-after-timeout"
stuff pertaining to https://github.com/erdewit/ib_insync/issues/363 for
now since we don't have a mechanism in place to cancel the re-cancel
task once the order is cancelled - plus who knows if this is even the
best way to do it..
Fills seems to be dual emitted from both the `status` and `fill` events
in `ib_insync` internals and more or less contain the same data nested
inside their `Trade` type. We started handling the 'fill' case to deal
with a race issue in commissions/cost report tracking but we don't
really want to leak that same race to incremental fills vs.
order-"closed" tracking.. So go back to only emitting the fill msgs
on statuses and a "closed" on `.remaining == 0`.
`ib` is super good not being reliable with order event sequence order
and duplication of fill info. This adds some guards to try and avoid
popping the last status status too early if we end up receiving
a `'closed'` before the expected `'fill`' event(s). Further delete the
`status_msg` ref on each iteration to avoid stale reference lookups in
the relay task/loop.
This includes darks, lives and alerts with all connecting clients
being broadcast all existing order-flow dialog states. Obviously
for now darks and alerts only live as long as the `emsd` actor lifetime
(though we will store these in local state eventually) and "live" orders
have lifetimes managed by their respective backend broker.
The details of this change-set is extensive, so here we go..
Messaging schema:
- change the messaging `Status` status-key set to:
`resp: Literal['pending', 'open', 'dark_open', 'triggered',
'closed', 'fill', 'canceled', 'error']`
which better reflects the semantics of order lifetimes and was
partially inspired by the status keys `kraken` provides for their
order-entry API. The prior key set was based on `ib`'s horrible
semantics which sound like they're right out of the 80s..
Also, we reflect this same set in the `BrokerdStatus` msg and likely
we'll just get rid of the separate brokerd-dialog side type
eventually.
- use `Literal` type annots for statuses where applicable and as they
are supported by `msgspec`.
- add additional optional `Status` fields:
-`req: Order` to allow each status msg to optionally ref its
commanding order-request msg allowing at least a request-response
style implicit tracing in all response msgs.
-`src: str` tag string to show the source of the msg.
-`reqid: str | int` such that the ems can relay the `brokerd`
request id both to the client side and have one spot to look
up prior status msgs and
- draft a (unused/commented) `Dialog` type which can be eventually used
at all EMS endpoints to track msg-flow states
EMS engine adjustments/rework:
- use the new status key set throughout and expect `BrokerdStatus` msgs
to use the same new schema as `Status`.
- add a `_DarkBook._active: dict[str, Status]` table which is now used for
all per-leg-dialog associations and order flow state tracking
allowing for the both the brokerd-relay and client-request handler loops
to read/write the same msg-table and provides for delivering
the overall EMS-active-orders state to newly/re-connecting clients
with minimal processing; this table replaces what the `._ems_entries`
table from prior.
- add `Router.client_broadcast()` to send a msg to all currently
connected peers.
- a variety of msg handler block logic tweaks including more `case:`
blocks to be both flatter and improve explicitness:
- for the relay loop move all `Status` msg update and sending to
within each block instead of a fallthrough case plus hard-to-follow
state logic.
- add a specific case for unhandled backend status keys and just log
them.
- pop alerts from `._active` immediately once triggered.
- where possible mutate status msgs fields over instantiating new
ones.
- insert and expect `Order` instances in the dark clearing loop and
adjust `case:` blocks accordingly.
- tag `dark_open` and `triggered` statuses as sourced from the ems.
- drop all the `ChainMap` stuff for now; we're going to make our own
`Dialog` type for this purpose..
Order mode rework:
- always parse the `Status` msg and use match syntax cases with object
patterns, hackily assign the `.req` in many blocks to work around not
yet having proper on-the-wire decoding yet.
- make `.load_unknown_dialog_from_msg()` expect a `Status` with boxed
`.req: Order` as input.
- change `OrderDialog` -> `Dialog` in prep for a general purpose type
of the same name.
`ib` backend order loading support:
- do "closed" status detection inside the msg-relay loop instead
of expecting the ems to do this..
- add an attempt to cancel inactive orders by scheduling cancel
submissions continually (no idea if this works).
- add a status map to go from the 80s keys to our new set.
- deliver `Status` msgs with an embedded `Order` for existing live order
loading and make sure to try an get the source exchange info (instead
of SMART).
Paper engine ported to match:
- use new status keys in `BrokerdStatus` msgs
- use `match:` syntax in request handler loop
Ideally every client that connects to the ems can know its state
(immediately) meaning relay all the order dialogs that are currently
active. This adds full (hacky WIP) support to receive those dialog
(msgs) from the `open_ems()` startup values via the `.started()` msg
from `_emsd_main()`.
Further this adds support to the order mode chart-UI to display existing
(live) orders on the chart during startup. Details include,
- add a `OrderMode.load_unknown_dialog_from_msg()` for processing and
displaying a ``BrokerdStatus`` (for now) msg from the EMS that was not
previously created by the current ems client and registering and
displaying it on the chart.
- break out the ems msg processing into a new
`order_mode.process_trade_msg()` func so that it can be called on the
startup dialog-msg set as well as eventually used a more general low
level auto-strat API (eg. when we get to displaying auto-strat and
group trading automatically on an observing chart UI.
- hackyness around msg-processing for the dialogs delivery since we're
technically delivering `BrokerdStatus` msgs when the client-side
processing technically expects `Status` msgs.. we'll rectify this
soon!
In order to avoid missed existing order message emissions on startup we
need to be sure the client side stream is registered with the router
first. So break out the starting of the
`translate_and_relay_brokerd_events()` task until inside the client
stream block and start the task using the dark clearing loop nursery.
Also, ensure `oid` (and thus for `ib` the equivalent re-used `reqid`)
are cast to `str` before registering the dark book. Deliver the dark
book entries as part of the `_emsd_main()` context `.started()` values.
This seems to have been broken in refactoring from commit 279c899de5
which was never tested against multiple accounts/clients.
The fix is 2 part:
- position tables are now correctly loaded ahead of time and used by
account for each connected client in processing of ledgers and
existing positions.
- a task for each API client is started (as implemented prior) so that
we actually get status updates for every client used for submissions.
Further we add a bit of code using `bisect.insort()` to normalize
ledgers to a datetime sorted list records (though pretty sure the `dict`
transform ruins it?) in an effort to avoid issues with ledger
transaction processing with previously minimized `Position.clears`
tables, which should (but might not?) avoid incorporating clear events
prior to the last "net-zero" positioning state.
This firstly changes `.audit_sizing()` => `.ensure_state()` and makes it
return `None` as well as only error when split ratio denoted (via
config) positions do not size as expected.
Further refinements,
- add an `.expired()` predicate method
- always return a size of zero from `.calc_size()` on expired assets
- load each `pps.toml` entry's clear tabe into `Transaction`s and use
`.add_clear()` during from config init.
In order to avoid issues with reloading ledger and API trades after an
existing `pps.toml` exists we have to make sure we not only avoid
duplicate entries but also avoid re-adding entries that would have been
removed during a prior call to the `Position.minimize_clears()` filter.
The easiest way to do this is to sort on timestamps and avoid adding any
record that pre-existed the last net-zero position ledger event that
`.minimize_clears()` discarded. In order to implement this it means
parsing config file clears table's timestamps into datetime objects for
inequality checks and we add a `Position.first_clear_dt` attr for
storing this value when managing pps in object form but never store it
in the config (since it should be obviously from the sorted clear event
table).
The (partial) fills from this sub are most indicative of clears (also
says support) whereas the msgs in the `ownTrades` sub are only emitted
after the entire order request has completed - there is no size-vlm
remaining.
Further enhancements:
- this also includes proper subscription-syncing inside `subscribe()` with
a small pre-msg-loop which waits on ack-msgs for each sub and raises any
errors. This approach should probably be implemented for the data feed
streams as well.
- configure the `ownTrades` sub to not bother sending historical data on
startup.
- make the `openOrders` sub include rate limit counters.
- handle the rare case where the ems is trying to cancel an order which
was just edited and hasn't yet had it's new `txid` registered.
Since we figured out how to pass through ems dialog ids to the
`openOrders` sub we don't really need to do much with status updates
other then error handling. This drops `process_status()` and moves the
error handling logic into a status handler sub-block; we now just
info-log status updates for troubleshooting purposes.
Why we need so many fields to accomplish passing through a dialog key to
orders is beyond me but this is how they do it with edits..
Allows not having to handle `editOrderStatus` msgs to update the dialog
key table and instead just do it in the `openOrders` sub by checking the
canceled msg for a 'cancel_reason' of 'Order replaced', in which case we
just pop the txid and wait for the new order the kraken backend engine
will submit automatically, which will now have the correct 'userref'
value we passed in via the `newuserref`, and then we add that new `txid`
to our table.
Turns out you can pass both thus making mapping an ems `oid` to
a brokerd-side `reqid` much more simple. This allows us to avoid keeping
as much local dialog state but with still the following caveats:
- ok `editOrder` msgs must update the reqid<->txid map
- only pop `reqids2txids` entries inside the `cancelOrderStatus` handler
If we don't have a pos table built out already (in mem) we can't figure
out the likely dst asset (since there's no pair entry to guide us) that
we should use to search for withdrawal transactions; so move it later.
Further this ports to the new api changes in `piker.pp`` that will land
with #365.
This ended up driving the rework of the `piker.pp` apis to use context
manager + table style which resulted in a much easier to follow
state/update system B). Also added is a flag to do a manual simulation
of a "fill triggered rt pp msg" which requires the user to delete the
last ledgered trade entry from config files and then allowing that trade
to emit through the `openOrders` sub and update client shortly after
order mode boot; this is how the rt updates were verified to work
without doing even more live orders 😂.
Patch details:
- open both `open_trade_ledger()` and `open_pps()` inside the trade
dialog startup and conduct a "pp state sync" logic phase where we now
pull the account balances and incrementally load pp data (in order,
from `pps.toml`, ledger, api) until we can generate the asset balance
by reverse incrementing through trade history eventually erroring out
if we can't reproduce the balance value.
- rework the `trade2pps()` to take in the `PpTable` and generate new
ems msgs from table updates.
- return the new `dict[str, Transaction]` expected from
`norm_trade_records()`
- only update pp config and ledger on dialog exit.
Since our ems doesn't actually do blocking style client-side submission
updates, thus resulting in the client being able to update an existing
order's state before knowing its current state, we can run into race
conditions where for some backends an order is updated using the wrong
order id. For kraken we manually implement detecting this race (lol, for
now anyway) such that when a new client side edit comes in before the
new `txid` is known, we simply expect the handler loop to cancel the
order. Further this adds cancellation on arbitrary status errors, like
rate limits.
Also this adds 2 leg (ems <-> brokerd <-> kraken) msg tracing using
a `collections.ChainMap` which is likely going to end up being the POC
for a more general data structure recommended for backends that need to
trace msg flow for translation with the ems.
Turns out the `openOrders` and `ownTrades` subs always return a `reqid`
value (the one brokerd sends to the kraken api in order requests) is
always set to zero, which seems to be a bug? So this includes patches to
work around that as well reliance on the `openOrders` sub to do most
`BrokerdStatus` updates since `XOrderStatus` events don't seem to have
much data in them at all (they almost look like pure ack events so maybe
they aren't affirmative of final state changes anyway..).
Other fixes:
- respond with a `BrokerdOrderAck` immediately after `requid` generation
not after order submission to ensure the ems has a valid `requid`
*before* kraken api events are relayed through.
- add a `reqids2txids: bidict[int, str]` which maps brokerd genned
`requid`s to kraken-side `txid`s since (as mentioned above) the
clearing and state endpoints don't relay back this value (it's always
0...)
- add log messages for each sub so that (at least for now) we can see
exact msg contents coming from kraken.
- drop `.remaining` calcs for now since we need to keep record of the
order states manually in order to retreive the original submission
vlm..
- fix the `openOrders` case for fills, in this case the message includes
no `status` field and thus we must catch it in a block *after* the
normal state handler to avoid masking.
- drop response msg generation from the cancel status case since we
can do it again from the `openOrders` handler and sending a double
status causes issues on the client side.
- add a shite ton of notes around all this missing `requid` stuff.
More or less just to avoid orders the user wasn't aware of from
persisting until we get "open order relaying" through the ems working.
Some further fixes which required a new `reqids2txids` map which keeps
track of which `kraken` "txid" is mapped to our `reqid: int`; mainly
this was needed for cancel requests which require knowing the underlying
`txid`s (since apparently kraken doesn't keep track of the "reqid" we
pass it). Pass the ws instance into `handle_order_updates()` to enable
the cancelling orders on startup. Don't key error on unknown `reqid`
values (for eg. when receiving historical trade events on startup).
Handle cancel requests first in the ems side loop.
Since we seem to always be able to get back the `reqid`/`userref` value
we send to kraken ws endpoints, we can use this as our brokerd side
order id and avoid all race cases with getting the true `txid` value
that `kraken` assigns (and which changes when you do "edits"
:eyeroll:). This simplifies status updates by allowing our relay loop
just to pass back our generated `.reqid` verbatim and allows responding
with a `BrokerdOrderAck` immediately in the request handler task which
should guarantee there are no further race conditions with the relay
loop and mapping `txid`s from kraken.. and figuring out wtf to do when
they change, etc.
Addressing same issue as in #350 where we need to compute position
updates using the *first read* from the ledger **before** we update it
to make sure `Position.lifo_update()` gets called and **not skipped**
because new trades were read as clears entries but haven't actually been
included in update calcs yet.. aka we call `Position.lifo_update()`.
Main change here is to convert `update_ledger()` into a context mngr so
that the ledger write is committed after pps updates using
`pp.update_pps_conf()`..
This is basically a hotfix to #346 as well.
Turns out the EMS can support this as originally expected: you can
update a `brokerd`-side `.reqid` through a `BrokerdAck` msg and the ems
which update its cross-dialog (leg) tracking correctly! The issue was
a bug in the `editOrderStatus` msg handling and appropriate tracking
of the correct `.oid` (ems uid) on the kraken side. This unfortunately
required adding a `emsflow: dict[str, list[BrokerdOrder]]` msg flow
tracing table which means the broker daemon is tracking all the msg flow
with the ems, though I'm wondering now if this is just good practise
anyway and maybe we should offer a small primitive type from our msging
utils to aid with this? I've used such constructs in event handling
systems prior.
There's a lot more factoring that can be done after these changes as
well but the quick detailed summary is,
- rework the `handle_order_requests()` loop to use `match:` syntax and
update the new `emsflow` table on every new request from the ems.
- fix the `editOrderStatus` case pattern to not include an error msg and
thus actually be triggered to respond to the ems with a `BrokerdAck`
containing the new `.reqid`, the new kraken side `txid`.
- skip any `openOrders` msgs which are detected as being kraken's
internal order "edits" by matching on the `cancel_reason` field.
- update the `emsflow` table in all ws-stream msg handling blocks
with responses sent to the ems.
Relates to #290
Move to using the websocket API for all order control ops and dropping
the sync rest api approach which resulted in a bunch of buggy races.
Further this gets us must faster (batch) order cancellation for free
and a simpler ems request handler loop. We now heavily leverage the new
py3.10 `match:` syntax for all kraken-side API msg parsing and
processing and handle both the `openOrders` and `ownTrades` subscription
streams.
We also block "order editing" (by immediate cancellation) for now since
the EMS isn't entirely yet equipped to handle brokerd side `.reqid`
changes (which is how kraken implements so called order "updates" or
"edits") for a given order-request dialog and we may want to even
consider just implementing "updates" ourselves via independent cancel
and submit requests? Definitely something to ponder. Alternatively we
can "masquerade" such updates behind the count-style `.oid` remapping we
had to implement anyway (kraken's limitation) and maybe everything will
just work?
Further details in this patch:
- create 2 tables for tracking the EMS's `.oid` (uui4) value to `int`s
that kraken expects (for `reqid`s): `ids` and `reqmsgs` which enable
local lookup of ems uids to piker-backend-client-side request ids and
received order messages.
- add `openOrders` sub support which more or less directly relays to
equivalent `BrokerdStatus` updates and calc the `.filled` and
`.remaining` values based on cleared vlm updates.
- add handler blocks for `[add/edit/cancel]OrderStatus` events including
error msg cases.
- don't do any order request response processing in
`handle_order_requests()` since responses are always received via one
(or both?) of the new ws subs: `ownTrades` and `openOrders` and thus
such msgs are now handled in the response relay loop.
Relates to #290Resolves#310, #296
This drops the use of `pp.update_pps_conf()` (and friends) and instead
moves to using the context style `open_trade_ledger()` and `open_pps()`
managers for faster pp msg gen due to delayed file writing (which was
the main source update latency).
In order to make this work with potentially multiple accounts this also
uses an exit stack which loads each ledger / `pps.toml` into an account
id mapped `dict`; a POC for likely how we should implement some higher
level position manager api.
The original implementation of `.calc_be_price()` wasn't correct since
the real so called "price per unit" (ppu), is actually defined by
a recurrence relation (which is why the original state-updated
`.lifo_update()` approach worked well) and requires the previous ppu to
be weighted by the new accumulated position size when considering a new
clear event. The ppu is the price that above or below which the trader
takes a win or loss on transacting one unit of the trading asset and
thus it is the true "break even price" that determines making or losing
money per fill. This patches fixes the implementation to use trailing
windows of the accumulated size and ppu to compute the next ppu value
for any new clear event as well as handle rare cases where the
"direction" changes polarity (eg. long to short in a single order). The
new method is `Position.calc_ppu()` and further details of the relation
can be seen in the doc strings.
This patch also includes a wack-ton of clean ups and removals in an
effort to refine position management api for easier use in new backends:
- drop `updaate_pps_conf()`, `load_pps_from_toml()` and rename
`load_trands_from_ledger()` -> `load_pps_from_ledger()`.
- extend `PpTable` to have a `.to_toml()` method which returns the
active set of positions ready to be serialized to the `pps.toml` file
which is collects from calling,
- `PpTable.dump_active()` which now returns double dicts of the
open/closed pp object maps.
- make `Position.minimize_clears()` now iterate the clears table in
chronological order (instead of reverse) and only drop fills prior
to any zero-size state (the old reversed way can result incorrect
history-size-retracement in cases where a position is lessened but
not completely exited).
- drop `Position.add_clear()` and instead just manually add entries
inside `.update_from_trans()` and also add a `accum_size` and `ppu`
field to ever entry thus creating a position "history" sequence of
the ppu and accum size for every position and prepares for being
and to show "position lifetimes" in the UI.
- move fqsn getting into `Position.to_pretoml()`.
Use the new `.calc_[be_price/size]()` methods when serializing to and
from the `pps.toml` format and add an audit method which will warn about
mismatched values and assign the clears table calculated values pre-write.
Drop the `.lifo_update()` method and instead allow both
`.size`/`.be_price` properties to exist (for non-ledger related uses of
`Position`) alongside the new calc methods and only get fussy about
*what* the properties are set to in the case of ledger audits.
Also changes `Position.update()` -> `.add_clear()`.
Since we're going to need them anyway for desired features, add
2 new `Position` methods:
- `.calc_be_price()` which computes the breakeven cost basis price
from the entries in the clears table.
- `.calc_size()` which just sums the clear sizes.
Add a `cost_scalar: float` control to the `.update_from_trans()` method
to allow manual adjustment of the cost weighting for the case where
a "non-symmetrical" model is wanted.
Go back to always trying to write the backing ledger files on exit, even
when there's an error (obvs without the `return` in the `finally:` block
f$#% up).
Can't believe i missed this but any `return` inside a `finally` will
suppress the error from the `try:` part... XD
Thought i was losing my mind when the ledger was mutated and then
an error just after wasn't getting raised.. lul.
Never again...
In order to avoid double transaction adds/updates and too-early-discard
of zero sized pps (like when trades are loaded from a backend broker but
were already added to a ledger or `pps.toml` prior) we now **don't** pop
such `Position` entries from the `.pps` table in order to keep each
position's clears table always in place. This avoids the edge case where
an entry was removed too early (due to zero size) but then duplicate
trade entries that were in that entrie's clears show up from the backend
and are entered into a new entry resulting in an incorrect size in a new
entry..We still only push non-net-zero entries to the `pps.toml`.
More fixes:
- return the updated set of `Positions` from `.lifo_update()`.
- return the full table set from `update_pps()`.
- use `PpTable.update_from_trans()` more throughout.
- always write the `pps.toml` on `open_pps()` exit.
- only return table from `load_pps_from_toml()`.
In an effort to begin allowing backends to have more granular control
over position updates, particular in the case where they need to be
reloaded from a trades ledger, this adds a new table API which can
be loaded using `open_pps()`.
- offer an `.update_trans()` method which takes in a `dict` of
`Transactions` and updates the current table of `Positions` from it.
- add a `.dump_active()` which renders the active pp entries dict in
a format ready for toml serialization and all closed positions since
the last update (we might want to not drop these?)
All other module-function apis currently in use should remain working as
before for the moment.
Change `.find_contract()` -> `.find_contracts()` to allow multi-search
for so called "ambiguous" contracts (like for `Future`s) such that the
method now returns a `list` of tracts and populates the contract cache
with all specific tracts retrieved. Let it take in an (unvalidated)
contract that will be fqsn-style-tokenized such that it can be called
from `.search_symbols()` (though we're not quite yet XD).
More stuff,
- add `Client.parse_patt2fqsn()` which is an fqsn to token unpacker
built from the original logic in the old `.find_contract()`.
- handle fiat/forex pairs with the `'CASH'` sectype.
- add a flag to allow unqualified contracts to fail with a warning msg.
- populate the client's contract cache with all expiries of
an ambiguous derivative.
- allow `.con_deats()` to warn msg instead of raise on def-not-found.
- add commented `assert 0` which was triggering a debugger deadlock in
`tractor` which we still haven't been able to create a unit test for.
Minimize calling `.data._shmarray.attach_shm_array()` as much as is
possible to avoid the crash from #332. This is the suggested hack from
issue #359.
Resolves https://github.com/pikers/piker/issues/359
Not sure why I put this off for so long but the check is in now such
that if the market isn't open or no rt quote comes in from the first
query, we just pull from the last shm history 'close' value.
Includes another fix to avoid raising when a double remove on the client
side stream from the registry sometimes happens.
Not sure this didn't get caught in usage, but basically real-time
updates got broken by a rework of `update_ledger_from_api_trades()`.
The issue is that the ledger was being updated **before** calling
`piker.pp.update_pps_conf()` which resulted in the `Position.size`
not being updated correctly since the [latest added] clears passed
in via the `trade_records` arg were already found in the `.clears` table
and thus were causing the loop to skip the `Position.lifo_update()`
call..
The solution here is to not update the ledger **until after** we call
`update_pps_conf()` - it's more read/writes but it's correct and we
figure out a less io heavy way to do the file writing later.
Further this includes a fix to avoid double emitting a pp update caused
by non-thorough logic that waits for a commission report to arrive
during a fill event; previously we were emitting the same message twice
due to the lack of a check for an existing comms report in the case
where the report arrives *after* the fill.
Moves to using the new `piker.pp` apis to both store real-time trade
events in a ledger file as well emit position update msgs (which were
not in this backend at all prior) when new orders clear (aka fill).
In terms of outstanding issues,
- solves the pp update part of the bugs reported in #310
- starts a msg case block in prep for #293
Details of rework:
- move the `subscribe()` ws fixture to module level and `partial()` in
the client token instead of passing it to the instance; in prep for
removal of the `.token` attr from the `NoBsWs` wrapper.
- drop `make_auth_sub()` since it was too thin and we can just
do it all succinctly in `subscribe()`
- filter trade update msgs to those not yet stored int the toml ledger
- much better kraken api msg unpacking using new `match:` synax B)
Resolves#311
No real-time update support (yet) but this is the first draft at writing
trades ledgers and `pps.toml` entries for the kraken backend.
Deatz:
- drop `pack_positions()`, no longer used.
- use `piker.pp` apis to both write a trades ledger file and update the
`pps.toml` inside the `trades_dialogue()` endpoint startup.
- drop the weird paper engine swap over if auth can't be done, we should
be doing something with messaging in the ems over this..
- more web API error response raising.
- pass the `pp.Transaction` set loaded from ledger into
`process_trade_msgs()` do avoid duplicate sends of already collected
trades msgs.
- add `norm_trade_records()` public endpoing (used by `piker.pp` api)
and `update_ledger()` helper.
- rejig `process_trade_msgs()` to drop the weird `try:` assertion block
and skip already-recorded-in-ledger trade msgs as well as yield *each*
trade instead of sub-sequences.
This was just implemented totally wrong but somehow worked XD
The idea was to include all trades that contribute to ongoing position
size since the last time the position was "net zero", i.e. no position
in the asset. Adjust arithmetic to *subtract* from the current size
until a zero size condition is met and then keep all those clears as
part of the "current state" clears table.
Additionally this fixes another bug where the positions freshly loaded
from a ledger *were not* being merged with the current `pps.toml` state.
Gah, was a remaining bug where if you tried to update the pps state with
both new trades and from the ledger you'd do a double add of
transactions that were cleared during a `update_pps()` loop. Instead now
keep all clears in tact until ready to serialize to the `pps.toml` file
in which cases we call a new method `Position.minimize_clears()` which
does the work of only keep clears since the last net-zero size.
Re-implement `update_pps_conf()` update logic as a single pass loop
which does expiry and size checking for closed pps all in one pass thus
allowing us to drop `dump_active()` which was kinda redundant anyway..
Before we weren't emitting pp msgs when a position went back to "net
zero" (aka the size is zero) nor when a new one was opened (wasn't
previously loaded from the `pps.toml`). This reworks a bunch of the
incremental update logic as well as ports to the changes in the
`piker.pp` module:
- rename a few of the normalizing helpers to be more explicit.
- drop calling `pp.get_pps()` in the trades dialog task and instead
create msgs iteratively, per account, by iterating through collected
position and API trade records and calling instead
`pp.update_pps_conf()`.
- always from-ledger-update both positions reported from ib's pp sys and
session api trades detected on ems-trade-dialog startup.
- `update_ledger_from_api_trades()` now does **just** that: only updates
the trades ledger and returns the transaction set.
- `update_and_audit_msgs()` now only the input list of msgs and properly
generates new msgs for newly created positions that weren't previously
loaded from the `pps.toml`.
- use `tomli` package for reading since it's the fastest pure python
reader available apparently.
- add new fields to each pp's clears table: price, size, dt
- make `load_pps_from_toml()`'s `reload_records` a dict that can be
passed in by the caller and is verbatim used to re-read a ledger and
filter to the specified symbol set to build out fresh pp objects.
- add a `update_from_ledger: bool` flag to `load_pps_from_toml()`
to allow forcing a full backend ledger read.
- if a set of trades records is passed into `update_pps_conf()` parse
out the meta data required to cause a ledger reload as per 2 bullets
above.
- return active and closed pps in separate by-account maps from
`update_pps_conf()`.
- drop the `key_by` kwarg.
This makes it possible to refresh a single fqsn-position in one's
`pps.toml` by simply deleting the file entry, in which case, if there is
new trade records passed to `load_pps_from_toml()` via the new
`reload_records` kwarg, then the backend ledger entries matching that
symbol will be filtered and used to recompute a fresh position.
This turns out to be super handy when you have crashes that prevent
a `pps.toml` entry from being updated correctly but where the ledger
does have all the data necessary to calculate a fresh correct entry.
Since some positions obviously expire and thus shouldn't continually
exist inside a `pps.toml` add naive support for tracking and discarding
expired contracts:
- add `Transaction.expiry: Optional[pendulum.datetime]`.
- add `Position.expiry: Optional[pendulum.datetime]` which can be parsed
from a transaction ledger.
- only write pps with a non-none expiry to the `pps.toml`
- change `Position.avg_price` -> `.be_price` (be is "breakeven")
since it's a much less ambiguous name.
- change `load_pps_from_legder()` to *not* call `dump_active()` since
for the only use case it ends up getting called later anyway.
We can probably make this better (and with less file sys accesses) later
such that we keep a consistent pps state in mem and only write async
maybe from another side-task?
What a nightmare this was.. main holdup was that cost (commissions)
reports are fired independent from "fills" so you can't really emit
a proper full position update until they both arrive.
Deatz:
- move `push_tradesies()` and relay loop in `deliver_trade_events()` to
the new py3.10 `match:` syntax B)
- subscribe for, and handle `CommissionReport` events from `ib_insync`
and repack as a `cost` event type.
- handle cons with no primary/listing exchange (like futes) in
`update_ledger_from_api_trades()` by falling back to the plain
'exchange' field.
- drop reverse fqsn lookup from ib positions map; just use contract
lookup for api trade logs since we're already connected..
- make validation in `update_and_audit()` optional via flag.
- pass in the accounts def, ib pp msg table and the proxies table to the
trade event relay task-loop.
- add `emit_pp_update()` too encapsulate a full api trade entry
incremental update which calls into the `piker.pp` apis to,
- update the ledger
- update the pps.toml
- generate a new `BrokerdPosition` msg to send to the ems
- adjust trades relay loop to only emit pp updates when a cost report
arrives for the fill/execution by maintaining a small table per exec
id.
I don't want to rant too much any more since it's pretty clear `ib` has
either zero concern for its (api) user's or a severely terrible data
management team and/or general inter-team coordination system, but this
patch more or less hacks the flex report records to be similar enough to
API "execution" / "fill" records such that they can be similarly
normalized and stored as well as processed for position calculations..
Dirty deats,
- use the `IB.fills()` method for pulling current session trade events
since it's both recommended in the docs and does seem to capture
more extensive meta-data.
- add a `update_ledger_from_api()` helper which does all the insane work
of making sure api trade entries are usable both within piker's global
fqsn system but also compatible with incremental updates of positions
computed from trade ledgers derived from ib's "flex reports".
- add "auditting" of `ib`'s reported positioning API messages by
comparison with piker's new "traders first" breakeven price style and
complain via logging on mismatches.
- handle buy vs. sell arithmetic (via a +ve or -ve multiplier) to make
"size" arithmetic work for API trade entries..
- draft out options contract transaction parsing but skip in pps
generation for now.
- always use the "execution id" as ledger keys both in flex and api
trade processing.
- for whatever weird reason `ib_insync` doesn't include the so called
"primary exchange" in contracts reported in fill events, so do manual
contract lookups in such cases such that pps entries can be placed
in the right fqsn section...
Still ToDo:
- incremental update on trade clears / position updates
- pps audit from ledger depending on user config?
This makes a few major changes but mostly is centered around including
transaction (aka trade-clear) costs in the avg breakeven price
calculation.
TL;DR:
- rename `TradeRecord` -> `Transaction`.
- make `Position.fills` a `dict[str, float]` which holds each clear's
cost value.
- change `Transaction.symkey` -> `.bsuid` for "backend symbol unique id".
- drop `brokername: str` arg to `update_pps()`
- rename `._split_active()` -> `dump_active()` and use input keys
verbatim in output map.
- in `update_pps_conf()` always incrementally update from trade records
even when no `pps.toml` exists yet since it may be both the case that
the ledger needs loading **and** the caller is handing new records not
yet in the ledger.
Begins the position tracking incremental update API which supports both
constructing a `pps.toml` both from trade ledgers as well diff-oriented
incremental update from an existing config assumed to be previously
generated from some prior ledger.
New set of routines includes:
- `_split_active()` a helper to split a position table into the active
and closed positions (aka pps of size 0) for determining entry updates
in the `pps.toml`.
- `update_pps_conf()` to maybe load a `pps.toml` and update it from
an input trades ledger including necessary (de)serialization to and
from `Position` object form(s).
- `load_pps_from_ledger()` a ledger parser-loader which constructs
a table of pps strictly from the broker-account ledger data without
any consideration for any existing pps file.
Each "entry" in `pps.toml` also contains a `fills: list` attr (name may
change) which references the set of trade records which make up its
state since the last net-zero position in the instrument.
Add a `TradeRecord` struct which holds the minimal field set to build
out position entries. Add `.update_pps()` to convert a set of records
into LIFO position entries, optionally allowing for an update to some
existing pp input set. Add `load_pps_from_ledger()` which does a full
ledger extraction to pp objects, ready for writing a `pps.toml`.
Since "flex reports" are only available for the current session's trades
the day after, this adds support for also collecting trade execution
records for the current session and writing them to the equivalent
ledger file.
Summary:
- add `trades_to_records()` to handle parsing both flex and API event
objects into a common record form.
- add `norm_trade_records()` to handle converting ledger entries into
`TradeRecord` types from the new `piker.pps` mod (coming in next
commit).
Start a generic "position related" util mod and bring in the `Position`
type from the allocator , convert it to a `msgspec.Struct` and add
a `.lifo_update()` method. Implement a WIP pp parser from a trades
ledger and use the new lifo method to gather position entries.
Add `ChartPlotWidget._on_screen: bool` which allows detecting for the
first state where there is y-range-able flow data loaded and able to be
drawn. Check for this flag to be set in `.maxmin()` such that until the
historical data is loaded `.default_view()` will be called to ensure
that a blank view is never shown: race with the UI starting versus the
data layer loading flow graphics can have this outcome.
This should hopefully make teardown more reliable and includes better
logic to fail over to a hard kill path after a 3 second timeout waiting
for the instance to complete using the `docker-py` wait API. Also
generalize the supervisor teardown loop by allowing the container config
endpoint to return 2 msgs to expect:
- a startup message that can be read from the container's internal
process logging that indicates it is fully up and ready.
- a teardown msg that can be polled for that indicates the container has
gracefully terminated after a cancellation request which is passed to
our container wrappers `.cancel()` method.
Make the marketstore config endpoint return the 2 messages we previously
had hard coded and use this new api.
This was introduced in #302 but after thorough testing was clear to be
not working XD. Adjust the display loop to update the last graphics
segment on both the OHLC and vlm charts (as well as all deriving fsp
flows) whenever the uppx >= 1 and there is no current path append
taking place (since more datums are needed to span an x-pixel in view).
Summary of tweaks:
- move vlm chart update code to be at the end of the cycle routine and
have that block include the tests for a "interpolated last datum in
view" line.
- make `do_append: bool` compare with a floor of the uppx value (i.e.
appends should happen when we're just fractionally over a pixel of
x units).
- never update the "volume" chart.
Allows for optionally updating a "downsampled" graphics type which is
currently necessary in the `BarItems` -> `FlattenedOHLC` curve switching
case; we don't want to be needlessly redrawing the `Flow.graphics`
object (which will be an OHLC curve) when in flattened curve mode.
Further add a `only_last_uppx: bool` flag to `.draw_last()` to allow
forcing a "last uppx's worth of data max/min" style interpolating line
as needed.
The single-file module was getting way out of hand size-wise with the
new flex report parsing stuff so this starts the process of breaking
things up into smaller modules oriented around trade, data, and ledger
related endpoints.
Add support for backends to declare sub-modules to enable in
a `__enable_modules__: list[str]` module var which is parsed by the
daemon spawning code passed to `tractor`'s `enable_modules: list[str]`
input.
When using m4, we downsample to the max and min of each
pixel-column's-worth of data thus preserving range / dispersion details
whilst not drawing more graphics then can be displayed by the available
amount of horizontal pixels.
Take and apply this exact same concept to the "last datum" graphics
elements for any `Flow` that is reported as being in a downsampled
state:
- take the xy output from the `Curve.draw_last_datum()`,
- slice out all data that fits in the last pixel's worth of x-range
by using the uppx,
- compute the highest and lowest value from that data,
- draw a singe line segment which spans this yrange thus creating
a simple vertical set of pixels which are "filled in" and show the
entire y-range for the most recent data "contained with that pixel".
Instead of using a bunch of internal logic to modify low level paint-able
elements create a `Curve` lineage that allows for graphics "style"
customization via a small set of public methods:
- `Curve.declare_paintables()` to allow setup of state/elements to be
drawn in later methods.
- `.sub_paint()` to allow painting additional elements along with the
defaults.
- `.sub_br()` to customize the `.boundingRect()` dimensions.
- `.draw_last_datum()` which is expected to produce the paintable
elements which will show the last datum in view.
Introduce the new sub-types and load as necessary in
`ChartPlotWidget.draw_curve()`:
- `FlattenedOHLC`
- `StepCurve`
Reimplement all `.draw_last()` routines as a `Curve` method
and call it the same way from `Flow.update_graphics()`
The basic logic is now this:
- when zooming out, uppx (units per pixel in x) can be >= 1
- if the uppx is `n` then the next pixel in view becomes occupied by
a new datum-x-coordinate-value when the diff between the last
datum step (since the last such update) is greater then the
current uppx -> `datums_diff >= n`
- if we're less then some constant uppx we just always update (because
it's not costly enough and we're not downsampling.
More or less this just avoids unnecessary real-time updates to flow
graphics until they would actually be noticeable via the next pixel
column on screen.
This was a bit of a nightmare to figure out but, it seems that the
coordinate caching system will really be a dick (like the nickname for
richard for you serious types) about leaving stale graphics if we don't
reset the cache on downsample full-redraw updates...Sooo, instead we do
this manual reset to avoid such artifacts and consequently (for now)
return a `reset: bool` flag in the return tuple from `Renderer.render()`
to indicate as such.
Some further shite:
- move the step mode `.draw_last()` equivalent graphics updates down
with the rest..
- drop some superfluous `should_redraw` logic from
`Renderer.render()` and compound it in the full path redraw block.
Adds a new pre-graphics data-format callback incremental update api to
our `Renderer`. `Renderer` instance can now overload these custom routines:
- `.update_xy()` a routine which accepts the latest [pre/a]pended data
sliced out from shm and returns it in a format suitable to store in
the optional `.[x/y]_data` arrays.
- `.allocate_xy()` which initially does the work of pre-allocating the
`.[x/y]_data` arrays based on the source shm sizing such that new
data can be filled in (to memory).
- `._xy_[first/last]: int` attrs to track index diffs between src shm
and the xy format data updates.
Implement the step curve data format with 3 super simple routines:
- `.allocate_xy()` -> `._pathops.to_step_format()`
- `.update_xy()` -> `._flows.update_step_xy()`
- `.format_xy()` -> `._flows.step_to_xy()`
Further, adjust `._pathops.gen_ohlc_qpath()` to adhere to the new
call signature.
We're doing this in `Flow.update_graphics()` atm and probably are going
to in general want custom graphics objects for all the diff curve / path
types. The new flows work seems to fix the bounding rect width calcs to
not require the ad-hoc extra `+ 1` in the step mode case; before it was
always a bit hacky anyway. This also tries to add a more correct
bounding rect adjustment for the `._last_line` segment.
Finally this gets us much closer to a generic incremental update system
for graphics wherein the input array diffing, pre-graphical format data
processing, downsampler activation and incremental update and storage of
any of these data flow stages can be managed in one modular sub-system
:surfer_boi:.
Dirty deatz:
- reorg and move all path logic into `Renderer.render()` and have it
take in pretty much the same flags as the old
`FastAppendCurve.update_from_array()` and instead storing all update
state vars (even copies of the downsampler related ones) on the
renderer instance:
- new state vars: `._last_uppx, ._in_ds, ._vr, ._avr`
- `.render()` input bools: `new_sample_rate, should_redraw,
should_ds, showing_src_data`
- add a hack-around for passing in incremental update data (for now)
via a `input_data: tuple` of numpy arrays
- a default `uppx: float = 1`
- add new render interface attrs:
- `.format_xy()` which takes in the source data array and produces out
x, y arrays (and maybe a `connect` array) that can be passed to
`.draw_path()` (the default for this is just to slice out the index
and `array_key: str` columns from the input struct array),
- `.draw_path()` which takes in the x, y, connect arrays and generates
a `QPainterPath`
- `.fast_path`, for "appendable" updates like there was on the fast
append curve
- move redraw (aka `.clear()` calls) into `.draw_path()` and trigger
via `redraw: bool` flag.
- our graphics objects no longer set their own `.path` state, it's done
by the `Flow.update_graphics()` method using output from
`Renderer.render()` (and it's state if necessary)
A bit hacky to get all graphics types working but this is hopefully the
first step toward moving all the generic update logic into `Renderer`
types which can be themselves managed more compactly and cached per
uppx-m4 level.
Which is basically just "deleting" rows from a column series.
You can only use the trim command from the `.cmd` cli and only with a so
called `LocalClient` currently; it's also sketchy af and caused
a machine to hang due to mem usage..
Ideally we can patch in this functionality for use by the rpc api
and have it not hang like this XD
Pertains to https://github.com/alpacahq/marketstore/issues/264
Yet another path ops routine which converts a 1d array into a data
format suitable for rendering a "step curve" graphics path (aka a "bar
graph" but implemented as a continuous line).
Also, factor the `BarItems` rendering logic (which determines whether to
render the literal bars lines or a downsampled curve) into a routine
`render_baritems()` until we figure out the right abstraction layer for
it.
Starts a module for grouping together all our `QPainterpath` related
generation and data format operations for creation of fast curve
graphics. To start, drops `FastAppendCurve.downsample()` and moves
it to a new `._pathops.xy_downsample()`.
Mostly just dropping old commented code for "step mode" format
generation. Always slice the tail part of the input data and move to the
new `ms_threshold` in the `pg` profiler'
Relates to the bug discovered in #310, this should avoid out-of-order
msgs which do not have a `.reqid` set to be error logged to console.
Further, add `pformat()` to kraken logging of ems msging.
Since downsampling with the more correct version of m4 (uppx driven
windows sizing) is super fast now we don't need to avoid downsampling
on low uppx values. Further all graphics objects now support in-view
slicing so make sure to use it on interaction updates. Pass in the view
profiler to update method calls for more detailed measuring.
Even moar,
- Add a manual call to `.maybe_downsample_graphics()` inside the mouse
wheel event handler since it seems that sometimes trailing events get
lost from the `.sigRangeChangedManually` signal which can result in
"non-downsampled-enough" graphics on chart given the scroll amount;
this manual call seems to entirely fix this?
- drop "max zoom" guard since internals now support (near) infinite
scroll out to graphics becoming a single pixel column line XD
- add back in commented xrange signal connect code for easy testing to
verify against range updates not happening without it
This took longer then i care to admit XD but it definitely adds a huge
speedup and with only a few outstanding correctness bugs:
- panning from left to right causes strange trailing artifacts in the
flows fsp (vlm) sub-plot but only when some data is off-screen on the
left but doesn't appear to be an issue if we keep the `._set_yrange()`
handler hooked up to the `.sigXRangeChanged` signal (but we aren't
going to because this makes panning way slower). i've got a feeling
this is a bug todo with the device coordinate cache stuff and we may
need to report to Qt core?
- factoring out the step curve logic from
`FastAppendCurve.update_from_array()` (un)fortunately required some
logic branch uncoupling but also meant we needed special input controls
to avoid things like redraws and curve appends for special cases,
this will hopefully all be better rectified in code when the core of
this method is moved into a renderer type/implementation.
- the `tina_vwap` fsp curve now somehow causes hangs when doing erratic
scrolling on downsampled graphics data. i have no idea why or how but
disabling it makes the issue go away (ui will literally just freeze
and gobble CPU on a `.paint()` call until you ctrl-c the hell out of
it). my guess is that something in the logic for standard line curves
and appends on large data sets is the issue?
Code related changes/hacks:
- drop use of `step_path_arrays_from_1d()`, it was always a bit hacky
(being based on `pyqtgraph` internals) and was generally hard to
understand since it returns 1d data instead of the more expected (N,2)
array of "step levels"; instead this is now implemented (uglily) in
the `Flow.update_graphics()` block for step curves (which will
obviously get cleaned up and factored elsewhere).
- add a bunch of new flags to the update method on the fast append
curve: `draw_last: bool`, `slice_to_head: int`, `do_append: bool`,
`should_redraw: bool` which are all controls to aid with previously
mentioned issues specific to getting step curve updates working
correctly.
- add a ton of commented tinkering related code (that we may end up
using) to both the flow and append curve methods that was written as
part of the effort to get this all working.
- implement all step curve updating inline in `Flow.update_graphics()`
including prepend and append logic for pre-graphics incremental step
data maintenance and in-view slicing as well as "last step" graphics
updating.
Obviously clean up commits coming stat B)
Since we have in-view style rendering working for all curve types
(finally) we can avoid the guard for low uppx levels and without losing
interaction speed. Further don't delay the profiler so that the nested
method calls correctly report upward - which wasn't working likely due
to some kinda GC collection related issue.
More or less this improves update latency like mad. Only draw data in
view and avoid full path regen as much as possible within a given
(down)sampling setting. We now support append path updates with in-view
data and the *SPECIAL CAVEAT* is that we avoid redrawing the whole curve
**only when** we calc an `append_length <= 1` **even if the view range
changed**. XXX: this should change in the future probably such that the
caller graphics update code can pass a flag which says whether or not to
do a full redraw based on it knowing where it's an interaction based
view-range change or a flow update change which doesn't require a full
path re-render.
After much effort (and exhaustion) but failure to get a view into our
`numpy` OHLC struct-array, this instead allocates an in-thread-memory
array which is updated with flattened data every flow update cycle.
I need to report what I think is a bug to `numpy` core about the whole
view thing not working but, more or less this gets the same behaviour
and minimizes work to flatten the sampled data for line-graphics drawing
thus improving refresh latency when drawing large downsampled curves.
Update the OHLC ds curve with view aware data sliced out from the
pre-allocated and incrementally updated data (we had to add a last index
var `._iflat` to track appends - this should be moved into a renderer
eventually?).
This begins the removal of data processing / analysis methods from the
chart widget and instead moving them to our new `Flow` API (in the new
module introduce here) and delegating the old chart methods to the
respective internal flow. Most importantly is no longer storing the
"last read" of an array from shm in an internal chart table (was
`._arrays`) and instead the `ShmArray` instance is passed as input and
stored in the `Flow` instance. This greatly simplifies lookup logic such
that the display loop now doesn't have to worry about reading shm, it
can be done by internal graphics logic as desired. Generally speaking,
all previous `._arrays`/`._graphics` lookups are now delegated to the
entries in the chart's `._flows` table.
The new `Flow` methods are generally better factored and provide more
detailed output regarding data-stream <-> graphics inter-relations for
the future purpose of allowing much more efficient update calls in the
display loop as well as supporting low latency interaction UX.
The concept here is that we're introducing an intermediary layer that
ties together graphics and real-time data flows such that widget code is
oriented around plot layout and the flow apis are oriented around
real-time low latency updates and providing an efficient high level
metric layer for the UX.
The summary api transition is something like:
- `update_graphics_from_array()` -> `.update_graphics_from_flow()`
- `.bars_range()` -> `Flow.datums_range()`
- `.bars_range()` -> `Flow.datums_range()`
Given that naming the port map is mostly pointless, since accounts can
be detected once the client connects, just expect a `brokers.toml` to
define a simple sequence of port numbers. Toss in a warning for using
the old map/`dict` style.
Now that we have working client auth thanks to:
https://github.com/barneygale/asyncvnc/pull/4 and related issue,
we can use a pw for the vnc server, though we should eventually
auto-generate a random one from a docker super obviously.
Add logic to the data reset hack loop to do a connection reset after
2 failed/timeout attempts at the regular data reset. We need to also add
this logic around reconnectionn events that are due to the host
network connection: aka roaming that's faster then timing logic
builtin to the gateway.
`ib-gw` seems particularly fragile to connections from clients with the
same id (can result in weird connect hangs and even crashes) and
`ib_insync` doesn't handle intermittent tcp disconnects that
well..(especially on dockerized IBC setups). This adds a bunch of
changes to our client caching and scan loop as well a proper
task-locking-to-cache-proxies so that,
- `asyncio`-side clients aren't double-loaded/connected even when
explicitly trying to reconnect repeatedly with a given client to work
around the unreliability of the `asyncio.Transport` design in
`ib_insync`.
- we can use `tractor.trionics.maybe_open_context()` to lock the `trio`
side from loading more then one `Client` on the `asyncio` side and
instead on cache hits only making a new `MethodProxy` around the
reused `asyncio`-side client (since each `trio` task needs its own
inter-task msg channel).
- a `finally:` block teardown on all clients loaded in the scan loop
avoids stale connections.
- the connect params are now exposed as named args to
`load_aio_clients()` can be easily controlled from caller code.
Oh, and we properly hooked up the internal `ib_insync` logging to our
own internal schema - makes it a lot easier to debug wtf is going on XD
In order to expose more `asyncio` powered `Client` methods to endpoint
task-code this adds a more extensive and layered set of `MethodProxy`
loading routines, in dependency order these are:
- `load_clients_for_trio()` a `tractor.to_asyncio.open_channel_from()`
entry-point factory for loading all scanned clients on the `asyncio` side
and delivering them over the inter-task channel to a `trio`-side task.
- `get_preferred_data_client()` a simple client instance loading routine
which reads from the users `brokers.toml -> `prefer_data_account:
list[str]` which must list account names, in priority order, that are
acceptable to be used as the main "data connection client" such that
only one of the detected clients is used for data (whereas the rest
are used only for order entry).
- `open_client_proxies()` which delivers the detected `Client` set
wrapped each in a `MethodProxy`.
- `open_data_client()` which directly delivers the preferred data client
as a proxy for `trio` tasks.
- update `open_client_method_proxy()` and `open_client_proxy` to require
an input `Client` instance.
Further impl details:
- add `MethodProxy._aio_ns` to ref the original `asyncio` side proxied instance
- add `Client.trades()` to pull executions from the last day/session
- load proxies inside `trades_dialogue` and use the new `.trades()`
method to try and pull a fill ledger for eventual correct pp price
calcs (pertains to #307)..
We return a copy (since since a view doesn't seem to work..) of the
(field filtered) shm array contents which is the same index-length as
the source data.
Further, fence off the resource tracker disable-hack into a helper
routine.
It seems once in a while a frame can get missed or dropped (at least
with binance?) so in those cases, when the request erlangs is already at
max, we just manually request the missing frame and presume things will
work out XD
Further, discard out of order frames that are "from the future" that
somehow end up in the async queue once in a while? Not sure why this
happens but it seems thus far just discarding them is nbd.
Bleh/🤦, the ``end_dt`` in scope is not the "earliest" frame's
`end_dt` in the async response queue.. Parse the queue's latest epoch
and use **that** to compare to the last last pushed datetime index..
Add more detailed logging to help debug any (un)expected datetime index
gaps.
When the tsdb has a last datum that is in the past less then a "frame's
worth" of sample steps we need to slice out only the data from the
latest frame that doesn't overlap; this fixes that slice logic..
Previously i dunno wth it was doing..
When the market isn't open the feed layer won't create a subscriber
entry in the sampler broadcast loop and so if a manual call to
``broadcast()`` is made (like when trying to update a chart from
a history prepend) we need to handle that case and just broadcast
a random `-1` for now..BD
Expect each backend to deliver a `config: dict[str, Any]` which provides
concurrency controls to `trimeter`'s batch task scheduler such that
backends can define their own concurrency limits.
The dirty deats in this patch include handling history "gaps" where
a query returns a history-frame-result which spans more then the typical
frame size (in seconds). In such cases we reset the target frame index
(datetime index sequence implemented with a `pendulum.Period`) using
a generator protocol `.send()` such that the sequence can be dynamically
re-indexed starting at the new (possibly) pre-gap datetime. The new gap
logic also allows us to detect out of order frames easier and thus wait
for the next-in-order to arrive before making more requests.
Use the new `open_history_client()` endpoint/API and expect backends to
provide a history "getter" routine that can be called to load historical
data into shm even when **not** using a tsdb. Add logic for filling in
data from the tsdb once the backend has provided data up to the last
recorded in the db. Add logic for avoiding overruns of the shm buffer
with more-then-necessary queries of tsdb data.
It turns out (i guess not so shockingly?) that `marketstore` doesn't
always teardown "gracefully" under SIGINT (seems to hang if there are
open client connections which are also in the midst of teardown?) so
this instead first tries the SIGINT and then fails over to a SIGKILL
(destroy loop) which seems to be much more reliable to ensure shutdown
without any downside - in terms of a "hard kill".
Originally i was thinking the issue was root perms related (which get
relegated solely to the `marketstored` daemon actor after spawn) but
actually it was indeed the signalling / application layer causing the
hold-up/latency on teardown. There's a bunch of lingering (now
commented) code which tried to solve this non-problem as well as a bunch
logging/prints to help decipher the root of the issue - this will all
get cleaned out shortly.
If `marketstore` is detected try to only load most recent missing data
from the data provider (broker) and the rest from the tsdb and push it
all to shm for display in the UI. If the provider/broker doesn't have
the history client endpoint, just use the old one for now so we can
start to incrementally add support. Don't start the ohlc step
incrementer task until the backend signals that the feed is live.
Add some basic `numpy` epoch slice logic to generate append and prepend
arrays to write to the db.
Mooar cool things,
- add a `Storage.delete_ts()` method to wipe a column series from the db
easily.
- don't attempt to read in any OHLC series by default on client load
- add some `pyqtgraph` profiling and drop manual latency measures
- if no db series for the fqsn exists write the entire shm array
Also, Start tinkering with `tractor.trionics.ipython_embed()`
In effort to get back to a usable REPL around the mkts client
this adds usage of the new `tractor` integration api as well as logic
for skipping backfilling if existing tsdb arrays are found.
Starts a wrapper around the `marketstore` client to do basic ohlcv query
and retrieval and prototypes out write methods for ohlc and tick.
Try to connect to `marketstore` automatically (which will fail if not
started currently) but we will eventually first do a service query.
Further:
- get `pikerd` working with and without `--tsdb` flag.
- support spawning `brokerd` with no real-time quotes.
- bring back in "fqsn" support that was originally not
in this history before commits factoring.
Not sure how I missed mapping the 5995 grpc port 🤦; done now.
Also adds graceful teardown using SIGINT with included container
logging relayed to the piker console B).
Found this caused breakage on `kraken` orders which triggered the
"insufficient funds" error response. Makes sense since they won't
generate an order id if the order can't ever be submitted.
The most important changes include:
- iterating the new `Flow` type and updating graphics
- adding detailed profiling
- increasing the min uppx before graphics updates are throttled
- including the L1 spread in y-range calcs so that you never have the
bid/ask go "out of view"..
- pass around `Flow`s instead of shms
- drop all the old prototyped downsampling code
If manually managing an overlay you'll likely call `.overlay_plotitem()`
and then a plotting method so we need to accept a plot item input so
that the chart's pi doesn't get assigned incorrectly in the `Flow` entry
(though it is by default if no input is provided).
More,
- add a `Flow.graphics` field and set it to the `pg.GraphicsObject`.
- make `Flow.maxmin()` return `None` in the "can't calculate" cases.
- set shm refs on `Flow` entries.
- don't run a graphics cycle on 'update' msgs from the engine
if the containing chart is hidden.
- drop `volume` from flows map and disable auto-yranging
once $vlm comes up.
Allows for removing resize callbacks for a flow/overlay that you wish to
remove from view (eg. unit volume after dollar volume is up) and thus
less general interaction callback overhead for any plot you don't wish
to show or resize.
Further,
- drop the `autoscale_linked_plots` block for now since with
multi-view-box overlays each register their own vb resize slots
- pull the graphics object from the chart's `Flow` map inside
`.maybe_downsample_graphics()`
This new type wraps a shm data flow and will eventually include things
like incremental path-graphics updates and serialization + bg downsampling
techniques. The main immediate motivation was to get a cached y-range max/min
calc going since profiling revealed the `numpy` equivalents were
actually quite slow as the data set grows large. Likely we can use all
this to drive a streaming mx/mn routine that's always launched as part
of each on-host flow.
This is our official foray into use of `msgspec.Struct` B) and I have to
say, pretty impressed; we'll likely completely ditch `pydantic` from
here on out.
We don't need update graphics on every x-range change since that's what
the display loop does. Instead, only on manual changes do we make manual
calls into `.update_graphics_from_array()` and be sure to iterate all
linked subplots and all their embedded graphics.
The pg profiler seems to have trouble with early `return`s in function
calls (likely muckery with the GC/`.__delete__()`) so let's just try
to avoid it for now until we either fix it (probably by implementing as
a ctx mngr) or use diff one.
Ugh, turns out the wacky `ChartView.maxmin` callback stuff we did (for
determining y-range sizings) currently requires that the volume array
has a "bars in view" result.. so let's make that keep working without
rendering the graphics for the curve (since we're disabling them once
$vlm comes up).
As with the `BarItems` graphics, this makes it possible to pass in a "in
view" range of array data that can be *only* rendered improving
performance for large(r) data sets. All the other normal behaviour is
kept (i.e a persistent, (pre/ap)pendable path can still be maintained)
if a ``view_range`` is not provided.
Further updates,
- drop the `.should_ds_or_redraw()` and `.maybe_downsample()` predicates
instead moving all that logic inside `.update_from_array()`.
- disable the "cache flipping", which doesn't seem to be needed to avoid
artifacts any more?
- handle all redraw/dowsampling logic in `.update_from_array()`.
- even more profiling.
- drop path `.reserve()` stuff until we better figure out how it's
supposed to work.
Drop all the logic originally in `.update_ds_line()` which is now done
internal to our `FastAppendCurve`. Add incremental update of the
flattened OHLC -> line curve (unfortunately using `np.concatenate()` for
the moment) and maintain a new `._ds_line_xy` arrays tuple which keeps
the internal state. Add `.maybe_downsample()` as per the new interaction
update method requirement. Draft out some fast path curve stuff like in
our line graphic. Short-circuit bars path updates when we downsample to
line. Oh, and add a ton more profiling in prep for getting
all this stuff faf.
Build out an interface that makes it super easy to downsample curves
using the m4 algorithm while keeping our incremental `QPainterPath`
update feature. A lot of hard work and tinkering went into getting this
working all in-thread correctly and there are quite a few details..
New interface methods:
- `.x_uppx()` which returns the x-axis "view units per pixel"
- `.px_width()` which returns the total (rounded) x-axis pixels spanned
by the curve in view.
- `.should_ds_or_redraw()` a predicate which checks internal state to
see if either downsampling of the curve should take place, or the curve
should have all downsampling removed and be redrawn with source array
data.
- `.downsample()` the actual ds processing routine which delegates into
the m4 algo impl.
- `.maybe_downsample()` a simple update method which can be called by
the view box when the user changes the zoom level.
Implementation details/changes:
- make `.update_from_array()` check for downsample (or revert to source
aka de-downsample) conditions exist and then downsample and re-draw
path graphics accordingly.
- in order to even further speed up path appends (since our main
bottleneck is measured to be `QPainter.drawPath()` calls with large
paths which are frequently updates), add a secondary path `.fast_path`
which is the path that is real-time updates by incremental appends and
which is painted separately for speed in `.pain()`.
- drop all the `QPolyLine` stuff since it was tested to be much slower
in general and especially so for append-updates.
- stop disabling the cache settings on updates since it doesn't seem to
be required any more?
- more move toward deprecating and removing all lingering interface
requirements from `pg.PlotCurveItem` (like `.xData`/`.yData`).
- adjust `.paint()` and `.boundingRect()` to compensate for the new
`.fast_path`
- add a butt-load of profiling B)
Pretty sure this was most of the cause of the stale (more downsampled)
curves showing when zooming in and out from bars mode quickly. All this
stuff needs to get factored out into a new abstraction anyway, but
i think this get's mostly correct functionality.
Only draw new ds curve on uppx steps >= 4 and stop adding/removing
graphics objects from the scene; doesn't seem to speed anything up
afaict. Add better reporting of ds scale changes.
Only if the uppx increases by more then 2 we redraw the entire line
otherwise just ds with previous params and update the current curve.
This *should* avoid strange lower sample rate artefacts from showing on
updates.
Summary:
- stash both uppx and px width in `._dsi` (downsample info)
- use the new `ohlc_to_m4_line()` flags
- add notes about using `.reserve()` and friends
- always delete last `._array` ref prior to line updates
In an effort to try and make `QPainterPath.reserve()` work, add internal
logic to use the same object without de-allocating memory from
a previous path write/creation.
Note this required the addition of a `._redraw` flag (to be used in
`.clear()` and a small patch to `pyqtgraph.functions.arrayToQPath` to
allow passing in an existing path (thus reusing the same underlying mem
alloc) which will likely be first pushed to our fork.
We were previously ad-hoc scaling up the px count/width to get more
detail at lower uppx values. Add a log scaling sigmoid that range scales
between 1 < px_width < 16.
Add in a flag to use the mxmn OH tracer in `ohlc_flatten()` if desired.
Helpers to quickly convert ohlc struct-array sequences into lines
for consumption by the m4 downsampler. Strip trailing zero entries
from the `ds_m4()` output if found (avoids lines back to origin).
This makes the `'r'` hotkey snap the last bar to the middle of the pp
line arrow marker no matter the zoom level. Now we also boot with
approximately the most number of x units on screen that keep the bars
graphics drawn in full (just before downsampling to a line).
Moved some internals around to get this all in place,
- drop `_anchors.marker_right_points()` and move it to a chart method.
- change `.pre_l1_x()` -> `.pre_l1_xs()` and just have it return the
two view-mapped x values from the former method.
Instead of using a guess about how many x-indexes to reset the last
datum in-view to, calculate and shift the latest index such that it's
just before any L1 spread labels on the y-axis. This makes the view
placement "widget aware" and gives a much more cross-display UX.
Summary:
- add `ChartPlotWidget.pre_l1_x()` which returns a `tuple` of
x view-coord points for the absolute x-pos and length of any L1
line/labels
- make `.default_view()` only shift to see the xlast just outside
the l1 but keep whatever view range xfirst as the first datum in view
- drop `LevelLine.right_point()` since this is now just a
`.pre_l1_x()` call and can be retrieved from the line's internal chart
ref
- drop `._style.bars_from/to_..` vars since we aren't using hard coded
offsets any more
`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.
You can get a weird "last line segment" artifact if *only* that segment
is drawn and the cache is enabled, so just disable unless in step mode
at startup and re-flash as normal when new path data is appended. Add
a `.disable_cache()` method for the multi-use in the update method. Use
line style on the `._last_line: QLineF` segment as well.
Enables retrieving all "named axes" on a particular "side" of the
overlayed plot items. This is useful for calculating how much space
needs to be allocated for the axes before the view box area starts.
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.
Since more curves costs more processing and since the vlm and $vlm
curves are normally very close to the same (graphically) we hide the
unit volume curve once the dollar volume is up (after the fsp daemon-task is
spawned) and just expect the user to understand the diff in axes units.
Also, use the new `title=` api to `.overlay_plotitem()`.
Use our internal `Label` with much better dpi based sizing of text and
placement below the y-axis ticks area for more minimalism and less
clutter.
Play around with `lru_cache` on axis label bounding rects and for now
just hack sizing by subtracting half the text height (not sure why) from
the width to avoid over-extension / overlap with any adjacent axis.
Allow passing in a formatter function for processing tick values on an
axis. This makes it easy to for example, `piker.calc.humanize()` dollar
volume on a subchart.
Factor `set_min_tick()` into the `PriceAxis` since it's not used on any
x-axis data thus far.
Adds `FspAdmin.open_fsp_chart()` which allows adding a real time graphics
display of an fsp's output with different options for where (which chart
or make a new one) to place it.
Further,
- change some method naming, namely the other fsp engine task methods to
`.open_chain()` and `.start_engine_task()`.
- make `run_fsp_ui()` a lone task function for now with the default
config parsing and chart setup logic (and it still includes a buncha
commented out stuff for doing graphics update which is now done in the
main loop to avoid task switching overhead).
- move all vlm related fsp config entries into the `open_vlm_displays()`
task for dedicated setup with the fsp admin api such as special
auto-yrange handling and graph overlays.
- `start_fsp_displays()` is now just a small loop through config entries
with synced startup status messages.
For wtv cucked reason all the viewbox/scene coordinate calcs do **not**
include a left axis in the geo (likely because it's a hacked in widget
+ layout thing managed by `PlotItem`). Detect if there's a left axis and
if so use it in the label placement scene coords calc. ToDo: probably
make this a non-move calc and only recompute any time the axis changes.
Other:
- rate limit mouse events down to the 60 (ish) Hz for now
- change one last lingering `'ohlc'` array lookup
- fix `.mouseMoved()` "event" type annot
This is a huge commit which moves a bunch of code around in order to
simplify some of our UI modules as well as support our first official
mult-axis chart: overlaid volume and "dollar volume". A good deal of
this change set is to make startup fast such that volume data which is
often shipped alongside OHLC history is loaded and shown asap and FSPs
are loaded in an actor cluster with their graphics overlayed
concurrently as each responsible worker generates plottable output.
For everything to work this commit requires use of a draft `pyqtgraph`
PR: https://github.com/pyqtgraph/pyqtgraph/pull/2162
Change summary:
- move remaining FSP actor cluster helpers into `.ui._fsp` mod as well
as fsp specific UI managers (`maybe_open_vlm_display()`,
`start_fsp_displays()`).
- add an `FspAdmin` API for starting fsp chains on the cluster
concurrently allowing for future work toward reload/unloading.
- bring FSP config dict into `start_fsp_displays()` and `.started()`-deliver
both the fsp admin and any volume chart back up to the calling display
loop code.
ToDo:
- repair `ChartView` click-drag interactions
- auto-range on $ vlm needs to use `ChartPlotWidget._set_yrange()`
- a lot better styling for the $_vlm overlay XD
As part of factoring `._set_yrange()` into the lower level view box,
move the y-range calculations into a new method. These calcs should
eventually be completely separate (as they are for the real-time version
in the graphics display update loop) and likely part of some kind of
graphics-related lower level management API. Draft such an API as an
`ArrayScene` (commented for now) as a sketch toward factoring array
tracking **out of** the chart widget. Drop the `'ohlc'` array name and
instead always use whatever `.name` was assigned to the chart widget
to lookup its "main" / source data array for now.
Enable auto-yranging on overlayed plotitems by enabling on its viewbox
and, for now, assign an ad-hoc `._maxmin()` since the widget version
from this commit has no easy way to know which internal array to use. If
an FSP (`dolla_vlm` in this case) is overlayed on an existing chart
without also having a full widget (which it doesn't in this case since
we're using an overlayed `PlotItem` instead of a full `ChartPlotWidget`)
we need some way to define the `.maxmin()` for the overlayed
data/graphics. This likely means the `.maxmin()` will eventually get
factored into wtv lowlevel `ArrayScene` API mentioned above.
Calculations for auto-yaxis ranging are both signalled and drawn by our
`ViewBox` so we might as well factor this handler down from the chart
widget into the view type. This makes it much easier (and clearer) that
`PlotItem` and other lower level overlayed `GraphicsObject`s can utilize
*size-to-data* style view modes easily without widget-level coupling.
Further changes,
- support a `._maxmin()` internal callable (temporarily) for allowing
a viewed graphics object to define it's own y-range max/min calc.
- add `._static_range` var (though usage hasn't been moved from the
chart plot widget yet
- drop y-axis click-drag zoom instead reverting back to default viewbox
behaviour with wheel-zoom and click-drag-pan on the axis.
This brings in the WIP components developed as part of
https://github.com/pyqtgraph/pyqtgraph/pull/2162.
Most of the history can be understood from that issue and effort but the
TL;DR is,
- add an event handler wrapper system which can be used to
wrap `ViewBox` methods such that multiple views can be overlayed and
a single event stream broadcast from one "main" view to others which
are overlaid with it.
- add in 2 relay `Signal` attrs to our `ViewBox` subtype (`Chartview`)
to accomplish per event `MouseEvent.emit()` style broadcasting to
multiple (sub-)views.
- Add a `PlotItemOverlay` api which does all the work of overlaying the
actual chart graphics and arranging multiple-axes without collision as
well as tying together all the event/signalling so that only a single
"focussed" view relays to all overlays.
Each `pyqtgraph.PlotItem` uses a `QGraphicsGridLayout` to place its view
box, axes and titles in the traditional graph format. With multiple
overlayed charts we need those axes to not collide with one another and
further allow for an "order" specified by the user. We accomplish this
by adding `QGraphicsLinearLayout`s for each axis "side": `{'left',
'right', 'top', 'bottom'}` such that plot axes can be inserted and moved
easily without having to constantly re-stack/order a grid layout (which
does not have a linked-list style API).
The new type is called `ComposedGridLayout` for now and offers a basic
list-like API with `.insert()`, `.append()`, and eventually a dict-style
`.pop()`. We probably want to also eventually offer a `.focus()` to
allow user switching of *which* main graphics object (aka chart) is "in
use".
This syncs with a dev branch in our `pyqtgraph` fork:
https://github.com/pyqtgraph/pyqtgraph/pull/2162
The main idea is to get mult-yaxis display fully functional with
multiple view boxes running in a "relay mode" where some focussed view
relays signals to overlaid views which may have independent axes. This
preps us for both displaying independent codomain-set FSP output as well
as so called "aggregate" feeds of multiple fins underlyings on the same
chart (eg. options and futures over top of ETFs and underlying stocks).
The eventual desired UX is to support fast switching of instruments for
order mode trading without requiring entirely separate charts as well as
simple real-time anal of associated instruments.
The first effort here is to display vlm and $_vlm alongside each other
as a built-in FSP subchart.
We can instead use the god widget's nursery to schedule all the feed
pause/resume requests and be even more concurrent during a view (of
symbols) switch.
Use `tractor.trionics.gather_contexts()` to start up the fsp and volume
chart-displays (for an additional conc speedup). Drop `dolla_vlm` again for
now until we figure out how we can display it *and* vlm on the same
sub-chart? It would be nice to avoid having to spawn an fsp process
before showing the volume curve.
Call the resize method only after all FSP subcharts have rendered
such that the main OHLC chart's final width is read.
Further tweaks:
- drop rsi by default
- drop the stream drain stuff
- fix failed-to-read shm logging
This fixes a weird re-render bug/slowdown/artifact that was introduced
with the order mode sidepane work. Prior to the sidepane addition, chart
switching was immediate with zero noticeable widget rendering steps.
The slow down was caused by 2 things:
- not yielding back to the Qt loop asap after re-showing/focussing
a linked split chart that was already in memory.
- pausing/resuming feeds only after a Qt loop render cycle has
completed.
This now restores the near zero latency UX.
There was a lingering issue where the fsp daemon would sync its shm
array with the source data and we'd set the start/end indices to the
same value. Under some races a reader would then read an empty `.array`
which it wasn't expecting. This fixes that as well as tidies up the
`ShmArray.push()` logic and adds a temporary check in `.array` for zero
length if the array hasn't been written yet.
We can now start removing read array length checks in consumer code
and hopefully no more races will show up.
Revert to old shm "last" meaning last row
It can now be declared inside an fsp config dict under the name
`dolla_vlm`. We still need to offer an engine control that zeros
the newest sample value instead of copying from the previous.
This also litters the engine code with `pyqtgraph` profiling to see if
we can improve startup times - likely it'll mean pre-allocating a small
fsp daemon cluster at startup.
Use a fixed worker count and don't respawn for every chart, instead
opting for a round-robin to tasks in a cluster and (for now) hoping for
the best in terms of trio scheduling, though we should obviously route
via symbol-locality next. This is currently a boon for chart spawning
startup times since actor creation is done AOT.
Additionally,
- use `zero_on_step` for dollar volume
- drop rsi on startup (again)
- add dollar volume (via fsp) along side unit volume
- litter more profiling to fsp chart startup sequence
- pre-define tick type classes for update loop
We are already packing framed ticks in extended lists from
the `.data._sampling.uniform_rate_send()` task so the natural solution
to avoid needless graphics cycles for HFT-ish feeds (like binance) is
to unpack those frames and for most cases only update graphics with the
"latest" data per loop iteration. Unpacking in this way also lessens
nested-iterations per tick type.
Btw, this also effectively solves all remaining issues of fast tick
feeds over-triggering the graphics loop renders as long as the original
quote stream is throttled appropriately, usually to the local display
rate.
Relates to #183, #192
Dirty deats:
- drop all per-tick rate checks, they were always somewhat pointless
when iterating a frame of ticks per render cycle XD.
- unpack tick frame into ticks per frame type, and last of each type;
the lasts are used to update each part of the UI/graphics by class.
- only skip the label update if we can't retrieve the last from from a
graphics source array; it seems `chart.update_curve_from_array()`
already does a `len` check internally.
- add some draft commented code for tick type classes and a possible
wire framed tick data structure.
- move `chart_maxmin()` range computer to module level, bind a chart to
it with a `partial.`
- only check rate limits in main quote loop thus reporting actual
overages
- add in commented logic for only updating the "last" cleared price from
the most recent framed value if we want to eventually (right now seems
like this is only relevant to ib and it's dark trades: `utrade`).
- rename `_clear_throttle_rate` -> `_quote_throttle_rate`, drop
`_book_throttle_rate`.
This is in prep toward doing fsp graphics updates from the main quotes
update loop (where OHLC and volume are done). Updating fsp output from
that task should, for the majority of cases, be fine presuming the
processing is derived from the quote stream as a source. Further,
calling an update function on each fsp subplot/overlay is of course
faster then a full task switch - which is how it currently works with
a separate stream for every fsp output. This also will let us delay
adding full `Feed` support around fsp streams for the moment while still
getting quote throttling dictated by the quote stream.
Going forward, We can still support a separate task/fsp stream for
updates as needed (ex. some kind of fast external data source that isn't
synced with price data) but it should be enabled as needed required by
the user.
The major change is moving the fsp "daemon" (more like wanna-be fspd)
endpoint to use the newer `tractor.Portal.open_context()` and
bi-directional streaming api.
There's a few other things in here too:
- make a helper for allocating single colume fsp shm arrays
- rename some some fsp related functions to be more explicit on their
purposes
Since our startup is very concurrent there is often races where widgets
have not fully spawned before python (re-)sizing code has a chance to
run sizing logic and thus incorrect dimensions are read. Instead ensure
the Qt render loop gets to run in between such checks.
Also add a `open_sidepane()` mngr for creating a minimal form widget for
FSP subchart sidepanes which can be configured from an input `dict`.
This should in theory result in increased burstiness since we remove
the plain `trio.sleep()` and instead always wait on the receive channel
as much as possible until the `trio.move_on_after()` (+ time diffing
calcs) times out and signals the next throttled send cycle. This also is
slightly easier to grok code-wise instead of the `try, except` and
another tight while loop until a `trio.WouldBlock`. The only simpler
way i can think to do it is with 2 tasks: 1 to collect ticks and the
other to read and send at the throttle rate.
Comment out the log msg for now to avoid latency and add much more
detailed comments. Add an overrun log msg to the main sample loop.
A `QRectF` is easier to make and draw (i think?) so use that and fill it
on volume events for decent sleek real-time look. Adjust the step array
generator to allow for an endpoints flag. Comment and/or clean out all
the old path filling calls that gave us perf issues..
Turns out the performance of updating and refilling step curves > 1k ish
points is super slow :sadkek:. Disabling the fill basically returns
normal performance, so it seems maybe we'll stick with unfilled volume
"bars" for now. The other tricky bit is getting the path to extend and
fill which is particularly slow if you use the `QPainterPath.united()`
(what `+` set op does) operation which seems to require an entire redraw
of the curve each paint iteration. Removing the pixel buffer cache makes
things that much worse too..
One technique i tried was only setting a `._fill` flag when so many
datums are in view (< 1k as determined by the chart widget), and this
helps, but under high load (trade rates) you still see more lag then
without the fill which makes me say screw it and let's stick with
unfilled bars for now. Trying go to get performant filled curves will be
an exercise for an aspiring graphics eng :P
In latest `pyqtgraph` it seems there's a discrepancy
since `function.arrayToQPath()` was reworked and now
we need to *not* connect the last point for each bar.
The prior PR for fixing fsp array misalignment also added
`tractor.Context` usage which wasn't reflected in the graphics update
loop (newer code added it but the prior PR was factored from path
dependent history) and thus was broken. Further in newer work we don't
have fsp actors actually stream value updates since the display loop can
already pull from the source feed and update graphics at a preferred
throttle rate. Re-enabled the fsp stream sending here by default until
that newer only-throttle-pull-from-source code is landed in the display
loop.
This should finally be correct fsp src-to-dst array syncing now..
There's a few edge cases but mostly we need to be sure we sync both
back-filled history diffs and avoid current step lag/leads. Use
a polling routine and the more stringent task re-spawn system to get
this right.
There was a lingering issue where the fsp daemon would sync its shm
array with the source data and we'd set the start/end indices to the
same value. Under some races a reader would then read an empty `.array`
which it wasn't expecting. This fixes that as well as tidies up the
`ShmArray.push()` logic and adds a temporary check in `.array` for zero
length if the array hasn't been written yet.
We can now start removing read array length checks in consumer code
and hopefully no more races will show up.
Litter the engine code with `pyqtgraph` profiling to see if we can
improve startup times - likely it'll mean pre-allocating a small fsp
daemon cluster at startup.
Split up the rather large `.ui._chart` module into its constituents:
- a `.ui._app` for the highlevel widget composition, qtractor entry
point and startup logic
- `.ui._display` for all the real-time graphics update tasks which
consume the `.ui._chart` widget apis
Must have run into some confusion with data structures in `brokerd` vs.
`emsd`. This fixes the ems `relay.positions` state tracking to be
composed maps, vs. messages from `brokerd` should just be a sequence.
This reverts commit 6fa8958acf.
We actually do need it since the selection widget of course won't tell
you its "key" that we assign and further we'd have to use a (value, key)
style invocation which isn't super pythonic.
The paper engine returns `"paper"` instead of `None` in the pp msgs so
expect that. Don't bother with fills tracking for now (since we'll need
either the account in the msg or a lookup table locally for oids to
accounts). Change the order line update handler to a local module function,
there was no reason for it to be a pane method.
Make a pp tracker per account and load on order mode boot.
Only show details on the pp tracker for the selected account.
Make the settings pane assign a `.current_pp` state on the order mode
instance (for the charted symbol) on account selection switches and no
longer keep a ref to a single pp tracker and allocator in the pane.
`SettingsPane.update_status_ui()` now expects an explicit tracker
reference as input. Still need to figure out the pnl update task logic
despite the intermittent account changes.
This adds full support for a single `brokerd` managing multiple API
endpoint clients in tandem. Get the client scan loop correct and load
accounts from all discovered clients as specified in a user's
`broker.toml`. We now just always re-scan for all clients and if there's
a cache hit just skip a creation/connection logic.
Route orders with an account name to the correct client in the
`handle_order_requests()` endpoint and spawn an event relay task per
client for transmitting trade events back to `emsd`.
Make the `handle_order_requests()` tasks now lookup the appropriate API
client for a given account (or error if it can't be found) and use it
for submission. Account names are loaded from the
`brokers.toml::accounts.ib` section both UI side and in the `brokerd`.
Change `_aio_get_client()` to a `load_aio_client()` which now tries to
scan and load api clients for all connections defined in the config as
well as deliver the client cache and account lookup tables.
Each backend broker may support multiple (types) of accounts; this patch
lets clients send order requests that pass through an `account` field in
certain `emsd` <-> `brokerd` transactions. This allows each provider to read
in and conduct logic based on what account value is passed via requests
to the `trades_dialogue()` endpoint as well as tie together positioning
updates with relevant account keys for display in UIs.
This also adds relay support for a `Status` msg with a `'broker_errored'`
status which for now will trigger the same logic as cancelled orders on
the client side and thus will remove order lines submitted on a chart.
Get rid of `PositionTracker.init_status_ui()` and instead make
a helper func `mk_allocator()` which takes in the alloc and adjusts
default settings on the allocator alone (which is expected to be
passed in). Expect a `Position` instance to be passed into the tracker
which will be looked up for UI updates. Move *update-from-position-msg*
ops into a `Position.update_from_msg()` method.
We weren't updating the LHS size labels on creation and we now use the
lot size digits to do so. Change `PositionTracker.update()` to
`.update_from_pp_msg()`.
Acts as a fix for lodpi and better sizing logic for the pp status bar.
Drop all the redundant passing of the form to its child layouts during
instantiating (since they're all added as layouts to the tree). Comment
out the feed status label for now since it's not hooked up to the
backend and we'll get it going in a new PR.
Down the road we probably want to do all the pp pane component-widget
sizing *after* the `pyqtgraph` chart is up; it's going to take some
reworking of the charting api tho.
We were re-implementing a few things order lines already support.
All we really needed was to not add a pp size label if one is provided.
Use `.hide_label()` in the mouse hover handler.
When exiting a pp toward net-zero, we may sometimes run into the issue
of having a "fractional slot" worth of units in allocator limit terms.
This is further nuanced by live orders which are submitted above the
current clearing price which get allocated a size (based on that staged
but non-cleared price) according to their limit size unit which can be
calculated to be less then the size that would have been allocated at
the actual clearing price. In the short term cope with this discrepancy
by simply using a "slot and a half" as the decision point of whether to
exit a slot's worth or the remaining pp's worth of units. In other words
if you can exit 1.5x a slot's worth or less, exit the remaining pp,
otherwise exit a slot's worth. This is a stop gap until we have a better
solution to limiting staged orders to (some range around) the currently
computed clear-able price.
Tyler Goodlet
goodboy
Guillermo Rodriguez
dinkus
Guillermo Rodriguez
Konstantine Tsafatinos
wattygetlood
wattygetlood