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.
We need a subtask to compute the current pp PnL in real-time but really
only if a pp exists - a spawnable subtask would be ideal for this. Stage
a tick streaming task using a stream bcaster; no actual pnl calc yet.
Since we're going to need subtasks anyway might as well stick the order
mode UI processing loop in a task as well and then just give the whole
thing a ctx mngr api. This'll probably be handy for when we have
auto-strats that need to dynamically use the mode's api as well.
Oh, and move the time -> index mapper to a chart method for now.
Use this method to go through writing all allocator parameters and then
reading all changes back into the order mode pane including updating the
limit and step labels by the fill bar.
Machinery changes:
- add `.limit()` and `.step_sizes()` methods to the allocator to
provide the appropriate data depending on the pp limit size unit (eg.
currency vs. units)
- humanize the label display text such that you have nice suffixes and
a fixed precision
- tweak the fill bar labels to be simpler since the values are now
humanized
- expect `.on_ui_settings_change()` to be called for every slots hotkey
tweak
Turned out to be pretty simple, on every pp update just recompute
the proportion of slots used based on the limit size units.
Don't assign the allocator callback method for alert lines since
there's no size to generate. Move from-existing-pp calculations
into the order pane itself.
Handling the edge cases in this was "fun", namely:
- entering with less then a slot's worth of units to purchase
before hitting the pp limit or, less then a slots worth when exiting
toward a net-zero position.
- round pp msg updates using the symbol tick and lot size digits to
avoid super small (1e-30 lel) positions lingering in the ems (happens
moreso with the paper engine).
- don't expect the next size method to be called for alert level changes
- pass label text and field widget key separately
- fix fill status bar slot sizing logic (once and for all) and
create a new type that allows generating / resizing the bar's
size / values with a `.set_slots()` method
- pull account names from allocator attr
- set `.fill_bar` as the fill status bar on the form for now
- make `GodWidget.load_symbol()` async
- track loaded feeds with a private `._feeds` dict
- add methods to pause/resume all feeds when chart is (un)focussed
- add some commented test code for 2nd feed consumer task and rsi2 fsp
- load async signal handler for view clicking
- generate lines from staged `Order` msgs
- apply level update callback to each order that dynamically
updates the order size from the allocator calcs
- pass order msg instances to the ems client for submission
- update order size on line moves
- add `Order` msg and `Symbol` refs to each dialog
In an effort to simplify line creation and management from an order
mode here's a slew of changes:
- use our new ``LevelMarker`` for order lines and fully drop usage
of the original marker implementation stuff from `pg.InfiniteLine`
- add a left side label which shows the instrument's "units" value
- the most fundamental unit for the "size" of the order
- allow passing in an optional `marker_size: str` so that `action: str`
doesn't necessarily have to be passed (eg. when copying from an
existing line)
- change a couple of internal line config options to be public attrs
which can now be configured dynamically in real-time (since they're
all `bool` anyway):
* `hl_on_hover` -> `highlight_on_hover`
* `_always_show_labels` -> `always_show_labels`
- `LevelLine.set_level()` now only sets the position if it was **not**
called from the position changed signal (which would be redundant)
Move all the ``pydantic`` finagling to an `_orm.py` and
just keep an `Allocator` as the backing model for our pp controls
in the position module. This all needs to be tied together in some sane
with with facility for multiple symbols/streams per chart for when we
get to charting-trading aggregate feeds.
It was becoming too much with all the labels and markers and lines..
Might as well package it all together instead of cramming it in the
order mode loop, chief.
The techincal summary,
- move `_lines.position_line()` -> `PositionInfo.position_line()`.
- slap a `.pp` on the order mode instance which *is* a `PositionInfo`
- drop the position info info label for now (let's see what users want
eventually but for now let's keep it super minimal).
- add a `LevelMarker` type to replace the old `LevelLine` internal
marker system (includes ability to change the style and level on the
fly).
- change `_annotate.mk_marker()` -> `mk_maker_path()` and expect caller
to wrap in a `QGraphicsPathItem` if needed.
Generate and maintain position messages in the paper engine for each
`pikerd` session. We no longer tear down the engine on each client
disconnect. Ensure -ve size on sells to make the math work.
This gives us fast search over a known set of symbols you can't search
for with the api such as futures and commodities contracts.
Toss in a new client method to lookup contract details
`Client.con_deats()` and avoid calling it for now from `.search_stock()`
for speed; it seems originally we were doing the 2nd lookup due to weird
suffixes in the `.primaryExchange` which we can just discard.
In order to ensure the lifetime of the feed can in fact be kept open
until the last consumer task has completed we need to maintain
a lifetime which is hierarchically greater then all consumer tasks.
This solution is somewhat hacky but seems to work well: we just use the
`tractor` actor's "service nursery" (the one normally used to invoke rpc
tasks) to launch the task which will start and keep open the target
cached async context manager. To make this more "proper" we may want to
offer a "root nursery" in all piker actors that is exposed through some
singleton api or even introduce a public api for it into `tractor`
directly.
Think this was fixed by passing through `**kwargs` in
`maybe_open_feed()`, the shielding for fsp respawns wasn't being
properly passed through..
This reverts commit 2f1455d423.
Maybe i've finally learned my lesson that exit stacks and per task ctx
manager caching is just not trionic.. Use the approach we've taken for
the daemon service manager as well: create a process global nursery for
each unique ctx manager we wish to cache and simply tear it down when
the number of consumers goes to zero.
This seems to resolve all prior issues and gets us error-free cached
feeds!
Try out he new broadcast channels from `tractor` for data feeds
we already have cached. Any time there's a cache hit we load the
cached feed and just slap a broadcast receiver on it for the local
consumer task.
Add a new type/api to manage "contents labels" (labels that sit in
a view and display info about viewed data) since it's mostly used by
the linked charts cursor. Make `LinkedSplits.cursor` the new and only
instance var for the cursor such that charts can look it up from that
common class. Drop the `ChartPlotWidget._ohlc` array, just add
a `'ohlc'` entry to `._arrays`.
Orders in order mode should be chart oriented since there's a mode per
chart. If you want all orders just ask the ems or query all the charts
in a loop.
This fixes cancel-all-orders such that when 'cc' is tapped only the
orders on the *current* chart are cancelled, lel.
Generalize the methods for cancelling groups of orders (all or those
under cursor) and add new group status support such that statuses for
each cancel or order submission is displayed in the status bar. In the
"cancel-all-orders" case, use the new group status stuff.
Allows for submitting a top level "group status" associated with
a "group key" which eventually resolves once all sub-statuses associated
with that group key (and thus top level status) complete and are also
removed. Also add support for a "final message" for each status such
that once the status clear callback is called a final msg is placed on
the status bar that is then removed when the next status is set.
It's all a questionable bunch of closures/callbacks but it worx.
Instead of callbacks for key presses/releases convert our `ChartView`'s
kb input handling to async code using our event relaying-over-mem-chan
system. This is a first step toward a more async driven modal control
UX. Changed a bunch of "chart" component naming as part of this as well,
namely: `ChartSpace` -> `GodWidget` and `LinkedSplitCharts` ->
`LinkedSplits`. Engage the view boxe's async handler code as part of new
symbol data loading in `display_symbol_data()`. More re-orging to come!
Add an `open_handler()` ctx manager for wholesale handling event sets
with a passed in async func. Better document and implement the event
filtering core including adding support for key "auto repeat" filtering;
it turns out the events delivered when `trio` does its guest-most tick
are not the same (Qt has somehow consumed them or something) so we have
to do certain things (like getting the `.type()`, `.isAutoRepeat()`,
etc.) before shipping over the mem chan. The alt might be to copy the
event objects first but haven't tried it yet. For now just offer
auto-repeat filtering through a flag.
If a client attaches to a quotes data feed and requests a throttle rate,
be sure to unsub that side-band memchan + task when it detaches and
especially so on any transport connection error.
Also, use an explicit `tractor.Context.cancel()` on the client feed
block exit since we removed the implicit cancel option from the
`tractor` api.
There is no reason to have more then `brokerd` trades dialogue stream
open per `emsd`. Here we minimize to managing that lone stream and
multiplexing msgs from each client such that multiple clients can be
connected to the ems, conducting trading without requiring multiple
ems-client connections to the backend broker and without the broker
being aware there are even multiple flows going on.
This patch also sets up for being able to have ems clients which
register to receive and track trade flows from other piker clients thus
enabling so called "multi-player" trading where orders for both paper
and live trades can be shared between multiple participants in the form
of a pre-broker, local clearing service and trade signals dark book.
This solves a bunch of issues to do with `brokerd` order status msgs
getting relayed for each order to **every** correspondingly connected
EMS client. Previously we weren't keeping track of which emsd orders
were associated with which clients so you had backend msgs getting
broadcast to all clients which not only resulted in duplicate (and
sometimes erroneous, due to state tracking) actions taking place in the
UI's order mode, but it's also just duplicate traffic (usually to the
same actor) over multiple logical streams. Instead, only keep up **one**
(cached) stream with the `trades_dialogue()` endpoint such that **all**
emsd orders route over that single connection to the particular
`brokerd` actor.
An async exit stack around the new `@tractor.context` is problematic
since a pushed context can't bubble errors unless the exit stack has
been closed. But in that case why do you need the exit stack if you're
going to push it and wait it right away; it seems more correct to use
a nursery and spawn a task in `pikerd` that waits on the both the
target context completion first (thus being able to bubble up any errors
from the remote, and top level service task) and the sub-actor portal.
(Sub)service Daemons are spawned with `.start_actor()` and thus will
block forever until cancelled so, add a way to cancel them explicitly
which we'll need eventually for restarts and dynamic feed management.
The big lesson here is that async exit stacks are not conducive to
spawning and monitoring service tasks, and especially so if
a `@tractor.context` is used since if the `.open_context()` call isn't
exited (only possible by the stack being closed), then there will be no
way for `trio` to cancel the task that pushed that context (since it
can't run a checkpoint while yielded inside the stack) without also
cancelling all other contexts pushed on that stack. Presuming one
`pikerd` task is used to do the original pushing (which it was) then
any error would have to kill all service daemon tasks which obviously
won't work.
I see this mostly as the painz of tinkering out an SC service manager
with `tractor` / `trio` for the first time, so try to go easy on the
process ;P
Adding binance's "hft" ws feeds has resulted in a lot of context
switching in our Qt charts, so much so it's chewin CPU and definitely
worth it to throttle to the detected display rate as per discussion in
issue #192.
This is a first very very naive attempt at throttling L1 tick feeds on
the `brokerd` end (producer side) using a constant and uniform delivery
rate by way of a `trio` task + mem chan. The new func is
`data._sampling.uniform_rate_send()`. Basically if a client request
a feed and provides a throttle rate we just spawn a task and queue up
ticks until approximately the next display rate's worth period of time
has passed before forwarding. It's definitely nothing fancy but does
provide fodder and a start point for an up and coming queueing eng to
start digging into both #107 and #109 ;)
Avoids some cyclical and confusing import time stuff that we needed to get
DPI aware fonts configured from the active display. Move the main window
singleton into its own module and add a `main_window()` getter for it.
Make `current_screen()` a ``MainWindow` method to avoid so many module
variables.
This moves the entire clearing system to use typed messages using
`pydantic.BaseModel` such that the streamed request-response order
submission protocols can be explicitly viewed in terms of message
schema, flow, and sequencing. Using the explicit message formats we can
now dig into simplifying and normalizing across broker provider apis to
get the best uniformity and simplicity.
The order submission sequence is now fully async: an order request is
expected to be explicitly acked with a new message and if cancellation
is requested by the client before the ack arrives, the cancel message is
stashed and then later sent immediately on receipt of the order
submission's ack from the backend broker. Backend brokers are now
controlled using a 2-way request-response streaming dialogue which is
fully api agnostic of the clearing system's core processing; This
leverages the new bi-directional streaming apis from `tractor`. The
clearing core (emsd) was also simplified by moving the paper engine to
it's own sub-actor and making it api-symmetric with expected `brokerd`
endpoints.
A couple of the ems status messages were changed/added:
'dark_executed' -> 'dark_triggered'
added 'alert_triggered'
More cleaning of old code to come!
This makes the paper engine look IPC-wise exactly like any
broker-provider backend module and uses the new ``trades_dialogue()``
2-way streaming endpoint for commanding order requests.
This serves as a first step toward truly distributed forward testing
since the paper engine can now be run out-of tree from `pikerd` if
needed thus demonstrating how real-time clearing signals can be shared
between fully distinct services.
This avoids somewhat convoluted "hackery" making 2 one-way streams
between the order client and the EMS and instead uses the new
bi-directional streaming and context API from `tractor`. Add a router
type to the EMS that gets setup by the initial service tree and which
we'll eventually use to work toward multi-provider executions and
order-trigger monitoring. Move to py3.9 style where possible throughout.
Makes it so we can move toward separate provider results fills in an
async way, on demand.
Also,
- add depth 1 iteration helper method
- add section finder helper method
- fix last selection loading to be mostly consistent
This allows for more deterministically managing long running sub-daemon
services under `pikerd` using the new context api from `tractor`.
The contexts are allocated in an async exit stack and torn down at root
daemon termination. Spawn brokerds using this method by changing the
persistence entry point to be a `@tractor.context`.
Some providers do well with a "longer" debounce period (like ib) since
searching them too frequently causes latency and stalls. By supporting
both a min and max debounce period on keyboard input we can only send
patterns to the slower engines when that period is triggered via
`trio.move_on_after()` and continue to relay to faster engines when the
measured period permits. Allow search routines to register their "min
period" such that they can choose to ignore patterns that arrive before
their heuristically known ideal wait.
Obviously this only supports stocks to start, it looks like we might
actually have to hard code some of the futures/forex/cmdtys that don't
have a search.. so lame. Special throttling is added here since the api
will grog out at anything more then 1Hz.
Additionally, decouple the bar loading request error handling from the
shm pushing loop so that we can always recover from a historical bars
throttle-error even if it's on the first try for a new symbol.
This allows for more deterministically managing long running sub-daemon
services under `pikerd` using the new context api from `tractor`.
The contexts are allocated in an async exit stack and torn down at root
daemon termination. Spawn brokerds using this method by changing the
persistence entry point to be a `@tractor.context`.
This gets the binance provider meeting the data feed schema requirements
of both the OHLC sampling/charting machinery as well as proper
formatting of historical OHLC history.
Notably,
- spec a minimal ohlc dtype based on the kline endpoint
- use a dataclass to parse out OHLC bar datums and pack into np.ndarray/shm
- add the ``aggTrade`` endpoint to get last clearing (traded) prices,
validate with ``pydantic`` and then normalize these into our tick-quote
format for delivery over the feed stream api.
- a notable requirement is that the "first" quote from the feed must
contain a 'last` field so the clearing system can start up correctly.
This required a fsp task spawning logic rework which ended up being
cleaner just spawning tasks in a loop sequentially instead of trying
a 2-phase spawn-then-initialize approach.
This also includes changes from the symbol search branch hacked in.
Mostly it includes isolating the main chart startup-sequence to a
function that can be run in a new task every time a new symbol is
requested by the selector/searcher. The actual search functionality
obviously isn't in here yet but minor changes are included as part of
pulling out the `tractor` stream api patch from the symbol search dev
branch.
Avoid bothering with a trio event and expect the caller to do manual shm
registering with the write loop. Provide OHLC sample period indexing
through a re-branded pub-sub func ``iter_ohlc_periods()``.
Move all feed/stream agnostic logic and shared mem writing into a new
set of routines inside the ``data`` sub-package. This lets us move
toward a more standard API for broker and data backends to provide
cache-able persistent streams to client apps.
The data layer now takes care of
- starting a single background brokerd task to start a stream for as
symbol if none yet exists and register that stream for later lookups
- the existing broker backend actor is now always re-used if possible
if it can be found in a service tree
- synchronization with the brokerd stream's startup sequence is now
oriented around fast startup concurrency such that client code gets
a handle to historical data and quote schema as fast as possible
- historical data loading is delegated to the backend more formally by
starting a ``backfill_bars()`` task
- write shared mem in the brokerd task and only destruct it once requested
either from the parent actor or further clients
- fully de-duplicate stream data by using a dynamic pub-sub strategy
where new clients register for copies of the same quote set per symbol
This new API is entirely working with the IB backend; others will need
to be ported. That's to come shortly.
Add a `Services` nurseries container singleton for spawning sub-daemons
inside the long running `pikerd` tree. Bring in `brokerd` spawning util
funcs to start getting eyes on what can be factored into a service api.
The direct open is needed for running `pikerd` cmd and
the ems spawn point is the first step toward detaching UI based order
entry from the engine itself.
- break (custom) graphics item style marker drawing into separate func
but keep using it since it still seems oddly faster then the
QGraphicsPathItem thing..
- unfactor hover handler; it was uncessary
- make both the graphics path item and custom graphics items approaches
both work inside ``.paint()``
Add support for drawing ``QPathGraphicsItem`` markers but don't use them
since they seem to be shitting up when combined with the infinite line
(bounding rect?): weird artifacts and whatnot. The only way to avoid
said glitches seems to be to update inside the infinite line's
`.paint()` but that slows stuff down.. Instead stick with the manual
paint job use the same pin point: left of the L1 spread graphics - where
the lines now also extend to.
Further stuff:
- Pin the y-label to a line's value on hover.
- Disable x-dimension line moving
- Rework the labelling to be more minimal
Add a line which shows the current average price position with and arrow
marker denoting the direction (long or short). Required some further
rewriting of the infinite line from pyqtgraph including:
- adjusting marker (arrow) placement to be offset from axis + l1 labels
- fixing the hover event to not require the `.movable` attribute to be
set
It's a super naive implementation with no slippage model or network
latency besides some slight delays. Clearing only happens on bid/ask
sweep ticks at the moment - simple last volume based clearing coming
up next.
This turned into a larger endeavour then intended but now we're using our
own label system on level lines to be able to display things nicely
**pinned wherever we want in the UI**. Keep the old ``LevelLabel`` for
now for the L1 graphics but we'll likely replace this as well since i'm
pretty sure the new label type (which wraps `QGraphicsTextItem`) is more
performant anyway.
For labels that want it add nice arrow paths that point just over the
respective axis. Couple label text offset from the axis line based on
parent 'tickTextOffset' setting. Drop `YSticky` it was not enough
meat to bother with.
The min tick size is the smallest step an instrument can move in value
(think the number of decimals places of precision the value can have).
We start leveraging this in a few places:
- make our internal "symbol" type expose it as part of it's api
so that it can be passed around by UI components
- in y-axis view box scaling, use it to keep the bid/ask spread (L1 UI)
always on screen even in the case where the spread has moved further
out of view then the last clearing price
- allows the EMS to determine dark order live order submission offsets
Async spawn a deats getter task whenever we load a symbol data feed.
Pass these symbol details in the first message delivered by the feed at
open. Move stream loop into a new func.
Basically a stop limit mode where the dirty execution-condition deats
are entirely held client side away from the broker. For now, there's
a static order size setting and a 0.5% limit setting relative to the
trigger price. Swap to using 'd' for dump and 'f' for fill - they're
easier for use with ctrl (which is used now to submit orders directly to
broker - ala "live (order) mode"). Still more kinks to work out with too
fast cancelled orders and alerts but we're getting there.
Our first major UI "mode" (yes kinda like the modes in emacs) that has
handles to a client side order book api, line and arrow editors, and
interacts with a spawned `emsd` (the EMS daemon actor).
Buncha cleaning and fixes in here for various thingers as well.
Since the "crosshair" is growing more and more UX implementation details
it probably makes sense to call it what it is; a python level mouse
abstraction. Add 2 internal sets: `_hovered` for allowing mouse hovered
objects to register themselves to other cursor aware components, and
`_trackers` for allowing scene items to "track" cursor movements via
a `on_tracked_source()` callback.
Support tracking the mouse cursor using a new `on_tracked_sources()`
callback method. Make hovered highlight a bit thicker and highlight when
click-dragged. Add a delete method for removing from the scene along
with label.
Leverages `QGraphicsItem.cacheMode` to speed up interactivity via
less `.paint()` calls (on mouse interaction) and redraws of the
underlying path when there are no transformations (other then a shift).
In order to keep the "flat bar on new time period" UX, a couple special
methods have to be triggered to get a redraw of the pixel buffer when
appending new data.
Use `QPainterPath.controlPointRect()` over `.boundingRect()` since
supposedly it's a lot faster. Drop all use of `QPicture` (since it seems
to conflict with the pixel buffer stuff?) and it doesn't give any
measurable speedup when drawing the "last bar" lines.
Oh, and add some profiling for now.
This is a bit hacky (what with array indexing semantics being relative
to the primary index's "start" value but it works. We'll likely want
to somehow wrap this index finagling into an API soon.
Tyler Goodlet
goodboy
dinkus
Guillermo Rodriguez
Konstantine Tsafatinos
wattygetlood
wattygetlood
Conrad Steenberg