Add `Flow` type with a real chitty mxmn cacheing method
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.marketstore_backup
Tyler Goodlet
parent
b3fde388dd
commit
1066d78918
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@ -34,10 +34,11 @@ from PyQt5.QtWidgets import (
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QVBoxLayout,
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QSplitter,
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)
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import msgspec
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import numpy as np
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# from pydantic import BaseModel
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import pyqtgraph as pg
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import trio
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from pydantic import BaseModel
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from ._axes import (
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DynamicDateAxis,
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@ -59,10 +60,14 @@ from ._style import (
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)
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from ..data.feed import Feed
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from ..data._source import Symbol
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from ..data._sharedmem import ShmArray
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from ..data._sharedmem import (
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ShmArray,
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# _Token,
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)
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from ..log import get_logger
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from ._interaction import ChartView
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from ._forms import FieldsForm
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from .._profile import pg_profile_enabled, ms_slower_then
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from ._overlay import PlotItemOverlay
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if TYPE_CHECKING:
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@ -663,19 +668,90 @@ class LinkedSplits(QWidget):
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# flows: dict[str, np.ndarray] = {}
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class Flow(BaseModel):
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class Flow(msgspec.Struct): # , frozen=True):
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'''
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(FinancialSignal-)Flow compound type which wraps a real-time
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graphics (curve) and its backing data stream together for high level
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access and control.
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'''
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class Config:
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arbitrary_types_allowed = True
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The intention is for this type to eventually be capable of shm-passing
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of incrementally updated graphics stream data between actors.
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'''
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name: str
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plot: pg.PlotItem
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shm: Optional[ShmArray] = None # may be filled in "later"
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is_ohlc: bool = False
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# TODO: hackery to be able to set a shm later
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# but whilst also allowing this type to hashable,
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# likely will require serializable token that is used to attach
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# to the underlying shm ref after startup?
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_shm: Optional[ShmArray] = None # currently, may be filled in "later"
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# cache of y-range values per x-range input.
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_mxmns: dict[tuple[int, int], tuple[float, float]] = {}
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@property
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def shm(self) -> ShmArray:
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return self._shm
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@shm.setter
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def shm(self, shm: ShmArray) -> ShmArray:
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self._shm = shm
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def maxmin(
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self,
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lbar,
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rbar,
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) -> tuple[float, float]:
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'''
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Compute the cached max and min y-range values for a given
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x-range determined by ``lbar`` and ``rbar``.
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'''
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rkey = (lbar, rbar)
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result = self._mxmns.get(rkey)
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if result:
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return result
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shm = self.shm
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if shm is None:
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# print(f'no shm {self.name}?')
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return 0, 0
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arr = shm.array
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# build relative indexes into shm array
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# TODO: should we just add/use a method
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# on the shm to do this?
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ifirst = arr[0]['index']
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slice_view = arr[
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lbar - ifirst:(rbar - ifirst) + 1]
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if not slice_view.size:
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# print(f'no data in view {self.name}?')
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return 0, 0
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if self.is_ohlc:
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ylow = np.min(slice_view['low'])
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yhigh = np.max(slice_view['high'])
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else:
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view = slice_view[self.name]
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ylow = np.min(view)
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yhigh = np.max(view)
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# else:
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# ylow, yhigh = 0, 0
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result = ylow, yhigh
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if result != (0, 0):
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self._mxmns[rkey] = result
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if self.name == 'drk_vlm':
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print(f'{self.name} mxmn @ {rkey} -> {result}')
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return result
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class ChartPlotWidget(pg.PlotWidget):
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@ -1005,6 +1081,13 @@ class ChartPlotWidget(pg.PlotWidget):
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data_key = array_key or name
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self._graphics[data_key] = graphics
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self._flows[data_key] = Flow(
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name=name,
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plot=self.plotItem,
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is_ohlc=True,
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)
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self._add_sticky(name, bg_color='davies')
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return graphics, data_key
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@ -1122,6 +1205,12 @@ class ChartPlotWidget(pg.PlotWidget):
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pi = self.plotItem
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self._flows[data_key] = Flow(
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name=name,
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plot=pi,
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is_ohlc=False,
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)
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# TODO: this probably needs its own method?
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if overlay:
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if isinstance(overlay, pg.PlotItem):
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@ -1130,10 +1219,6 @@ class ChartPlotWidget(pg.PlotWidget):
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f'{overlay} must be from `.plotitem_overlay()`'
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)
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pi = overlay
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# anchor_at = ('bottom', 'left')
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self._flows[name] = Flow(name=name, plot=pi)
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else:
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# anchor_at = ('top', 'left')
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@ -1342,46 +1427,33 @@ class ChartPlotWidget(pg.PlotWidget):
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If ``bars_range`` is provided use that range.
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'''
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l, lbar, rbar, r = bars_range or self.bars_range()
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# TODO: logic to check if end of bars in view
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# extra = view_len - _min_points_to_show
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# begin = self._arrays['ohlc'][0]['index'] - extra
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# # end = len(self._arrays['ohlc']) - 1 + extra
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# end = self._arrays['ohlc'][-1]['index'] - 1 + extra
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profiler = pg.debug.Profiler(
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disabled=not pg_profile_enabled(),
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gt=ms_slower_then,
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delayed=True,
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)
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# bars_len = rbar - lbar
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# log.debug(
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# f"\nl: {l}, lbar: {lbar}, rbar: {rbar}, r: {r}\n"
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# f"view_len: {view_len}, bars_len: {bars_len}\n"
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# f"begin: {begin}, end: {end}, extra: {extra}"
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# )
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l, lbar, rbar, r = bars_range or self.bars_range()
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profiler(f'{self.name} got bars range')
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# TODO: here we should instead look up the ``Flow.shm.array``
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# and read directly from shm to avoid copying to memory first
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# and then reading it again here.
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a = self._arrays.get(name or self.name)
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if a is None:
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return None
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ifirst = a[0]['index']
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bars = a[lbar - ifirst:(rbar - ifirst) + 1]
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if not len(bars):
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# likely no data loaded yet or extreme scrolling?
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log.error(f"WTF bars_range = {lbar}:{rbar}")
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return
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flow_key = name or self.name
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flow = self._flows.get(flow_key)
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if (
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self.data_key == self.linked.symbol.key
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flow is None
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):
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# ohlc sampled bars hi/lo lookup
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ylow = np.nanmin(bars['low'])
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yhigh = np.nanmax(bars['high'])
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print(f"flow {flow_key} doesn't exist in chart {self.name}")
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return 0, 0
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else:
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view = bars[name or self.data_key]
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ylow = np.nanmin(view)
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yhigh = np.nanmax(view)
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key = round(lbar), round(rbar)
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res = flow.maxmin(*key)
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profiler(f'{key} max-min {res}')
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if res == (0, 0):
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log.error(
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f"{flow_key} -> (0, 0) for bars_range = {key}"
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)
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# print(f'{(ylow, yhigh)}')
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return ylow, yhigh
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return res
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