from deephaven import ui, agg, empty_table
from deephaven.stream.table_publisher import table_publisher
from deephaven.stream import blink_to_append_only
from deephaven.plot import express as dx
from deephaven import updateby as uby
from deephaven import dtypes as dht
stocks = dx.data.stocks().reverse()
def set_bol_properties(fig):
fig.update_layout(showlegend=False)
fig.update_traces(fill="tonexty", fillcolor='rgba(255,165,0,0.08)')
@ui.component
def line_plot(
filtered_source,
exchange, window_size, bol_bands):
window_size_key = {
"5 seconds": ("PriceAvg5s", "PriceStd5s"),
"30 seconds": ("PriceAvg30s", "PriceStd30s"),
"1 minute": ("PriceAvg1m", "PriceStd1m"),
"5 minutes": ("PriceAvg5m", "PriceStd5m")}
bol_bands_key = {"None": None, "80%": 1.282, "90%": 1.645, "95%": 1.960, "99%": 2.576}
base_plot = ui.use_memo(lambda: (
dx.line(filtered_source, x="Timestamp", y="Price", by="Exchange" if exchange == "All" else None,
unsafe_update_figure=lambda fig: fig.update_traces(opacity=0.4))
), [filtered_source, exchange])
window_size_avg_key_col = window_size_key[window_size][0]
window_size_std_key_col = window_size_key[window_size][1]
avg_plot = ui.use_memo(lambda: dx.line(filtered_source,
x="Timestamp", y=window_size_avg_key_col,
color_discrete_sequence=["orange"],
labels={window_size_avg_key_col: "Rolling Average"}),
[filtered_source, window_size_avg_key_col]
)
bol_bands_key_col = bol_bands_key[bol_bands]
bol_plot = ui.use_memo(lambda: (
dx.line(filtered_source \
.update([
f"errorY={window_size_avg_key_col} + {bol_bands_key_col}*{window_size_std_key_col}",
f"errorYMinus={window_size_avg_key_col} - {bol_bands_key_col}*{window_size_std_key_col}",
]),
x="Timestamp", y=["errorYMinus", "errorY"],
color_discrete_sequence=["rgba(255,165,0,0.3)", "rgba(255,165,0,0.3)"],
unsafe_update_figure=set_bol_properties)
if bol_bands_key_col is not None else None
), [filtered_source, window_size_avg_key_col, window_size_std_key_col, bol_bands_key_col])
plot = ui.use_memo(lambda: dx.layer(base_plot, avg_plot, bol_plot), [base_plot, avg_plot, bol_plot])
return ui.panel(plot, title="Prices")
@ui.component
def full_table(source):
return ui.panel(source, title="Full Table")
@ui.component
def filtered_table(source, exchange):
if exchange == "All":
return ui.panel(source \
.drop_columns([
"PriceAvg5s", "PriceStd5s", "PriceAvg30s", "PriceStd30s",
"PriceAvg1m", "PriceStd1m", "PriceAvg5m", "PriceStd5m"]) \
.reverse(), title="Filtered Table")
return ui.panel(source \
.drop_columns([
"PriceAvg5s", "PriceStd5s", "PriceAvg30s", "PriceStd30s",
"PriceAvg1m", "PriceStd1m", "PriceAvg5m", "PriceStd5m"]) \
.where(f"exchange == `{exchange}`")
.reverse(), title="Filtered Table")
@ui.component
def parameters_panel(
symbols,
exchanges,
symbol, set_symbol,
exchange, set_exchange,
window_size, set_window_size,
bol_bands, set_bol_bands):
symbol_picker = ui.picker(
*symbols,
label="Symbol",
on_selection_change=set_symbol,
selected_key=symbol,
)
exchange_picker = ui.picker(
*exchanges,
label="Exchange",
on_selection_change=set_exchange,
selected_key=exchange,
)
window_size_selector = ui.button_group(
ui.button("5 seconds", variant="accent" if window_size == "5 seconds" else None, on_press=lambda: set_window_size("5 seconds")),
ui.button("30 seconds", variant="accent" if window_size == "30 seconds" else None, on_press=lambda: set_window_size("30 seconds")),
ui.button("1 minute", variant="accent" if window_size == "1 minute" else None, on_press=lambda: set_window_size("1 minute")),
ui.button("5 minutes", variant="accent" if window_size == "5 minutes" else None, on_press=lambda: set_window_size("5 minutes")),
margin_x=10
)
bolinger_band_selector = ui.button_group(
ui.button("None", variant="accent" if bol_bands == "None" else None, on_press=lambda: set_bol_bands("None")),
ui.button("80%", variant="accent" if bol_bands == "80%" else None, on_press=lambda: set_bol_bands("80%")),
ui.button("90%", variant="accent" if bol_bands == "90%" else None, on_press=lambda: set_bol_bands("90%")),
ui.button("95%", variant="accent" if bol_bands == "95%" else None, on_press=lambda: set_bol_bands("95%")),
ui.button("99%", variant="accent" if bol_bands == "99%" else None, on_press=lambda: set_bol_bands("99%")),
margin_x=10
)
return ui.panel(
ui.flex(
ui.flex(
symbol_picker,
exchange_picker,
gap="size-200"
),
ui.flex(
ui.text("Window size:"),
ui.flex(window_size_selector, direction="row"),
gap="size-100",
direction="column"
),
ui.flex(
ui.text("Bolinger bands:"),
ui.flex(bolinger_band_selector, direction="row"),
gap="size-100",
direction="column"
),
margin="size-200",
direction="column",
gap="size-200"
),
title="Parameters"
)
@ui.component
def orderbook_panel(symbols):
symbol, set_symbol = ui.use_state("")
size, set_size = ui.use_state(0)
blink_table, publisher = ui.use_memo(
lambda: table_publisher(
"Order table", {"Sym": dht.string, "Size": dht.int32, "Side": dht.string}
),
[],
)
t = ui.use_memo(lambda: blink_to_append_only(blink_table), [blink_table])
def submit_order(order_sym, order_size, side):
publisher.add(
empty_table(1).update(
[f"Sym=`{order_sym}`", f"Size={order_size}", f"Side=`{side}`"]
)
)
def handle_buy(_):
submit_order(symbol, size, "buy")
def handle_sell(_):
submit_order(symbol, size, "sell")
symbol_picker = ui.picker(
*symbols,
label="Symbol",
label_position="side",
on_selection_change=set_symbol,
selected_key=symbol
)
size_selector = ui.number_field(
label="Size",
label_position="side",
value=size,
on_change=set_size
)
return ui.panel(
ui.flex(
symbol_picker,
size_selector,
ui.button("Buy", on_press=handle_buy, variant="accent", style="fill"),
ui.button("Sell", on_press=handle_sell, variant="negative", style="fill"),
gap="size-200",
margin="size-200",
wrap=True,
),
t,
title="Order Book"
)
@ui.component
def my_layout(source, source_with_stats):
symbols = ui.use_column_data(source.agg_by(agg.unique(cols="Sym"), by="Sym"))
exchanges = ui.use_column_data(source.agg_by(agg.unique(cols="Exchange"), by="Exchange"))
exchanges.append("All")
symbol, set_symbol = ui.use_state(symbols[0])
exchange, set_exchange = ui.use_state("All")
window_size, set_window_size = ui.use_state("30 seconds")
bol_bands, set_bol_bands = ui.use_state("90%")
single_symbol = ui.use_memo(lambda: (
source_with_stats \
.where([f"Sym == `{symbol}`"]) \
.drop_columns([
"PriceAvg5s", "PriceStd5s", "PriceAvg30s", "PriceStd30s",
"PriceAvg1m", "PriceStd1m", "PriceAvg5m", "PriceStd5m"]) \
.rename_columns([
"PriceAvg5s=PriceAvg5sAvg", "PriceStd5s=PriceStd5sAvg",
"PriceAvg30s=PriceAvg30sAvg", "PriceStd30s=PriceStd30sAvg",
"PriceAvg1m=PriceAvg1mAvg", "PriceStd1m=PriceStd1mAvg",
"PriceAvg5m=PriceAvg5mAvg", "PriceStd5m=PriceStd5mAvg"])
if exchange == "All" else
source_with_stats \
.where([f"Sym == `{symbol}`", f"Exchange == `{exchange}`"]) \
.drop_columns([
"PriceAvg5sAvg", "PriceStd5sAvg", "PriceAvg30sAvg", "PriceStd30sAvg",
"PriceAvg1mAvg", "PriceStd1mAvg", "PriceAvg5mAvg", "PriceStd5mAvg"]) \
), [symbol, source_with_stats]
)
return ui.row(
ui.column(
line_plot(
single_symbol, exchange, window_size, bol_bands
),
ui.stack(
full_table(source),
filtered_table(single_symbol, exchange),
),
width=65
),
ui.column(
ui.row(
parameters_panel(
symbols, exchanges,
symbol, set_symbol,
exchange, set_exchange,
window_size, set_window_size,
bol_bands, set_bol_bands
),
height=40
),
ui.row(
orderbook_panel(symbols),
height=60
),
width=35
)
)
_sorted_stocks = stocks.sort("Timestamp")
_stocks_with_stats = _sorted_stocks \
.update_by([
uby.rolling_avg_time("Timestamp", "PriceAvg5sAvg=Price", "PT2.5s", "PT2.5s"),
uby.rolling_avg_time("Timestamp", "PriceAvg30sAvg=Price", "PT15s", "PT15s"),
uby.rolling_avg_time("Timestamp", "PriceAvg1mAvg=Price", "PT30s", "PT30s"),
uby.rolling_avg_time("Timestamp", "PriceAvg5mAvg=Price", "PT150s", "PT150s"),
uby.rolling_std_time("Timestamp", "PriceStd5sAvg=Price", "PT2.5s", "PT2.5s"),
uby.rolling_std_time("Timestamp", "PriceStd30sAvg=Price", "PT15s", "PT15s"),
uby.rolling_std_time("Timestamp", "PriceStd1mAvg=Price", "PT30s", "PT30s"),
uby.rolling_std_time("Timestamp", "PriceStd5mAvg=Price", "PT150s", "PT150s"),
], by = ["Sym"]) \
.update_by([
uby.rolling_avg_time("Timestamp", "PriceAvg5s=Price", "PT2.5s", "PT2.5s"),
uby.rolling_avg_time("Timestamp", "PriceAvg30s=Price", "PT15s", "PT15s"),
uby.rolling_avg_time("Timestamp", "PriceAvg1m=Price", "PT30s", "PT30s"),
uby.rolling_avg_time("Timestamp", "PriceAvg5m=Price", "PT150s", "PT150s"),
uby.rolling_std_time("Timestamp", "PriceStd5s=Price", "PT2.5s", "PT2.5s"),
uby.rolling_std_time("Timestamp", "PriceStd30s=Price", "PT15s", "PT15s"),
uby.rolling_std_time("Timestamp", "PriceStd1m=Price", "PT30s", "PT30s"),
uby.rolling_std_time("Timestamp", "PriceStd5m=Price", "PT150s", "PT150s"),
], by = ["Sym", "Exchange"])
dashboard = ui.dashboard(my_layout(stocks, _stocks_with_stats))