aljaz/hummingbot-dashboard
1
0
Fork 0
mirror of https://github.com/aljazceru/hummingbot-dashboard.git synced 2026-01-26 00:24:20 +01:00
Code Issues Packages Projects Releases Wiki Activity

(feat) refactor page to use the new candles

Browse Source
This commit is contained in:
cardosofede
2023-06-22 19:32:07 +01:00
parent 4ba05b0788
commit 0a3d7e9dbe
1 changed files with 19 additions and 30 deletions
Download Patch File Download Diff File Expand all files Collapse all files

49
pages/2_🚀_Strategy_Performance.py
View File

@@ -16,8 +16,10 @@ st.set_page_config(
st.title("🚀 Strategy Performance")
intervals = {
# "1m": 60,
"1m": 60,
"3m": 60 * 3,
"5m": 60 * 5,
"15m": 60 * 15,
"30m": 60 * 30,
"1h": 60 * 60,
"6h": 60 * 60 * 6,
@@ -30,17 +32,6 @@ def get_database(db_name: str):
return db_manager
@st.cache_data(ttl=60)
def get_ohlc(trading_pair: str, exchange: str, interval: str, start_timestamp: int, end_timestamp: int):
# TODO: Remove hardcoded exchange by using the new data collected by the bot.
connector = getattr(ccxt, "binance")()
limit = max(int((end_timestamp - start_timestamp) / intervals[interval]), 10)
bars = connector.fetch_ohlcv(trading_pair.replace("-", ""), timeframe=interval, since=start_timestamp * 1000, limit=limit)
df = pd.DataFrame(bars, columns=["timestamp", "open", "high", "low", "close", "volume"])
df["datetime"] = pd.to_datetime(df["timestamp"], unit="ms")
return df
with st.container():
col1, col2 = st.columns(2)
with col1:
@@ -68,22 +59,16 @@ with st.container():
with col2:
selected_trading_pair = st.selectbox("Select a trading pair:", [] if selected_config_file is None else exchanges_trading_pairs[selected_exchange])
with col3:
interval = st.selectbox("Candles Interval:", intervals.keys(), index=0)
interval = st.selectbox("Candles Interval:", intervals.keys(), index=2)
if selected_exchange and selected_trading_pair:
single_market_strategy_data = strategy_data.get_single_market_strategy_data(selected_exchange, selected_trading_pair)
single_market_strategy_data = strategy_data.get_single_market_strategy_data(selected_exchange,
selected_trading_pair)
date_array = pd.date_range(start=strategy_data.start_time, end=strategy_data.end_time, periods=60)
ohlc_extra_time = 60
with st.spinner("Loading candles..."):
candles_df = get_ohlc(single_market_strategy_data.trading_pair, single_market_strategy_data.exchange, interval,
int(strategy_data.start_time.timestamp() - ohlc_extra_time),
int(strategy_data.end_time.timestamp() + ohlc_extra_time))
start_time, end_time = st.select_slider("Select a time range to analyze", options=date_array.tolist(),
value=(date_array[0], date_array[-1]))
candles_df_filtered = candles_df[(candles_df["timestamp"] >= int(start_time.timestamp() * 1000)) & (
candles_df["timestamp"] <= int(end_time.timestamp() * 1000))]
strategy_data_filtered = single_market_strategy_data.get_filtered_strategy_data(start_time, end_time)
strategy_data_filtered = single_market_strategy_data.get_filtered_strategy_data(start_time, end_time)
row = st.container()
col11, col12, col13 = st.columns([1, 2, 3])
with row:
@@ -120,14 +105,18 @@ with st.container():
st.metric(label='End Price', value=round(strategy_data_filtered.end_price, 4))
st.metric(label='Average Buy Price', value=round(strategy_data_filtered.average_buy_price, 4))
st.metric(label='Average Sell Price', value=round(strategy_data_filtered.average_sell_price, 4))
cg = CandlesGraph(candles_df_filtered, show_volume=True, extra_rows=2)
cg.add_buy_trades(strategy_data_filtered.buys)
cg.add_sell_trades(strategy_data_filtered.sells)
cg.add_base_inventory_change(strategy_data_filtered)
cg.add_pnl(strategy_data_filtered)
fig = cg.figure()
st.plotly_chart(fig, use_container_width=True)
if strategy_data_filtered.market_data is not None:
candles_df = strategy_data_filtered.get_market_data_resampled(interval=f"{intervals[interval]}S")
cg = CandlesGraph(candles_df, show_volume=False, extra_rows=2)
cg.add_buy_trades(strategy_data_filtered.buys)
cg.add_sell_trades(strategy_data_filtered.sells)
cg.add_pnl(strategy_data_filtered, row=2)
cg.add_base_inventory_change(strategy_data_filtered, row=3)
fig = cg.figure()
st.plotly_chart(fig, use_container_width=True)
else:
st.warning("Market data is not available so the candles graph is not available. "
"Make sure that you are using the latest version of Hummingbot and market data recorder activated.")
st.subheader("💵Trades")
st.write(strategy_data_filtered.trade_fill)