mirror of
https://github.com/aljazceru/hummingbot-dashboard.git
synced 2026-01-29 01:54:19 +01:00
Merge pull request #51 from hummingbot/feat/strategy-performance-pagination
Feat/strategy performance pagination
This commit is contained in:
dardonacci
@@ -1,6 +1,7 @@
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import os
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import pandas as pd
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import streamlit as st
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import math
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from utils.database_manager import DatabaseManager
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from utils.graphs import CandlesGraph
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@@ -23,86 +24,125 @@ intervals = {
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@st.cache_resource
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def get_database(db_name: str):
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db_manager = DatabaseManager(db_name)
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return db_manager
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def get_databases():
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sqlite_files = [db_name for db_name in os.listdir("data") if db_name.endswith(".sqlite")]
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databases_list = [DatabaseManager(db) for db in sqlite_files]
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return {database.db_name: database for database in databases_list}
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with st.container():
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col1, col2 = st.columns(2)
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def download_csv(df: pd.DataFrame, filename: str, key: str):
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csv = df.to_csv(index=False).encode('utf-8')
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return st.download_button(
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label="Press to Download",
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data=csv,
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file_name=f"{filename}.csv",
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mime="text/csv",
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key=key
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)
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st.session_state["dbs"] = get_databases()
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db_names = [x.db_name for x in st.session_state["dbs"].values() if x.status == 'OK']
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if not db_names:
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st.warning("No trades have been recorded in the selected database")
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selected_db_name = None
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selected_db = None
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else:
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st.subheader("⚙️ Filters")
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col1, col2, col3, col4 = st.columns(4)
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with col1:
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db_names = [db_name for db_name in os.listdir("data") if db_name.endswith(".sqlite")]
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selected_db_name = st.selectbox("Select a database to use:",
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db_names if len(db_names) > 0 else ["No databases found"])
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if selected_db_name == "No databases found":
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st.warning("No databases available to analyze. Please run a backtesting first.")
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else:
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db_manager = get_database(selected_db_name)
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config_files = db_manager.get_config_files()
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if config_files == []:
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with col1:
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st.warning('No trades have been recorded in the selected database')
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with col2:
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selected_config_file = st.selectbox("Select a config file to analyze:", config_files)
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if selected_config_file is not None:
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exchanges_trading_pairs = db_manager.get_exchanges_trading_pairs_by_config_file(selected_config_file)
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strategy_data = db_manager.get_strategy_data(selected_config_file)
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selected_db_name = st.selectbox("Select a database to use:", db_names)
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st.session_state["selected_db"] = st.session_state["dbs"][selected_db_name]
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with col2:
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if st.session_state.selected_db:
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st.session_state.selected_config_file = st.selectbox("Select a config file to analyze:", st.session_state.selected_db.config_files)
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else:
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st.session_state.selected_config_file = None
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with col3:
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if st.session_state.selected_config_file:
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st.session_state.selected_exchange = st.selectbox("Exchange:", st.session_state.selected_db.configs[st.session_state.selected_config_file].keys())
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with col4:
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if st.session_state.selected_exchange:
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st.session_state.selected_trading_pair = st.selectbox("Trading Pair:", options=st.session_state.selected_db.configs[st.session_state.selected_config_file][st.session_state.selected_exchange])
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single_market = True
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if single_market:
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strategy_data = st.session_state["dbs"][selected_db_name].get_strategy_data(st.session_state.selected_config_file)
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single_market_strategy_data = strategy_data.get_single_market_strategy_data(st.session_state.selected_exchange, st.session_state.selected_trading_pair)
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date_array = pd.date_range(start=strategy_data.start_time, end=strategy_data.end_time, periods=60)
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start_time, end_time = st.select_slider("Select a time range to analyze",
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options=date_array.tolist(),
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value=(date_array[0], date_array[-1]))
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strategy_data_filtered = single_market_strategy_data.get_filtered_strategy_data(start_time, end_time)
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st.markdown("<hr>", unsafe_allow_html=True)
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with st.container():
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col1, col2, col3 = st.columns(3)
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col1, col2 = st.columns(2)
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with col1:
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selected_exchange = st.selectbox("Select an exchange:", [] if selected_config_file is None else list(exchanges_trading_pairs.keys()))
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st.subheader(f"🏦 Market")
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with col2:
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selected_trading_pair = st.selectbox("Select a trading pair:", [] if selected_config_file is None else exchanges_trading_pairs[selected_exchange])
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st.subheader("📋 General stats")
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col1, col2, col3, col4 = st.columns(4)
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with col1:
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st.metric(label="Exchange", value=strategy_data_filtered.exchange.capitalize())
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with col2:
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st.metric(label="Trading pair", value=strategy_data_filtered.trading_pair.upper())
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with col3:
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interval = st.selectbox("Candles Interval:", intervals.keys(), index=2)
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st.metric(label='Start date', value=strategy_data_filtered.start_time.strftime("%Y-%m-%d %H:%M"))
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st.metric(label='End date', value=strategy_data_filtered.end_time.strftime("%Y-%m-%d %H:%M"))
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with col4:
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st.metric(label='Duration (Hours)', value=round(strategy_data_filtered.duration_seconds / 3600, 2))
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st.metric(label='Price change', value=f"{round(strategy_data_filtered.price_change * 100, 2)} %")
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if selected_exchange and selected_trading_pair:
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single_market_strategy_data = strategy_data.get_single_market_strategy_data(selected_exchange,
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selected_trading_pair)
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date_array = pd.date_range(start=strategy_data.start_time, end=strategy_data.end_time, periods=60)
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start_time, end_time = st.select_slider("Select a time range to analyze", options=date_array.tolist(),
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value=(date_array[0], date_array[-1]))
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st.markdown("<hr>", unsafe_allow_html=True)
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st.subheader("📈 Performance")
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col131, col132, col133, col134 = st.columns(4)
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with col131:
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st.metric(label=f'Net PNL {strategy_data_filtered.quote_asset}',
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value=round(strategy_data_filtered.net_pnl_quote, 2))
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st.metric(label=f'Trade PNL {strategy_data_filtered.quote_asset}',
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value=round(strategy_data_filtered.trade_pnl_quote, 2))
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st.metric(label=f'Fees {strategy_data_filtered.quote_asset}',
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value=round(strategy_data_filtered.cum_fees_in_quote, 2))
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with col132:
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st.metric(label='Total Trades', value=strategy_data_filtered.total_orders)
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st.metric(label='Total Buy Trades', value=strategy_data_filtered.total_buy_trades)
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st.metric(label='Total Sell Trades', value=strategy_data_filtered.total_sell_trades)
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with col133:
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st.metric(label='Inventory change in Base asset',
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value=round(strategy_data_filtered.inventory_change_base_asset, 4))
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st.metric(label='Total Buy Trades Amount',
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value=round(strategy_data_filtered.total_buy_amount, 2))
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st.metric(label='Total Sell Trades Amount',
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value=round(strategy_data_filtered.total_sell_amount, 2))
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with col134:
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st.metric(label='End Price', value=round(strategy_data_filtered.end_price, 4))
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st.metric(label='Average Buy Price', value=round(strategy_data_filtered.average_buy_price, 4))
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st.metric(label='Average Sell Price', value=round(strategy_data_filtered.average_sell_price, 4))
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strategy_data_filtered = single_market_strategy_data.get_filtered_strategy_data(start_time, end_time)
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row = st.container()
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col11, col12, col13 = st.columns([1, 2, 3])
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with row:
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with col11:
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st.header(f"🏦 Market")
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st.metric(label="Exchange", value=strategy_data_filtered.exchange.capitalize())
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st.metric(label="Trading pair", value=strategy_data_filtered.trading_pair.upper())
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with col12:
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st.header("📋 General stats")
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col121, col122 = st.columns(2)
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with col121:
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st.metric(label='Duration (Hours)', value=round(strategy_data_filtered.duration_seconds / 3600, 2))
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st.metric(label='Start date', value=strategy_data_filtered.start_time.strftime("%Y-%m-%d %H:%M"))
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st.metric(label='End date', value=strategy_data_filtered.end_time.strftime("%Y-%m-%d %H:%M"))
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with col122:
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st.metric(label='Price change', value=f"{round(strategy_data_filtered.price_change * 100, 2)} %")
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with col13:
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st.header("📈 Performance")
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col131, col132, col133, col134 = st.columns(4)
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with col131:
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st.metric(label=f'Net PNL {strategy_data_filtered.quote_asset}', value=round(strategy_data_filtered.net_pnl_quote, 2))
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st.metric(label=f'Trade PNL {strategy_data_filtered.quote_asset}', value=round(strategy_data_filtered.trade_pnl_quote, 2))
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st.metric(label=f'Fees {strategy_data_filtered.quote_asset}', value=round(strategy_data_filtered.cum_fees_in_quote, 2))
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with col132:
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st.metric(label='Total Trades', value=strategy_data_filtered.total_orders)
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st.metric(label='Total Buy Trades', value=strategy_data_filtered.total_buy_trades)
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st.metric(label='Total Sell Trades', value=strategy_data_filtered.total_sell_trades)
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with col133:
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st.metric(label='Inventory change in Base asset',
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value=round(strategy_data_filtered.inventory_change_base_asset, 4))
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st.metric(label='Total Buy Trades Amount', value=round(strategy_data_filtered.total_buy_amount, 2))
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st.metric(label='Total Sell Trades Amount', value=round(strategy_data_filtered.total_sell_amount, 2))
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with col134:
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st.metric(label='End Price', value=round(strategy_data_filtered.end_price, 4))
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st.metric(label='Average Buy Price', value=round(strategy_data_filtered.average_buy_price, 4))
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st.metric(label='Average Sell Price', value=round(strategy_data_filtered.average_sell_price, 4))
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if strategy_data_filtered.market_data is not None:
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candles_df = strategy_data_filtered.get_market_data_resampled(interval=f"{intervals[interval]}S")
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st.markdown("<hr>", unsafe_allow_html=True)
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st.subheader("🕯️ Candlestick")
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if strategy_data_filtered.market_data is not None:
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with st.expander("Market activity", expanded=True):
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col1, col2, col3 = st.columns([1, 1, 2])
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with col1:
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interval = st.selectbox("Candles Interval:", intervals.keys(), index=2)
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with col2:
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rows_per_page = st.number_input("Candles per Page", value=100, min_value=1, max_value=5000)
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with col3:
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total_rows = len(strategy_data_filtered.get_market_data_resampled(interval=f"{intervals[interval]}S"))
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total_pages = math.ceil(total_rows / rows_per_page)
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if total_pages > 1:
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selected_page = st.select_slider("Select page", list(range(total_pages)), key="page_slider")
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else:
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selected_page = 0
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start_idx = selected_page * rows_per_page
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end_idx = start_idx + rows_per_page
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candles_df = strategy_data_filtered.get_market_data_resampled(interval=f"{intervals[interval]}S").iloc[
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start_idx:end_idx]
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start_time_page = candles_df.index.min()
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end_time_page = candles_df.index.max()
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page_data_filtered = single_market_strategy_data.get_filtered_strategy_data(start_time_page, end_time_page)
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cg = CandlesGraph(candles_df, show_volume=False, extra_rows=2)
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cg.add_buy_trades(strategy_data_filtered.buys)
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cg.add_sell_trades(strategy_data_filtered.sells)
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@@ -110,15 +150,17 @@ with st.container():
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cg.add_base_inventory_change(strategy_data_filtered, row=3)
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fig = cg.figure()
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st.plotly_chart(fig, use_container_width=True)
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else:
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st.warning("Market data is not available so the candles graph is not going to be rendered. "
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"Make sure that you are using the latest version of Hummingbot and market data recorder activated.")
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st.subheader("💵Trades")
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else:
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st.warning("Market data is not available so the candles graph is not going to be rendered. "
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"Make sure that you are using the latest version of Hummingbot and market data recorder activated.")
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st.markdown("<hr>", unsafe_allow_html=True)
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st.subheader("Tables")
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with st.expander("💵 Trades"):
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st.write(strategy_data_filtered.trade_fill)
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st.subheader("📩 Orders")
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download_csv(strategy_data_filtered.trade_fill, "trade_fill", "download-trades")
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with st.expander("📩 Orders"):
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st.write(strategy_data_filtered.orders)
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st.subheader("⌕ Order Status")
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download_csv(strategy_data_filtered.orders, "orders", "download-orders")
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with st.expander("⌕ Order Status"):
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st.write(strategy_data_filtered.order_status)
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download_csv(strategy_data_filtered.order_status, "order_status", "download-order-status")
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@@ -16,6 +16,28 @@ class DatabaseManager:
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self.engine = create_engine(self.db_path, connect_args={'check_same_thread': False})
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self.session_maker = sessionmaker(bind=self.engine)
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@property
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def status(self):
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try:
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with self.session_maker() as session:
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query = 'SELECT DISTINCT config_file_path FROM TradeFill'
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config_files = pd.read_sql_query(query, session.connection())
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if len(config_files) > 0:
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# TODO: improve error handling, think what to do with other cases
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return "OK"
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else:
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return "No records found in the TradeFill table with non-null config_file_path"
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except Exception as e:
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return f"Error: {str(e)}"
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@property
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def config_files(self):
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return self.get_config_files()
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@property
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def configs(self):
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return {config_file: self.get_exchanges_trading_pairs_by_config_file(config_file) for config_file in self.config_files}
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def get_config_files(self):
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with self.session_maker() as session:
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query = 'SELECT DISTINCT config_file_path FROM TradeFill'
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@@ -16,6 +16,8 @@ class CandlesGraph:
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specs = [[{"secondary_y": True}]] * rows
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self.base_figure = make_subplots(rows=rows, cols=1, shared_xaxes=True, vertical_spacing=0.005,
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row_heights=heights, specs=specs)
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self.min_time = candles_df.reset_index().timestamp.min()
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self.max_time = candles_df.reset_index().timestamp.max()
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self.add_candles_graph()
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if self.show_volume:
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self.add_volume()
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@@ -231,7 +233,9 @@ class CandlesGraph:
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x=1
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),
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height=1500,
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xaxis_rangeslider_visible=False,
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xaxis=dict(rangeslider_visible=False,
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range=[self.min_time, self.max_time]),
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yaxis=dict(range=[self.candles_df.low.min(), self.candles_df.high.max()]),
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hovermode='x unified'
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)
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self.base_figure.update_yaxes(title_text="Price", row=1, col=1)
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@@ -5,11 +5,12 @@ import inspect
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import streamlit as st
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def initialize_st_page(title: str, icon: str, layout="wide"):
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def initialize_st_page(title: str, icon: str, layout="wide", initial_sidebar_state="collapsed"):
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st.set_page_config(
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page_title=title,
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page_icon=icon,
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layout=layout,
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initial_sidebar_state=initial_sidebar_state
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)
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st.title(f"{icon} {title}")
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caller_frame = inspect.currentframe().f_back
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