diff --git a/pages/strategy_performance/app.py b/pages/strategy_performance/app.py
index 629565a..6491ec6 100644
--- a/pages/strategy_performance/app.py
+++ b/pages/strategy_performance/app.py
@@ -1,6 +1,7 @@
import os
import pandas as pd
import streamlit as st
+import math
from utils.database_manager import DatabaseManager
from utils.graphs import CandlesGraph
@@ -23,86 +24,125 @@ intervals = {
@st.cache_resource
-def get_database(db_name: str):
- db_manager = DatabaseManager(db_name)
- return db_manager
+def get_databases():
+ sqlite_files = [db_name for db_name in os.listdir("data") if db_name.endswith(".sqlite")]
+ databases_list = [DatabaseManager(db) for db in sqlite_files]
+ return {database.db_name: database for database in databases_list}
-with st.container():
- col1, col2 = st.columns(2)
+def download_csv(df: pd.DataFrame, filename: str, key: str):
+ csv = df.to_csv(index=False).encode('utf-8')
+ return st.download_button(
+ label="Press to Download",
+ data=csv,
+ file_name=f"{filename}.csv",
+ mime="text/csv",
+ key=key
+ )
+
+
+st.session_state["dbs"] = get_databases()
+db_names = [x.db_name for x in st.session_state["dbs"].values() if x.status == 'OK']
+if not db_names:
+ st.warning("No trades have been recorded in the selected database")
+ selected_db_name = None
+ selected_db = None
+else:
+ st.subheader("βοΈ Filters")
+ col1, col2, col3, col4 = st.columns(4)
with col1:
- db_names = [db_name for db_name in os.listdir("data") if db_name.endswith(".sqlite")]
- selected_db_name = st.selectbox("Select a database to use:",
- db_names if len(db_names) > 0 else ["No databases found"])
- if selected_db_name == "No databases found":
- st.warning("No databases available to analyze. Please run a backtesting first.")
- else:
- db_manager = get_database(selected_db_name)
- config_files = db_manager.get_config_files()
- if config_files == []:
- with col1:
- st.warning('No trades have been recorded in the selected database')
- with col2:
- selected_config_file = st.selectbox("Select a config file to analyze:", config_files)
- if selected_config_file is not None:
- exchanges_trading_pairs = db_manager.get_exchanges_trading_pairs_by_config_file(selected_config_file)
- strategy_data = db_manager.get_strategy_data(selected_config_file)
-
+ selected_db_name = st.selectbox("Select a database to use:", db_names)
+ st.session_state["selected_db"] = st.session_state["dbs"][selected_db_name]
+ with col2:
+ if st.session_state.selected_db:
+ st.session_state.selected_config_file = st.selectbox("Select a config file to analyze:", st.session_state.selected_db.config_files)
+ else:
+ st.session_state.selected_config_file = None
+ with col3:
+ if st.session_state.selected_config_file:
+ st.session_state.selected_exchange = st.selectbox("Exchange:", st.session_state.selected_db.configs[st.session_state.selected_config_file].keys())
+ with col4:
+ if st.session_state.selected_exchange:
+ 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])
+
+ single_market = True
+ if single_market:
+ strategy_data = st.session_state["dbs"][selected_db_name].get_strategy_data(st.session_state.selected_config_file)
+ single_market_strategy_data = strategy_data.get_single_market_strategy_data(st.session_state.selected_exchange, st.session_state.selected_trading_pair)
+ date_array = pd.date_range(start=strategy_data.start_time, end=strategy_data.end_time, periods=60)
+ start_time, end_time = st.select_slider("Select a time range to analyze",
+ options=date_array.tolist(),
+ value=(date_array[0], date_array[-1]))
+ strategy_data_filtered = single_market_strategy_data.get_filtered_strategy_data(start_time, end_time)
+
+ st.markdown("
", unsafe_allow_html=True)
with st.container():
- col1, col2, col3 = st.columns(3)
+ col1, col2 = st.columns(2)
with col1:
- selected_exchange = st.selectbox("Select an exchange:", [] if selected_config_file is None else list(exchanges_trading_pairs.keys()))
+ st.subheader(f"π¦ Market")
with col2:
- selected_trading_pair = st.selectbox("Select a trading pair:", [] if selected_config_file is None else exchanges_trading_pairs[selected_exchange])
+ st.subheader("π General stats")
+ col1, col2, col3, col4 = st.columns(4)
+ with col1:
+ st.metric(label="Exchange", value=strategy_data_filtered.exchange.capitalize())
+ with col2:
+ st.metric(label="Trading pair", value=strategy_data_filtered.trading_pair.upper())
with col3:
- interval = st.selectbox("Candles Interval:", intervals.keys(), index=2)
+ st.metric(label='Start date', value=strategy_data_filtered.start_time.strftime("%Y-%m-%d %H:%M"))
+ st.metric(label='End date', value=strategy_data_filtered.end_time.strftime("%Y-%m-%d %H:%M"))
+ with col4:
+ st.metric(label='Duration (Hours)', value=round(strategy_data_filtered.duration_seconds / 3600, 2))
+ st.metric(label='Price change', value=f"{round(strategy_data_filtered.price_change * 100, 2)} %")
- if selected_exchange and 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)
- start_time, end_time = st.select_slider("Select a time range to analyze", options=date_array.tolist(),
- value=(date_array[0], date_array[-1]))
+ st.markdown("
", unsafe_allow_html=True)
+ st.subheader("π Performance")
+ col131, col132, col133, col134 = st.columns(4)
+ with col131:
+ st.metric(label=f'Net PNL {strategy_data_filtered.quote_asset}',
+ value=round(strategy_data_filtered.net_pnl_quote, 2))
+ st.metric(label=f'Trade PNL {strategy_data_filtered.quote_asset}',
+ value=round(strategy_data_filtered.trade_pnl_quote, 2))
+ st.metric(label=f'Fees {strategy_data_filtered.quote_asset}',
+ value=round(strategy_data_filtered.cum_fees_in_quote, 2))
+ with col132:
+ st.metric(label='Total Trades', value=strategy_data_filtered.total_orders)
+ st.metric(label='Total Buy Trades', value=strategy_data_filtered.total_buy_trades)
+ st.metric(label='Total Sell Trades', value=strategy_data_filtered.total_sell_trades)
+ with col133:
+ st.metric(label='Inventory change in Base asset',
+ value=round(strategy_data_filtered.inventory_change_base_asset, 4))
+ st.metric(label='Total Buy Trades Amount',
+ value=round(strategy_data_filtered.total_buy_amount, 2))
+ st.metric(label='Total Sell Trades Amount',
+ value=round(strategy_data_filtered.total_sell_amount, 2))
+ with col134:
+ 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))
- 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:
- with col11:
- st.header(f"π¦ Market")
- st.metric(label="Exchange", value=strategy_data_filtered.exchange.capitalize())
- st.metric(label="Trading pair", value=strategy_data_filtered.trading_pair.upper())
- with col12:
- st.header("π General stats")
- col121, col122 = st.columns(2)
- with col121:
- st.metric(label='Duration (Hours)', value=round(strategy_data_filtered.duration_seconds / 3600, 2))
- st.metric(label='Start date', value=strategy_data_filtered.start_time.strftime("%Y-%m-%d %H:%M"))
- st.metric(label='End date', value=strategy_data_filtered.end_time.strftime("%Y-%m-%d %H:%M"))
- with col122:
- st.metric(label='Price change', value=f"{round(strategy_data_filtered.price_change * 100, 2)} %")
- with col13:
- st.header("π Performance")
- col131, col132, col133, col134 = st.columns(4)
- with col131:
- st.metric(label=f'Net PNL {strategy_data_filtered.quote_asset}', value=round(strategy_data_filtered.net_pnl_quote, 2))
- st.metric(label=f'Trade PNL {strategy_data_filtered.quote_asset}', value=round(strategy_data_filtered.trade_pnl_quote, 2))
- st.metric(label=f'Fees {strategy_data_filtered.quote_asset}', value=round(strategy_data_filtered.cum_fees_in_quote, 2))
- with col132:
- st.metric(label='Total Trades', value=strategy_data_filtered.total_orders)
- st.metric(label='Total Buy Trades', value=strategy_data_filtered.total_buy_trades)
- st.metric(label='Total Sell Trades', value=strategy_data_filtered.total_sell_trades)
- with col133:
- st.metric(label='Inventory change in Base asset',
- value=round(strategy_data_filtered.inventory_change_base_asset, 4))
- st.metric(label='Total Buy Trades Amount', value=round(strategy_data_filtered.total_buy_amount, 2))
- st.metric(label='Total Sell Trades Amount', value=round(strategy_data_filtered.total_sell_amount, 2))
- with col134:
- 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))
- if strategy_data_filtered.market_data is not None:
- candles_df = strategy_data_filtered.get_market_data_resampled(interval=f"{intervals[interval]}S")
+ st.markdown("
", unsafe_allow_html=True)
+ st.subheader("π―οΈ Candlestick")
+ if strategy_data_filtered.market_data is not None:
+ with st.expander("Market activity", expanded=True):
+ col1, col2, col3 = st.columns([1, 1, 2])
+ with col1:
+ interval = st.selectbox("Candles Interval:", intervals.keys(), index=2)
+ with col2:
+ rows_per_page = st.number_input("Candles per Page", value=100, min_value=1, max_value=5000)
+ with col3:
+ total_rows = len(strategy_data_filtered.get_market_data_resampled(interval=f"{intervals[interval]}S"))
+ total_pages = math.ceil(total_rows / rows_per_page)
+ if total_pages > 1:
+ selected_page = st.select_slider("Select page", list(range(total_pages)), key="page_slider")
+ else:
+ selected_page = 0
+ start_idx = selected_page * rows_per_page
+ end_idx = start_idx + rows_per_page
+ candles_df = strategy_data_filtered.get_market_data_resampled(interval=f"{intervals[interval]}S").iloc[
+ start_idx:end_idx]
+ start_time_page = candles_df.index.min()
+ end_time_page = candles_df.index.max()
+ page_data_filtered = single_market_strategy_data.get_filtered_strategy_data(start_time_page, end_time_page)
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)
@@ -110,15 +150,17 @@ with st.container():
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 going to be rendered. "
- "Make sure that you are using the latest version of Hummingbot and market data recorder activated.")
-
- st.subheader("π΅Trades")
+ else:
+ st.warning("Market data is not available so the candles graph is not going to be rendered. "
+ "Make sure that you are using the latest version of Hummingbot and market data recorder activated.")
+ st.markdown("
", unsafe_allow_html=True)
+ st.subheader("Tables")
+ with st.expander("π΅ Trades"):
st.write(strategy_data_filtered.trade_fill)
-
- st.subheader("π© Orders")
+ download_csv(strategy_data_filtered.trade_fill, "trade_fill", "download-trades")
+ with st.expander("π© Orders"):
st.write(strategy_data_filtered.orders)
-
- st.subheader("β Order Status")
+ download_csv(strategy_data_filtered.orders, "orders", "download-orders")
+ with st.expander("β Order Status"):
st.write(strategy_data_filtered.order_status)
+ download_csv(strategy_data_filtered.order_status, "order_status", "download-order-status")
diff --git a/utils/database_manager.py b/utils/database_manager.py
index 2a05cd7..ce9f6e9 100644
--- a/utils/database_manager.py
+++ b/utils/database_manager.py
@@ -16,6 +16,28 @@ class DatabaseManager:
self.engine = create_engine(self.db_path, connect_args={'check_same_thread': False})
self.session_maker = sessionmaker(bind=self.engine)
+ @property
+ def status(self):
+ try:
+ with self.session_maker() as session:
+ query = 'SELECT DISTINCT config_file_path FROM TradeFill'
+ config_files = pd.read_sql_query(query, session.connection())
+ if len(config_files) > 0:
+ # TODO: improve error handling, think what to do with other cases
+ return "OK"
+ else:
+ return "No records found in the TradeFill table with non-null config_file_path"
+ except Exception as e:
+ return f"Error: {str(e)}"
+
+ @property
+ def config_files(self):
+ return self.get_config_files()
+
+ @property
+ def configs(self):
+ return {config_file: self.get_exchanges_trading_pairs_by_config_file(config_file) for config_file in self.config_files}
+
def get_config_files(self):
with self.session_maker() as session:
query = 'SELECT DISTINCT config_file_path FROM TradeFill'
diff --git a/utils/graphs.py b/utils/graphs.py
index 12678fc..abd610c 100644
--- a/utils/graphs.py
+++ b/utils/graphs.py
@@ -16,6 +16,8 @@ class CandlesGraph:
specs = [[{"secondary_y": True}]] * rows
self.base_figure = make_subplots(rows=rows, cols=1, shared_xaxes=True, vertical_spacing=0.005,
row_heights=heights, specs=specs)
+ self.min_time = candles_df.reset_index().timestamp.min()
+ self.max_time = candles_df.reset_index().timestamp.max()
self.add_candles_graph()
if self.show_volume:
self.add_volume()
@@ -231,7 +233,9 @@ class CandlesGraph:
x=1
),
height=1500,
- xaxis_rangeslider_visible=False,
+ xaxis=dict(rangeslider_visible=False,
+ range=[self.min_time, self.max_time]),
+ yaxis=dict(range=[self.candles_df.low.min(), self.candles_df.high.max()]),
hovermode='x unified'
)
self.base_figure.update_yaxes(title_text="Price", row=1, col=1)
diff --git a/utils/st_utils.py b/utils/st_utils.py
index 51800d1..36e545b 100644
--- a/utils/st_utils.py
+++ b/utils/st_utils.py
@@ -5,11 +5,12 @@ import inspect
import streamlit as st
-def initialize_st_page(title: str, icon: str, layout="wide"):
+def initialize_st_page(title: str, icon: str, layout="wide", initial_sidebar_state="collapsed"):
st.set_page_config(
page_title=title,
page_icon=icon,
layout=layout,
+ initial_sidebar_state=initial_sidebar_state
)
st.title(f"{icon} {title}")
caller_frame = inspect.currentframe().f_back