migrating

.gitignore

@@ -1,5 +1,4 @@
 # Freqtrade rules
-config*.json
 *.sqlite
 *.sqlite-shm
 *.sqlite-wal
@@ -9,8 +8,9 @@ user_data/*
 !user_data/notebooks
 !user_data/models
 !user_data/freqaimodels
+!user_data/dashboards
+!user_data/strategies
 user_data/models/*
-user_data/notebooks/*
 freqtrade-plot.html
 freqtrade-profit-plot.html
 freqtrade/rpc/api_server/ui/*

user_data/dashboards/FeatureImportanceDash.py

@@ -0,0 +1,30 @@
+import streamlit as st
+import sqlite3
+import pandas as pd
+import seaborn as sns
+import matplotlib.pyplot as plt
+
+# Connect to the SQLite database
+conn = sqlite3.connect("litmus.sqlite")
+# Query the data
+data = pd.read_sql_query("SELECT * FROM feature_importance_history", conn)
+# Disconnect from the database
+conn.close()
+
+
+# Print
+st.dataframe(data)
+
+# Boxplot
+data = data[data["pair"] == "SOL/USDT:USDT"]
+ranks = data.groupby("feature_id")["importance"].mean().sort_values()[::-1].index
+
+sns.set_theme(style="ticks")
+
+fig, ax = plt.subplots(figsize=(7, 200))
+sns.boxplot(x="importance", y="feature_id", data=data,
+            whis=[0, 100], width=.6, palette="vlag", order=ranks)
+ax.xaxis.grid(True)
+ax.set(ylabel="")
+sns.despine(trim=True, left=True)
+st.pyplot(fig)

user_data/dashboards/demo.py

@@ -0,0 +1,36 @@
+import streamlit as st
+import numpy as np
+import pandas as pd
+
+st.write("# Litmus Dashboard")
+st.write("Here's our first attempt at using data to create a table:")
+st.write(pd.DataFrame({
+    'first column': [1, 2, 3, 4],
+    'second column': [10, 20, 30, 40]
+}))
+
+st.write("### Line chart")
+chart_data = pd.DataFrame(
+     np.random.randn(20, 3),
+     columns=['a', 'b', 'c'])
+st.line_chart(chart_data)
+
+st.write("### Map demo")
+map_data = pd.DataFrame(
+    np.random.randn(1000, 2) / [50, 50] + [37.76, -122.4],
+    columns=['lat', 'lon'])
+st.map(map_data)
+
+st.write("### Slider")
+x = st.slider('x')  # 👈 this is a widget
+st.write(x, 'squared is', x * x)
+
+st.text_input("Your name", key="name")
+st.session_state.name
+
+if st.checkbox('Show dataframe'):
+    chart_data = pd.DataFrame(
+       np.random.randn(20, 3),
+       columns=['a', 'b', 'c'])
+
+    chart_data