tested running for a month

get_latest_from_db.txt

@@ -0,0 +1,12 @@
+# Retrieve the last value for building_total
+sqlite3 power_data.db "SELECT * FROM building_totals ORDER BY timestamp DESC LIMIT 1;"
+
+# Retrieve the last value for each individual record in room_breakdown
+sqlite3 power_data.db "
+SELECT r1.*
+FROM room_breakdown r1
+INNER JOIN (
+    SELECT room_number, MAX(timestamp) AS max_timestamp
+    FROM room_breakdown
+    GROUP BY room_number
+) r2 ON r1.room_number = r2.room_number AND r1.timestamp = r2.max_timestamp;"

not-tested/dash_power_room_n_customer.py

@@ -0,0 +1,205 @@
+import dash
+from dash import dcc, html, Input, Output, callback_context
+import plotly.express as px
+import pandas as pd
+import sqlite3
+from datetime import datetime, timedelta
+
+# Initialize the Dash app
+app = dash.Dash(__name__)
+
+# Connect to the SQLite database
+def get_db_connection():
+    conn = sqlite3.connect('power_data.db')
+    return conn
+
+# Function to fetch data from the database
+def fetch_data(time_range):
+    conn = get_db_connection()
+    query = f"""
+    SELECT * FROM building_totals
+    WHERE timestamp >= datetime('now', '-{time_range} hours')
+    """
+    df = pd.read_sql_query(query, conn)
+    conn.close()
+    return df
+
+# Function to calculate kWh and round timestamps for building totals
+def calculate_building_kwh(df):
+    df['timestamp'] = pd.to_datetime(df['timestamp'])
+    df['timestamp'] = df['timestamp'].dt.round('5min')  # Round to 5-minute intervals
+    df = df.set_index('timestamp')
+    df['kWh'] = df['total_power'] * (5 / 60)  # Convert power to kWh for 5-minute intervals
+    return df
+
+# Function to calculate kWh and round timestamps for room and customer breakdowns
+def calculate_breakdown_kwh(df):
+    df['timestamp'] = pd.to_datetime(df['timestamp'])
+    df['timestamp'] = df['timestamp'].dt.round('5min')  # Round to 5-minute intervals
+    df = df.set_index('timestamp')
+    df['kWh'] = df['power'] * (5 / 60)  # Convert power to kWh for 5-minute intervals
+    return df
+
+# Define the layout of the dashboard
+app.layout = html.Div([
+    html.H1("Power Usage Overview", style={'textAlign': 'center'}),
+
+    dcc.Dropdown(
+        id='time-range',
+        options=[
+            {'label': '6 Hours', 'value': '6'},
+            {'label': '12 Hours', 'value': '12'},
+            {'label': '24 Hours', 'value': '24'},
+            {'label': '1 Week', 'value': '168'},
+            {'label': '2 Weeks', 'value': '336'},
+            {'label': '1 Month', 'value': '720'},
+            {'label': '2 Months', 'value': '1440'},
+            {'label': '1 Year', 'value': '8760'},
+        ],
+        value='6',
+        style={'width': '200px', 'margin': '0 auto'}
+    ),
+
+    dcc.Graph(id='building-graph', style={'width': '100%', 'height': '400px'}),
+
+    dcc.Tabs(id='tabs', value='room-breakdown', children=[
+        dcc.Tab(label='Room Breakdown', value='room-breakdown'),
+        dcc.Tab(label='Customer Breakdown', value='customer-breakdown'),
+    ]),
+
+    html.Div([
+        dcc.Dropdown(id='drill-down', multi=False, style={'width': '200px', 'margin': '0 auto'}),
+        dcc.Graph(id='breakdown-graph', style={'width': '100%', 'height': '400px'}),
+    ])
+])
+
+# Combined callback to update the building total graph and handle zoom events
+@app.callback(
+    Output('building-graph', 'figure'),
+    [Input('time-range', 'value'),
+     Input('building-graph', 'relayoutData')],
+    [dash.dependencies.State('building-graph', 'figure')]
+)
+def update_building_graph(time_range, relayoutData, figure):
+    ctx = callback_context
+
+    if not ctx.triggered:
+        return dash.no_update
+
+    df = fetch_data(time_range)
+    df = calculate_building_kwh(df)
+
+    # Initialize fig
+    fig = px.line(df, x=df.index, y=['total_current', 'total_power', 'kWh'],
+                  labels={'value': 'Value', 'variable': 'Metric'},
+                  title='Building Total Metrics')
+    fig.update_layout(legend_title_text='Metrics', yaxis_type="log")  # Use logarithmic scale
+
+    if 'time-range' in ctx.triggered[0]['prop_id']:
+        pass  # fig is already initialized
+
+    elif relayoutData and 'xaxis.range[0]' in relayoutData and 'xaxis.range[1]' in relayoutData:
+        start = pd.to_datetime(relayoutData['xaxis.range[0]'])
+        end = pd.to_datetime(relayoutData['xaxis.range[1]'])
+        df = df.loc[start:end]
+        fig = px.line(df, x=df.index, y=['total_current', 'total_power', 'kWh'],
+                      labels={'value': 'Value', 'variable': 'Metric'},
+                      title='Building Total Metrics')
+        fig.update_layout(legend_title_text='Metrics', yaxis_type="log")  # Use logarithmic scale
+
+    # Update legend to show total values
+    for trace in fig.data:
+        if trace.name == 'kWh':
+            trace.name = f"{trace.name}: {df['kWh'].sum():.2f}"
+        else:
+            trace.name = f"{trace.name}: {df[trace.name].iloc[-1]:.2f}"
+
+    return fig
+
+# Callback to update the drill-down dropdown
+@app.callback(
+    Output('drill-down', 'options'),
+    [Input('tabs', 'value')]
+)
+def update_drill_down_options(tab):
+    conn = get_db_connection()
+    if tab == 'room-breakdown':
+        query = "SELECT DISTINCT room_number FROM room_breakdown"
+    else:
+        query = "SELECT DISTINCT customer_name FROM customer_breakdown"
+    df = pd.read_sql_query(query, conn)
+    conn.close()
+    return [{'label': i, 'value': i} for i in df.iloc[:, 0]]
+
+# Callback to set the default value for the drill-down dropdown
+@app.callback(
+    Output('drill-down', 'value'),
+    [Input('drill-down', 'options')]
+)
+def set_drill_down_value(options):
+    if options:
+        return options[0]['value']
+    return None
+
+# Callback to update the breakdown graph and handle zoom events
+@app.callback(
+    Output('breakdown-graph', 'figure'),
+    [Input('tabs', 'value'),
+     Input('drill-down', 'value'),
+     Input('time-range', 'value'),
+     Input('breakdown-graph', 'relayoutData')],
+    [dash.dependencies.State('breakdown-graph', 'figure')]
+)
+def update_breakdown_graph(tab, drill_down, time_range, relayoutData, figure):
+    ctx = callback_context
+
+    if not ctx.triggered:
+        return dash.no_update
+
+    conn = get_db_connection()
+    if tab == 'room-breakdown':
+        query = f"""
+        SELECT * FROM room_breakdown
+        WHERE room_number = '{drill_down}'
+        AND timestamp >= datetime('now', '-{time_range} hours')
+        """
+    else:
+        query = f"""
+        SELECT * FROM customer_breakdown
+        WHERE customer_name = '{drill_down}'
+        AND timestamp >= datetime('now', '-{time_range} hours')
+        """
+    df = pd.read_sql_query(query, conn)
+    conn.close()
+    df = calculate_breakdown_kwh(df)
+
+    # Initialize fig
+    fig = px.line(df, x=df.index, y=['current', 'power', 'kWh'],
+                  labels={'value': 'Value', 'variable': 'Metric'},
+                  title=f'{tab.replace("-", " ").title()} Metrics')
+    fig.update_layout(legend_title_text='Metrics', yaxis_type="log")  # Use logarithmic scale
+
+    if 'time-range' in ctx.triggered[0]['prop_id'] or 'drill-down' in ctx.triggered[0]['prop_id']:
+        pass  # fig is already initialized
+
+    elif relayoutData and 'xaxis.range[0]' in relayoutData and 'xaxis.range[1]' in relayoutData:
+        start = pd.to_datetime(relayoutData['xaxis.range[0]'])
+        end = pd.to_datetime(relayoutData['xaxis.range[1]'])
+        df = df.loc[start:end]
+        fig = px.line(df, x=df.index, y=['current', 'power', 'kWh'],
+                      labels={'value': 'Value', 'variable': 'Metric'},
+                      title=f'{tab.replace("-", " ").title()} Metrics')
+        fig.update_layout(legend_title_text='Metrics', yaxis_type="log")  # Use logarithmic scale
+
+    # Update legend to show total values
+    for trace in fig.data:
+        if trace.name == 'kWh':
+            trace.name = f"{trace.name}: {df['kWh'].sum():.2f}"
+        else:
+            trace.name = f"{trace.name}: {df[trace.name].iloc[-1]:.2f}"
+
+    return fig
+
+# Run the app
+if __name__ == '__main__':
+    app.run(host='0.0.0.0', port=8050, debug=True)