tested running for a month

not-tested/dash-power_room.py

@@ -0,0 +1,146 @@
+import dash
+from dash import dcc, html, Input, Output, State
+import plotly.express as px
+import sqlite3
+import pandas as pd
+from datetime import datetime, timedelta
+
+# Create a Dash app
+app = dash.Dash(__name__)
+
+# Function to fetch data from the SQLite database
+def fetch_data():
+    conn = sqlite3.connect('power_data.db')
+    building_totals = pd.read_sql_query('SELECT * FROM building_totals', conn)
+    room_breakdown = pd.read_sql_query('SELECT * FROM room_breakdown', conn)
+    conn.close()
+    return building_totals, room_breakdown
+
+# Function to calculate kWh usage
+def calculate_kwh(data, power_column):
+    data = data.copy()  # Create a copy of the DataFrame to avoid SettingWithCopyWarning
+    data.loc[:, 'timestamp'] = pd.to_datetime(data['timestamp'], format='ISO8601')
+    data = data.sort_values('timestamp')
+    data.loc[:, 'time_diff'] = data['timestamp'].diff().dt.total_seconds() / 3600  # Convert to hours
+    data.loc[:, 'kwh'] = data[power_column] * data['time_diff']
+    data.loc[:, 'cumulative_kwh'] = data['kwh'].cumsum()
+    return data
+
+# Define the layout of the dashboard
+app.layout = html.Div([
+    html.H1("Power and Current Data Dashboard"),
+    dcc.Dropdown(
+        id='time-range-selector',
+        options=[
+            {'label': 'Last 6 Hours', 'value': 6},
+            {'label': 'Last 12 Hours', 'value': 12},
+            {'label': 'Last 1 Day', 'value': 24},
+            {'label': 'Last 2 Days', 'value': 48},
+            {'label': 'Last 1 Week', 'value': 168},
+            {'label': 'Last 1 Month', 'value': 720},
+            {'label': 'Last 2 Months', 'value': 1440},
+            {'label': 'Last 1 Year', 'value': 8760}
+        ],
+        value=6,
+        clearable=False
+    ),
+    dcc.Graph(id='building-totals-graph'),
+    dcc.Dropdown(
+        id='room-selector',
+        options=[{'label': room, 'value': room} for room in fetch_data()[1]['room_number'].unique()],
+        value=fetch_data()[1]['room_number'].iloc[0] if not fetch_data()[1].empty else None,
+        placeholder="Select a room"
+    ),
+    dcc.Graph(id='room-graph')
+])
+
+# Define callbacks to update the graphs
+@app.callback(
+    Output('building-totals-graph', 'figure'),
+    Input('time-range-selector', 'value'),
+    Input('building-totals-graph', 'relayoutData')
+)
+def update_building_totals_graph(time_range, relayoutData):
+    building_totals, _ = fetch_data()
+    building_totals = calculate_kwh(building_totals, 'total_power')
+
+    # Handle time range selection
+    end_time = datetime.now()
+    start_time = end_time - timedelta(hours=time_range)
+    filtered_data = building_totals[(building_totals['timestamp'] >= start_time) & (building_totals['timestamp'] <= end_time)]
+
+    # Handle zoom level
+    if relayoutData and 'xaxis.range[0]' in relayoutData:
+        zoom_start = pd.to_datetime(relayoutData['xaxis.range[0]'])
+        zoom_end = pd.to_datetime(relayoutData['xaxis.range[1]'])
+        filtered_data = filtered_data[(filtered_data['timestamp'] >= zoom_start) & (filtered_data['timestamp'] <= zoom_end)]
+
+    latest_data = filtered_data.iloc[-1] if not filtered_data.empty else None
+
+    fig = px.line(filtered_data, x='timestamp', y=['total_current', 'total_power', 'cumulative_kwh'],
+                  title='Building Totals', labels={'value': 'Value', 'variable': 'Metric'})
+
+    if latest_data is not None:
+        fig.update_traces(
+            name=f"Total Current: {latest_data['total_current']} A",
+            selector=dict(name="total_current")
+        )
+        fig.update_traces(
+            name=f"Total Power: {latest_data['total_power']} kW",
+            selector=dict(name="total_power")
+        )
+        fig.update_traces(
+            name=f"Cumulative kWh: {round(latest_data['cumulative_kwh'], 3)} kWh",
+            selector=dict(name="cumulative_kwh")
+        )
+
+    return fig
+
+@app.callback(
+    Output('room-graph', 'figure'),
+    Input('time-range-selector', 'value'),
+    Input('room-selector', 'value'),
+    Input('room-graph', 'relayoutData')
+)
+def update_room_graph(time_range, selected_room, relayoutData):
+    if selected_room:
+        _, room_breakdown = fetch_data()
+        room_data = room_breakdown[room_breakdown['room_number'] == selected_room]
+        room_data = calculate_kwh(room_data, 'power')
+
+        # Handle time range selection
+        end_time = datetime.now()
+        start_time = end_time - timedelta(hours=time_range)
+        filtered_data = room_data[(room_data['timestamp'] >= start_time) & (room_data['timestamp'] <= end_time)]
+
+        # Handle zoom level
+        if relayoutData and 'xaxis.range[0]' in relayoutData:
+            zoom_start = pd.to_datetime(relayoutData['xaxis.range[0]'])
+            zoom_end = pd.to_datetime(relayoutData['xaxis.range[1]'])
+            filtered_data = filtered_data[(filtered_data['timestamp'] >= zoom_start) & (filtered_data['timestamp'] <= zoom_end)]
+
+        latest_data = filtered_data.iloc[-1] if not filtered_data.empty else None
+
+        fig = px.line(filtered_data, x='timestamp', y=['current', 'power', 'cumulative_kwh'],
+                      title=f'Room {selected_room}', labels={'value': 'Value', 'variable': 'Metric'})
+
+        if latest_data is not None:
+            fig.update_traces(
+                name=f"Current: {latest_data['current']} A",
+                selector=dict(name="current")
+            )
+            fig.update_traces(
+                name=f"Power: {latest_data['power']} kW",
+                selector=dict(name="power")
+            )
+            fig.update_traces(
+                name=f"Cumulative kWh: {round(latest_data['cumulative_kwh'], 3)} kWh",
+                selector=dict(name="cumulative_kwh")
+            )
+
+        return fig
+    return px.line(title='Select a room to display its graph')
+
+# Run the app
+if __name__ == '__main__':
+    app.run(host='0.0.0.0', port=8050, debug=True)