add rounding to nearest 5m n dash
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163
dash_power_room_n_customer.py
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163
dash_power_room_n_customer.py
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@@ -0,0 +1,163 @@
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import dash
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from dash import dcc, html, Input, Output
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import plotly.express as px
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import pandas as pd
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import sqlite3
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from datetime import datetime, timedelta
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# Initialize the Dash app
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app = dash.Dash(__name__)
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# Connect to the SQLite database
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def get_db_connection():
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conn = sqlite3.connect('power_data.db')
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return conn
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# Function to fetch data from the database
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def fetch_data(time_range):
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conn = get_db_connection()
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query = f"""
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SELECT * FROM building_totals
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WHERE timestamp >= datetime('now', '-{time_range} hours')
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"""
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df = pd.read_sql_query(query, conn)
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conn.close()
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return df
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# Function to calculate kWh and round timestamps for building totals
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def calculate_building_kwh(df):
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df['timestamp'] = pd.to_datetime(df['timestamp'])
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df['timestamp'] = df['timestamp'].dt.round('5min') # Round to 5-minute intervals
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df = df.set_index('timestamp')
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df['kWh'] = df['total_power'] * (5 / 60) # Convert power to kWh for 5-minute intervals
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return df
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# Function to calculate kWh and round timestamps for room and customer breakdowns
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def calculate_breakdown_kwh(df):
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df['timestamp'] = pd.to_datetime(df['timestamp'])
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df['timestamp'] = df['timestamp'].dt.round('5min') # Round to 5-minute intervals
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df = df.set_index('timestamp')
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df['kWh'] = df['power'] * (5 / 60) # Convert power to kWh for 5-minute intervals
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return df
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# Define the layout of the dashboard
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app.layout = html.Div([
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html.H1("Power Usage Overview", style={'textAlign': 'center'}),
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dcc.Dropdown(
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id='time-range',
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options=[
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{'label': '6 Hours', 'value': '6'},
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{'label': '12 Hours', 'value': '12'},
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{'label': '24 Hours', 'value': '24'},
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{'label': '1 Week', 'value': '168'},
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{'label': '2 Weeks', 'value': '336'},
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{'label': '1 Month', 'value': '720'},
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{'label': '2 Months', 'value': '1440'},
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{'label': '1 Year', 'value': '8760'},
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],
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value='6',
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style={'width': '200px', 'margin': '0 auto'}
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),
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dcc.Graph(id='building-graph', style={'width': '100%', 'height': '400px'}),
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dcc.Tabs(id='tabs', value='room-breakdown', children=[
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dcc.Tab(label='Room Breakdown', value='room-breakdown'),
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dcc.Tab(label='Customer Breakdown', value='customer-breakdown'),
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]),
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html.Div([
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dcc.Dropdown(id='drill-down', multi=False, style={'width': '200px', 'margin': '0 auto'}),
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dcc.Graph(id='breakdown-graph', style={'width': '100%', 'height': '400px'}),
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])
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])
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# Callback to update the building total graph
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@app.callback(
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Output('building-graph', 'figure'),
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[Input('time-range', 'value')]
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)
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def update_building_graph(time_range):
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df = fetch_data(time_range)
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df = calculate_building_kwh(df)
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fig = px.line(df, x=df.index, y=['total_current', 'total_power', 'kWh'],
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labels={'value': 'Value', 'variable': 'Metric'},
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title='Building Total Metrics')
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fig.update_layout(legend_title_text='Metrics')
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# Update legend to show recent values
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for trace in fig.data:
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if trace.name == 'kWh':
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trace.name = f"{trace.name}: {df['kWh'].sum():.2f}"
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else:
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trace.name = f"{trace.name}: {df[trace.name].iloc[-1]:.2f}"
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return fig
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# Callback to update the drill-down dropdown
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@app.callback(
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Output('drill-down', 'options'),
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[Input('tabs', 'value')]
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)
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def update_drill_down_options(tab):
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conn = get_db_connection()
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if tab == 'room-breakdown':
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query = "SELECT DISTINCT room_number FROM room_breakdown"
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else:
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query = "SELECT DISTINCT customer_name FROM customer_breakdown"
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df = pd.read_sql_query(query, conn)
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conn.close()
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return [{'label': i, 'value': i} for i in df.iloc[:, 0]]
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# Callback to set the default value for the drill-down dropdown
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@app.callback(
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Output('drill-down', 'value'),
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[Input('drill-down', 'options')]
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)
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def set_drill_down_value(options):
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if options:
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return options[0]['value']
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return None
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# Callback to update the breakdown graph
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@app.callback(
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Output('breakdown-graph', 'figure'),
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[Input('tabs', 'value'),
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Input('drill-down', 'value'),
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Input('time-range', 'value')]
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)
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def update_breakdown_graph(tab, drill_down, time_range):
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conn = get_db_connection()
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if tab == 'room-breakdown':
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query = f"""
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SELECT * FROM room_breakdown
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WHERE room_number = '{drill_down}'
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AND timestamp >= datetime('now', '-{time_range} hours')
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"""
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else:
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query = f"""
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SELECT * FROM customer_breakdown
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WHERE customer_name = '{drill_down}'
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AND timestamp >= datetime('now', '-{time_range} hours')
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"""
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df = pd.read_sql_query(query, conn)
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conn.close()
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df = calculate_breakdown_kwh(df)
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fig = px.line(df, x=df.index, y=['current', 'power', 'kWh'],
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labels={'value': 'Value', 'variable': 'Metric'},
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title=f'{tab.replace("-", " ").title()} Metrics')
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fig.update_layout(legend_title_text='Metrics')
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# Update legend to show recent values
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for trace in fig.data:
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if trace.name == 'kWh':
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trace.name = f"{trace.name}: {df['kWh'].sum():.2f}"
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else:
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trace.name = f"{trace.name}: {df[trace.name].iloc[-1]:.2f}"
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return fig
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# Run the app
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if __name__ == '__main__':
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app.run(host='0.0.0.0', port=8050, debug=True)
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@@ -3,7 +3,7 @@ import requests
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from collections import defaultdict
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import argparse
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import sqlite3
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from datetime import datetime
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from datetime import datetime, timedelta
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import time
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# Configuration
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@@ -55,14 +55,31 @@ def create_tables(conn):
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except sqlite3.Error as e:
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print(e)
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def round_to_nearest_5_minutes(dt):
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"""Round a datetime object to the nearest 5-minute interval."""
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# Calculate the number of seconds since the last 5-minute interval
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seconds_since_last_interval = dt.minute % 5 * 60 + dt.second + dt.microsecond / 1e6
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# Round to the nearest 5-minute interval
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if seconds_since_last_interval < 150: # 150 seconds = 2.5 minutes
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rounded_dt = dt - timedelta(seconds=seconds_since_last_interval)
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else:
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rounded_dt = dt + timedelta(seconds=300 - seconds_since_last_interval) # 300 seconds = 5 minutes
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# Set seconds and microseconds to zero
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rounded_dt = rounded_dt.replace(second=0, microsecond=0)
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return rounded_dt
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def insert_building_total(conn, total_current, total_power):
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"""Insert building total data into the database."""
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try:
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cursor = conn.cursor()
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rounded_timestamp = round_to_nearest_5_minutes(datetime.now())
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cursor.execute('''
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INSERT INTO building_totals (total_current, total_power, timestamp)
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VALUES (?, ?, ?)
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''', (round(total_current, 3), round(total_power, 3), datetime.now().isoformat()))
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''', (round(total_current, 3), round(total_power, 3), rounded_timestamp.isoformat()))
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conn.commit()
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except sqlite3.Error as e:
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print(e)
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@@ -71,10 +88,11 @@ def insert_room_breakdown(conn, room_number, current, power):
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"""Insert room breakdown data into the database."""
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try:
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cursor = conn.cursor()
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rounded_timestamp = round_to_nearest_5_minutes(datetime.now())
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cursor.execute('''
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INSERT INTO room_breakdown (room_number, current, power, timestamp)
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VALUES (?, ?, ?, ?)
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''', (room_number, round(current, 3), round(power, 3), datetime.now().isoformat()))
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''', (room_number, round(current, 3), round(power, 3), rounded_timestamp.isoformat()))
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conn.commit()
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except sqlite3.Error as e:
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print(e)
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@@ -83,14 +101,16 @@ def insert_customer_breakdown(conn, customer_name, current, power):
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"""Insert customer breakdown data into the database."""
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try:
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cursor = conn.cursor()
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rounded_timestamp = round_to_nearest_5_minutes(datetime.now())
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cursor.execute('''
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INSERT INTO customer_breakdown (customer_name, current, power, timestamp)
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VALUES (?, ?, ?, ?)
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''', (customer_name, round(current, 3), round(power, 3), datetime.now().isoformat()))
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''', (customer_name, round(current, 3), round(power, 3), rounded_timestamp.isoformat()))
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conn.commit()
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except sqlite3.Error as e:
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print(e)
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def get_device_ids(debug=False):
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"""Fetch all device IDs from the LibreNMS API."""
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response = requests.get(f'http://{LIBRENMS_IP}/api/v0/devices', headers=HEADERS, verify=False)
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@@ -286,5 +306,5 @@ if __name__ == '__main__':
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main(debug=args.debug, update_db=not args.no_db_update, concurrency_level=args.concurrency_level)
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runs += 1
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if args.runs is None:
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time.sleep(240) # Wait for 5 minutes before the next run
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time.sleep(250) # Wait for 5 minutes before the next run
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