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# LibreNMS-power-dash # Power Monitoring System
Python code to extract and visualise power data collected from nLogic and APC pdu's via LibreNMS API ## Overview
# Power and Current Data Dashboard The Power Monitoring System is designed to collect, store, and visualize power usage data from various devices, primarily PDUs (Power Distribution Units). The system consists of two main components: a data collection script and a dashboard for visualizing the collected data.
This project consists of two main scripts: one for collecting power and current data from a LibreNMS server and storing it in a SQLite database, and another for visualizing this data using a Plotly Dash dashboard.
## Table of Contents
- [Prerequisites](#prerequisites)
- [Installation](#installation)
- [Data Collection Script](#data-collection-script)
- [Dashboard Script](#dashboard-script)
- [Running the Dashboard](#running-the-dashboard)
- [Accessing the Dashboard](#accessing-the-dashboard)
## Prerequisites
Before you begin, ensure you have the following installed:
- Python 3.11 or later
- SQLite
- LibreNMS server with API access
## Installation
Install the required dependencies using pip:
dash
plotly
pandas
sqlite3
You can install these dependencies by running the following command:
pip install dash plotly pandas
## Data Collection Script ## Data Collection Script
The data collection script fetches power and current data from a LibreNMS server and stores it in a SQLite database. ### Purpose
### Configuration The data collection script is responsible for fetching power usage data from devices via an API, processing this data, and storing it in a SQLite database. The script is designed to run at regular intervals to ensure up-to-date data collection.
1. API Configuration:
- Set the API_KEY and LIBRENMS_IP variables in the script to match your LibreNMS server details.
2. Running the Script:
- Run the script using the command: python get_all_by_room.py
### Features ### Features
- Fetches device IDs and their locations from the LibreNMS server. - **Concurrent API Requests**: The script uses concurrent requests to efficiently gather data from multiple devices simultaneously, reducing the overall execution time.
- Collects sensor data for current and power. - **Data Rounding**: Timestamps for the collected data are rounded to the nearest 5-minute interval to ensure consistency and alignment with the dashboard's requirements.
- Stores the collected data in a SQLite database (power_data.db). - **Configurable Concurrency**: The concurrency level can be adjusted to balance between speed and system load, ensuring optimal performance without overloading the API server.
- **Database Storage**: Collected data is stored in a SQLite database, with separate tables for building totals, room breakdowns, and customer breakdowns.
## Dashboard Script ### Usage
The dashboard script visualizes the data stored in the SQLite database using Plotly Dash. 1. **Configuration**: Ensure that the API key, LibreNMS IP, and other necessary configurations are set in the script.
2. **Running the Script**: Execute the script with the desired options, such as enabling debug output, limiting the number of runs, disabling database updates, and setting the concurrency level.
3. **Scheduling**: Schedule the script to run at regular intervals (e.g., every 5 minutes) using a task scheduler like `cron` or the Task Scheduler.
### Configuration ### Command Line Options
1. Database Configuration: - `--debug`: Enable debug output for troubleshooting.
- Ensure the SQLite database (power_data.db) is in the same directory as the script or provide the correct path. - `--runs`: Limit the number of runs for testing purposes.
- `--no-db-update`: Disable updates to the database to run the script in a read-only mode.
- `--concurrency-level`: Set the concurrency level for API requests to optimize performance.
2. Running the Dashboard: ## Dashboard
- Run the script using the command: python dash-power.py
### Purpose
The dashboard provides a visual representation of the power usage data collected by the script. It allows users to monitor power consumption, identify trends, and make informed decisions based on the data.
### Features ### Features
- Displays graphs for building totals and individual rooms. - **Data Visualization**: The dashboard displays power usage data in an easy-to-understand format, with charts and graphs for building totals, room breakdowns, and customer breakdowns.
- Allows selection of different time ranges (e.g., last 6 hours, last 1 day, etc.). - **Regular Updates**: The dashboard is updated at regular intervals to reflect the latest data collected by the script.
- Dynamically updates the legend values based on the zoom level. - **User-Friendly Interface**: The dashboard is designed to be intuitive and user-friendly, allowing users to quickly access the information they need.
- Accessible on external IP addresses.
## Running the Dashboard ### Usage
1. Start the Dashboard: 1. **Accessing the Dashboard**: Open the dashboard in a web browser to view the power usage data.
- Run the script using the command: python dash-power.py 2. **Interpreting the Data**: Use the charts and graphs to monitor power consumption and identify any trends or anomalies.
3. **Customization**: Customize the dashboard as needed to display the most relevant information for your use case.
2. Access the Dashboard: ## System Requirements
- Open a web browser and navigate to http://127.0.0.1:8050/ to view the dashboard locally.
- To access the dashboard on an external IP, ensure your network settings allow external connections and navigate to http://<your-external-ip>:8050/.
## Accessing the Dashboard - **Python**: The data collection script is written in Python and requires a Python environment to run.
- **SQLite**: The script uses SQLite for data storage, so SQLite must be installed and accessible.
- **LibreNMS API**: The script interacts with the LibreNMS API to fetch power usage data, so access to this API is required.
- Local Access: http://127.0.0.1:8050/ ## Conclusion
- External Access: http://<your-external-ip>:8050/
Ensure that your firewall and router settings allow incoming connections on port 8050. The Power Monitoring System provides a comprehensive solution for collecting and visualizing power usage data. By using the data collection script and dashboard together, users can efficiently monitor power consumption and make data-driven decisions.