network-latency-monitor 0.1.4

Monitor your network latency using real-time plots and cumulative plots

NLM: Network Latency Monitor

NLM is a tool designed to monitor network latency across specified IP addresses, providing real-time feedback through progress bars and latency graphs.

It also collects data, and plots graphs using seaborn to visualize latency data. Real-time charts are drawn in the terminal using asciichartpy.

Features include:

• Asynchronous Ping Monitoring: Efficiently pings multiple IP addresses simultaneously.
• Real-time ASCII-based Latency Graphs: Visualizes latency data directly in the terminal.
• OS-specific Directory Management: Manages logs, results, and plots in OS-specific directories.
• Comprehensive Documentation: Generated from code docstrings for accuracy and consistency.

Installation

You can install NLM (Network Latency Monitor) using pip from PyPI.

Installation via pip

pip install network-latency-monitor

Install from Source

To install NLM from source, follow these steps:

Prerequisites

• Python
• Poetry

1. Clone the Repository

git clone https://github.com/yourusername/network-latency-monitor.git
cd network-latency-monitor

2. Install Dependencies with Poetry

 poetry install

3. Activate the Virtual Environment

poetry shell

4. Verify Installation

poetry shell
poetry run nlm --help

4. Build the Documentation (Optional)

cd docs
make html

5. View the Documentation

   Open docs/build/html/index.html in your web browser

After installing NLM, you can start monitoring network latency.

Usage

Configuration

Before running NLM, configure your settings in the [config.yaml]{.title-ref} file.

Sample config.yaml:

"duration": 10800,  # in seconds
"ip_addresses": ["8.8.8.8"],
"ping_interval": 1,  # in seconds
"latency_threshold": 200.0,  # in ms
"no_aggregation": False,
"no_segmentation": False,
"file": None,  # Optional: Specify a ping result file to process
"clear": False,  # Set to True to clear all data
"clear_results": False,  # Set to True to clear results folder
"clear_plots": False,  # Set to True to clear plots folder
"clear_logs": False,  # Set to True to clear logs folder
"yes": False,  # Set to True to auto-confirm prompts

The config.yaml file is auto-generated the first time that the program is run. It is saved in default directories based on your operating system.

For Linux users: /home/username/.config/network_latency_monitor/config.yaml For Windows users: %APPDATA%\nlm\config.yaml For MacOS users: ~/Library/Application Support/nlm/config.yaml

Running the Program

Running from Source

If you have installed from source using [poetry]{.title-ref}, then you can run the program using [poetry run]{.title-ref}.

To run the program with all default parameters (as obtained from [config.yaml]{.title-ref}):

poetry run nlm

Running from Pip Installation

If you are running the program after installing it through pip, you can run it simply by:

nlm

This will run the program with default parameters as obtained from config.yaml.

To view all command-line options and a simple guide, run

nlm --help

Usage Examples

• Monitor two IP addresses for 1 hour with a 2-second interval between pings:

  nlm 8.8.8.8 1.1.1.1 --duration 3600 --ping-interval 2
  

• Process an existing ping results file and disable data aggregation:

  nlm --file results/ping_results_8.8.8.8.txt --no-aggregation
  

• Clear all data (results, plots, logs) without confirmation:

  nlm --clear --yes
  

• Monitor a single IP address with a custom latency threshold:

  nlm 8.8.4.4 --latency-threshold 150.0
  

• Regenerate the default config.yaml file:

  nlm --regen-config
  

• Disable segmentation of latency plots:

  nlm 8.8.8.8 --no-segmentation
  

• Monitor a single IP for 2 hours, with default settings:

  nlm 8.8.8.8 --duration 7200
  

• Clear only the plots folder:

  nlm --clear-plots
  

Contributing

Contributions are welcome! If you have suggestions for new features, bug fixes, or improvements, feel free to open an issue or submit a pull request.

How to Contribute

1. Fork the repository to your GitHub account.

2. Clone your fork locally:

   git clone https://github.com/yourusername/network-latency-monitor.git
   cd network-latency-monitor
   

3. Monitor a single IP for 2 hours, with default settings:

   git checkout -b feature-branch-name
   

4. Make your changes and ensure the code passes any pre-existing tests or linters.

5. Push your changes to your forked repository:

   git push origin feature-branch-name
   

6. Submit a pull request to the main branch.

License

This project is licensed under the MIT License. See the LICENSE file for more details.

Roadmap

The following features and improvements are planned for future releases of NLM (Network Latency Monitor):

1. Improve argparse Functionality:

   • Add Verbosity Levels: Introduce options to control output verbosity (e.g., -v for verbose mode, -q for quiet mode).
   • Enhanced Error Handling: Improve feedback and error reporting for invalid inputs or failed pings.
   
   

2. Add Support for Multiple Protocols: Extend support for protocols beyond ICMP (e.g., TCP, UDP) to enable more comprehensive network monitoring.

3. Data Export Options: Allow users to export monitoring data in multiple formats such as CSV, JSON, and XML for easier data processing and analysis.

4. Custom Results and Plots Directory: Add command-line options to specify custom directories for storing results and plots, making the tool more flexible for use in shell scripts and automated environments.

5. Improved Plotting Options (Future): Enhance plotting capabilities with customizable graph styles, better scaling, and export options to PNG and other formats.

Support

If you encounter any issues, feel free to open an issue on GitHub Issues.

Acknowledgments

• asciichartpy for the ASCII-based chart rendering.
• Poetry for Python packaging and dependency management.

Documentation

Full documentation for NLM (Network Latency Monitor) is available at Read the Docs.

The documentation includes:

• Installation Instructions: Step-by-step guide for installing the tool.
• Usage Examples: Detailed usage examples and advanced configurations.
• API Reference: Auto-generated API reference from code docstrings.

For detailed information, visit the NLM Documentation.