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README_netmap.md

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Network Infrastructure Mapping Tool (NetMap CLI)

NetMap CLI is a Python tool that generates network topology diagrams and graph data files from a simple CSV input. It's designed to quickly visualize device connectivity.

Features

  • CSV Input: Reads network links from a CSV file with 'SourceDevice' and 'TargetDevice' columns.
  • Graph Visualization: Generates a PNG image of the network map using matplotlib and networkx.
    • Supports multiple layout algorithms: spring (default), kamada_kawai, circular, random, shell, spectral.
  • Graph Data Export: Can export the network graph to:
    • GEXF format (for use in Gephi or other graph analysis tools).
    • GraphML format (another common format for graph tools).
  • Command-Line Interface: Easy-to-use CLI for specifying input and output options.

Prerequisites

  • Python 3.6+
  • Libraries: networkx, matplotlib, scipy (SciPy is a dependency for some networkx layout algorithms).

Installation

  1. Clone the repository or download the files. Ensure you have the netmap_tool directory (containing main.py, mapper.py, __init__.py) and the requirements.txt file.

  2. Create a virtual environment (recommended):

    python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

  3. Install dependencies: Navigate to the directory containing requirements.txt and run:

    pip install -r requirements.txt

Usage

The tool is run from the command line using python -m netmap_tool.main.

Command-Line Arguments

  • --input_csv INPUT_CSV: (Required) Path to the input CSV file.
    • The CSV file must contain 'SourceDevice' and 'TargetDevice' headers.
    • Each row defines a link between the two specified devices.
  • --output_png OUTPUT_PNG: (Optional) Path to save the output PNG image (e.g., mymap.png).
  • --layout {spring,kamada_kawai,circular,random,shell,spectral}: (Optional) Layout algorithm for the PNG map. Defaults to spring.
  • --output_gexf OUTPUT_GEXF: (Optional) Path to save the graph in GEXF format (e.g., mymap.gexf).
  • --output_graphml OUTPUT_GRAPHML: (Optional) Path to save the graph in GraphML format (e.g., mymap.graphml).
  • -h, --help: Show help message and exit.

Examples

  1. Generate a PNG map with the default spring layout:

    python -m netmap_tool.main --input_csv path/to/your/links.csv --output_png network_diagram.png

  2. Generate a PNG map with the Kamada-Kawai layout:

    python -m netmap_tool.main --input_csv links.csv --output_png map_kk.png --layout kamada_kawai

  3. Export the graph to GEXF format:

    python -m netmap_tool.main --input_csv links.csv --output_gexf my_network.gexf

  4. Generate a PNG and also export to GraphML:

    python -m netmap_tool.main --input_csv links.csv --output_png visual_map.png --output_graphml data_map.graphml

  5. Only build the graph and print info (no file output):

    python -m netmap_tool.main --input_csv links.csv

    (The tool will inform you that no output options were specified)

CSV File Format

Your input CSV file must have a header row with SourceDevice and TargetDevice.

Example links.csv:

SourceDevice,TargetDevice
RouterA,Switch1
RouterB,Switch1
RouterA,RouterB
Firewall,RouterA
Switch1,ServerX

File Structure

.
├── netmap_tool/
│   ├── __init__.py     # Makes 'netmap_tool' a Python package
│   ├── main.py         # CLI entry point
│   └── mapper.py       # Core logic for graph building, drawing, and exporting
├── requirements.txt      # Python dependencies
└── README_netmap.md      # This documentation file

Limitations

  • Simplicity: This tool is designed for simple, direct device-to-device connectivity visualization. It does not parse complex configurations or infer relationships beyond what's explicitly in the CSV.
  • Layouts: Graph layout can be challenging for large or complex networks. The default layouts are good for small to medium-sized graphs. For very large networks, using the GEXF/GraphML export with a dedicated tool like Gephi is recommended for better layout control and exploration.
  • No Device Details: The map does not include interface names, IP addresses, VLANs, or other detailed device information. It only shows device names and their connections.
  • Error Handling: Basic error handling for file operations and CSV parsing is included. More complex CSV issues might require manual data cleaning.

Future Enhancements (Potential)

  • Support for other input formats (e.g., JSON, YAML).
  • Ability to add attributes to nodes/edges via CSV (e.g., device type, link speed) and visualize them.
  • More sophisticated layout options or interactivity (would likely require different libraries e.g., web-based).
  • Basic parsing of simplified device configuration snippets (e.g., show cdp neighbor output).