netwlens 1.3.2

Network topology visualization and analysis tool with comprehensive data validation

Netwlens - Network Topology Visualization

A Python package for network topology visualization and analysis with IP Fabric integration. Features comprehensive data validation, automatic root device selection, and intelligent topology discovery.

Smart Network Visualization

Installation

For Users

# Install with Poetry (recommended)
pip install poetry  # if you don't have Poetry installed
poetry add netwlens

# Or using pip
pip install netwlens

For Developers

# Clone the repository
git clone <repository-url>
cd netwlens

# Create and activate virtual environment
python -m venv .venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate

# Install with Poetry (recommended)
pip install poetry  # if you don't have Poetry installed
poetry install

# Or using pip
pip install -e .

Quick Start

from netwlens import DataCollector, DataVisualizer

# Collect site-specific network data
collector = DataCollector()
data_dir = collector.collect_site_data(
    site="London-3X",
    protocol="cdp",
    output="mynetwork"
)

# Or collect all inventory data (NEW!)
data_dir = collector.collect_data(
    site_name=None,  # None = all inventory
    protocol="cdp",
    output="all-network"
)

# Create visualization with automatic root selection (NEW!)
visualizer = DataVisualizer()
viz_path = visualizer.create_topology(
    input_dir=data_dir,
    # Automatically selects device with most connections
    format_type="svg"
)

CLI Usage

# Collect site-specific data
netwlens collect --site London-3X --protocol cdp --output mynetwork

# Collect all inventory data (NEW!)
netwlens collect --protocol cdp --output all-data

# Create visualization with auto root selection (NEW!)
netwlens visualize --input netwlens_data/mynetwork

# Create visualization with manual root selection
netwlens visualize --input netwlens_data/mynetwork --root core-switch

Output Structure

netwlens_data/
├── mynetwork/                      # Data collection output
│   ├── inventory.json              # Device inventory
│   ├── connections_raw.json        # Raw connections from IP Fabric
│   ├── connections_normalized.json # Processed connections (enriched + deduplicated)
│   └── topology/                   # Visualization output
│       ├── topology_hierarchical.svg
│       ├── topology_hierarchical.png
│       └── view_svg_topology.html

Key Features

🔄 Flexible Data Collection

• Site-Specific Collection: Extract data for specific network sites
• All Inventory Collection: Collect data from entire network infrastructure
• Protocol Support: CDP, LLDP, and CEF protocols
• Comprehensive Data Validation: Multi-layer validation ensures data quality (NEW!)
• Backward Compatibility: Existing APIs preserved while adding new capabilities

🎯 Smart Visualization

• Automatic Root Selection: Intelligently selects device with most connections as topology root
• Data Quality Assurance: Automatic validation before visualization with detailed error reporting (NEW!)
• Connectivity Analysis: Device relationship validation and protocol consistency checks (NEW!)
• Manual Root Override: Specify custom root device when needed
• Clean Orthogonal Layouts: Professional diagrams with 90-degree connections
• Multiple Output Formats: SVG, PNG, and interactive HTML viewers
• Smart Logging: Connection analysis, validation summary, and root selection rationale

🛡️ Data Validation (NEW!)

• Multi-Layer Validation: File existence → JSON structure → Data quality → Visualization readiness
• Quality Metrics: Connected vs isolated devices, missing device detection, protocol consistency
• Early Error Detection: Comprehensive validation before expensive graph operations
• Actionable Feedback: Clear error messages explaining exactly what needs to be fixed
• Smart Warnings: Non-blocking issues like isolated devices are flagged appropriately

🏗️ Developer-Friendly

• Simple API: Clean DataCollector and DataVisualizer classes
• Robust Validation: Dedicated DataValidator class with comprehensive checks
• CLI Interface: Modern subcommand-based command line tools with built-in validation
• Package Installation: Standard pip install workflow
• Comprehensive Documentation: Detailed API docs and examples

Requirements

• Python 3.11+
• IP Fabric access (for data collection)
• Graphviz (for visualization)
• Poetry (recommended) or pip

Configuration

Set your IP Fabric credentials in environment variables or .env file:

IPF_URL=https://your-ipfabric-instance.com
IPF_TOKEN=your-api-token

For detailed documentation, see the docs/ directory or visit the project repository.