networktree-py#

A Python library for managing hierarchical networks with lifecycle management. Networktree combines tree structures and network relationships to create powerful and flexible data models.

Features#

🌳 Tree Structure

Hierarchical organization of objects
Parent-child relationships
Path-based navigation
Recursive operations

🕸️ Network Capabilities

Node-link relationships
Bidirectional connections
Network analysis
Graph operations

⚙️ Lifecycle Management

Controlled initialization
Clean resource management
State tracking
Event handling

🔍 Advanced Features

Matrix representations
Path finding algorithms
Clustering support
Flow analysis

Installation#

Install using pip:

pip install networktree

Or directly from source:

git clone https://framagit.org/your-username/networktree-py.git
cd networktree-py
pip install -e .

Quick Start#

Basic Usage#

from networktree import Object

# Create a simple hierarchical structure
class Component(Object):
    def onPreSetup(self):
        print(f"Setting up {self.name}")
        
    def onPreCleanup(self):
        print(f"Cleaning up {self.name}")

# Create objects with hierarchy
root = Component(name="root")
child1 = Component(name="child1", parent=root)
child2 = Component(name="child2", parent=root)

# Initialize the structure
root.setup()  # Will recursively setup all children

# Cleanup when done
root.cleanup()  # Will recursively cleanup all children

Network Relationships#

from networktree import Object

# Create network nodes with relationships
class Node(Object):
    def connect_to(self, target):
        self.create_link(target)
        
# Create and connect nodes
node1 = Node(name="node1")
node2 = Node(name="node2")
node3 = Node(name="node3")

node1.connect_to(node2)
node2.connect_to(node3)

# Analyze relationships
print(node1.outputs)  # Shows connections from node1
print(node2.inputs)   # Shows connections to node2

Advanced Features#

from networktree.structures.advanced import MatrixNode

# Create a matrix-based analysis
class NetworkAnalyzer(MatrixNode):
    def analyze_connections(self):
        matrix = self.build_matrix()
        return self.analyze_connectivity(matrix)

# Use for network analysis
analyzer = NetworkAnalyzer()
results = analyzer.analyze_connections()

Documentation#

Comprehensive documentation is available at networktree.readthedocs.io

Key Topics#

Use Cases#

Networktree is ideal for:

Complex data structures
Resource management systems
Plugin architectures
Process workflows
Dependency management
Configuration systems
Analysis tools

Development#

Setup Development Environment#

# Clone the repository
git clone https://framagit.org/your-username/networktree-py.git
cd networktree-py

# Install development dependencies
pip install -e .[dev]

# Run tests
pytest

# Check code style
black .
isort .

Contributing#

Fork the repository
Create a feature branch
Commit your changes
Push to the branch
Create a Merge Request

License#

This project is licensed under the MIT License - see the LICENSE file for details.

Support#

Issue Tracker: Framagit Issues
Source Code: Framagit Repository

Acknowledgments#

Inspired by various tree and network implementations
Built with modern Python practices
Developed with extensibility in mind

Citation#

If you use networktree in your research, please cite:

@software{networktree2024,
  author = {Your Name},
  title = {networktree-py: A Python Library for Hierarchical Networks},
  year = {2024},
  publisher = {Framagit},
  url = {https://framagit.org/your-username/networktree-py}
}

Contact#

Maintainer: Your Name
Email: your.email@example.com