wardleymap 0.1.7

A Python package to create and visualize Wardley Maps

WardleyMap

WardleyMap is a Python package designed for creating and visualizing Wardley Maps. Wardley Maps provide a visual representation of the strategic landscape and the positioning of components within it, facilitating better decision-making in business strategy and technology development.

Features

• Parse and interpret Wardley Map syntax.
• Visualize maps using matplotlib for easy integration into Python workflows.
• Export maps to SVG format for embedding in web applications or documents.
• Streamlit integration for interactive web-based map visualization.

Installation

Install wardleymap using pip:

pip install wardleymap

Ensure you have Python 3.6 or newer installed.

Quick Start

To create and visualize a Wardley Map, follow these steps:

from wardleymap import wardlemap

# Define the structure of your Wardley Map using a string.
map_definition = """
title Business Value Chain
anchor Customer [0.95, 0.9]
component User Needs [0.8, 0.8]
component Website [0.6, 0.6]
component Hosting [0.3, 0.4]
User Needs -> Website
Website -> Hosting
"""

# Process the Wardley Map text and generate a plot of the map
map, map_plot = wardley(map=map_text)

# Convert the map plot into an SVG
svg_map = create_svg_map(map_plot)

Documentation

For detailed usage and API documentation, please refer to the docs directory.

Contributing

Contributions to WardleyMap are welcome! Please read the CONTRIBUTING.md file for guidelines on how to contribute to this project.

License

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

Acknowledgements

• Special thanks to the open-source community for the invaluable tools and libraries.
• Inspired by Simon Wardley's work on mapping and strategy.

Example Usage

Below is an example of how to use the wardleymap package to create and visualize a Wardley Map:

from wardleymap import wardlemap

# Define the structure of your Wardley Map using a string.
map_definition = """
title Business Value Chain
anchor Customer [0.95, 0.9]
component User Needs [0.8, 0.8]
component Website [0.6, 0.6]
component Hosting [0.3, 0.4]
User Needs -> Website
Website -> Hosting
"""

# Process the Wardley Map text and generate a plot of the map
map, map_plot = wardley(map=map_text)

# Convert the map plot into an SVG
svg_map = create_svg_map(map_plot)