This Python-based utility generates high-quality, readable visualizations of your SQLAlchemy ORM models with almost no effort. With a focus on clarity and detail, it uses Graphviz to render each model as a directed graph, making it easier to understand the relationships between tables in your database schema.
- Automatically maps SQLAlchemy ORM models to a directed graph.
- Table-like representation of each model with fields, types, and constraints.
- Export diagrams to SVG format for high-quality viewing and printing using Roboto font.
pip install sqlalchemy-data-model-visualizer
# Suppose these are your SQLAlchemy data models defined above in the usual way, or imported from another file:
models = [GenericUser, Customer, ContentCreator, UserSession, FileStorage, ServiceRequest, GenericAuditLog, GenericFeedback, GenericAPIKey, GenericNotification, GenericAPICreditLog, GenericSubscriptionType, GenericSubscription, GenericSubscriptionUsage, GenericBillingInfo]
output_file_name = 'my_data_model_diagram'
generate_data_model_diagram(models, output_file_name)
add_web_font_and_interactivity('my_data_model_diagram.svg', 'my_interactive_data_model_diagram.svg')
To get started, clone the repository and install the required packages.
git clone https://github.com/Dicklesworthstone/sqlalchemy_data_model_visualizer.git
cd sqlalchemy_data_model_visualizer
python3 -m venv venv
source venv/bin/activate
python3 -m pip install --upgrade pip
python3 -m pip install wheel
pip install -r requirements.txt
- Python 3.x
- SQLAlchemy
- Graphviz
- lxml
First, paste in your SQLAlchemy models. A set of fairly complex data models are provided in the code directly as an example-- just replace these with your own from your application.
Then, simply call the generate_data_model_diagram
function. This will generate an SVG file with the name my_data_model_diagram.svg
.
models
: List of SQLAlchemy models you want to visualize.output_file
: Name of the output SVG file.add_labels
: Set to False to hide labels on the edges between tables
Contributions are welcome! Please open an issue or submit a pull request.
This project is licensed under the MIT License.