sqlmodel-data-modeling

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Guide for ORM-based data modeling with SQLModel. Use for defining database models, fields, constraints, relationships (1:N, N:M), inheritance, validators, and handling JSON fields and timestamps. Provides templates for User, Task, and Category models.

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[SQL and Databases]

When & Why to Use This Skill

This Claude skill provides a comprehensive guide for ORM-based data modeling using SQLModel. It streamlines the process of defining database schemas, managing complex relationships (1:N, N:M), and implementing data validation, ensuring robust and type-safe database architecture for Python applications.

Use Cases

  • Designing relational database schemas for web applications using Python and SQLModel to ensure data consistency.
  • Implementing complex many-to-many relationships between entities, such as linking Tasks to multiple Categories or Users to various Roles.
  • Setting up automated data validation and audit timestamps (created_at/updated_at) to maintain high data integrity and traceability.
  • Refactoring legacy database models into modern, type-safe SQLModel structures utilizing inheritance and advanced JSON field handling.
namesqlmodel-data-modeling
descriptionGuide for ORM-based data modeling with SQLModel. Use for defining database models, fields, constraints, relationships (1:N, N:M), inheritance, validators, and handling JSON fields and timestamps. Provides templates for User, Task, and Category models.

SQLModel Data Modeling

This skill provides guidance and code patterns for creating robust and efficient data models using SQLModel.

Workflow

  1. Define Basic Models: Start by defining the basic structure of your models. Refer to references/model_definition.md for defining tables, fields, and constraints. It includes templates for User, Task, and Category models.
  2. Establish Relationships: Define relationships between your models. See references/relationships.md for patterns on creating one-to-many (1:N) and many-to-many (N:M) relationships.
  3. Implement Advanced Patterns: For more complex scenarios, consult references/advanced_patterns.md. This guide covers model inheritance, a base model with audit timestamp fields, computed properties, and handling of JSON data.
  4. Add Validation: Implement data validation to ensure integrity. Examples of model validation using SQLModel's features are in references/validation.md.

Always consult the relevant reference document for detailed code examples and best practices for each step.