bayesflow-packaging

What problem does it solve?

This Skill addresses the complexities of structuring, versioning, and configuring Python packages, specifically for the BayesFlow ecosystem, ensuring consistency and adherence to best practices.

Core Features & Use Cases

• Package Structure: Enforces the src/ layout convention for cleaner project organization.
• API Management: Guides on managing __all__ for public symbol visibility and version detection.
• Dependency Handling: Provides templates for pyproject.toml, including optional dependencies and CI configuration.
• Use Case: When adding a new feature that requires an optional dependency like calibration, this skill helps correctly define it in pyproject.toml and implement guarded imports in your code.

Quick Start

Use the bayesflow-packaging skill to set up a new BayesFlow extension package with a standard src-layout and pyproject.toml.