Importspy

🎉 Highlights

- **YAML contract support** → Say goodbye to hardcoded `SpyModel`.
- **Dual validation modes**:
- ✅ Embedded (runtime enforcement)
- ✅ External CLI (for CI/CD, scripting, or pipelines)
- **Powerful new CLI** using [Typer](https://typer.tiangolo.com/)
- **New architecture** for reflection, validation, and error messaging

---

✨ What’s New

✅ YAML-based Contract System

- Modules now validated against external `.yml` definitions
- Define required:
- Classes, methods, attributes
- Runtime (Python version, OS, arch, environment variables)
- Deployment-specific logic

🔧 CLI Integration

bash
importspy -s contracts.yml mymodule.py

To install or upgrade to the latest version:

bash
pip install --upgrade importspy

Changelog:
- **Dependency Updates**:
- **Pydantic**: Updated from `2.10.3` to `2.10.4`.
- Includes bug fixes and compatibility improvements. Notable changes:
- Resolved an `AttributeError` when using data classes with `defer_build=True`.
- Fixed URL compatibility issues between versions `2.9.2` and `2.10.X`.
- Details: [GitHub Issues](https://github.com/pydantic/pydantic/issues/10910)
- **Jinja2**: Updated from `3.1.4` to `3.1.5`.
- Introduced critical security fixes and minor bug resolutions to enhance stability.
- Details: [New Releases](https://newreleases.io/project/pypi/Jinja2/release/3.1.5)
- **Pytest**: Updated from `8.3.3` to `8.3.4`.
- General improvements and bug fixes for the Python testing framework.
- **Sphinx-rtd-theme**: Updated from `3.0.1` to `3.0.2`.
- Minor updates to improve the style and functionality of Sphinx-generated documentation.

- **Why Upgrade?**
This release ensures a more stable, secure, and feature-rich environment. Dependency updates address known issues and provide important improvements.

For further details, see the links provided for specific dependency updates.

Enhancements
- **Improved Error Messages for Validation:**
- Enhanced error messages for class methods, attributes, and superclass mismatches to provide clearer, more actionable feedback during validation.
- Added specific error messages for missing and mismatched functions, classes, attributes, and environment variables.

- **Modular Validation Refactoring:**
- Refactored the `is_subset` function for better modularity:
- Introduced helper functions `list_compare` and `dict_compare` to simplify validation logic and improve code readability.

How to Upgrade
Update to the latest version using pip:
bash
pip install --upgrade importspy

🔥 New Features:
- **Environment Variable Support**:
- You can now define `env_vars` as a dictionary in `SpyModel`, enabling validation of required environment variables and their values.
- Example:
python
env_vars: dict = {
"CI": "true",
"DATA_PATH": "/data/"
}


🔧 Improvements:
- **Enhanced Variables Validation**:
- Variables are now represented as a dictionary in `SpyModel` (`variables: dict`), allowing developers to validate both the names and the expected values of module-level variables.
- Example:
python
variables: dict = {
"default_timeout": "30",
"max_connections": "100"
}

- **`name` Field in Classes Now Mandatory**:
- The `name` field in `ClassModel` is now required, ensuring clarity and consistency in class validation.

---

How to Update:
1. Update your package:
bash
pip install --upgrade importspy

- **Proactive Validation Enhancements**: Enhanced the `is_subset` function to raise descriptive `ValueErrors` for each validation failure, improving the clarity and maintainability of error handling.
- **Documentation Updates**: Updated all documentation to reflect changes in code and added examples on how to handle new validation exceptions.

Continuous Integration Improvements
- **Python Package Testing Workflow**: Introduced a new GitHub Actions workflow to automate the testing process, ensuring that each push or pull request to the 'main' branch triggers a series of actions that validate the codebase across different environments and Python versions.
- Setup steps for Python environment and dependencies using Poetry.
- Code linting with flake8 to enforce coding standards and identify issues early.
- Automated tests with pytest to verify that new changes do not break existing functionalities.
- Documentation build using Sphinx to keep the project documentation up to date.

Documentation and README Updates
- **Enhanced Documentation**: Updated the documentation and README files to better reflect the current functionalities and how to implement the module within other projects.
- **Workflow Integration**: Detailed the inclusion of a new GitHub Actions workflow that automates testing across multiple Python versions (3.9, 3.10, 3.11, 3.12) to ensure compatibility and reliability.
- **Example Code Added**: New example codes and usage scenarios have been added to the documentation to assist users in understanding how to use the validation features effectively.

Other Improvements
- **Simplified File Path Extraction**: Refactored string handling to ensure compatibility with Python versions 3.9 to 3.11, making the codebase more future-proof.

Improvements
- Improved error message clarity in the validation process.

We encourage all users to update to this latest version to benefit from these improvements.