franckalbinet marisco .cursorrules file for Jupyter Notebook (stars: 4)

Python Expert Guidelines
You are an expert in Python, Marisco, and nbdev conventions. Ensure your code follows these guidelines:
- Write concise, technical responses with accurate Python examples.
- Use descriptive variable names that clearly indicate their purpose.
- Prioritize readability and maintainability; follow PEP 8 style guidelines.
- Utilize comments and docstrings for clarity, ensuring they follow nbdev conventions.
- Structure code logically with a clear separation of concerns (modules, classes, functions).
- Implement effective error handling and input validation.
- Use type hints for all function signatures to enhance code clarity and usability.
- Leverage fastcore and other utility libraries to enhance functionality and efficiency.

IMFA Pattern Reminder
Remember the IMFA Pattern for remapping nomenclatures:
1. Inspect data provider nomenclature.
2. Match automatically against MARIS nomenclature using fuzzy matching algorithms.
3. Fix potential mismatches.
4. Apply the lookup table to the dataframe.
Use the `Remapper` object to facilitate this process.

Error Handling and Validation
Ensure robust error handling and input validation:
- Implement graceful error handling for unexpected conditions.
- Use informative exceptions and log error messages for easier debugging.
- Validate input data rigorously before processing to avoid runtime errors.

Marisco Guidelines
Follow Marisco's architectural patterns:
- Use structured data formats (like NetCDF and CSV) and ensure data integrity.
- Implement callbacks for modular data transformations and serializers for consistent data output.
- Utilize configuration files for managing constants and settings.
- Use appropriate functions from Marisco utility and config modules.
- Maintain a consistent approach to data manipulation and ensure reproducibility.

Performance Optimization
Consider performance optimization:
- Use vectorized operations and efficient algorithms for data processing.
- Implement caching and other optimization techniques for large datasets.
- Ensure functions are modular and reusable to promote code efficiency.