DHI / DHI/python-package-development
Add content on deprecating functionality
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- Jupyter Notebook
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Description
## Problem
The course covers semantic versioning and breaking changes in Module 7, but lacks content on **deprecation strategies** - a critical skill for package maintainers.
## Proposed Content
Add a section to Module 7 (`07_packaging.qmd`) covering:
### 1. Deprecation Warnings
- Using Python's `warnings` module
- Proper `stacklevel` usage
- **DeprecationWarning vs FutureWarning**:
- `DeprecationWarning`: For developers (filtered by default, shown when running tests)
- `FutureWarning`: For end users (always visible, for changes affecting user code)
### 2. Deprecation Timeline
- Announce in version X.Y
- Remove in version (X+1).0
- Maintain for 1-2 minor releases minimum
### 3. Communication Strategy
- CHANGELOG updates
- Release notes
- Documentation migration guides
- Clear docstring warnings
### 4. Code Examples
```python
import warnings
def old_function(x):
warnings.warn(
"old_function is deprecated and will be removed in version 2.0. "
"Use new_function instead.",
DeprecationWarning,
stacklevel=2
)
return new_function(x)
```
### 5. Real-World Examples
Reference deprecation practices from popular packages (pandas, numpy, scikit-learn).
## Location
Module 7 - after the "Breaking changes" section (around line 132)
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