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- Added capabilities for weighted skill profiles, allowing trainers to compare training modules, frameworks, and regression paths based on skill contributions. - Updated the skill scoring specification to include peer context separation and list filtering, ensuring accurate comparisons among visible artifacts of the same type. - Enhanced the API to support batch summaries for skill profiles and discovery suggestions, improving data retrieval efficiency. - Refactored frontend components to display skill metrics, including scores and peer percentages, with improved filtering options for better user experience. - Updated documentation to reflect the latest changes and enhancements in the skill scoring system.
21 lines
903 B
Python
21 lines
903 B
Python
"""Normalisierung Übung ↔ Fähigkeit Intensität."""
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from routers.exercises import normalize_exercise_skill_intensity
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def test_normalize_exercise_skill_intensity_defaults_to_mittel():
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assert normalize_exercise_skill_intensity(None) == "mittel"
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assert normalize_exercise_skill_intensity("") == "mittel"
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assert normalize_exercise_skill_intensity("—") == "mittel"
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def test_normalize_exercise_skill_intensity_canonical():
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assert normalize_exercise_skill_intensity("niedrig") == "niedrig"
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assert normalize_exercise_skill_intensity("mittel") == "mittel"
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assert normalize_exercise_skill_intensity("hoch") == "hoch"
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def test_normalize_exercise_skill_intensity_legacy_aliases():
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assert normalize_exercise_skill_intensity("low") == "niedrig"
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assert normalize_exercise_skill_intensity("medium") == "mittel"
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assert normalize_exercise_skill_intensity("high") == "hoch"
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