Lars
ebca44829e
- Updated the `validate_csv_template` function to normalize both the column signature and field mappings for accurate comparison, preventing false warnings about mismatches. - Enhanced warning messages to provide clearer guidance on the relationship between normalized signatures and raw field mappings. - Added a new test to ensure that normalized signatures do not trigger false warnings when compared to raw mappings.
71 lines
2.3 KiB
Python
71 lines
2.3 KiB
Python
"""Formatprüfung CSV-Vorlagen (template_validator)."""
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from __future__ import annotations
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from csv_parser.template_validator import validate_csv_template
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def test_validate_kj_column_warns_without_source_unit():
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r = validate_csv_template(
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"activity",
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{"Aktive Energie (kJ)": "kcal_active", "Start": "start_time", "Trainingsart": "activity_type"},
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{"start_time": {"type": "datetime", "format": "yyyy-mm-dd HH:MM:SS", "flexible": True}},
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None,
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None,
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)
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assert r["valid"] is True
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codes = {w["code"] for w in r["warnings"]}
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assert "energy_kj_without_source_unit" in codes
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def test_validate_invalid_target_error():
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r = validate_csv_template(
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"activity",
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{"X": "not_a_field"},
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{},
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None,
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None,
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)
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assert r["valid"] is False
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assert any(e["code"] == "invalid_field_mapping" for e in r["errors"])
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def test_signature_normalized_vs_raw_mapping_no_false_warning():
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"""Analyse liefert normalisierte Signatur; field_mappings nutzt Original-Header wie im Seed."""
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r = validate_csv_template(
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"blood_pressure",
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{
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"Datum": "measured_date",
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"Zeit": "measured_time",
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"Systolisch (mmHg)": "systolic",
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"Diastolisch (mmHg)": "diastolic",
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"Puls (bpm)": "pulse",
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},
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{
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"measured_date": {"type": "date", "format": "dd.mm.yyyy"},
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"measured_time": {"type": "time", "format": "HH:MM"},
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"systolic": {"type": "int"},
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"diastolic": {"type": "int"},
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"pulse": {"type": "int"},
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},
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None,
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["datum", "diastolisch_mmhg", "puls_bpm", "systolisch_mmhg", "zeit"],
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)
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assert r["valid"] is True
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assert not any(w["code"] == "signature_vs_mappings_mismatch" for w in r["warnings"])
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def test_validate_duplicate_target_warning():
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r = validate_csv_template(
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"weight",
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{"A": "weight", "B": "weight", "Tag": "date"},
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{
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"weight": {"type": "float", "decimal_separator": "."},
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"date": {"type": "date", "format": "yyyy-mm-dd", "flexible": True},
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},
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None,
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None,
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)
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assert r["valid"] is True
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assert any(w["code"] == "duplicate_target_columns" for w in r["warnings"])
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