Lars
c0fcdea1fe
- Updated the nutrition import logic to utilize a new row processing specification, improving data aggregation and validation. - Refactored the template rendering process in the workflow executor to use Jinja2's Environment with ChainableUndefined for better handling of missing attributes. - Added backward-compatible shortcuts for accessing decision signals in node contexts, enhancing flexibility in template usage. - Introduced import row processing options in CSV templates, allowing for more customizable data handling during imports.
68 lines
2.0 KiB
Python
68 lines
2.0 KiB
Python
"""Tests für CSV-Zeilenaggregation (import_row_processing)."""
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from __future__ import annotations
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import datetime as dt
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import pytest
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from csv_parser.import_row_processing import (
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aggregate_mapped_rows,
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resolve_import_row_processing,
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validate_import_row_processing,
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)
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def test_validate_rejects_unknown_aggregate():
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with pytest.raises(ValueError, match="ungültige Operation"):
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validate_import_row_processing(
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"nutrition",
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{"group_by": ["date"], "aggregates": {"kcal": "bogus"}},
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{"Kal": "date", "E": "kcal"},
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)
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def test_validate_group_by_must_be_mapped():
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with pytest.raises(ValueError, match="keiner CSV-Spalte zugeordnet"):
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validate_import_row_processing(
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"nutrition",
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{"group_by": ["date"], "aggregates": {"kcal": "sum"}},
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{"Kal": "kcal"}, # date nicht gemappt
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)
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def test_aggregate_mapped_rows_sums_same_group():
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d = dt.date(2024, 1, 15)
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rows = [
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{"date": d, "kcal": 500.0, "protein_g": 20},
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{"date": d, "kcal": 300.0, "protein_g": 15},
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]
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spec = {"group_by": ["date"], "aggregates": {"kcal": "sum", "protein_g": "sum"}}
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out = aggregate_mapped_rows(rows, spec)
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assert len(out) == 1
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assert out[0]["kcal"] == 800.0
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assert out[0]["protein_g"] == 35
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def test_resolve_explicit_overrides_default():
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m = {
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"import_row_processing": {"group_by": ["date"], "aggregates": {"kcal": "mean"}},
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}
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spec = resolve_import_row_processing("nutrition", m)
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assert spec is not None
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assert spec["aggregates"]["kcal"] == "mean"
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def test_resolve_empty_dict_falls_back_to_module_default():
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m: dict = {"import_row_processing": {}}
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spec = resolve_import_row_processing("nutrition", m)
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assert spec is not None
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assert spec["group_by"] == ["date"]
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assert spec["aggregates"]["kcal"] == "sum"
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def test_resolve_none_uses_nutrition_default():
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spec = resolve_import_row_processing("nutrition", {})
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assert spec is not None
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assert "date" in (spec.get("group_by") or [])
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