- Added a new function to strip header keys of unwanted characters, improving CSV import consistency. - Updated CSV row iteration to utilize the new header normalization function, ensuring cleaner data processing. - Enhanced date parsing capabilities to support flexible formats, accommodating various date representations in CSV files. - Introduced additional tests to validate the new header normalization and date parsing functionalities.
160 lines
5.0 KiB
Python
160 lines
5.0 KiB
Python
"""Tests für CSV-Parser Foundation (Issue #21)."""
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import pytest
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from csv_parser.core import (
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decode_raw_bytes,
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sniff_delimiter,
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parse_csv_sample,
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column_signature,
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headers_signature_match_score,
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get_csv_import_limits,
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iter_csv_dict_rows,
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)
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from csv_parser.type_converter import convert_value, build_row_after_mapping
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def test_decode_bom_utf8():
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raw = "\ufeffa;b;c\n1;2;3".encode("utf-8-sig")
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t = decode_raw_bytes(raw)
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assert not t.startswith("\ufeff")
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assert "a;b;c" in t
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def test_sniff_delimiter():
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assert sniff_delimiter("a;b;c;d") == ";"
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assert sniff_delimiter("a,b,c") == ","
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def test_parse_csv_sample_header():
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text = "Date;kcal\n2024-01-01;2000\n"
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headers, rows, delim = parse_csv_sample(text, delimiter=";", max_data_rows=3)
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assert headers == ["Date", "kcal"]
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assert delim == ";"
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assert rows[0]["Date"] == "2024-01-01"
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assert rows[0]["kcal"] == "2000"
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def test_column_signature_sorted_unique():
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sig = column_signature(["B", "a", "a"])
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assert sig == ["a", "b"]
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def test_jaccard():
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s1 = column_signature(["Date", "Calories"])
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s2 = column_signature(["Date", "Calories", "Fat"])
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assert headers_signature_match_score(s1, s2) == pytest.approx(2 / 3)
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def test_get_csv_import_limits_default():
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assert get_csv_import_limits(None)["max_rows_per_file"] == 50_000
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def test_convert_date_and_kcal_factor():
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d = convert_value("15.01.2024", "date", {"type": "date", "format": "dd.mm.yyyy"})
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assert d.year == 2024 and d.month == 1 and d.day == 15
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k = convert_value("8000", "kcal", {"type": "float", "conversion_factor": 0.239, "decimal_separator": "."})
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assert abs(k - 8000 * 0.239) < 0.01
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def test_iter_csv_dict_rows_full_file():
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text = "a;b\n1;2\n3;4\n"
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rows = list(iter_csv_dict_rows(text, ";", has_header=True))
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assert rows == [{"a": "1", "b": "2"}, {"a": "3", "b": "4"}]
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def test_build_row_after_mapping():
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csv_row = {"Datum": "01.01.2024", "kj": "4200"}
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fm = {"Datum": "date", "kj": "kcal"}
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tc = {
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"date": {"type": "date", "format": "dd.mm.yyyy"},
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"kcal": {"type": "float", "conversion_factor": 0.239, "decimal_separator": "."},
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}
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out = build_row_after_mapping(csv_row, fm, tc)
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assert out["date"].month == 1
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assert out["kcal"] is not None
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def test_build_row_fddb_raw_header_keys_match_normalized_template():
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"""FDDB: DictReader liefert deutsche Überschrift, Seed nutzt normalisierten Key."""
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csv_row = {
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"Datum Tag Monat Jahr Stunde Minute": "01.01.2024 8:30",
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"kJ": "42000",
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"Fett (g)": "50",
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"KH (g)": "200",
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"Protein (g)": "100",
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}
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fm = {
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"datum_tag_monat_jahr_stunde_minute": "date",
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"kj": "kcal",
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"fett_g": "fat_g",
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"kh_g": "carbs_g",
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"protein_g": "protein_g",
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}
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tc = {
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"date": {"type": "date", "format": "dd.mm.yyyy HH:MM", "extract": "date_only"},
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"kcal": {
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"type": "float",
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"conversion_factor": 0.239,
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"decimal_separator": ",",
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},
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"fat_g": {"type": "float", "decimal_separator": ","},
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"carbs_g": {"type": "float", "decimal_separator": ","},
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"protein_g": {"type": "float", "decimal_separator": ","},
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}
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out = build_row_after_mapping(csv_row, fm, tc)
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assert out["date"].year == 2024 and out["date"].month == 1 and out["date"].day == 1
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def test_convert_date_ddmm_with_seconds():
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d = convert_value(
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"15.01.2024 14:30:00",
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"date",
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{"type": "date", "format": "dd.mm.yyyy HH:MM", "extract": "date_only"},
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)
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assert d.month == 1 and d.day == 15
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def test_float_decimal_separator_auto_eu_us():
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assert abs(convert_value("1.234,56", "x", {"type": "float", "decimal_separator": "auto"}) - 1234.56) < 1e-9
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assert abs(convert_value("1,234.56", "x", {"type": "float", "decimal_separator": "auto"}) - 1234.56) < 1e-9
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assert abs(convert_value("1234,5", "x", {"type": "float", "decimal_separator": "auto"}) - 1234.5) < 1e-9
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def test_float_flexible_falls_back_to_auto():
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spec = {"type": "float", "decimal_separator": ",", "flexible": True}
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assert abs(convert_value("1234.56", "x", spec) - 1234.56) < 1e-9
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def test_date_flexible_iso_while_primary_ddmm():
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spec = {
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"type": "date",
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"format": "dd.mm.yyyy",
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"flexible": True,
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"extract": "date_only",
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}
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d1 = convert_value("2024-03-15", "d", spec)
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d2 = convert_value("15.03.2024", "d", spec)
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assert d1 == d2
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def test_date_extra_formats_without_days_in_name():
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spec = {
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"type": "date",
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"format": "yyyy-mm-dd",
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"formats": ["%d.%m.%Y"],
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"extract": "date_only",
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}
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assert convert_value("08.04.2026", "d", spec).day == 8
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def test_int_flexible_thousands():
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assert convert_value("1.234", "n", {"type": "int", "flexible": True}) == 1234
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def test_datetime_flexible():
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spec = {"type": "datetime", "format": "yyyy-mm-dd HH:MM:SS", "flexible": True}
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dtv = convert_value("15.01.2024 14:30:00", "t", spec)
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assert dtv.month == 1 and dtv.day == 15 and dtv.hour == 14
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