mitai-jinkendo/backend/tests/test_csv_parser_core.py
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feat(csv-parser): Enhance CSV parsing with header normalization and flexible date handling
- 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.
2026-04-10 06:23:46 +02:00

160 lines
5.0 KiB
Python

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