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3291500 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 | """Tests for src.loader — config loading and data normalization."""
import sys
from pathlib import Path
from unittest.mock import patch
import pandas as pd
sys.path.insert(0, str(Path(__file__).resolve().parent.parent))
from src.loader import load_config, normalize_columns, _clean_numeric, get_available_weeks
class TestLoadConfig:
def test_loads_config(self):
config_path = Path(__file__).resolve().parent.parent / "config.yaml"
if config_path.exists():
config = load_config(config_path)
assert "google_sheets" in config
assert "metrics" in config
assert isinstance(config["metrics"], list)
class TestNormalizeColumns:
def test_renames_by_index(self):
df = pd.DataFrame({
"A": ["US"], "B": ["Google"], "C": ["Awareness"],
"D": ["campaign1"], "E": ["2026-01-01"],
})
config = {"columns": {
"country_idx": 0, "platform_idx": 1,
"campaign_type_idx": 2, "campaign_name_idx": 3,
"date_idx": 4,
}}
result = normalize_columns(df, config)
assert "country" in result.columns
assert "platform" in result.columns
assert "date" in result.columns
assert result["country"].iloc[0] == "US"
class TestCleanNumeric:
def test_plain_number(self):
s = pd.Series(["100", "200.5", "0"])
result = _clean_numeric(s)
assert list(result) == [100.0, 200.5, 0.0]
def test_dollar_sign(self):
s = pd.Series(["$1,234.56", "$0.50"])
result = _clean_numeric(s)
assert abs(result.iloc[0] - 1234.56) < 0.01
assert abs(result.iloc[1] - 0.50) < 0.01
def test_percentage(self):
s = pd.Series(["2.50%", "10.00%"])
result = _clean_numeric(s)
assert abs(result.iloc[0] - 0.025) < 0.001
assert abs(result.iloc[1] - 0.10) < 0.001
def test_nan_handling(self):
s = pd.Series(["", "abc", "100"])
result = _clean_numeric(s)
assert pd.isna(result.iloc[0])
assert pd.isna(result.iloc[1])
assert result.iloc[2] == 100.0
class TestGetAvailableWeeks:
def test_returns_sorted_pairs(self):
df = pd.DataFrame({
"year": [2026, 2026, 2025, 2026],
"week": [2, 1, 52, 3],
})
result = get_available_weeks(df)
assert result == [(2025, 52), (2026, 1), (2026, 2), (2026, 3)]
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