| import pandas as pd |
| import pytest |
|
|
| from expense_ml.data.normalize import normalize_text, prepare_dataframe |
| from expense_ml.data.taxonomy import canonicalize_category |
|
|
|
|
| def test_normalize_text_collapses_whitespace_and_unicode(): |
| assert normalize_text(" Café\u00a0Coffee ") == "café coffee" |
|
|
|
|
| def test_prepare_dataframe_removes_empty_rows_and_exact_duplicates(): |
| frame = pd.DataFrame( |
| { |
| "text": ["Food Shop", "food shop", "food shop"], |
| "label": ["Food", "food", "food"], |
| "source": ["a", "b", "b"], |
| "country": ["USA", "India", "India"], |
| } |
| ) |
| result = prepare_dataframe(frame) |
| assert len(result) == 2 |
| assert set(result["source"]) == {"a", "b"} |
| assert set(result["country"]) == {"USA", "India"} |
|
|
|
|
| def test_prepare_dataframe_preserves_canonical_category_ids(): |
| frame = pd.DataFrame( |
| { |
| "text": ["food transaction", "transport transaction"], |
| "label": ["food_dining", "transportation"], |
| "source": ["prepared"] * 2, |
| } |
| ) |
| result = prepare_dataframe(frame) |
| assert result["label"].tolist() == ["food_dining", "transportation"] |
|
|
|
|
| def test_taxonomy_maps_source_labels_to_stable_categories(): |
| assert canonicalize_category("Food & Dining", "global-transaction-categorization") == "food_dining" |
| assert canonicalize_category("food", "finee-india") == "food_dining" |
| assert canonicalize_category("Transportation & Gas", "synthetic-indian-transactions") == "transportation" |
|
|
|
|
| def test_taxonomy_rejects_unknown_configured_source_labels(): |
| with pytest.raises(ValueError, match="Unknown category"): |
| canonicalize_category("brand-new-category", "finee-india") |
|
|
|
|
| def test_prepare_dataframe_preserves_country_and_currency(): |
| frame = pd.DataFrame( |
| { |
| "text": ["Uber ride", "Tesco purchase"], |
| "label": ["Transportation", "Shopping & Retail"], |
| "source": ["global-transaction-categorization"] * 2, |
| "country": ["USA", "uk"], |
| "currency": ["usd", "gbp"], |
| } |
| ) |
| result = prepare_dataframe(frame) |
| assert result["country"].tolist() == ["USA", "UK"] |
| assert result["currency"].tolist() == ["USD", "GBP"] |
|
|
