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| """Campaign Name 解ζε¨εε ζ΅θ―γ""" | |
| import sys | |
| from pathlib import Path | |
| sys.path.insert(0, str(Path(__file__).resolve().parent.parent)) | |
| import pandas as pd | |
| import pytest | |
| from src.campaign_parser import ( | |
| parse_campaign_name, | |
| enrich_dataframe, | |
| AUDIENCE_REMARKETING, | |
| AUDIENCE_ASC, | |
| AUDIENCE_COLD, | |
| ) | |
| class TestParseCampaignName: | |
| """parse_campaign_name εε½ζ°ζ΅θ―γ""" | |
| def test_standard_12_fields(self): | |
| name = "US_Conversion_Meta_All_Purchase_Bone-Conduction_Others_AO_ASC_Mix_20260123_coreNumber" | |
| r = parse_campaign_name(name) | |
| assert r["market"] == "US" | |
| assert r["funnel"] == "Conversion" | |
| assert r["parsed_platform"] == "Meta" | |
| assert r["channel"] == "All" | |
| assert r["ad_objective"] == "Purchase" | |
| assert r["product_line"] == "Bone-Conduction" | |
| assert r["product_model"] == "Others" | |
| assert r["project_type"] == "AO" | |
| assert r["audience_raw"] == "ASC" | |
| assert r["creative_type"] == "Mix" | |
| assert r["campaign_date"] == "20260123" | |
| assert r["note"] == "coreNumber" | |
| assert r["parse_ok"] is True | |
| def test_audience_rmkt(self): | |
| name = "US_Conversion_Meta_All_Purchase_Bone-Conduction_Others_AO_RMKT_Mix_20260123_note" | |
| r = parse_campaign_name(name) | |
| assert r["audience_type"] == AUDIENCE_REMARKETING | |
| assert r["objective_group"] == "Purchase_RMKT" | |
| def test_audience_asc(self): | |
| name = "US_Conversion_Meta_All_Purchase_Bone-Conduction_Others_AO_ASC_Mix_20260123_note" | |
| r = parse_campaign_name(name) | |
| assert r["audience_type"] == AUDIENCE_ASC | |
| assert r["objective_group"] == "Purchase_ASC" | |
| def test_audience_cold(self): | |
| name = "US_Conversion_Meta_All_Purchase_Bone-Conduction_Others_AO_INT_Mix_20260123_note" | |
| r = parse_campaign_name(name) | |
| assert r["audience_type"] == AUDIENCE_COLD | |
| assert r["objective_group"] == "Purchase_Cold" | |
| def test_broad_audience(self): | |
| name = "CA_Conversion_Google_All_Purchase_Bone-Conduction_X_AO_Broad_Video_20260101_test" | |
| r = parse_campaign_name(name) | |
| assert r["audience_type"] == AUDIENCE_COLD | |
| assert r["objective_group"] == "Purchase_Cold" | |
| def test_lal_audience(self): | |
| name = "US_Consideration_Meta_IG_Linkclick_Bone-Conduction_X_AO_LAL_Image_20260101_test" | |
| r = parse_campaign_name(name) | |
| assert r["audience_type"] == AUDIENCE_COLD | |
| assert r["objective_group"] == "Linkclick" | |
| def test_less_than_5_fields(self): | |
| name = "US_Conversion_Meta" | |
| r = parse_campaign_name(name) | |
| assert r["parse_ok"] is False | |
| assert r["market"] == "US" | |
| assert r["ad_objective"] is None | |
| def test_exactly_5_fields(self): | |
| name = "US_Conversion_Meta_All_Purchase" | |
| r = parse_campaign_name(name) | |
| assert r["parse_ok"] is True | |
| assert r["ad_objective"] == "Purchase" | |
| assert r["product_line"] is None | |
| def test_more_than_12_fields(self): | |
| name = "US_Conversion_Meta_All_Purchase_BC_O_AO_ASC_Mix_20260101_note1_extra1_extra2" | |
| r = parse_campaign_name(name) | |
| assert r["note"] == "note1_extra1_extra2" | |
| assert r["parse_ok"] is True | |
| def test_invalid_market(self): | |
| name = "UK_Conversion_Meta_All_Purchase_BC_O_AO_ASC_Mix_20260101_note" | |
| r = parse_campaign_name(name) | |
| assert r["parse_ok"] is False | |
| def test_non_purchase_objective_group(self): | |
| name = "US_Consideration_Meta_All_Linkclick_BC_O_AO_INT_Mix_20260101_note" | |
| r = parse_campaign_name(name) | |
| assert r["objective_group"] == "Linkclick" | |
| def test_unknown_objective(self): | |
| name = "US_Conversion_Meta_All_SomethingNew_BC_O_AO_INT_Mix_20260101_note" | |
| r = parse_campaign_name(name) | |
| assert r["objective_group"] == "Other" | |
| class TestEnrichDataframe: | |
| """enrich_dataframe ζΉι解ζζ΅θ―γ""" | |
| def test_basic_enrichment(self): | |
| df = pd.DataFrame({ | |
| "campaign_name": [ | |
| "US_Conversion_Meta_All_Purchase_Bone-Conduction_Others_AO_ASC_Mix_20260123_core", | |
| "CA_Awareness_Google_All_Pageview_Bone-Conduction_X_AO_Broad_Video_20260101_test", | |
| ], | |
| "Cost": [100.0, 50.0], | |
| }) | |
| result = enrich_dataframe(df) | |
| assert "market" in result.columns | |
| assert "funnel" in result.columns | |
| assert "ad_objective" in result.columns | |
| assert "audience_type" in result.columns | |
| assert "objective_group" in result.columns | |
| assert result.iloc[0]["market"] == "US" | |
| assert result.iloc[1]["market"] == "CA" | |
| assert result.iloc[0]["objective_group"] == "Purchase_ASC" | |
| assert result.iloc[1]["objective_group"] == "Pageview" | |
| def test_missing_campaign_name_column(self): | |
| df = pd.DataFrame({"Cost": [100.0]}) | |
| result = enrich_dataframe(df) | |
| assert "market" not in result.columns | |
| def test_does_not_modify_original(self): | |
| df = pd.DataFrame({"campaign_name": ["US_Conversion_Meta_All_Purchase"], "Cost": [1.0]}) | |
| original_cols = list(df.columns) | |
| enrich_dataframe(df) | |
| assert list(df.columns) == original_cols | |
| def test_parse_ok_rate_logging(self, caplog): | |
| df = pd.DataFrame({ | |
| "campaign_name": [ | |
| "US_Conversion_Meta_All_Purchase", | |
| "INVALID", | |
| "US_Awareness_Meta_All_Pageview", | |
| ], | |
| "Cost": [1.0, 2.0, 3.0], | |
| }) | |
| import logging | |
| with caplog.at_level(logging.INFO, logger="ad-agent"): | |
| result = enrich_dataframe(df) | |
| assert result["parse_ok"].sum() == 2 | |
| if __name__ == "__main__": | |
| pytest.main([__file__, "-v"]) | |