from src.dataframes import * import pandas as pd from unittest.mock import patch from datetime import datetime as dt class TestCreateDimDesign: def test_dim_design_returns_dataframe(self): d = {"test": ["Hello", "Bye"], "design_id": ["Hello", "Bye"], "design_name": ["Hello", "Bye"], "file_name": ["Hello", "Bye"], "file_location": ["Hello", "Bye"], "Hello": ["Hello", "Bye"]} test_df = {"design": pd.DataFrame(data=d)} result = create_dim_design(test_df) assert isinstance(result, pd.DataFrame) def test_dim_design_returns_correct_columns_and_values(self): d = {"test": ["Hello", "Bye"], "design_id": ["Hello", "Bye"], "design_name": ["Hello", "Bye"], "file_name": ["Hello", "Bye"], "file_location": ["Hello", "Bye"], "Hello": ["Hello", "Bye"]} test_df = {"design": pd.DataFrame(data=d)} result = create_dim_design(test_df) d2 = {"design_id": ["Hello", "Bye"], "design_name": ["Hello", "Bye"], "file_name": ["Hello", "Bye"], "file_location": ["Hello", "Bye"]} expected_df = pd.DataFrame(data=d2) expected_result = expected_df.copy() assert result.equals(expected_result) class TestCreateDimStaff: def test_dim_staff_returns_dataframe(self): d = {"staff_id": ["Hello", "Bye"], "first_name": ["Hello", "Bye"], "last_name": ["Hello", "Bye"], "department_id": ["Hello", "Bye"]} d2 = {"department_name": ["Hello", "Bye"], "location": ["Hello", "Bye"], "email_address": ["Hello", "Bye"], "department_id": ["Hello", "Bye"]} test_df = {"staff": pd.DataFrame(data=d), "department": pd.DataFrame(data=d2)} result = create_dim_staff(test_df) assert isinstance(result, pd.DataFrame) def test_dim_staff_returns_correct_columns_and_values(self): d = {"staff_id": ["Hello", "Bye"], "first_name": ["Hello", "Bye"], "last_name": ["Hello", "Bye"], "department_id": ["Hello", "Bye"]} d2 = {"department_name": ["Hello", "Bye"], "location": ["Hello", "Bye"], "email_address": ["Hello", "Bye"], "department_id": ["Hello", "Bye"]} test_df = {"staff": pd.DataFrame(data=d), "department": pd.DataFrame(data=d2)} result = create_dim_staff(test_df) expected_d = {"staff_id": ["Hello", "Bye"], "first_name": ["Hello", "Bye"], "last_name": ["Hello", "Bye"], "department_name": ["Hello", "Bye"], "location": ["Hello", "Bye"], "email_address": ["Hello", "Bye"]} expected_df = pd.DataFrame(data=expected_d) expected_result = expected_df.copy() assert result.equals(expected_result) class TestCreatePaymentType: def test_create_dim_payment_type_returns_correct_columns_and_values(self): d = {"payment_type_id": ["Hello", "Bye"], "payment_type_name": ["Hello", "Bye"]} test_df = {"payment_type": pd.DataFrame(data=d)} result = create_dim_payment_type(test_df) expected_columns = ["payment_type_id", "payment_type_name"] expected_d = {"payment_type_id": ["Hello", "Bye"], "payment_type_name": ["Hello", "Bye"]} expected_df = pd.DataFrame(data=expected_d) assert isinstance(result, pd.DataFrame) assert list(result.columns) == expected_columns assert result.equals(expected_df) class TestCreateDimCounterparty: def test_create_dim_counterparty_type_returns_correct_columns_and_object(self): data_l = pd.DataFrame(data={"counterparty_id": ["Hello", "Bye"], "counterparty_legal_name": ["Hello", "Bye"], "commercial_contact": ["Hello", "Bye"], "legal_address_id": ["bond street", "regent street"]}) data_a = pd.DataFrame(data={"address_id":["bond street", "regent street"], "postcode":[98365,93753]}) test_df = {"address": data_a,"counterparty":data_l} result = create_dim_counterparty(test_df) expected_columns = ["counterparty_id", "counterparty_legal_name", "commercial_contact", "counterparty_legal_postcode"] print(data_l) print(data_a) assert isinstance(result, pd.DataFrame) assert list(result.columns) == expected_columns class TestCreateDimCurrency: def test_dim_currency_returns_columns_and_values(self): nones = [None,None,None] d = {"currency_id": [1, 2, 3], "currency_code": ["USD", "EUR", "GBP"],"created_at":nones,"last_updated":nones} test_df = {"currency": pd.DataFrame(data=d)} scraper_output = pd.DataFrame({"currency_code":["RUS","USD","PHP","GBP","EUR"],"currency_name":["Rubble","US Dollar","Peso","Pound","Euro"]}) result = create_dim_currency(test_df,names=scraper_output).sort_values(by="currency_code",axis=0) expected_d = {"currency_id": [1, 2, 3], "currency_code": ["USD", "EUR", "GBP"], "currency_name": ["US Dollar", "Euro", "Pound"]} expected_df = pd.DataFrame(data=expected_d).sort_values(by="currency_code",axis=0) assert isinstance(result, pd.DataFrame) assert result.equals(expected_df) def test_scrape_currency_names_returns_dataframe_with_correct_collumns(self): result = scrape_currency_names() assert isinstance(result,pd.DataFrame) assert list(result.columns) == ['currency_code', 'currency_name'] class TestCreateDimDate: def test_returns_required_columns(self): df_one = pd.DataFrame(data={'updated_date':dt(2020, 5, 17),'created_date':dt(2021, 5, 13),'not_dat':None},index=[0]) df_two = pd.DataFrame(data={'updated_date':dt(2020, 5, 17),'created_date':dt(2021, 9, 13)},index=[0]) df_three = pd.DataFrame(data={'updated_date':dt(2022, 5, 17),'created_date':dt(2023, 5, 13)},index=[0]) expected_df = pd.DataFrame(data= [[dt(2020,5,17),2020,5,17,6,'Sunday','May',2], [dt(2021,5,13),2021,5,13,3,'Thursday','May',2], [dt(2021,9,13),2021,9,13,0,'Monday','September',3], [dt(2022,5,17),2022,5,17,1,'Tuesday','May',2], [dt(2023,5,13),2023,5,13,5,'Saturday','May',2]], columns=['date_id','year','month','day','day_of_week','day_name','month_name','quarter']) with patch("src.dataframes.create_fact_payment") as mock_fp: with patch("src.dataframes.create_fact_purchase_orders") as mock_fpo: with patch("src.dataframes.create_fact_sales_order") as mock_fso: mock_fp.return_value = df_one mock_fpo.return_value = df_two mock_fso.return_value = df_three result = create_dim_date({'dum':0}) result.reset_index(inplace=True,drop=True) assert result.eq(expected_df, axis="columns").all(axis=None) class TestCreateDimLocation: def test_returns_correct_columns_lo(self): dict_df = {'address':pd.DataFrame(data=[['some_time','some_other_time',1,'SE18 9QO']], columns=['created_at','last_updated','address_id','postal_code'])} result = create_dim_location(dict_df) assert list(result.columns) == ['location_id','postal_code'] class TestCreateDimTransaction: def test_returns_correct_columns_tr(self): dict_df = {'transaction':pd.DataFrame(data=[['some_time','some_other_time',1,'SE18 9QO']], columns=['created_at','last_updated','transaction_id','some_other_id'])} result = create_dim_transaction(dict_df) assert list(result.columns) == ['transaction_id','some_other_id'] class TestCreateFactPayment: def test_returns_correct_columns_payment(self): dict_df = {'payment':pd.DataFrame(data=[[dt.strptime('2022-11-03 14:20:49.962846','%Y-%m-%d %H:%M:%S.%f'), dt.strptime('2022-12-14 16:20:49.962194','%Y-%m-%d %H:%M:%S.%f'),1,'SE18 9QO','2020-07-16']], columns=['created_at','last_updated','payment_id','some_other_id','payment_date'])} expected_cols = ['payment_record_id','created_date','created_time','last_updated_date', 'last_updated_time','payment_date','payment_id','some_other_id'] result = create_fact_payment(dict_df) assert isinstance(result,pd.DataFrame) for col in list(result.columns): assert col in expected_cols for col in expected_cols: if '_date' in col: print(col) assert result[col].dtype == 'datetime64[ns]' if '_time' in col: print(col) assert result[col].dtype == 'O' #<< O for object