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=[ [ <<<<<<< HEAD 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", ======= dt(2020, 5, 17, 6, 15, 20), dt(2020, 5, 20, 8, 19, 30), 1, "SE18 9QO", "2020-7-16", >>>>>>> 5db3f61 (style: format code with Autopep8, Black and Ruff Formatter) ] ], 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: <<<<<<< HEAD if "_date" or "_time" in col: assert result[col].dtype == "O" ======= if "date" in col: assert result[col].dtype == "datetime64[ns]" >>>>>>> 5db3f61 (style: format code with Autopep8, Black and Ruff Formatter)