diff options
Diffstat (limited to 'tests/test_fact_sales_order.py')
| -rw-r--r-- | tests/test_fact_sales_order.py | 246 |
1 files changed, 246 insertions, 0 deletions
diff --git a/tests/test_fact_sales_order.py b/tests/test_fact_sales_order.py new file mode 100644 index 0000000..a245379 --- /dev/null +++ b/tests/test_fact_sales_order.py @@ -0,0 +1,246 @@ +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"] |