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