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-rw-r--r--tests/test_dataframes.py144
1 files changed, 144 insertions, 0 deletions
diff --git a/tests/test_dataframes.py b/tests/test_dataframes.py
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+++ b/tests/test_dataframes.py
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+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(2020,5,17,6,15,20),dt(2020,5,20,8,19,30),1,'SE18 9QO','2020-7-16']],
+ 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:
+ assert result[col].dtype == 'datetime64[ns]'
+
+ \ No newline at end of file
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