style: format code with Autopep8, Black and Ruff Formatter

This commit fixes the style issues introduced in 821e241 according to the output
from Autopep8, Black and Ruff Formatter.

Details: https://github.com/ajschofield/de-project-bentley/pull/96

1 files changed, 176 insertions, 59 deletions

diff --git a/tests/test_fact_sales_order.py b/tests/test_fact_sales_order.py
index f0796eb..a245379 100644
--- a/tests/test_fact_sales_order.py
+++ b/tests/test_fact_sales_order.py
@@ -3,42 +3,88 @@ 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"]}
+        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"]}
+        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"]}
+        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"]}
+        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)  
+        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"]}
+        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_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)  
+        assert result.equals(expected_result)
+
 
 class TestCreatePaymentType:
     def test_create_dim_payment_type_returns_correct_columns_and_values(self):
@@ -46,84 +92,155 @@ class TestCreatePaymentType:
         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_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}
+        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"]
+        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}
+        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)  
+        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']
+        assert isinstance(result, pd.DataFrame)
+        assert list(result.columns) == ["currency_code", "currency_name"]
 
-class TestCreateDimDate:
 
+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'])
+        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)
+                    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:
 
+
+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'])}        
+        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']
-    
+        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'])}        
+    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']
-    
\ No newline at end of file
+        assert list(result.columns) == ["transaction_id", "some_other_id"]