style: format code with Autopep8, Black and Ruff Formatter

This commit fixes the style issues introduced in 8e20c5c according to the output
from Autopep8, Black and Ruff Formatter.

Details: https://github.com/ajschofield/de-project-bentley/pull/93

2 files changed, 83 insertions, 23 deletions

diff --git a/tests/test_fact_sales_order.py b/tests/test_fact_sales_order.py
index 82845d7..87e3ade 100644
--- a/tests/test_fact_sales_order.py
+++ b/tests/test_fact_sales_order.py
@@ -1,57 +1,109 @@
-from src.fact_sales_order import create_dim_design, create_dim_staff, create_dim_currency
+from src.fact_sales_order import (
+    create_dim_design,
+    create_dim_staff,
+    create_dim_currency,
+)
 import pandas as pd
 
+
 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 TestCreateDimCurrency:
     def test_dim_currency_returns_dataframe(self):
         d = {"currency_id": [1, 2, 3], "currency_code": ["USD", "EUR", "GBP"]}
         test_df = {"currency": pd.DataFrame(data=d)}
         result = create_dim_currency(test_df)
-        assert isinstance(result, pd.DataFrame)  
-        
+        assert isinstance(result, pd.DataFrame)
+
     def test_dim_currency_returns_columns_and_values(self):
         d = {"currency_id": [1, 2, 3], "currency_code": ["USD", "EUR", "GBP"]}
         test_df = {"currency": pd.DataFrame(data=d)}
         result = create_dim_currency(test_df)
-        expected_d = {"currency_id": [1, 2, 3], "currency_code": ["USD", "EUR", "GBP"], "currency_name": ["US Dollar", "Euro", "Pound"]}
+        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)
         expected_result = expected_df.copy()
         assert result.equals(expected_result)
-
-    
\ No newline at end of file
diff --git a/tests/test_transform_lambda.py b/tests/test_transform_lambda.py
index 516f83b..a91da92 100644
--- a/tests/test_transform_lambda.py
+++ b/tests/test_transform_lambda.py
@@ -39,7 +39,12 @@ class TestReadFromS3:
         )
         print(result)
         expected_df = pd.DataFrame(
-            np.array([["Vegetable", "Sour", "Green", "2022-11-03 14:20:49.962"], ["Berry", "Sweet", "Red", "2022-11-03 14:20:49.962"]]),
+            np.array(
+                [
+                    ["Vegetable", "Sour", "Green", "2022-11-03 14:20:49.962"],
+                    ["Berry", "Sweet", "Red", "2022-11-03 14:20:49.962"],
+                ]
+            ),
             columns=["Food_type", "Flavour", "Colour", "last_updated"],
         )
         assert isinstance(result, dict)
@@ -56,7 +61,12 @@ class TestReadFromS3:
             tables, bucket="dummy_buc", client=s3_client
         )
         expected_foods_df = pd.DataFrame(
-            np.array([["Vegetable", "Sour", "Green", "2022-11-03 14:20:49.962"], ["Berry", "Sweet", "Red", "2022-11-03 14:20:49.962"]]),
+            np.array(
+                [
+                    ["Vegetable", "Sour", "Green", "2022-11-03 14:20:49.962"],
+                    ["Berry", "Sweet", "Red", "2022-11-03 14:20:49.962"],
+                ]
+            ),
             columns=["Food_type", "Flavour", "Colour", "last_updated"],
         )
         expected_cars_df = pd.DataFrame(
@@ -72,5 +82,3 @@ class TestReadFromS3:
         assert list(result.keys()) == tables
         assert result["Foods"].eq(expected_foods_df, axis="columns").all(axis=None)
         assert result["Cars"].eq(expected_cars_df, axis="columns").all(axis=None)
-
-