Merge pull request #94 from ajschofield/feature/transform-fact-sales-order

PR: rebased the fact-sales branch with the datafrrames branch - now merging into development 

2 files changed, 124 insertions, 4 deletions

diff --git a/tests/test_fact_sales_order.py b/tests/test_fact_sales_order.py
new file mode 100644
index 0000000..48426b4
--- /dev/null
+++ b/tests/test_fact_sales_order.py
@@ -0,0 +1,110 @@
+import pandas as pd
+from 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,
+)
+
+
+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 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)
+
+    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_df = pd.DataFrame(data=expected_d)
+        expected_result = expected_df.copy()
+        assert result.equals(expected_result)
diff --git a/tests/test_transform_lambda.py b/tests/test_transform_lambda.py
index 4c689f7..37ca08f 100644
--- a/tests/test_transform_lambda.py
+++ b/tests/test_transform_lambda.py
@@ -40,8 +40,13 @@ class TestReadFromS3:
         )
         print(result)
         expected_df = pd.DataFrame(
-            np.array([["Vegetable", "Sour", "Green"], ["Berry", "Sweet", "Red"]]),
-            columns=["Food_type", "Flavour", "Colour"],
+            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)
         assert list(result.keys())[0] == "Foods"
@@ -58,8 +63,13 @@ class TestReadFromS3:
             tables, bucket="dummy_buc", client=s3_client
         )
         expected_foods_df = pd.DataFrame(
-            np.array([["Vegetable", "Sour", "Green"], ["Berry", "Sweet", "Red"]]),
-            columns=["Food_type", "Flavour", "Colour"],
+            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(
             np.array(