added test cases for high level functions

Author: JaskaranIntugle

src/data_tools/analysis/models.py

@@ -119,7 +119,7 @@ def profile(self) -> None:
         Profiles the dataset including table and columns and stores the result in the 'results' dictionary.
         This is a convenience method to run profiling on the raw dataframe.
         """
-        if not self.raw_df:
+        if self.raw_df.empty:
             raise ValueError("The raw dataframe is empty. Cannot perform profiling.")
         self.profile_table().profile_columns()
         return self
@@ -129,7 +129,7 @@ def identify_datatypes(self) -> None:
         Identifies the data types for the dataset and stores the result in the 'results' dictionary.
         This is a convenience method to run data type identification on the raw dataframe.
         """
-        if not self.raw_df:
+        if self.raw_df.empty:
             raise ValueError("The raw dataframe is empty. Cannot perform data type identification.")
         self.identify_datatypes_l1().identify_datatypes_l2()
         return self

tests/analysis/test_high_level.py

@@ -0,0 +1,94 @@
+import pandas as pd
+import pytest
+
+from data_tools.analysis.models import DataSet
+
+
+@pytest.fixture
+def sample_dataframe():
+    """Fixture to provide a sample DataFrame for testing."""
+    return pd.DataFrame({
+        "user_id": [1, 2, 3, 4, 5],
+        "product_name": ["Laptop", "Mouse", "Keyboard", "Monitor", "Webcam"],
+        "price": [1200.50, 25.00, 75.99, 300.00, 55.50],
+        "purchase_date": pd.to_datetime([
+            "2023-01-15", "2023-01-16", "2023-01-17", "2023-01-18", "2023-01-19"
+        ]),
+    })
+
+
+def test_profile(sample_dataframe):
+    """Test the profile convenience method."""
+    dataset = DataSet(df=sample_dataframe, name="test_table")
+    dataset.profile()
+
+    assert "table_profile" in dataset.results
+    table_profile = dataset.results["table_profile"]
+    assert table_profile is not None
+    assert table_profile.count == 5
+    assert set(table_profile.columns) == {"user_id", "product_name", "price", "purchase_date"}
+
+    assert "column_profiles" in dataset.results
+    column_profiles = dataset.results["column_profiles"]
+    assert column_profiles is not None
+    assert len(column_profiles) == 4
+
+
+def test_identify_datatypes(sample_dataframe):
+    """Test the identify_datatypes convenience method."""
+    dataset = DataSet(df=sample_dataframe, name="test_table")
+    dataset.profile()
+    dataset.identify_datatypes()
+
+    assert "column_datatypes_l1" in dataset.results
+    column_datatypes_l1 = dataset.results["column_datatypes_l1"]
+    assert column_datatypes_l1 is not None
+    assert len(column_datatypes_l1) == 4
+
+    assert "column_datatypes_l2" in dataset.results
+    column_datatypes_l2 = dataset.results["column_datatypes_l2"]
+    assert column_datatypes_l2 is not None
+    assert len(column_datatypes_l2) == 4
+
+
+def test_identify_keys(sample_dataframe):
+    """Test the identify_keys method."""
+    dataset = DataSet(df=sample_dataframe, name="test_table")
+    dataset.profile()
+    dataset.identify_datatypes()
+    dataset.identify_keys()
+
+    assert "key" in dataset.results
+    key = dataset.results["key"]
+    assert key is not None
+
+
+def test_generate_glossary(sample_dataframe):
+    """Test the generate_glossary method."""
+    dataset = DataSet(df=sample_dataframe, name="test_table")
+    dataset.profile()
+    dataset.identify_datatypes()
+    dataset.generate_glossary(domain="ecommerce")
+
+    assert "business_glossary_and_tags" in dataset.results
+    glossary = dataset.results["business_glossary_and_tags"]
+    assert glossary is not None
+    assert "table_glossary" in dataset.results
+    table_glossary = dataset.results["table_glossary"]
+    assert table_glossary is not None
+
+
+def test_save_yaml(sample_dataframe, tmp_path):
+    """Test the save_yaml method."""
+    dataset = DataSet(df=sample_dataframe, name="test_table")
+    dataset.profile()
+    dataset.identify_datatypes()
+    dataset.generate_glossary(domain="ecommerce")
+
+    file_path = tmp_path / "test_table.yml"
+    dataset.save_yaml(file_path=str(file_path))
+
+    assert file_path.exists()
+    with open(file_path, "r") as file:
+        content = file.read()
+        assert "sources" in content