ML for Developers

tests/data/test_dataset.py

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+def test_dataset(df):
+    """Test dataset quality and integrity."""
+    column_list = ["id", "created_on", "title", "description", "tag"]
+    df.expect_table_columns_to_match_ordered_list(column_list=column_list)  # schema adherence
+    tags = ["computer-vision", "natural-language-processing", "mlops", "other"]
+    df.expect_column_values_to_be_in_set(column="tag", value_set=tags)  # expected labels
+    df.expect_compound_columns_to_be_unique(column_list=["title", "description"])  # data leaks
+    df.expect_column_values_to_not_be_null(column="tag")  # missing values
+    df.expect_column_values_to_be_unique(column="id")  # unique values
+    df.expect_column_values_to_be_of_type(column="title", type_="str")  # type adherence
+
+    # Expectation suite
+    expectation_suite = df.get_expectation_suite(discard_failed_expectations=False)
+    results = df.validate(expectation_suite=expectation_suite, only_return_failures=True).to_json_dict()
+    assert results["success"]