feat: add support and tests for struct fields (#146)

* feat(bigquery): add support and tests for struct fields

* feat(bigquery): bump pyarrow version for python3

* feat(bigquery): nit

google/cloud/bigquery/_pandas_helpers.py

@@ -287,13 +287,14 @@ def dataframe_to_bq_schema(dataframe, bq_schema):
     """
     if bq_schema:
         bq_schema = schema._to_schema_fields(bq_schema)
-        for field in bq_schema:
-            if field.field_type in schema._STRUCT_TYPES:
-                raise ValueError(
-                    "Uploading dataframes with struct (record) column types "
-                    "is not supported. See: "
-                    "https://github.com/googleapis/google-cloud-python/issues/8191"
-                )
+        if six.PY2:
+            for field in bq_schema:
+                if field.field_type in schema._STRUCT_TYPES:
+                    raise ValueError(
+                        "Uploading dataframes with struct (record) column types "
+                        "is not supported under Python2. See: "
+                        "https://github.com/googleapis/python-bigquery/issues/21"
+                    )
         bq_schema_index = {field.name: field for field in bq_schema}
         bq_schema_unused = set(bq_schema_index.keys())
     else:

setup.py

@@ -47,10 +47,8 @@
     ],
     "pandas": ["pandas>=0.17.1"],
     # Exclude PyArrow dependency from Windows Python 2.7.
-    'pyarrow: platform_system != "Windows" or python_version >= "3.4"': [
-        # Bad Linux release for 0.14.0.
-        # https://issues.apache.org/jira/browse/ARROW-5868
-        "pyarrow>=0.4.1, != 0.14.0"
+    'pyarrow: platform_system != "Windows" or python_version >= "3.5"': [
+        "pyarrow>=0.17.0"
     ],
     "tqdm": ["tqdm >= 4.0.0, <5.0.0dev"],
     "fastparquet": [

tests/system.py

@@ -131,6 +131,8 @@
 
 PANDAS_MINIMUM_VERSION = pkg_resources.parse_version("1.0.0")
 PANDAS_INSTALLED_VERSION = pkg_resources.get_distribution("pandas").parsed_version
+PYARROW_MINIMUM_VERSION = pkg_resources.parse_version("0.17.0")
+PYARROW_INSTALLED_VERSION = pkg_resources.get_distribution("pyarrow").parsed_version
 
 
 def _has_rows(result):
@@ -1075,6 +1077,48 @@ def test_load_table_from_dataframe_w_explicit_schema(self):
         self.assertEqual(tuple(table.schema), table_schema)
         self.assertEqual(table.num_rows, 3)
 
+    @unittest.skipIf(
+        pyarrow is None or PYARROW_INSTALLED_VERSION < PYARROW_MINIMUM_VERSION,
+        "Only `pyarrow version >=0.17.0` is supported",
+    )
+    @unittest.skipIf(pandas is None, "Requires `pandas`")
+    def test_load_table_from_dataframe_w_struct_datatype(self):
+        """Test that a DataFrame with struct datatype can be uploaded if a
+        BigQuery schema is specified.
+
+        https://github.com/googleapis/python-bigquery/issues/21
+        """
+        dataset_id = _make_dataset_id("bq_load_test")
+        self.temp_dataset(dataset_id)
+        table_id = "{}.{}.load_table_from_dataframe_w_struct_datatype".format(
+            Config.CLIENT.project, dataset_id
+        )
+        table_schema = [
+            bigquery.SchemaField(
+                "bar",
+                "RECORD",
+                fields=[
+                    bigquery.SchemaField("id", "INTEGER", mode="REQUIRED"),
+                    bigquery.SchemaField("age", "INTEGER", mode="REQUIRED"),
+                ],
+                mode="REQUIRED",
+            ),
+        ]
+        table = retry_403(Config.CLIENT.create_table)(
+            Table(table_id, schema=table_schema)
+        )
+        self.to_delete.insert(0, table)
+
+        df_data = [{"id": 1, "age": 21}, {"id": 2, "age": 22}, {"id": 2, "age": 23}]
+        dataframe = pandas.DataFrame(data={"bar": df_data}, columns=["bar"])
+
+        load_job = Config.CLIENT.load_table_from_dataframe(dataframe, table_id)
+        load_job.result()
+
+        table = Config.CLIENT.get_table(table_id)
+        self.assertEqual(table.schema, table_schema)
+        self.assertEqual(table.num_rows, 3)
+
     def test_load_table_from_json_basic_use(self):
         table_schema = (
             bigquery.SchemaField("name", "STRING", mode="REQUIRED"),

tests/unit/test_client.py

@@ -7373,19 +7373,22 @@ def test_load_table_from_dataframe_w_nullable_int64_datatype_automatic_schema(se
 
     @unittest.skipIf(pandas is None, "Requires `pandas`")
     @unittest.skipIf(pyarrow is None, "Requires `pyarrow`")
-    def test_load_table_from_dataframe_struct_fields_error(self):
+    def test_load_table_from_dataframe_struct_fields(self):
+        from google.cloud.bigquery.client import _DEFAULT_NUM_RETRIES
         from google.cloud.bigquery import job
         from google.cloud.bigquery.schema import SchemaField
 
         client = self._make_client()
 
-        records = [{"float_column": 3.14, "struct_column": [{"foo": 1}, {"bar": -1}]}]
-        dataframe = pandas.DataFrame(data=records)
+        records = [(3.14, {"foo": 1, "bar": 1})]
+        dataframe = pandas.DataFrame(
+            data=records, columns=["float_column", "struct_column"]
+        )
 
         schema = [
             SchemaField("float_column", "FLOAT"),
             SchemaField(
-                "agg_col",
+                "struct_column",
                 "RECORD",
                 fields=[SchemaField("foo", "INTEGER"), SchemaField("bar", "INTEGER")],
             ),
@@ -7396,14 +7399,49 @@ def test_load_table_from_dataframe_struct_fields_error(self):
             "google.cloud.bigquery.client.Client.load_table_from_file", autospec=True
         )
 
-        with pytest.raises(ValueError) as exc_info, load_patch:
-            client.load_table_from_dataframe(
-                dataframe, self.TABLE_REF, job_config=job_config, location=self.LOCATION
+        if six.PY2:
+            with pytest.raises(ValueError) as exc_info, load_patch:
+                client.load_table_from_dataframe(
+                    dataframe,
+                    self.TABLE_REF,
+                    job_config=job_config,
+                    location=self.LOCATION,
+                )
+
+            err_msg = str(exc_info.value)
+            assert "struct" in err_msg
+            assert "not support" in err_msg
+
+        else:
+            get_table_patch = mock.patch(
+                "google.cloud.bigquery.client.Client.get_table",
+                autospec=True,
+                side_effect=google.api_core.exceptions.NotFound("Table not found"),
+            )
+            with load_patch as load_table_from_file, get_table_patch:
+                client.load_table_from_dataframe(
+                    dataframe,
+                    self.TABLE_REF,
+                    job_config=job_config,
+                    location=self.LOCATION,
+                )
+
+            load_table_from_file.assert_called_once_with(
+                client,
+                mock.ANY,
+                self.TABLE_REF,
+                num_retries=_DEFAULT_NUM_RETRIES,
+                rewind=True,
+                job_id=mock.ANY,
+                job_id_prefix=None,
+                location=self.LOCATION,
+                project=None,
+                job_config=mock.ANY,
             )
 
-        err_msg = str(exc_info.value)
-        assert "struct" in err_msg
-        assert "not support" in err_msg
+            sent_config = load_table_from_file.mock_calls[0][2]["job_config"]
+            assert sent_config.source_format == job.SourceFormat.PARQUET
+            assert sent_config.schema == schema
 
     @unittest.skipIf(pandas is None, "Requires `pandas`")
     @unittest.skipIf(pyarrow is None, "Requires `pyarrow`")