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feat(bigquery): expose date_as_object parameter to users (#150)
* feat(bigquery): expose date_as_object parameter for users

* feat(bigquery): nit

* feat(bigquery): add unit test for date as object without pyarrow

* feat(bigquery): docs fixed

* feat(bigquery): nit

* feat(bigquery): nit
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HemangChothani committed Jun 29, 2020
1 parent bc33a67 commit cbd831e08024a67148723afd49e1db085e0a862c
Showing with 96 additions and 8 deletions.
  1. +11 −3 google/cloud/bigquery/job.py
  2. +13 −4 google/cloud/bigquery/table.py
  3. +72 −1 tests/unit/test_job.py
@@ -3320,6 +3320,7 @@ def to_dataframe(
dtypes=None,
progress_bar_type=None,
create_bqstorage_client=True,
date_as_object=True,
):
"""Return a pandas DataFrame from a QueryJob
@@ -3350,16 +3351,22 @@ def to_dataframe(
for details.
..versionadded:: 1.11.0
create_bqstorage_client (bool):
Optional. If ``True`` (default), create a BigQuery Storage API
client using the default API settings. The BigQuery Storage API
create_bqstorage_client (Optional[bool]):
If ``True`` (default), create a BigQuery Storage API client
using the default API settings. The BigQuery Storage API
is a faster way to fetch rows from BigQuery. See the
``bqstorage_client`` parameter for more information.
This argument does nothing if ``bqstorage_client`` is supplied.
..versionadded:: 1.24.0
date_as_object (Optional[bool]):
If ``True`` (default), cast dates to objects. If ``False``, convert
to datetime64[ns] dtype.
..versionadded:: 1.26.0
Returns:
A :class:`~pandas.DataFrame` populated with row data and column
headers from the query results. The column headers are derived
@@ -3373,6 +3380,7 @@ def to_dataframe(
dtypes=dtypes,
progress_bar_type=progress_bar_type,
create_bqstorage_client=create_bqstorage_client,
date_as_object=date_as_object,
)

def __iter__(self):
@@ -1633,6 +1633,7 @@ def to_dataframe(
dtypes=None,
progress_bar_type=None,
create_bqstorage_client=True,
date_as_object=True,
):
"""Create a pandas DataFrame by loading all pages of a query.
@@ -1673,16 +1674,22 @@ def to_dataframe(
progress bar as a graphical dialog box.
..versionadded:: 1.11.0
create_bqstorage_client (bool):
Optional. If ``True`` (default), create a BigQuery Storage API
client using the default API settings. The BigQuery Storage API
create_bqstorage_client (Optional[bool]):
If ``True`` (default), create a BigQuery Storage API client
using the default API settings. The BigQuery Storage API
is a faster way to fetch rows from BigQuery. See the
``bqstorage_client`` parameter for more information.
This argument does nothing if ``bqstorage_client`` is supplied.
..versionadded:: 1.24.0
date_as_object (Optional[bool]):
If ``True`` (default), cast dates to objects. If ``False``, convert
to datetime64[ns] dtype.
..versionadded:: 1.26.0
Returns:
pandas.DataFrame:
A :class:`~pandas.DataFrame` populated with row data and column
@@ -1722,7 +1729,7 @@ def to_dataframe(
bqstorage_client=bqstorage_client,
create_bqstorage_client=create_bqstorage_client,
)
df = record_batch.to_pandas()
df = record_batch.to_pandas(date_as_object=date_as_object)
for column in dtypes:
df[column] = pandas.Series(df[column], dtype=dtypes[column])
return df
@@ -1799,6 +1806,7 @@ def to_dataframe(
dtypes=None,
progress_bar_type=None,
create_bqstorage_client=True,
date_as_object=True,
):
"""Create an empty dataframe.
@@ -1807,6 +1815,7 @@ def to_dataframe(
dtypes (Any): Ignored. Added for compatibility with RowIterator.
progress_bar_type (Any): Ignored. Added for compatibility with RowIterator.
create_bqstorage_client (bool): Ignored. Added for compatibility with RowIterator.
date_as_object (bool): Ignored. Added for compatibility with RowIterator.
Returns:
pandas.DataFrame: An empty :class:`~pandas.DataFrame`.
@@ -5504,7 +5504,15 @@ def test_to_dataframe_column_dtypes(self):
},
}
row_data = [
["1.4338368E9", "420", "1.1", "1.77", "Cash", "true", "1999-12-01"],
[
"1.4338368E9",
"420",
"1.1",
"1.77",
"Cto_dataframeash",
"true",
"1999-12-01",
],
["1.3878117E9", "2580", "17.7", "28.5", "Cash", "false", "1953-06-14"],
["1.3855653E9", "2280", "4.4", "7.1", "Credit", "true", "1981-11-04"],
]
@@ -5533,6 +5541,69 @@ def test_to_dataframe_column_dtypes(self):
self.assertEqual(df.complete.dtype.name, "bool")
self.assertEqual(df.date.dtype.name, "object")

@unittest.skipIf(pyarrow is None, "Requires `pyarrow`")
@unittest.skipIf(pandas is None, "Requires `pandas`")
def test_to_dataframe_column_date_dtypes(self):
begun_resource = self._make_resource()
query_resource = {
"jobComplete": True,
"jobReference": {"projectId": self.PROJECT, "jobId": self.JOB_ID},
"totalRows": "1",
"schema": {"fields": [{"name": "date", "type": "DATE"}]},
}
row_data = [
["1999-12-01"],
]
rows = [{"f": [{"v": field} for field in row]} for row in row_data]
query_resource["rows"] = rows
done_resource = copy.deepcopy(begun_resource)
done_resource["status"] = {"state": "DONE"}
connection = _make_connection(
begun_resource, query_resource, done_resource, query_resource
)
client = _make_client(project=self.PROJECT, connection=connection)
job = self._make_one(self.JOB_ID, self.QUERY, client)
df = job.to_dataframe(date_as_object=False, create_bqstorage_client=False)

self.assertIsInstance(df, pandas.DataFrame)
self.assertEqual(len(df), 1) # verify the number of rows
exp_columns = [field["name"] for field in query_resource["schema"]["fields"]]
self.assertEqual(list(df), exp_columns) # verify the column names

self.assertEqual(df.date.dtype.name, "datetime64[ns]")

@unittest.skipIf(pandas is None, "Requires `pandas`")
def test_to_dataframe_column_date_dtypes_wo_pyarrow(self):
begun_resource = self._make_resource()
query_resource = {
"jobComplete": True,
"jobReference": {"projectId": self.PROJECT, "jobId": self.JOB_ID},
"totalRows": "1",
"schema": {"fields": [{"name": "date", "type": "DATE"}]},
}
row_data = [
["1999-12-01"],
]
rows = [{"f": [{"v": field} for field in row]} for row in row_data]
query_resource["rows"] = rows
done_resource = copy.deepcopy(begun_resource)
done_resource["status"] = {"state": "DONE"}
connection = _make_connection(
begun_resource, query_resource, done_resource, query_resource
)
client = _make_client(project=self.PROJECT, connection=connection)
job = self._make_one(self.JOB_ID, self.QUERY, client)

with mock.patch("google.cloud.bigquery.table.pyarrow", None):
df = job.to_dataframe(date_as_object=False, create_bqstorage_client=False)

self.assertIsInstance(df, pandas.DataFrame)
self.assertEqual(len(df), 1) # verify the number of rows
exp_columns = [field["name"] for field in query_resource["schema"]["fields"]]
self.assertEqual(list(df), exp_columns) # verify the column names

self.assertEqual(df.date.dtype.name, "object")

@unittest.skipIf(pandas is None, "Requires `pandas`")
@unittest.skipIf(tqdm is None, "Requires `tqdm`")
@mock.patch("tqdm.tqdm")

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