def test_row_as_table_row(self):
schema_definition = [
('s', 'STRING'),
('i', 'INTEGER'),
('f', 'FLOAT'),
('b', 'BOOLEAN'),
('r', 'RECORD')]
data_defination = [
'abc',
123,
123.456,
True,
{'a': 'b'}]
str_def = '{"s": "abc", "i": 123, "f": 123.456, "b": true, "r": {"a": "b"}}'
schema = bigquery.TableSchema(
fields=[bigquery.TableFieldSchema(name=k, type=v)
for k, v in schema_definition])
coder = TableRowJsonCoder(table_schema=schema)
test_row = bigquery.TableRow(
f=[bigquery.TableCell(v=to_json_value(e)) for e in data_defination])
self.assertEqual(str_def, coder.encode(test_row))
self.assertEqual(test_row, coder.decode(coder.encode(test_row)))
# A coder without schema can still decode.
self.assertEqual(
test_row, TableRowJsonCoder().decode(coder.encode(test_row)))
def test_row_and_no_schema(self):
coder = TableRowJsonCoder()
test_row = bigquery.TableRow(
f=[bigquery.TableCell(v=to_json_value(e))
for e in ['abc', 123, 123.456, True]])
with self.assertRaises(AttributeError) as ctx:
coder.encode(test_row)
self.assertTrue(
ctx.exception.message.startswith('The TableRowJsonCoder requires'))
def json_compliance_exception(self, value):
with self.assertRaises(ValueError) as exn:
schema_definition = [('f', 'FLOAT')]
schema = bigquery.TableSchema(
fields=[bigquery.TableFieldSchema(name=k, type=v)
for k, v in schema_definition])
coder = TableRowJsonCoder(table_schema=schema)
test_row = bigquery.TableRow(
f=[bigquery.TableCell(v=to_json_value(value))])
coder.encode(test_row)
self.assertTrue(bigquery.JSON_COMPLIANCE_ERROR in exn.exception.message)
def decode(self, encoded_table_row):
od = json.loads(
encoded_table_row, object_pairs_hook=collections.OrderedDict)
return bigquery.TableRow(
f=[bigquery.TableCell(v=to_json_value(e)) for e in od.itervalues()])
def get_test_rows(self):
now = time.time()
dt = datetime.datetime.utcfromtimestamp(float(now))
ts = dt.strftime('%Y-%m-%d %H:%M:%S.%f UTC')
expected_rows = [
{
'i': 1,
's': 'abc',
'f': 2.3,
'b': True,
't': ts,
'dt': '2016-10-31',
'ts': '22:39:12.627498',
'dt_ts': '2008-12-25T07:30:00',
'r': {'s2': 'b'},
'rpr': [{'s3': 'c', 'rpr2': [{'rs': ['d', 'e'], 's4': None}]}]
},
{
'i': 10,
's': 'xyz',
'f': -3.14,
'b': False,
'rpr': [],
't': None,
'dt': None,
'ts': None,
'dt_ts': None,
'r': None,
}]
nested_schema = [
bigquery.TableFieldSchema(
name='s2', type='STRING', mode='NULLABLE')]
nested_schema_2 = [
bigquery.TableFieldSchema(
name='s3', type='STRING', mode='NULLABLE'),
bigquery.TableFieldSchema(
name='rpr2', type='RECORD', mode='REPEATED', fields=[
bigquery.TableFieldSchema(
name='rs', type='STRING', mode='REPEATED'),
bigquery.TableFieldSchema(
name='s4', type='STRING', mode='NULLABLE')])]
schema = bigquery.TableSchema(
fields=[
bigquery.TableFieldSchema(
name='b', type='BOOLEAN', mode='REQUIRED'),
bigquery.TableFieldSchema(
name='f', type='FLOAT', mode='REQUIRED'),
bigquery.TableFieldSchema(
name='i', type='INTEGER', mode='REQUIRED'),
bigquery.TableFieldSchema(
name='s', type='STRING', mode='REQUIRED'),
bigquery.TableFieldSchema(
name='t', type='TIMESTAMP', mode='NULLABLE'),
bigquery.TableFieldSchema(
name='dt', type='DATE', mode='NULLABLE'),
bigquery.TableFieldSchema(
name='ts', type='TIME', mode='NULLABLE'),
bigquery.TableFieldSchema(
name='dt_ts', type='DATETIME', mode='NULLABLE'),
bigquery.TableFieldSchema(
name='r', type='RECORD', mode='NULLABLE',
fields=nested_schema),
bigquery.TableFieldSchema(
name='rpr', type='RECORD', mode='REPEATED',
fields=nested_schema_2)])
table_rows = [
bigquery.TableRow(f=[
bigquery.TableCell(v=to_json_value('true')),
bigquery.TableCell(v=to_json_value(str(2.3))),
bigquery.TableCell(v=to_json_value(str(1))),
bigquery.TableCell(v=to_json_value('abc')),
# For timestamps cannot use str() because it will truncate the
# number representing the timestamp.
bigquery.TableCell(v=to_json_value('%f' % now)),
bigquery.TableCell(v=to_json_value('2016-10-31')),
bigquery.TableCell(v=to_json_value('22:39:12.627498')),
bigquery.TableCell(v=to_json_value('2008-12-25T07:30:00')),
# For record we cannot use dict because it doesn't create nested
# schemas correctly so we have to use this f,v based format
bigquery.TableCell(v=to_json_value({'f': [{'v': 'b'}]})),
bigquery.TableCell(v=to_json_value([{'v':{'f':[{'v': 'c'}, {'v':[
{'v':{'f':[{'v':[{'v':'d'}, {'v':'e'}]}, {'v':None}]}}]}]}}]))
]),
bigquery.TableRow(f=[
bigquery.TableCell(v=to_json_value('false')),
bigquery.TableCell(v=to_json_value(str(-3.14))),
bigquery.TableCell(v=to_json_value(str(10))),
bigquery.TableCell(v=to_json_value('xyz')),
bigquery.TableCell(v=None),
bigquery.TableCell(v=None),
bigquery.TableCell(v=None),
bigquery.TableCell(v=None),
bigquery.TableCell(v=None),
bigquery.TableCell(v=to_json_value([]))])]
return table_rows, schema, expected_rows