def test_heterogeneous_configs(self):
expected1 = pandas.DataFrame(data={'x': [3, 10]})
expected2 = pandas.DataFrame(data={'y': [4]})
expected3 = pandas.DataFrame(data={'x': ['b'], 'y': ['a']})
populate()
config1 = LoadConfig(source='dataframe',
destination='dataset',
dataframe=expected1,
data_name='a10')
config2 = LoadConfig(source='query',
destination='dataframe',
query='select 4 as y')
config3 = LoadConfig(source='query',
destination='bucket',
query="select 'b' as x, 'a' as y",
data_name='a11')
gpl = create_loader(bucket_dir_path=constants.bucket_subdir_path)
load_results = gpl.multi_load([config1, config2, config3])
self.assertEqual(len(load_results), 3)
self.assertTrue(load_results[0] is None)
self.assertTrue(load_results[2] is None)
computed1 = load.dataset_to_dataframe('a10')
self.assert_pandas_equal(expected1, computed1)
computed2 = load_results[1]
self.assert_pandas_equal(expected2, computed2)
blob_name = ids.build_blob_name_2('a11-000000000000.csv.gz')
computed3 = load.bucket_to_dataframe(blob_name, decompress=True)
self.assert_pandas_equal(expected3, computed3)
def test_query_to_dataframe(self):
expected = pandas.DataFrame(data={'x': [3, 2], 'y': ['a', 'b']})
populate()
gpl = create_loader(separator='#')
computed = gpl.load(
source='query',
destination='dataframe',
query="select 3 as x, 'a' as y union all select 2 as x, 'b' as y")
self.assert_pandas_equal(expected, computed)
def test_dataframe_to_dataset(self):
expected = pandas.DataFrame(data={'x': [1, 2, 3], 'y': [1, 2, 4]})
populate()
gpl = create_loader_quick_setup()
gpl.load(source='dataframe',
destination='dataset',
dataframe=expected,
data_name='a1')
computed = load.dataset_to_dataframe('a1')
self.assert_pandas_equal(expected, computed)
def test_config_repeated(self):
expected = pandas.DataFrame(data={'x': [3]})
populate()
config = LoadConfig(source='query',
destination='dataframe',
query='select 3 as x')
gpl = create_loader_quick_setup(
local_dir_path=constants.local_subdir_path)
computeds = gpl.multi_load(configs=[config] * 3)
for computed in computeds:
self.assert_pandas_equal(expected, computed)
def test_dataframe_to_bucket(self):
expected = pandas.DataFrame(data={'x': [1, 2, 3], 'y': [1, 2, 4]})
populate()
gpl = create_loader()
gpl.load(source='dataframe',
destination='bucket',
dataframe=expected,
data_name='a1')
blob_name = ids.build_blob_name_0('a1.csv.gz')
computed = load.bucket_to_dataframe(blob_name, decompress=True)
self.assert_pandas_equal(expected, computed)
def test_bucket_to_dataframe(self):
expected = pandas.DataFrame(data={'x': [3, 2], 'y': ['a', 'b']})
populate()
blob_name = ids.build_blob_name_2('a10')
load.dataframe_to_bucket(expected, blob_name)
gpl = create_loader(bq_client=None,
dataset_id=None,
bucket_dir_path=constants.bucket_subdir_path,
local_dir_path=constants.local_subdir_path)
computed = gpl.load(source='bucket',
destination='dataframe',
data_name='a10')
self.assert_pandas_equal(expected, computed)
def test_post_clear_dataframe_to_dataset(self):
populate()
blob_name = ids.build_blob_name_2('a10')
local_file_path = ids.build_local_file_path_0('a10')
self.assertTrue(exist.blob_exists(blob_name))
self.assertTrue(exist.local_file_exists(local_file_path))
gpl = create_loader_quick_setup(
bucket_dir_path=constants.bucket_subdir_path)
gpl.load(source='dataframe',
destination='dataset',
dataframe=pandas.DataFrame(data={'x': [1]}),
data_name='a10')
self.assertFalse(exist.blob_exists(blob_name))
self.assertFalse(exist.local_file_exists(local_file_path))
def test_post_clear_query_to_dataframe(self):
populate()
blob_name = ids.build_blob_name_0('a10')
local_file_path = ids.build_local_file_path_1('a10')
self.assertTrue(exist.table_exists('a10'))
self.assertTrue(exist.blob_exists(blob_name))
self.assertTrue(exist.local_file_exists(local_file_path))
gpl = create_loader(local_dir_path=constants.local_subdir_path)
gpl.load(source='query',
destination='dataframe',
query='select 3',
data_name='a10')
self.assertFalse(exist.table_exists('a10'))
self.assertFalse(exist.blob_exists(blob_name))
self.assertFalse(exist.local_file_exists(local_file_path))
def test_upload_download(self):
expected = pandas.DataFrame(data={'x': [1], 'y': [3]})
populate()
gpl = create_loader(bucket_dir_path=constants.bucket_subdir_path,
separator='#',
chunk_size=2**18,
timeout=15)
gpl.load(source='dataframe',
destination='dataset',
dataframe=expected,
data_name='a9')
query = f'select * from {constants.dataset_id}.a9'
computed = gpl.load(source='query',
destination='dataframe',
query=query)
self.assert_pandas_equal(expected, computed)
def test_no_skip_blank_lines(self):
df0 = pandas.DataFrame(data={'x': [3, numpy.nan]})
df1 = pandas.DataFrame(data={'x': [numpy.nan, 4]})
df2 = pandas.DataFrame(data={'x': [numpy.nan, 5], 'y': [numpy.nan, 6]})
df3 = pandas.DataFrame(data={'x': [7, numpy.nan], 'y': [8, numpy.nan]})
expecteds = [df0, df1, df2, df3]
populate()
query0 = 'select 3 as x union all select null as x'
query1 = 'select null as x union all select 4 as x'
query2 = 'select null as x, null as y union all ' \
'select 5 as x, 6 as y'
query3 = 'select 7 as x, 8 as y union all ' \
'select null as x, null as y'
queries = [query0, query1, query2, query3]
configs = []
for query in queries:
config = LoadConfig(source='query',
destination='dataframe',
query=query)
configs.append(config)
gpl = create_loader()
computed = gpl.multi_load(configs)
for df, dg in zip(expecteds, computed):
self.assert_pandas_equal(df, dg)
