def test_without_tags_and_fields_with_nan(self):
from influxdb_client.extras import pd, np
df = pd.DataFrame({
'a': np.arange(0., 3.),
'b': [0., np.nan, 1.],
}).set_index(
pd.to_datetime(
['2021-01-01 0:00', '2021-01-01 0:01', '2021-01-01 0:02']))
points = data_frame_to_list_of_points(
data_frame=df,
data_frame_measurement_name="test",
point_settings=PointSettings())
self.assertEqual(3, len(points))
self.assertEqual("test a=0.0,b=0.0 1609459200000000000", points[0])
self.assertEqual("test a=1.0 1609459260000000000", points[1])
self.assertEqual("test a=2.0,b=1.0 1609459320000000000", points[2])
def test_convert_data_frame(self):
from influxdb_client.extras import pd, np
num_rows=1500000
col_data={
'time': np.arange(0, num_rows, 1, dtype=int),
'col1': np.random.choice(['test_a', 'test_b', 'test_c'], size=(num_rows,)),
}
for n in range(2, 9):
col_data[f'col{n}'] = np.random.rand(num_rows)
data_frame = pd.DataFrame(data=col_data)
print(data_frame)
start = time.time()
data_frame_to_list_of_points(data_frame, PointSettings(),
data_frame_measurement_name='h2o_feet',
data_frame_tag_columns=['location'])
print("Time elapsed: ", (time.time() - start))
"""
url = 'http://localhost:8086'
token = 'my-token'
org = 'my-org'
bucket = 'my-bucket'
"""
Generate Dataframe
"""
print()
print("=== Generating DataFrame ===")
print()
dataframe_rows_count = 150_000
col_data = {
'time':
np.arange(0, dataframe_rows_count, 1, dtype=int),
'tag':
np.random.choice(['tag_a', 'tag_b', 'test_c'],
size=(dataframe_rows_count, )),
}
for n in range(2, 2999):
col_data[f'col{n}'] = random.randint(1, 10)
data_frame = pd.DataFrame(data=col_data).set_index('time')
print(data_frame)
"""
Ingest DataFrame
"""
print()
print("=== Ingesting DataFrame via batching API ===")
print()