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from influxdb_client import Point, InfluxDBClient
from influxdb_client.client.util.date_utils_pandas import PandasDateTimeHelper
from influxdb_client.client.write_api import SYNCHRONOUS
"""
Set PandasDate helper which supports nanoseconds.
"""
import influxdb_client.client.util.date_utils as date_utils
date_utils.date_helper = PandasDateTimeHelper()
"""
Prepare client.
"""
with InfluxDBClient(url="http://localhost:8086", token="my-token", org="my-org") as client:
write_api = client.write_api(write_options=SYNCHRONOUS)
"""
Prepare data
"""
point = Point("h2o_feet") \
.field("water_level", 10) \
.tag("location", "pacific") \
.time('1996-02-25T21:20:00.001001231Z')
print(f'Time serialized with nanosecond precision: {point.to_line_protocol()}')
print()
write_api.write(bucket="my-bucket", record=point)
query_api = client.query_api()
"""
Query: using Stream
"""
query = '''
from(bucket:"my-bucket")
|> range(start: 0, stop: now())
|> filter(fn: (r) => r._measurement == "h2o_feet")
'''
records = query_api.query_stream(query)
for record in records:
print(f'Temperature in {record["location"]} is {record["_value"]} at time: {record["_time"]}')
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