Python Flight client
Apache Arrow Python bindings integrate with Python scripts and applications to query data stored in InfluxDB.
Use InfluxDB 3 client libraries
We recommend using the influxdb3-python Python client library for integrating InfluxDB 3 with your Python application code.
InfluxDB 3 client libraries wrap Apache Arrow Flight clients and provide convenient methods for writing, querying, and processing data stored in InfluxDB Cloud Serverless. Client libraries can query using SQL or InfluxQL.
The following examples show how to use the pyarrow.flight and pandas Python modules to query and format data stored in an InfluxDB Cloud Serverless bucket:
# Using pyarrow>=12.0.0 FlightClient
from pyarrow.flight import FlightClient, Ticket, FlightCallOptions
import json
import pandas
import tabulate
# Downsampling query groups data into 2-hour bins
sql="""
SELECT DATE_BIN(INTERVAL '2 hours',
time,
'1970-01-01T00:00:00Z') AS time,
room,
selector_max(temp, time)['value'] AS 'max temp',
selector_min(temp, time)['value'] AS 'min temp',
avg(temp) AS 'average temp'
FROM home
GROUP BY
1,
room
ORDER BY room, 1"""
flight_ticket = Ticket(json.dumps({
"namespace_name": "BUCKET_NAME",
"sql_query": sql,
"query_type": "sql"
}))
token = (b"authorization", bytes(f"Bearer API_TOKEN".encode('utf-8')))
options = FlightCallOptions(headers=[token])
client = FlightClient(f"grpc+tls://cloud2.influxdata.com:443")
reader = client.do_get(flight_ticket, options)
arrow_table = reader.read_all()
# Use pyarrow and pandas to view and analyze data
data_frame = arrow_table.to_pandas()
print(data_frame.to_markdown())# Using pyarrow>=12.0.0 FlightClient
from pyarrow.flight import FlightClient, Ticket, FlightCallOptions
import json
import pandas
import tabulate
# Downsampling query groups data into 2-hour bins
influxql="""
SELECT FIRST(temp)
FROM home
WHERE room = 'kitchen'
AND time >= now() - 100d
AND time <= now() - 10d
GROUP BY time(2h)"""
flight_ticket = Ticket(json.dumps({
"namespace_name": "BUCKET_NAME",
"sql_query": influxql,
"query_type": "influxql"
}))
token = (b"authorization", bytes(f"Bearer API_TOKEN".encode('utf-8')))
options = FlightCallOptions(headers=[token])
client = FlightClient(f"grpc+tls://cloud2.influxdata.com:443")
reader = client.do_get(flight_ticket, options)
arrow_table = reader.read_all()
# Use pyarrow and pandas to view and analyze data
data_frame = arrow_table.to_pandas()
print(data_frame.to_markdown())Replace the following:
BUCKET_NAME: your InfluxDB Cloud Serverless bucketAPI_TOKEN: a token with sufficient permissions to the bucket
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Thank you for being part of our community! We welcome and encourage your feedback and bug reports for InfluxDB Cloud Serverless and this documentation. To find support, use the following resources:
Customers with an annual or support contract can contact InfluxData Support.