Documentation

Python Flight SQL DBAPI client

The Python flightsql-dbapi Flight SQL DBAPI library integrates with Python applications using SQL to query data stored in an InfluxDB 3 Enterprise database. The flightsql-dbapi library uses the Flight SQL protocol to query and retrieve data.

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 3 Enterprise. Client libraries can query using SQL or InfluxQL.

Installation

The flightsql-dbapi Flight SQL library for Python provides a DB API 2 interface and SQLAlchemy dialect for Flight SQL. Installing flightsql-dbapi also installs the pyarrow library that you’ll use for working with Arrow data.

In your terminal, use pip to install flightsql-dbapi:

pip install flightsql-dbapi

Importing the module

The flightsql-dbapi package provides the flightsql module. From the module, import the FlightSQLClient class method:

from flightsql import FlightSQLClient
  • flightsql.FlightSQLClient class: an interface for initializing a client and interacting with a Flight SQL server.

API reference

Class FlightSQLClient

Provides an interface for initializing a client and interacting with a Flight SQL server.

Syntax

__init__(self, host=None, token=None, metadata=None, features=None)

Initializes and returns a FlightSQLClient instance for interacting with the server.

Initialize a client

The following example shows how to use Python with flightsql-dbapi and the DB API 2 interface to instantiate a Flight SQL client configured for an InfluxDB database.

from flightsql import FlightSQLClient

# Instantiate a FlightSQLClient configured for a database
client = FlightSQLClient(host='localhost:8181',
                        token='
DATABASE_TOKEN
'
,
metadata={'database': '
DATABASE_NAME
'
},
features={'metadata-reflection': 'true'})

Replace the following:

  • DATABASE_TOKEN: an InfluxDB 3 Enterprise database token with read permissions on the databases you want to query
  • DATABASE_NAME: the name of your InfluxDB 3 Enterprise database

Instance methods

FlightSQLClient.execute

Sends a Flight SQL RPC request to execute the specified SQL Query.

Syntax

execute(query: str, call_options: Optional[FlightSQLCallOptions] = None)

Example

# Execute the query
info = client.execute("SELECT * FROM home")

The response contains a flight.FlightInfo object that contains metadata and an endpoints: [...] list. Each endpoint contains the following:

  • A list of addresses where you can retrieve query result data.
  • A ticket value that identifies the data to retrieve.

FlightSQLClient.do_get

Passes a Flight ticket (obtained from a FlightSQLClient.execute response) and retrieves Arrow data identified by the ticket. Returns a pyarrow.flight.FlightStreamReader for streaming the data.

Syntax

 do_get(ticket, call_options: Optional[FlightSQLCallOptions] = None)

Example

The following sample shows how to use Python with flightsql-dbapi and pyarrow to query InfluxDB and retrieve data.

from flightsql import FlightSQLClient

# Instantiate a FlightSQLClient configured for a database
client = FlightSQLClient(host='localhost:8181',
    token='DATABASE_TOKEN',
    metadata={'database': 'DATABASE_NAME'},
    features={'metadata-reflection': 'true'})

# Execute the query to retrieve FlightInfo
info = client.execute("SELECT * FROM home")

# Extract the token for retrieving data
ticket = info.endpoints[0].ticket

# Use the ticket to request the Arrow data stream.
# Return a FlightStreamReader for streaming the results.
reader = client.do_get(ticket)

# Read all data to a pyarrow.Table
table = reader.read_all()

print(table)

do_get(ticket) returns a pyarrow.flight.FlightStreamReader for streaming Arrow record batches.

To read data from the stream, call one of the following FlightStreamReader methods:

  • read_all(): Read all record batches as a pyarrow.Table.
  • read_chunk(): Read the next RecordBatch and metadata.
  • read_pandas(): Read all record batches and convert them to a pandas.DataFrame.

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New in InfluxDB 3.6

Key enhancements in InfluxDB 3.6 and the InfluxDB 3 Explorer 1.4.

See the Blog Post

InfluxDB 3.6 is now available for both Core and Enterprise. This release introduces the 1.4 update to InfluxDB 3 Explorer, featuring the beta launch of Ask AI, along with new capabilities for simple startup and expanded functionality in the Processing Engine.

For more information, check out:

InfluxDB Docker latest tag changing to InfluxDB 3 Core

On February 3, 2026, the latest tag for InfluxDB Docker images will point to InfluxDB 3 Core. To avoid unexpected upgrades, use specific version tags in your Docker deployments.

If using Docker to install and run InfluxDB, the latest tag will point to InfluxDB 3 Core. To avoid unexpected upgrades, use specific version tags in your Docker deployments. For example, if using Docker to run InfluxDB v2, replace the latest version tag with a specific version tag in your Docker pull command–for example:

docker pull influxdb:2