docs-v2/content/influxdb/cloud-dedicated/query-data/influxql/execute-queries/python.md

title	description	weight	menu	influxdb/cloud-dedicated/tags	related	list_code_example
Use Python to query data with InfluxQL	Use Python and the `influxdb3-python` library to query data stored in InfluxDB with InfluxQL.	401	influxdb_cloud_dedicated parent name identifier influxql-execute-queries Use Python query-with-python-influxql	query influxql python	/influxdb/cloud-dedicated/process-data/tools/pandas/ /influxdb/cloud-dedicated/process-data/tools/pyarrow/ /influxdb/cloud-dedicated/reference/influxql/	```py from influxdb_client_3 import InfluxDBClient3 # Instantiate an InfluxDB client client = InfluxDBClient3( host='cluster-id.influxdb.io', token='DATABASE_TOKEN', database='DATABASE_NAME' ) # Execute the query and return an Arrow table table = client.query( query="SELECT * FROM home", language="influxql" ) # Return query results as a markdown table print(table.to_pandas().to_markdown()) ```

Use the influxdb3-python client library to query data stored in InfluxDB with InfluxQL. The influxdb3-client uses InfluxDB v3's Flight RPC protocol to query data from InfluxDB and return results in Apache Arrow format.

• Get started using Python to query InfluxDB
• Create a Python virtual environment
  • Install Python
  • Create a project virtual environment
  • Install Anaconda
• Query InfluxDB
  • Install the influxdb3-python library
  • Create an InfluxDB client
  • Execute a query

{{% warn %}}

InfluxQL feature support

InfluxQL is being rearchitected to work with the InfluxDB IOx storage engine. This process is ongoing and some InfluxQL features are still being implemented. For information about the current implementation status of InfluxQL features, see InfluxQL feature support. {{% /warn %}}

Get started using Python to query InfluxDB

This guide follows the recommended practice of using Python virtual environments. If you don't want to use virtual environments and you have Python installed, continue to Query InfluxDB.

Create a Python virtual environment

Python virtual environments keep the Python interpreter and dependencies for your project self-contained and isolated from other projects.

To install Python and create a virtual environment, choose one of the following options:

• Python venv: The venv module comes standard in Python as of version 3.5.

• Anaconda® Distribution: A Python/R data science distribution that provides Python and the conda package and environment manager.

  {{< tabs-wrapper >}} {{% tabs "small" %}} venv Anaconda {{% /tabs %}} {{% tab-content %}}

Install Python

1. Follow the Python installation instructions to install a recent version of the Python programming language for your system.

2. Check that you can run python and pip commands. pip is a package manager included in most Python distributions.

   In your terminal, enter the following commands:

   python --version
   

   pip --version
   

   Depending on your system, you may need to use version-specific commands--for example.

   python3 --version
   

   pip3 --version
   

   If neither pip nor pip<PYTHON_VERSION> works, follow one of the Pypa.io Pip installation methods for your system.

Create a project virtual environment

1. Create a directory for your Python project and change to the new directory--for example:

   mkdir ./PROJECT_DIRECTORY && cd $_
   

2. Use the Python venv module to create a virtual environment--for example:

   python -m venv envs/virtualenv-1
   

   venv creates the new virtual environment directory in your project.

3. To activate the new virtual environment in your terminal, run the source command and pass the file path of the virtual environment activate script:

   source envs/VIRTUAL_ENVIRONMENT_NAME/bin/activate
   

   For example:

   source envs/virtualenv-1/bin/activate
   

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Install Anaconda

1. Follow the Anaconda installation instructions for your system.

2. Check that you can run the conda command:

   conda
   

3. Use conda to create a virtual environment--for example:

   conda create --prefix envs/virtualenv-1 
   

   conda creates a virtual environment in a directory named ./envs/virtualenv-1.

4. To activate the new virtual environment, use the conda activate command and pass the directory path of the virtual environment:

   conda activate envs/VIRTUAL_ENVIRONMENT_NAME
   

   For example:

   conda activate ./envs/virtualenv-1
   

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When a virtual environment is activated, the name displays at the beginning of your terminal command line--for example:

{{% code-callout "(virtualenv-1)"%}}

(virtualenv-1) $ PROJECT_DIRECTORY

{{% /code-callout %}}

Query InfluxDB

1. Install the influxdb3-python library
2. Create an InfluxDB client
3. Execute a query

Install the influxdb3-python library

The influxdb_client_3 module provides a simple and convenient way to interact with {{< cloud-name >}} using Python. This module supports both writing data to InfluxDB and querying data using SQL or InfluxQL queries.

Installing inflxudb3-python also installs the pyarrow library that you'll use for working with Arrow data returned from queries.

In your terminal, use pip to install influxdb3-python:

pip install influxdb3-python

With influxdb3-python and pyarrow installed, you're ready to query and analyze data stored in an InfluxDB database.

Create an InfluxDB client

The following example shows how to use Python with influxdb3-python and to instantiate a client configured for an InfluxDB database.

In your editor, copy and paste the following sample code to a new file--for example, query-example.py:

{{% code-placeholders "DATABASE_(NAME|TOKEN)" %}}

# query-example.py

from influxdb_client_3 import InfluxDBClient3

# Instantiate an InfluxDBClient3 client configured for your database
client = InfluxDBClient3(
    host='cluster-id.influxdb.io',
    token='DATABASE_TOKEN',
    database='DATABASE_NAME'
)

{{% /code-placeholders %}}

Replace the following configuration values:

• {{% code-placeholder-key %}}DATABASE_TOKEN{{% /code-placeholder-key %}}: Your InfluxDB token with read permissions on the databases you want to query.
• {{% code-placeholder-key %}}DATABASE_NAME{{% /code-placeholder-key %}}: The name of your InfluxDB database.

Execute a query

To execute an InfluxQL query, call the client's query(query,language) method and specify the following arguments:

• query: InfluxQL query string to execute.
• language: influxql

Syntax

query(query: str, language: str)

Example

{{% code-placeholders "DATABASE_(NAME|TOKEN)" %}}

# query-example.py

from influxdb_client_3 import InfluxDBClient3

client = InfluxDBClient3(
    host='cluster-id.influxdb.io',
    token='DATABASE_TOKEN',
    database='DATABASE_NAME'
)

# Execute the query and return an Arrow table
table = client.query(
    query="SELECT * FROM home",
    language="influxql"
)

# Return query results as a markdown table
print(table.to_pandas().to_markdown())

{{% /code-placeholders %}}

Next, learn how to use Python tools to work with time series data:

• Use PyArrow
• Use pandas