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

title	description	weight	menu	influxdb/cloud-dedicated/tags	aliases	related	list_code_example
Use Python to query data with SQL	Use the `influxdb_client_3` Python module and SQL to query data stored in InfluxDB.	101	influxdb_cloud_dedicated parent name identifier sql-execute-queries Use Python query-with-python-sql	query flightsql python sql	/influxdb/cloud-dedicated/query-data/execute-queries/flight-sql/python/	/influxdb/cloud-dedicated/query-data/tools/pandas/ /influxdb/cloud-dedicated/query-data/tools/pyarrow/ /influxdb/cloud-dedicated/reference/sql/	```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="sql" ) # Return query results as a markdown table print(table.to_pandas().to_markdown()) ```

Use the InfluxDB influxdb_client_3 Python client library module and SQL to query data stored in InfluxDB. Execute queries and retrieve data over the Flight protocol, and then process data using common Python tools.

• 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

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
   

{{% /tab-content %}} {{% tab-content %}}

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
   

{{% /tab-content %}} {{< /tabs-wrapper >}}

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 influxdb3-python package provides the influxdb_client_3 module for integrating {{% cloud-name %}} with your Python code. The module supports writing data to InfluxDB and querying data using SQL or InfluxQL.

{{% note %}} To query data with InfluxQL and Python, see Use InfluxQL with Python. {{% /note %}}

Install the following dependencies:

{{< req type="key" text="Already installed in the Write data section" color="magenta" >}}

• influxdb3-python {{< req text="* " color="magenta" >}}: Provides the influxdb_client_3 module and also installs the pyarrow package for working with Arrow data returned from queries.
• pandas: Provides pandas modules for analyzing and manipulating data.
• tabulate: Provides the tabulate function for formatting tabular data.

Enter the following command in your terminal:

pip install influxdb3-python pandas tabulate

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 the influxdb_client_3 module to instantiate a client configured for an {{% cloud-name %}} bucket.

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
import pandas

# 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 {{% cloud-name %}} database.

Execute a query

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

• query: SQL query string to execute.
• language: sql

Example

The following example shows how to use SQL to select all fields in a measurement, and then output the results formatted as a Markdown table.

{{% 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="sql"
)

# 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