Integrations¶

SQLAlchemy¶

Install SQLAlchemy

pip install sqlalchemy-exasol

Connect to Exasol database using SQLAlchemy

from sqlalchemy import create_engine
url = "exa+websocket://<user>:<password>@<host>:<port>/<schema>?CONNECTIONLCALL=en_US.UTF-8"
e = create_engine(url)
r = e.execute("select 42 from dual").fetchall()

Please also refer to sqlalchemy exasol documentation.

JupySQL¶

How to work with JupySQL in JupyterLab is described in Environments.

Pandas¶

Importing Data into Pandas¶

You can fetch data from Exasol into a Pandas DataFrame using pyexasol.

import pandas as pd

# Execute a query and fetch data into a Pandas DataFrame, Conn is an existing pyexasol connection.
df = conn.export_to_pandas('SELECT * FROM <your_table_name>')

# Display the DataFrame
print(df)

Exporting Data from Pandas to Exasol¶

You can also export data from a Pandas DataFrame to an Exasol table.

# Assume you have a Pandas DataFrame `df` you wish to export
conn.import_from_pandas(df, '<your_target_table_name>')

Ibis¶

Please refer to the IBIS documentation.

You can also watch this video for a step by step walk through of using Ibis with Exasol via AI Lab.