Jupysql - full SQL client on Jupyter. It allows you to run SQL and plot large datasets in Jupyter via a %sql and %%sql magics. It also allows users plotting the data directly from the DB ( via %sqlplot magics).

Jupysql facilitates working with databases and Jupyter. You can download it here or run a pip install jupysql.

You can consider an option to interact with MindsDB directly from MySQL CLI or Postgres CLI.

How to Connect


  • Make sure you have jupysql installed: To install it, run pip install jupysql
  • Make sure you have pymysql installed: To install it, run pip install pymysql

You can easily verify the installation of jupysql by running this code:

%load_ext sql

This command loads the package and allows you to run cell magics on top of Jupyter.

And for pymysql, validate by running this command:

import pymysql

Please follow the instructions below to connect into your MindsDB via Jupysql and Jupyter.

  • Local MindsDB

  • MindsDB Cloud

  • MindsDB Pro

You can use the Python code below to connect your Jupyter notebook (or lab) to Local MindsDB database (via Jupysql). Load the extension:

%load_ext sql

Connect to your DB:

%sql mysql+pymysql://mindsdb:@

Testing connection by listing the existing tables (pure SQL):

%sql show tables

Please note that we use the following connection details:

  • Username is mindsdb
  • Password is left empty
  • Host is
  • Port is 47335
  • Database name is mindsdb

Docker - connecting to docker might have a different port.

Create a database connection and execute the code above. On success, only the last command which lists the tables will output. The expected output is:

*  mysql+pymysql://mindsdb:***@
2 rows affected.

What’s Next?

Now that you are all set, we recommend you check out our Tutorials and Community Tutorials sections, where you’ll find various examples of regression, classification, and time series predictions with MindsDB.

To learn more about MindsDB itself, follow the guide on MindsDB database structure. Also, don’t miss out on the remaining pages from the SQL API section, as they explain a common SQL syntax with examples.

Have fun!