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.
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:
This command loads the package and allows you to run cell magics on top of Jupyter.
And for pymysql, validate by running this command:
Please follow the instructions below to connect into your MindsDB via Jupysql and Jupyter.
You can use the Python code below to connect your Jupyter notebook (or lab) to Local MindsDB database (via Jupysql). Load the extension:
Connect to your DB:
Testing connection by listing the existing tables (pure SQL):
%sql show tables
Please note that we use the following connection details:
- Username is
- Password is left empty
- Host is
- Port is
- Database name is
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:***@127.0.0.1:47335/mindsdb 2 rows affected. Tables_in_mindsdb models models_versions
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.