jupysql

library0.11.1pypypiunverified

JupySQL (version 0.11.1) enhances SQL interaction within Jupyter notebooks, allowing users to connect to various databases and execute queries directly using IPython magic commands. It supports advanced features like variable interpolation, caching, and data visualization. The project is actively maintained with frequent releases, typically every few weeks.

database data

pip install jupysql

github ↗package ↗homepage ↗

INSTALL

IMPORT

SIG · JUPYSQL

jupysql

databasepythonv0.11.1

Install

6.0s avg

Import

—

Disk

65MB

Pass rate

10/ 10

Env Coverage10 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v0.11.1 · pip install

no network on importno background threads

Install × environment matrix

Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux

musl

py 3.10–3.920 runs

installs and imports cleanly · install 0.0s · import 0.000s · 66.9MB

glibc

py 3.10–3.920 runs

installs and imports cleanly · install 6.0s · import 0.000s · 66MB

65MB installed

● package 65MB

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

sql

✓ import jupysql

✗ import sql

This quickstart demonstrates how to load the JupySQL extension, connect to an in-memory SQLite database, create a table, insert data, and execute a simple SQL query using the `%sql` and `%%sql` magic commands.

# Load the JupySQL extension %load_ext sql # Connect to an in-memory SQLite database %sql sqlite:///:memory: # Create a table and insert some data %%sql CREATE TABLE employees ( id INTEGER PRIMARY KEY, name TEXT, department TEXT, salary INTEGER ); INSERT INTO employees (id, name, department, salary) VALUES (1, 'Alice', 'Sales', 50000), (2, 'Bob', 'Marketing', 60000), (3, 'Charlie', 'Sales', 55000); # Query the data %sql SELECT * FROM employees WHERE department = 'Sales';

Debug

Known issues

breakingThe `jupysql.configure` function's arguments `display_limit` and `style` were changed. `display_limit` was renamed to `result_limit`, and `style` was moved to `jupysql.plot.configure_styles`.

fix

Update your `jupysql.configure` calls:
- Replace `display_limit` with `result_limit`.
- For style configuration, use `from jupysql import plot; plot.configure_styles(...)`.

affects: Prior to 0.10.0

gotchaJupySQL's primary functionality relies on IPython magic commands (`%sql`, `%%sql`). These require `%load_ext sql` to be run at the beginning of each new notebook or IPython session.

fix

Always include `%load_ext sql` as the first line in your Jupyter notebooks or when starting an interactive IPython session where you intend to use JupySQL magic commands.

affects: All versions

gotchaJupySQL uses `{{variable}}` syntax for Python variable interpolation within SQL queries, which differs from standard f-strings or `.format()` methods.

fix

When embedding Python variables into SQL queries, use the double curly brace syntax: `my_var = 'Sales'; %sql SELECT * FROM employees WHERE department = '{{my_var}}'`.

affects: All versions

Upgrade

Version history

0.11.1latest on PyPI · released Mar 25, 2025

Audit

Dependencies

sqlalchemyrequiredCore ORM and SQL toolkit used for database connectivity.

psycopg2optionalPostgreSQL driver. Install via `jupysql[postgres]` extra.

pymysqloptionalMySQL driver. Install via `jupysql[mysql]` extra.

Agent activity

11 hits · last 30 days

node

Amazon

Resources

githubhttps://github.com/ploomber/jupysql ↗

packagehttps://pypi.org/project/jupysql/ ↗

homepagehttps://jupysql.ploomber.io ↗