squirrels 0.5.1

Squirrels - API Framework for Data Analytics

Squirrels

Squirrels is an API framework that lets you create REST APIs for dynamic data analytics!

Documentation: https://squirrels-analytics.github.io/

Source Code: https://github.com/squirrels-analytics/squirrels

Table of Contents

• Main Features
• License
• Contributing to Squirrels
  • Setup
  • Testing
  • Project Structure

Main Features

Here are a few of the things that Squirrels can do:

• Connect to any database by specifying its SQLAlchemy url (in squirrels.yml) or by using its native connector library in python (in connections.py).
• Configure API routes for datasets (in squirrels.yml) without writing code.
• Configure parameter widgets (types include single-select, multi-select, date, number, etc.) for your datasets (in parameters.py).
• Use SQL templates (templated with Jinja, like dbt) or python functions (that return a Python dataframe in polars or pandas) to define dynamic query logic based on parameter selections.
• Query multiple databases and join the results together in a final view in one API endpoint/dataset!
• Test your API endpoints with Squirrels Studio or by a command line that generates rendered sql queries and results as files (for a given set of parameter selections).
• Define User model (in user.py) and authorize privacy scope per dataset (in squirrels.yml). The user's attributes can even be used in your query logic!
• Serve dataset metadata and results to AI agents via MCP (Model Context Protocol)

Quick Start

In a new virtual environment, install squirrels. Then, in your project directory, activate the virtual environment and run the following commands:

sqrl new --use-defaults --curr-dir
sqrl build

To run the API server, simply run:

sqrl run

License

Squirrels is released under the Apache 2.0 license.

See the file LICENSE for more details.

Contributing to Squirrels

The sections below describe how to set up your local environment for Squirrels development and run unit tests. A high level overview of the project structure is also provided.

Setup

This project requires python version 3.10 or above to be installed. It also uses the python package manager uv. Information on setting up poetry can be found at: https://docs.astral.sh/uv/getting-started/installation/.

Then, to install all dependencies in a virtual environment, run:

uv sync

And activate the virtual environment with:

source .venv/bin/activate

To confirm that the setup worked, run the following to show the help page for all Squirrels CLI commands:

sqrl -h

Testing

Run uv run pytest. Or if you have the virtual environment activated, simply run pytest.

Project Structure

From the root of the git repo, the source code can be found in the squirrels folder and unit tests can be found in the tests folder.

To understand what a specific Squirrels command is doing, start from the _command_line.py file as your entry point.

The library version is maintained in both the pyproject.toml and the squirrels/_version.py files.