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Smoothly make sense of your large multi-modal datasets

Project description

SmooSense Python SDK

SmooSense is a web-based application for exploring and analyzing large-scale multi-modal tabular data. It provides an intuitive interface for working with CSV, Parquet, and other data formats with powerful SQL querying capabilities.

This repo contains source code for "SmooSense Python SDK".

Feature highlights

  • Natively visualize multimodal data (images, videos, json, bbox, image mask, 3d assets etc)
  • Effortlessly look at distribution. Automatic drill-through from statistics to random samples.
  • Graphical and interactive slice-n-dice of your dataset.
  • Large scale support for 100 million rows on your laptop.
  • Easy to integrate; SmooSense directly work with table file (parquet, csv, jsonl, etc)
  • Low cost. Free and open source to use on your laptop. Compute efficient when deployed.

Demo: https://demo.smoosense.ai

How to use

CLI

Install uv, and then

uv tool install -U smoosense

In terminal, cd into the folder containing your data files, and then run sense

Jupyter Notebook

pip install -U "smoosense[jupyter]"

Inside Jupyter notebook:

from smoosense.widget import Sense
import pandas as pd
import numpy as np

df = pd.DataFrame(np.random.randn(500, 5), columns=["a", "b", "c", "d", "e"])

Sense(df)  # Displays automatically in Jupyter

License

SmooSense Python SDK is licensed under Apache 2.0.

This is a permissive open source license that allows you to:

  • ✅ Use SmooSense for any purpose, including commercial use
  • ✅ Modify and distribute the software
  • ✅ Use it in proprietary software
  • ✅ Deploy it in production environments
  • ✅ Include it as a dependency in your projects

See the full LICENSE file for complete terms and conditions.

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