Skip to main content

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.

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

smoosense-0.0.1rc23.tar.gz (49.9 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

smoosense-0.0.1rc23-py3-none-any.whl (77.5 kB view details)

Uploaded Python 3

File details

Details for the file smoosense-0.0.1rc23.tar.gz.

File metadata

  • Download URL: smoosense-0.0.1rc23.tar.gz
  • Upload date:
  • Size: 49.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.8.3

File hashes

Hashes for smoosense-0.0.1rc23.tar.gz
Algorithm Hash digest
SHA256 deaf8cc13ddf5f050ff8a35fc0e28ff2a2d1103cc9a87ba2583081de4b8f8371
MD5 2288abcd18030717f1fab98f5d93360e
BLAKE2b-256 c5bec246b7c993096b66b7f92fe83d54952cef11752bedc169d654a2ff18c81c

See more details on using hashes here.

File details

Details for the file smoosense-0.0.1rc23-py3-none-any.whl.

File metadata

File hashes

Hashes for smoosense-0.0.1rc23-py3-none-any.whl
Algorithm Hash digest
SHA256 0e8b4c69c7f15f0c1c339e6f16273928b782555daf1c237b36e9599f19be63db
MD5 c6711fbb61489e6a39a3cf11b3c10e4e
BLAKE2b-256 352f5eb0efd13f7d43cfcf49f0a1b5498e665a5c9fcd415acba2b0d0fff2182c

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page