Skip to main content

Squirrel public datasets collection

Project description

Squirrel Datasets Core

Python PyPI Conda Documentation Status Downloads License DOI Generic badge Slack


What is Squirrel Datasets Core?

squirrel-datasets-core is a hub where the user can 1) explore existing datasets registered in the data mesh by other users and 2) preprocess their datasets and share them with other users. As an end user, you will be able to load many publically available datasets with ease and speed with the help of squirrel, or load and preprocess your own datasets with the tools we provide here.

For preprocessing, we currently support Spark as the main tool to carry out the task.

If you have any questions or would like to contribute, join our Slack community!

Installation

Install squirrel-core and squirrel-datasets-core with pip:

pip install squirrel-core[all]
pip install squirrel-datasets-core[all]

Documentation

Visit our documentation on Readthedocs.

Contributing

squirrel-datasets-core is open source and community contributions are welcome!

The humans behind Squirrel

We are Merantix Momentum, a team of ~30 machine learning engineers, developing machine learning solutions for industry and research. Each project comes with its own challenges, data types and learnings, but one issue we always faced was scalable data loading, transforming and sharing. We were looking for a solution that would allow us to load the data in a fast and cost-efficient way, while keeping the flexibility to work with any possible dataset and integrate with any API. That's why we build Squirrel – and we hope you'll find it as useful as we do! By the way, we are hiring!

Citation

If you use Squirrel Datasets in your research, please cite Squirrel using:

@article{2022squirrelcore,
  title={Squirrel: A Python library that enables ML teams to share, load, and transform data in a collaborative, flexible, and efficient way.},
  author={Squirrel Developer Team},
  journal={GitHub. Note: https://github.com/merantix-momentum/squirrel-core},
  year={2022}
}

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

squirrel_datasets_core-0.1.0.dev76788.tar.gz (35.2 kB view details)

Uploaded Source

Built Distribution

File details

Details for the file squirrel_datasets_core-0.1.0.dev76788.tar.gz.

File metadata

  • Download URL: squirrel_datasets_core-0.1.0.dev76788.tar.gz
  • Upload date:
  • Size: 35.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/33.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.63.0 importlib-metadata/4.11.2 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.8.9

File hashes

Hashes for squirrel_datasets_core-0.1.0.dev76788.tar.gz
Algorithm Hash digest
SHA256 4b1e865d2d9aaa517723995a6226ad82241ecedb3e30cb4c7811f2a7e4cca1f0
MD5 5aa5898f673c51781b647049c5903bf1
BLAKE2b-256 4e25c91e2f84bbcaf007023f52596fb7a15df58d3ceb78ce927542de7d691afd

See more details on using hashes here.

File details

Details for the file squirrel_datasets_core-0.1.0.dev76788-py3-none-any.whl.

File metadata

  • Download URL: squirrel_datasets_core-0.1.0.dev76788-py3-none-any.whl
  • Upload date:
  • Size: 48.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/33.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.63.0 importlib-metadata/4.11.2 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.8.9

File hashes

Hashes for squirrel_datasets_core-0.1.0.dev76788-py3-none-any.whl
Algorithm Hash digest
SHA256 75769677bfe4c742c0aca14c89d595bac6d0c2b2c1c3250a2d66d681f0555217
MD5 57103d30e548bbd24a9e173eb0555e66
BLAKE2b-256 f722ec9b8287c59dbcbd68cf199587dede3de3b4404d2494b2fe8568240c62db

See more details on using hashes here.

Supported by

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