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-0.1.1.dev419.tar.gz (35.2 kB view details)

Uploaded Source

Built Distribution

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

squirrel_datasets_core-0.1.1.dev419-py3-none-any.whl (48.0 kB view details)

Uploaded Python 3

File details

Details for the file squirrel_datasets_core-0.1.1.dev419.tar.gz.

File metadata

  • Download URL: squirrel_datasets_core-0.1.1.dev419.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-0.1.1.dev419.tar.gz
Algorithm Hash digest
SHA256 f008d2cbc4a819b4ce5aa819389500babbec81fc85a39ee199259339684251fa
MD5 bb9450f2c3fe71915fcdef9ee946a596
BLAKE2b-256 b66a90942b23015288f1b7d6e32a740f318e5a6ed14de2dcfae06a7c133fa011

See more details on using hashes here.

File details

Details for the file squirrel_datasets_core-0.1.1.dev419-py3-none-any.whl.

File metadata

  • Download URL: squirrel_datasets_core-0.1.1.dev419-py3-none-any.whl
  • Upload date:
  • Size: 48.0 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-0.1.1.dev419-py3-none-any.whl
Algorithm Hash digest
SHA256 dbcfd438097923e88f66df5bd95e4e4c712473f69114ddcdadb8be73eb562575
MD5 226b8fd70a30191350ec1e97155c0801
BLAKE2b-256 98ca47c98ae25a75a3e419a98bbbb2ca692ef411257ef971d1cd929029c7a01d

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