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https://github.com/amazon-science/bears

Excessively Fast Processing of Multimodal DataFrames

https://github.com/amazon-science/bears

Science Score: 26.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ○
    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ○
    DOI references
  • ○
    Academic publication links
  • ○
    Academic email domains
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (6.4%) to scientific vocabulary
Last synced: 6 months ago · JSON representation

Repository

Excessively Fast Processing of Multimodal DataFrames

Basic Info
  • Host: GitHub
  • Owner: amazon-science
  • License: apache-2.0
  • Language: Python
  • Default Branch: main
  • Homepage:
  • Size: 1.43 MB
Statistics
  • Stars: 3
  • Watchers: 2
  • Forks: 1
  • Open Issues: 10
  • Releases: 6
Created about 1 year ago · Last pushed 10 months ago
Metadata Files
Readme Contributing License Code of conduct

README.md

Run your Machine Learning and Deep Learning workloads at any scale.

bears delivers lightning-fast data-processing, whether you need to run a single row or 100M+ rows.

bears works with your existing data tools while optimizing data-layouts between Pandas, Dask, Torch, Python dicts for maximum performance. Drop-in compatibility with the Pandas API means you can use bears today with zero code changes.

bear-in-the-night-sky

Help build a bears!

See CONTRIBUTING for more information.

License

This project is licensed under the Apache-2.0 License.

Owner

  • Name: Amazon Science
  • Login: amazon-science
  • Kind: organization

GitHub Events

Total
  • Create event: 11
  • Issues event: 8
  • Release event: 5
  • Watch event: 4
  • Delete event: 3
  • Issue comment event: 14
  • Push event: 160
  • Pull request event: 21
  • Fork event: 1
Last Year
  • Create event: 11
  • Issues event: 8
  • Release event: 5
  • Watch event: 4
  • Delete event: 3
  • Issue comment event: 14
  • Push event: 160
  • Pull request event: 21
  • Fork event: 1

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 7
  • Total pull requests: 12
  • Average time to close issues: 6 minutes
  • Average time to close pull requests: 6 days
  • Total issue authors: 1
  • Total pull request authors: 3
  • Average comments per issue: 0.29
  • Average comments per pull request: 0.75
  • Merged pull requests: 9
  • Bot issues: 0
  • Bot pull requests: 1
Past Year
  • Issues: 7
  • Pull requests: 12
  • Average time to close issues: 6 minutes
  • Average time to close pull requests: 6 days
  • Issue authors: 1
  • Pull request authors: 3
  • Average comments per issue: 0.29
  • Average comments per pull request: 0.75
  • Merged pull requests: 9
  • Bot issues: 0
  • Bot pull requests: 1
View more stats
Top Authors
Issue Authors
  • adivekar-utexas (7)
Pull Request Authors
  • adivekar-utexas (10)
  • dependabot[bot] (1)
  • SibaRajendran (1)
Top Labels
Issue Labels
enhancement (2) good first issue (2) bug 😩 (2) migration (1) enhancement 🚀 (1)
Pull Request Labels
bug (3) dependencies (1) python (1) enhancement 🚀 (1) bug 😩 (1)

Dependencies

.github/workflows/linting.yml actions
  • actions/checkout v4 composite
  • astral-sh/ruff-action v3 composite
.github/workflows/release.yml actions
  • actions/checkout v3 composite
  • actions/setup-python v4 composite
.github/workflows/tests.yml actions
  • actions/checkout v3 composite
  • actions/setup-python v4 composite
pyproject.toml pypi
  • XlsxWriter *
  • autoenum *
  • boto3 *
  • cloudpickle >=3.0.0
  • fastparquet *
  • numpy *
  • openpyxl *
  • pandas ==2.*
  • pyarrow *
  • pydantic ==1.10.15
  • pytest *
  • pyyaml *
  • requests *
  • s3fs *
  • tqdm *
  • urllib3 *
  • xlrd *