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https://github.com/intake/intake

Intake is a lightweight package for finding, investigating, loading and disseminating data.

https://github.com/intake/intake

Science Score: 13.0%

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

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    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
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    .zenodo.json file
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    DOI references
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    Scientific vocabulary similarity
    Low similarity (16.3%) to scientific vocabulary

Keywords

data-access data-catalog python
Last synced: 4 months ago · JSON representation

Repository

Intake is a lightweight package for finding, investigating, loading and disseminating data.

Basic Info
Statistics
  • Stars: 1,055
  • Watchers: 40
  • Forks: 148
  • Open Issues: 113
  • Releases: 0
Topics
data-access data-catalog python
Created over 8 years ago · Last pushed 5 months ago
Metadata Files
Readme License

README.md

Intake: Take 2

A general python package for describing, loading and processing data

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Build Status Documentation Status

Taking the pain out of data access and distribution

Intake is an open-source package to:

  • describe your data declaratively
  • gather data sets into catalogs
  • search catalogs and services to find the right data you need
  • load, transform and output data in many formats
  • work with third party remote storage and compute platforms

Documentation is available at Read the Docs.

Please report issues at https://github.com/intake/intake/issues

Install

Recommended method using conda: bash conda install -c conda-forge intake

You can also install using pip, in which case you have a choice as to how many of the optional dependencies you install, with the simplest having least requirements

bash pip install intake

Note that you may well need specific drivers and other plugins, which usually have additional dependencies of their own.

Development

  • Create development Python environment with the required dependencies, ideally with conda. The requirements can be found in the yml files in the scripts/ci/ directory of this repo.
    • e.g. conda env create -f scripts/ci/environment-py311.yml and then conda activate test_env
  • Install intake using pip install -e .
  • Use pytest to run tests.
  • Create a fork on github to be able to submit PRs.
  • We respect, but do not enforce, pep8 standards; all new code should be covered by tests.

Support

Work on this repository is supported in part by:

"Anaconda, Inc. - Advancing AI through open source."

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<a href="https://anaconda.com/"><img src="https://camo.githubusercontent.com/b8555ef2222598ed37ce38ac86955febbd25de7619931bb7dd3c58432181d3b6/68747470733a2f2f626565776172652e6f72672f636f6d6d756e6974792f6d656d626572732f616e61636f6e64612f616e61636f6e64612d6c617267652e706e67" alt="anaconda logo" width="40%"/></a>