Metadata-Version: 2.1
Name: cloudknot
Version: 0.5.1
Summary: Cloudknot: a python library designed to run your existing python code on AWS Batch
Home-page: https://nrdg.github.io/cloudknot
Author: Adam Richie-Halford
Author-email: richiehalford@gmail.com
Maintainer: Adam Richie-Halford
Maintainer-email: richiehalford@gmail.com
License: MIT
Download-URL: https://github.com/nrdg/cloudknot
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        # cloudknot
        
        A knot is a collective noun for a group of snakes. Cloudknot is a python
        library designed to run your existing python code on
        [AWS Batch](https://aws.amazon.com/batch).
        
        Cloudknot takes as input a python function, Dockerizes it for use in an
        Amazon ECS instance, and creates all the necessary AWS Batch constituent
        resources to submit jobs. You can then use cloudknot to submit and view jobs
        for a range of inputs.
        
        To get started using cloudknot, please see the [cloudknot documentation](https://nrdg.github.io/cloudknot/)
        
        This is the cloudknot development site. You can view the source code, file new
        issues, and contribute to cloudknot's development. If you are just getting
        started, you should look at the
        [cloudknot documentation](https://nrdg.github.io/cloudknot/).
        
        ## Contributing
        
        We love contributions! Cloudknot is open source, built on open source,
        and we'd love to have you hang out in our community.
        
        We have developed some [guidelines](CONTRIBUTING.md) for contributing to
        cloudknot.
        
        **Imposter syndrome disclaimer**: We want your help. No, really.
        
        There may be a little voice inside your head that is telling you that
        you're not ready to be an open source contributor; that your skills
        aren't nearly good enough to contribute. What could you possibly offer a
        project like this one?
        
        We assure you - the little voice in your head is wrong. If you can
        write code at all, you can contribute code to open source. Contributing
        to open source projects is a fantastic way to advance one's coding
        skills. Writing perfect code isn't the measure of a good developer (that
        would disqualify all of us!); it's trying to create something, making
        mistakes, and learning from those mistakes. That's how we all improve,
        and we are happy to help others learn.
        
        Being an open source contributor doesn't just mean writing code, either.
        You can help out by writing documentation, tests, or even giving
        feedback about the project (and yes - that includes giving feedback
        about the contribution process). Some of these contributions may be the
        most valuable to the project as a whole, because you're coming to the
        project with fresh eyes, so you can see the errors and assumptions that
        seasoned contributors have glossed over.
        
        ## Citing cloudknot
        
        If you use cloudknot in a scientific publication, please see our [citation
        instructions](https://nrdg/github.io/cloudknot/index.html#citing-cloudknot).
        
        ## Credits
        
        Cloudknot development is supported through a grant from the [Gordon
        and Betty Moore Foundation](https://www.moore.org/) and from the
        [Alfred P. Sloan Foundation](https://sloan.org/) to the [University of
        Washington eScience Institute](http://escience.washington.edu/), as
        well as NIH Collaborative Research in Computational Neuroscience grant
        R01EB027585-01 through the National Institute of Biomedical Imaging and
        Bioengineering to Eleftherios Garyfallidis (Indiana University) and
        Ariel Rokem (University of Washington).
        
        This package was created with
        [shablona](https://github.com/uwescience/shablona).
        
        The imposter syndrome disclaimer was originally written by
        [Adrienne Lowe](https://github.com/adriennefriend) for a [PyCon
        talk](https://www.youtube.com/watch?v=6Uj746j9Heo), and was
        adapted based on its use in the README file for the [MetPy
        project](https://github.com/Unidata/MetPy).
        
Platform: OS Independent
Classifier: Development Status :: 3 - Alpha
Classifier: Environment :: Console
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Topic :: Scientific/Engineering
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Provides-Extra: dev
Provides-Extra: maint
