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A data science cookiecutter #415

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sfmig opened this issue Jun 12, 2024 · 6 comments
Open

A data science cookiecutter #415

sfmig opened this issue Jun 12, 2024 · 6 comments
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enhancement New feature or request

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@sfmig
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sfmig commented Jun 12, 2024

Is Your Feature Request Related to a Problem? Please Describe

We recently chatted with @samcunliffe and Niko from SWC (cannot tag him) about a cookiecutter for data science / scientific analysis / exploratory Python projects.

The idea would be to have some lighter requirements than for a fully-fledged Python package. And maybe some data science specific additions (like for example functionality for formatting and checking notebooks). This could be useful for many researchers, and maybe a good entry point to getting into good software practices.

Describe the Solution You'd Like

If we find this could be useful, we could have it:

  • in a separate repo, or
  • as part of this repo, and ask the user in the initial config phase which version they want to instantiate. @samcunliffe mentioned we could maybe use hidden variables for this.

Alternatively, we can just point to a good cookiecutter for this purpose if that already exists.

Describe Alternatives You've Considered

There are some examples of research cookiecutter:

  • this one is very basic (mostly a directory structure) but maybe a good starting point if we decide we want to implement this ourselves.
  • this one seems more recent and quite well documented. It may be a good one to point to if we decide that doing one ourselves is out of scope

Additional Context

No response

@sfmig sfmig added the enhancement New feature or request label Jun 12, 2024
@samcunliffe
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A minimal solution would be to add a couple of trusted/tested data science templates to The Templates Page. I'd propose a section above "Community-specific..."

@sfmig
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sfmig commented Jun 14, 2024

this website and the associated cookiecutter may be a nice one to try out

@paddyroddy
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this website and the associated cookiecutter may be a nice one to try out

Does feel a shame to be recommending a rival 🤔

@samcunliffe
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this one seems more recent and quite well documented. It may be a good one to point to if we decide that doing one ourselves is out of scope

I heard good things about ccds. Never actually used it. Should we ask in #datascience on Slack? If we're making a recommendation under the ARC logo, perhaps they should be consulted.

@dstansby
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(like for example functionality for formatting and checking notebooks)

This sounds like something we could add here anyway?

@paddyroddy
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This sounds like something we could add here anyway?

👍 #49

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