neonutilities submission

[cklunch]

Submitting Author: Claire Lunch (@cklunch) All current maintainers: (@cklunch, @bhass-neon, @znickerson8) Package Name: neonutilities One-Line Description of Package: neonutilities is a package for accessing and wrangling data generated and published by the National Ecological Observatory Network. Repository Link: https://github.com/NEONScience/NEON-utilities-python Version submitted: v1.0.1 EiC: @cmarmo Editor: TBD
Reviewer 1: TBD
Reviewer 2: TBD
Archive: TBD JOSS DOI: TBD Version accepted: TBD Date accepted (month/day/year): TBD

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Description

The neonutilities Python package provides utilities for discovering, downloading, and working with data files published by the National Ecological Observatory Network (NEON). NEON data files can be downloaded from the NEON Data Portal or API. The neonutilities package includes wrapper functions for the API and functions to reformat and stack NEON tabular data for analysis. This is a Python-native adaptation of the heavily used neonUtilities R package.

Scope

• Please indicate which category or categories. Check out our package scope page to learn more about our scope. (If you are unsure of which category you fit, we suggest you make a pre-submission inquiry):

  • [x] Data retrieval
  • [ ] Data extraction
  • [x] Data processing/munging
  • [ ] Data deposition
  • [ ] Data validation and testing
  • [ ] Data visualization[^1]
  • [ ] Workflow automation
  • [ ] Citation management and bibliometrics
  • [ ] Scientific software wrappers
  • [ ] Database interoperability

Domain Specific

• [ ] Geospatial
• [ ] Education

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[^1]: Please fill out a pre-submission inquiry before submitting a data visualization package.

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  • Who is the target audience and what are scientific applications of this package?

The target audience is scientists doing research using NEON data. The package enables programmatic workflows for data downloading, and provides a standardized way to merge the product-site-month data files NEON publishes, making them analysis-ready.

• Are there other Python packages that accomplish the same thing? If so, how does yours differ?

There is an incomplete package on PyPi here that was started in 2020 by a student at a coding camp. It doesn't appear to have been finished, and is not maintained. Some NEON users have developed their own code to do some of the functionality covered by neonutilities, but as far as I know none of them have shared it broadly.

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• [x] contains a tutorial with examples of its essential functions and uses.
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[cmarmo]

Editor in Chief checks

Hi @cklunch! Thank you for submitting your package for pyOpenSci review. Below are the basic checks that your package needs to pass to begin our review. If some of these are missing, we will ask you to work on them before the review process begins.

Please check our Python packaging guide for more information on the elements below.

• [x] Installation The package can be installed from a community repository such as PyPI (preferred), and/or a community channel on conda (e.g. conda-forge, bioconda).
  • [x] The package imports properly into a standard Python environment import package.
• [x] Fit The package meets criteria for fit and overlap.
• [ ] Documentation The package has sufficient online documentation to allow us to evaluate package function and scope without installing the package. This includes:
  • [ ] User-facing documentation that overviews how to install and start using the package.
  • [ ] Short tutorials that help a user understand how to use the package and what it can do for them.
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• [x] Core GitHub repository Files
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• [x] Initial onboarding survey was filled out We appreciate each maintainer of the package filling out this survey individually. :raised_hands: Thank you authors in advance for setting aside five to ten minutes to do this. It truly helps our organization. :raised_hands:

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Editor comments

Here my comments to clarify why I haven't ticked all the check-boxes.

• Documentation: I've found a lot of relevant information in the https://www.neonscience.org/ page, however there is no standalone documentation for the package, even if a docs directory is present in the repo with an empty index.md. I strongly recommend to add some documentation pages in order to structure the access to the information. There is no need to rewrite what is already on https://www.neonscience.org/, just linking and structuring, following for example the structure suggested in the pre-review checks. Also, it is not clear to me what is part of the Neon Data API and what is part of the python implementation.
• The README does not contain the documentation about how to contribute: it is true that the CONTRIBUTING file specifies that external contributions will not be considered for now. Perhaps a link to the CONTRIBUTING would be enough.
• As opening issues is the only way to contribute for now, it would be nice to have issue templates for different kind of contributions (bug reports, new feature suggestions, documentation,...)

I think the fluidity of the review process will benefit from those improvements.

Thank you so much for your understanding!

[lwasser]

hey there @cklunch @bhass-neon @znickerson8 👋🏻 it's nice to see you here on GitHub! I have a question for you about your contributing doc which says:

The neonutilities package is currently not accepting external contributions. If you have a suggestion for a fix or enhancement to the package, please create an Issue in this repository, or contact us using the NEON Contact Us page.

We do consider opening issues to report bugs and to request useful features to be contributions. They are a different type than a PR of course. What is the intent of "we are not accepting contributions" is in this case? We are having some discussions around our pyOpenSci policies, maintainer responsiveness to users and open source processes in general related to this package. Any input from you would be super helpful! thank you!!