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: @JuliMillan
Reviewer 1: @ethanwhite
Reviewer 2: @benjamindonnachie
Archive:
JOSS DOI: TBD
Version accepted: v1.1.0
Date accepted (month/day/year): 05/ 10/2025

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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):

  • Data retrieval
  • Data extraction
  • Data processing/munging
  • Data deposition
  • Data validation and testing
  • Data visualization¹
  • Workflow automation
  • Citation management and bibliometrics
  • Scientific software wrappers
  • Database interoperability

Domain Specific

• Geospatial
• Education

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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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• contains a README with instructions for installing the development version.
• includes documentation with examples for all functions.
• contains a tutorial with examples of its essential functions and uses.
• has a test suite.
• has continuous integration setup, such as GitHub Actions CircleCI, and/or others.

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Footnotes

1. Please fill out a pre-submission inquiry before submitting a data visualization package. ↩

[cmarmo]

Editor in Chief checks

Hi @cklunch! Thank you for submitting your package for pyOpenSci review.
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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.

• 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).
  • The package imports properly into a standard Python environment import package.
• 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.
  • API documentation (documentation for your code's functions, classes, methods and attributes): this includes clearly written docstrings with variables defined using a standard docstring format.
• Core GitHub repository Files
  • README The package has a README.md file with clear explanation of what the package does, instructions on how to install it, and a link to development instructions.
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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!!

[cklunch]

@cmarmo @lwasser Thanks for the feedback!

For documentation, the intent was for the tutorials that are linked in the readme to provide the documentation users need to understand how to use the package. The Download and Explore tutorial provides instructions in the most commonly used functions, and some context and common follow-up data wrangling, and the neonUtilities tutorial provides a function index. If this isn't what you're looking for, or if different content is needed, do you have an example of documentation that would be appropriate?

For contributing, of course bug reports and requests are always welcome! We've found with the R package that it isn't realistic for external folks to contribute code directly. The package is so specific to the NEON publication system, it's hard for people who aren't deeply familiar with that system to write generic code for it. It's almost always easier for us to incorporate requested changes ourselves than to work with external PRs. But if there's a better way to express that in the documentation, I'm very happy to.

I'll get issue templates set up in the repo, and wait to update documentation based on what we decide in this discussion. Thanks!

[lwasser]

hey there @cklunch

Have a look at our packaging guide here. Typically, python packages have a documentation "website". You might also have a look at some of the structures for other packages in our ecosystem.

tutorials are great, but it's also important to document the code base for easier future maintenance, help people get started with installing the package, etc. Please have a look at those resources and let us know if you have any questions!

[cmarmo]

For documentation, the intent was for the tutorials that are linked in the readme to provide the documentation users need to understand how to use the package. The Download and Explore tutorial provides instructions in the most commonly used functions, and some context and common follow-up data wrangling, and the neonUtilities tutorial provides a function index. If this isn't what you're looking for, or if different content is needed, do you have an example of documentation that would be appropriate?

Indeed, that's why I said that a lot of information is already there. The way it is structured though is not easy to browse for someone new to the neon ecosystem.
It would be easier also for the review, to have a reference documentation page (like your index.md), rendered by github pages or similar, with a table of contents and the essential information: Getting started, tutorials, API, and then the links to the related pages already available in the neon website.
Does that sound reasonable?

[cklunch]

@lwasser @cmarmo Thanks for the clarification. I'll see about creating a dedicated page.

[cklunch]

@lwasser @cmarmo Changes to neonutilities have been pushed, including creating issue templates, clarifying in the CONTRIBUTING file, and creating a ReadTheDocs page. Thank you for your guidance!

https://github.com/NEONScience/NEON-utilities-python

[cmarmo]

Thank you for your work @cklunch !
I have checked the related items in my initial comment.... just a nitpick ... at the end of the get started page the link to the tutorials is not linked....

I'm going to start looking for an editor.