Solar Data Tools Submission

[pluflou]

Submitting Author: Sara Miskovich (@pluflou)
All current maintainers: (@pluflou, @bmeyers)
Package Name: Solar Data Tools
One-Line Description of Package: Library of tools for analyzing photovoltaic power time-series data.
Repository Link: https://github.com/slacgismo/solar-data-tools
Version submitted: 1.6.4
EiC: @cmarmo
Editor: @shirubana
Reviewer 1: @jinningwang
Reviewer 2: @echedey-ls
Reviewer 3: @cdeline
Archive: TBD
JOSS DOI: TBD
Version accepted: TBD
Date accepted (month/day/year): TBD

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Description

• Include a brief paragraph describing what your package does:
  Solar Data Tools is an open-source Python library for analyzing PV power (and irradiance) time-series data. It provides methods for data I/O, cleaning, filtering, plotting, and analysis. These methods are largely automated and require little to no input from the user regardless of system type—from utility tracking systems to multi-pitch rooftop systems. Solar Data Tools was developed to enable analysis of unlabeled PV data, i.e. with no model, no meteorological data, and no performance index required, by taking a statistical signal processing approach in the algorithms used in the package’s main data processing pipeline.

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?
    This package is for anyone dealing with photovoltaic data, especially data with no meteorological information (unlabeled). This includes photovoltaic professionals (in private solar industry or utility companies for example), researchers and students in the solar power domain, community solar owners, and anyone with a rooftop system. The scientific goal of the package is to facilitate analysis of photovoltaic data for any system, even those that are difficult to model, and the package uses signal decomposition to achieve that.

  • Are there other Python packages that accomplish the same thing? If so, how does yours differ?
    There are two other packages that are similar in that they offer data analysis tools for solar applications: PVAnalytics and RdTools. They are both model driven, and require the user to define their own analysis. PVAnalytics focuses on preprocessing and QA, while RdTools focuses on loss factor analysis. Solar Data Tools provides both data quality and loss factor analysis, runs automatically with little to no setup, and is model-free and does not require any weather or other information. Solar Data Tools is most suited for when users want a pre-defined pipeline to get information on complex systems/sites that can't be modeled easily and that no meteorological data. A recent tutorial that was part of a virtual tutorial series on open-source tools and open-access solar data held by DOE’s Solar Technology Office in March 2024 goes over the differences in these packages and when each tool is appropriate to use. You can find the recording here and the slide deck here (see slide 16 for a summary).

  • If you made a pre-submission enquiry, please paste the link to the corresponding issue, forum post, or other discussion, or @tag the editor you contacted:
    Solar Data Tools pre-submission inquiry #204 (@cmarmo)

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[cmarmo]

Editor in Chief checks

Hi @pluflou ! 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.

• 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).
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• Fit The package meets criteria for fit and overlap.
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• Initial onboarding survey was filled out
  We appreciate each maintainer of the package filling out this survey individually. 🙌
  Thank you authors in advance for setting aside five to ten minutes to do this. It truly helps our organization. 🙌

---

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Editor comments

Solar Data Tools is in excellent condition! Congratulation for all your work! 🚀

My only comment is related to the test coverage, which could be improved.
We don't set a minimal threshold for test coverage in order to start the review process, so, if you don't mind, just keep my comment somewhere as a reminder for future developments, and I'm going to look right away for an editor.

[cmarmo]

I saw a new 1.6.2 version was released while waiting for my feedback: I took the liberty to update the version submitted so the reviewers would deal with the latest version available.

[pluflou]

I saw a new 1.6.2 version was released while waiting for my feedback: I took the liberty to update the version submitted so the reviewers would deal with the latest version available.

Thank you!!

[cmarmo]

Hi @pluflou , I am glad to announce that we have an editor for Solar Data Tools review.

@shirubana kindly accepted to take care of your submission. I am letting her introduce herself here and wishing a nice review process to all people involved.

[pluflou]

Thank you @shirubana for volunteering to review our package! We are excited to work with you on this. In the meantime, please let us know if you have any questions!

[shirubana]

Hi, starting on this and navigating the various resources to do this properly.

[shirubana]

Ok, I think I am acquainted now with the steps/my job after perusing the guide and slack. I have started to look for reviewers.

[bmeyers]

Thank you @shirubana! Looking forward to working with you on this.

[bmeyers]

Hi @shirubana! I just wanted to check in and see if there were any updates, and if there was anything you needed from us. Thank you!

[pluflou]

@cmarmo @shirubana is it possible to update to the latest version (1.6.4)? This version is now available on conda-forge (previous versions were on a private channel).

[cmarmo]

@pluflou , since the review has not started yet, I have updated the information about the submitted version in the description.

@shirubana, please let us know if you need any help to find reviewers.... unfortunately, onboarding reviewers can be tricky....

[pluflou]

Hi @cmarmo @shirubana, happy new year! Just wanted to check in on how things are going, and have a small update. We have the JOSS paper in a branch's (joss_paper) root dir under paper/ and I'm just wondering if we should merge that into main or if we should provide the link to the branch. Thank you!

[lwasser]

Hi Team 👋🏻 it would be great to move this review forward. I am happy to post on social to try to help find reviewers if someone can help me understand what we need here! ✨ I know it's a challenging time here in the US for science so it's super understandable that things might move more slowly because of that!

[cmarmo]

Hi @lwasser, I'm checking our reviewer list right now and will see if I can onboard some new reviewer.
I'm back to you all soon.

[cmarmo]

Dear all,
I have one positive answer from a reviewer.
They are very interested in the package, however they are asking for an extended timeline (~3 months) because of their current academic tasks.

I know this package has already waited a lot (and I am also looking for a second reviewer), so I would like to know if the maintainers are fine with this arrangement ... it is quite a challenge to find reviewers ....

Please @pluflou , @bmeyers , let me know what do you think.

Thanks a lot for your patience!

[bmeyers]

Hi @cmarmo, we certainly appreciate any and all volunteer effort that folks can put in here. The proposed timeline is far from ideal, but I'm not sure we're in much of a position to push back. In short, we'll take what we can get!

[cmarmo]

Thank you @bmeyers for your answer and your understanding!
We have our first reviewer then.
I am glad to say that @jinningwang has kindly accepted to review this package.

Before beginning your review, please fill out our pre-review survey. This helps us improve all aspects of our review and better understand our community. No personal data will be shared from this survey - it will only be used in an aggregated format by our Executive Director to improve our processes and programs.

The following resources will help you complete your review:

1. Here is the reviewers guide. This guide contains all of the steps and information needed to complete your review.
2. Here is the review template that you will need to fill out and submit
   here as a comment, once your review is complete.

Please get in touch with any questions or concerns!

As we discussed offline, let's keep in mind a three month timeline for this review... hopefully, things will go smoothly and perhaps the review can come in sooner 🤞

[shirubana]

Hi, sorry, this fell out my radar, I did succeed in getting one extra reviewer. @cdeline , are you still available to help?

Can I act as a reviewer too as I have not been very good as an editor?

[cmarmo]

@shirubana, don't worry! We all struggle with our schedules.

I'm fine with you as a reviewer as long as we can keep an open communication about the timeline.
Would you have time to finalize the review together with our first reviewer (or sooner... :) )?
Thank you for your help!

[cmarmo]

Hello everybody,
touching base here: my first round of inquiries for a second reviewer didn't succeed.
I have sent some new bottles in the ocean... wish me luck... 🤞

[cmarmo]

I am happy to share that we have our second reviewer for Solar Data Tools! 🥳

@echedey-ls kindly accepted to help us with this review.

@echedey-ls, before beginning your review, please fill out our pre-review survey. This helps us improve all aspects of our review and better understand our community. No personal data will be shared from this survey - it will only be used in an aggregated format by our Executive Director to improve our processes and programs.

The following resources will help you complete your review:

Here is the reviewers guide. This guide contains all of the steps and information needed to complete your review.
Here is the review template that you will need to fill out and submit here as a comment, once your review is complete.

Please get in touch with any questions or concerns!

The deadline for this review for both reviewers is the end of April.

Thank you very much for your help @jinningwang and @echedey-ls!

[pluflou]

That's great news. Thank you @cmarmo for your hard work in finding reviewers. And thank you @jinningwang and @echedey-ls, we look forward to working with you!

[cdeline]

Hi @shirubana - I've emerged from some of my previous obligations and can try to spend time as backup reviewer #3 on this project, with a mid April review timeline. If you could use another reviewer.

[echedey-ls]

Hi everybody,
@cmarmo convinced me so here I am :D
I plan on opening issues in SDT where I find adequate, to reduce the amount of walls of texts I tend to make. I will be cross-linking and briefly describing them here. Lastly, I'll announce once the review template has been filled out and I consider my review finished. I can't tell whether I will fulfil the deadline time, but I'll try my best to do so.

Review - will be updated over time

Package Review

Please check off boxes as applicable, and elaborate in comments below. Your review is not limited to these topics, as described in the reviewer guide

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Documentation

The package includes all the following forms of documentation:

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NOTE: If the README has many more badges, you might want to consider using a table for badges: see this example. Such a table should be more wide than high. (Note that the a badge for pyOpenSci peer-review will be provided upon acceptance.)

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Reviewers are encouraged to submit suggestions (or pull requests) that will improve the usability of the package as a whole.
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  • All tests pass on the reviewer's local machine for the package version submitted by the author. Ideally this should be a tagged version making it easy for reviewers to install.
  • Tests cover essential functions of the package and a reasonable range of inputs and conditions.
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  A few notable highlights to look at:
  • Package supports modern versions of Python and not End of life versions.
  • Code format is standard throughout package and follows PEP 8 guidelines (CI tests for linting pass)

For packages also submitting to JOSS

• The package has an obvious research application according to JOSS's definition in their submission requirements.

Note: Be sure to check this carefully, as JOSS's submission requirements and scope differ from pyOpenSci's in terms of what types of packages are accepted.

The package contains a paper.md matching JOSS's requirements with:

• A short summary describing the high-level functionality of the software
• Authors: A list of authors with their affiliations
• A statement of need clearly stating problems the software is designed to solve and its target audience.
• References: With DOIs for all those that have one (e.g. papers, datasets, software).

Final approval (post-review)

• The author has responded to my review and made changes to my satisfaction. I recommend approving this package.

Estimated hours spent reviewing:

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Review Comments

[cdeline]

Hi. I look forward to following @echedey-ls 's example as I learn this process. I will be submitting review pull requests from my fork at https://github.com/cdeline/solar-data-tools. My reviewer template is copied below:

Review - will be updated over time

Package Review

Please check off boxes as applicable, and elaborate in comments below. Your review is not limited to these topics, as described in the reviewer guide

- [ ] As the reviewer I confirm that there are no conflicts of interest for me to review this work (If you are unsure whether you are in conflict, please speak to your editor before starting your review).
I do have to disclose that I've worked with Bennet in the past, have coauthored papers, and will be working more closely with him in the future. I hope that this doesn't affect my objectivity in my review.

Documentation

The package includes all the following forms of documentation:

• A statement of need clearly stating problems the software is designed to solve and its target audience in README.
• Installation instructions: for the development version of the package and any non-standard dependencies in README.
• Vignette(s) demonstrating major functionality that runs successfully locally.
• Function Documentation: for all user-facing functions.
• Examples for all user-facing functions.
• Community guidelines including contribution guidelines in the README or CONTRIBUTING.
• Metadata including author(s), author e-mail(s), a url, and any other relevant metadata e.g., in a pyproject.toml file or elsewhere.

Readme file requirements
The package meets the readme requirements below:

• Package has a README.md file in the root directory.

The README should include, from top to bottom:

• The package name
• Badges for:
  • Continuous integration and test coverage,
  • Docs building (if you have a documentation website),
  • A repostatus.org badge,
  • Python versions supported,
  • Current package version (on PyPI / Conda).

NOTE: If the README has many more badges, you might want to consider using a table for badges: see this example. Such a table should be more wide than high. (Note that the a badge for pyOpenSci peer-review will be provided upon acceptance.)

• Short description of package goals.
• Package installation instructions
• Any additional setup required to use the package (authentication tokens, etc.)
• Descriptive links to all vignettes. If the package is small, there may only be a need for one vignette which could be placed in the README.md file.
  • Brief demonstration of package usage (as it makes sense - links to vignettes could also suffice here if package description is clear)
• Link to your documentation website.
• If applicable, how the package compares to other similar packages and/or how it relates to other packages in the scientific ecosystem.
• Citation information

Usability

Reviewers are encouraged to submit suggestions (or pull requests) that will improve the usability of the package as a whole.
Package structure should follow general community best-practices. In general please consider whether:

• Package documentation is clear and easy to find and use.
• The need for the package is clear
• All functions have documentation and associated examples for use
• The package is easy to install

Functionality

• Installation: Installation succeeds as documented.

• Functionality: Any functional claims of the software been confirmed.

• Performance: Any performance claims of the software been confirmed. (N/A)

• Automated tests:

  • All tests pass on the reviewer's local machine for the package version submitted by the author. Ideally this should be a tagged version making it easy for reviewers to install.
  • Tests cover essential functions of the package and a reasonable range of inputs and conditions.
    (some unit tests are included - overall test coverage of 35% isn't great, but I won't hold up a review just because of low test coverage. It seems like there could be some easy tests that could be added just to confirm functionality)

• Continuous Integration: Has continuous integration setup (We suggest using Github actions but any CI platform is acceptable for review)

• Packaging guidelines: The package conforms to the pyOpenSci packaging guidelines.
  A few notable highlights to look at:

  • Package supports modern versions of Python and not End of life versions.
  • Code format is standard throughout package and follows PEP 8 guidelines (CI tests for linting pass) (yes - code analysis in Spyder returns code formatting scores 6/10 or better)

For packages also submitting to JOSS

• The package has an obvious research application according to JOSS's definition in their submission requirements.

Note: Be sure to check this carefully, as JOSS's submission requirements and scope differ from pyOpenSci's in terms of what types of packages are accepted.

The package contains a paper.md (yes - in the joss_paper branch) matching JOSS's requirements with:

• A short summary describing the high-level functionality of the software
• Authors: A list of authors with their affiliations
• A statement of need clearly stating problems the software is designed to solve and its target audience.
• References: With DOIs for all those that have one (e.g. papers, datasets, software).

Final approval (post-review)

• The author has responded to my review and made changes to my satisfaction. I recommend approving this package.

Estimated hours spent reviewing: 4-5

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Review Comments

[cmarmo]

Hi @cdeline , thank you for your help!
Well, let's say that Solar Data Tools waited a bit more than expected and now have a wonderful team of reviewers! 💓

[cdeline]

Hi, I think I've completed my review. Everything checks out for the most part - I opened a couple of issues that should be pretty simple to address, and there can never be too many pytests. I'm happy to wait for incorporation of my comments, or not - they're pretty trivial. Overall the software looks good and was pretty easy to navigate - admittedly I have loads of experience with time-series PV data, but I expect that someone else without as much experience would be able to get started with this package and could successfully follow the examples and get their own analysis up and running.

[pluflou]

Thank you @cdeline for your review! I will create a new branch on the main repo and work on addressing your comments/issues there. I'll link it here when I push some changes.