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): 06/13/2025

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  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.

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  • Data retrieval
  • Data extraction
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• Geospatial
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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).

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    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.
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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!

[jinningwang]

Sorry for the late reply. I finished my defense earlier this month, and should be able to give my comments in two or three days.

[bmeyers]

@jinningwang congrats on the defense!

[jinningwang]

Thanks for the efforts in this work! My review report is here.

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Estimated hours spent reviewing:
2.5

Review Comments

The package is well structured and easy to use.
The documentation is clear and provides good examples of how to use the package.
The installation process is straightforward and works as documented.
Some concerns are listed as below:

1. A list of supported Python versions would be helpful in the README file.
2. Formatting issues are present in the codebase. My local test is excerpted at the end of this review for your reference.
3. A repostatus.org badge in the README file might be useful to indicate the status of the package.

Additional info is provided below:
My local test environment is created via conda with following packages:

• Python 3.12.10
• numpy 2.2.5
• pandas 2.2.3
• pytest 8.3.5
• flake8 7.2.0
• solar-data-tools 1.7.1

Testing lint using flake8 on commit 18e2939bcf673eb2c234353e142a9152b7db4c66, shows some formatting issues.
Some of them are:

./solardatatools/clear_day_detection.py:60:80: E501 line too long (105 > 79 characters)
./solardatatools/clear_day_detection.py:61:80: E501 line too long (99 > 79 characters)
./solardatatools/clear_day_detection.py:63:80: E501 line too long (118 > 79 characters)
./solardatatools/clear_day_detection.py:65:80: E501 line too long (81 > 79 characters)
./solardatatools/clear_day_detection.py:71:80: E501 line too long (83 > 79 characters)
./solardatatools/clear_day_detection.py:72:80: E501 line too long (81 > 79 characters)
./solardatatools/clear_day_detection.py:78:80: E501 line too long (80 > 79 characters)
./solardatatools/clear_day_detection.py:88:80: E501 line too long (111 > 79 characters)
./solardatatools/clear_day_detection.py:96:80: E501 line too long (84 > 79 characters)
./solardatatools/clear_day_detection.py:98:80: E501 line too long (91 > 79 characters)
./solardatatools/clear_time_labeling.py:30:80: E501 line too long (83 > 79 characters)
./solardatatools/clear_time_labeling.py:32:80: E501 line too long (82 > 79 characters)
./solardatatools/clear_time_labeling.py:40:80: E501 line too long (83 > 79 characters)
./solardatatools/clear_time_labeling.py:42:80: E501 line too long (85 > 79 characters)
./solardatatools/clear_time_labeling.py:43:80: E501 line too long (81 > 79 characters)
./solardatatools/data_filling.py:10:1: F401 'matplotlib.pyplot as plt' imported but unused
./solardatatools/data_filling.py:11:1: F401 'solardatatools.daytime.find_daytime' imported but unused
./solardatatools/data_handler.py:17:17: E401 multiple imports on one line
./solardatatools/data_handler.py:46:1: E402 module level import not at top of file

[cmarmo]

Thank you so much @jinningwang ! And congratulations on your defense!
We have officially all the reviews in!

[pluflou]

Thank you so much everyone! We really appreciate your time and comments! I will work on getting the changes/responses back by the end of May.

[pluflou]

Hi all,

Many thanks to @cdeline, @echedey-ls and @jinningwang for their reviews. I have created three PRs that address the reviewers' comments, as well as Issues that note things that were raised that weren't gating for this review for future work. Please feel free to review/comment as needed.

Open PRs

• PyOS review updates and fixes (part 1) slacgismo/solar-data-tools#197 contains most of the requested changes and closes all of the related open issues
• Update precommit hooks and add ruff linting (PyOS review part 2) slacgismo/solar-data-tools#198 follows @jinningwang's suggestion to implement linting
• Remove StatisticalClearSky slacgismo/solar-data-tools#200 isn't directly related to the comments, but it removes the deprecated StatisticalClearSky package, and I plan to merge this one first and update PRs 197 and 198 accordingly

Open Issues (for future work)

• DOC: Remove duplicate notebooks slacgismo/solar-data-tools#201
• ENH: put packages under once namespace and move to src/ repo layout slacgismo/solar-data-tools#202
• ENH: Add ax parameter to DataHandler.plot_* methods slacgismo/solar-data-tools#203

If I missed anything, please let me know, otherwise, I'll wait for comments/approvals/confirmation before we merge the PRs. Thank you all!

[cmarmo]

@pluflou thank you for your work!
I believe you can merge the PRs related to the review, so the reviewers will have to check the main code base for the final acceptation: it will make life easier for them and spped up the final review.
What do you think?

[pluflou]

@cmarmo ok great, that sounds reasonable to me! I'll merge it tomorrow and ping everyone when I'm done. Thank you!

[pluflou]

Hi all, I have merged the changes to the main branch. Please let me know if you have any comments. Thank you!

[cmarmo]

Thank you @pluflou for your follow-up!
@cdeline , @echedey-ls , @jinningwang do you mind letting us know if your are happy with the changes and the answers to your comments?
Thanks a lot!

[cdeline]

Looks good to me. I pulled changes and tested notebooks for functionality, everything appears to be working. Thanks for your efforts!

[cmarmo]

Thank you @cdeline for your answer! Do you mind checking the checkbox (sorry for the lack of vocabulary...) accepting the package at the end of your review if you are happy with the changes? Thanks!

[jinningwang]

Thanks for the improvement and most changes are good to me.

One last concern is: Code format is standard throughout package and follows PEP 8 guidelines (CI tests for linting pass)

1. With flake8 7.2.0, I ran tests on slacgismo/solar-data-tools@792df3f, some format issues occurred.
   If there is a lint config file or linter specified, feel free to let me know

./sdt_dask/clients/local_client.py:61:80: E501 line too long (80 > 79 characters)
./sdt_dask/clients/local_client.py:62:80: E501 line too long (80 > 79 characters)
./sdt_dask/clients/local_client.py:70:80: E501 line too long (80 > 79 characters)
./sdt_dask/clients/local_client.py:80:80: E501 line too long (93 > 79 characters)
./sdt_dask/clients/local_client.py:85:80: E501 line too long (104 > 79 characters)
./sdt_dask/dask_tool/runner.py:3:80: E501 line too long (82 > 79 characters)
./sdt_dask/dask_tool/runner.py:4:80: E501 line too long (86 > 79 characters)
./sdt_dask/dask_tool/runner.py:75:80: E501 line too long (80 > 79 characters)
./sdt_dask/dask_tool/runner.py:89:80: E501 line too long (82 > 79 characters)
./sdt_dask/dask_tool/runner.py:118:80: E501 line too long (128 > 79 characters)
./sdt_dask/dask_tool/runner.py:135:80: E501 line too long (82 > 79 characters)
./sdt_dask/dask_tool/runner.py:156:80: E501 line too long (82 > 79 characters)
./sdt_dask/dask_tool/runner.py:201:80: E501 line too long (81 > 79 characters)
./sdt_dask/dask_tool/runner.py:214:80: E501 line too long (81 > 79 characters)
./sdt_dask/dataplugs/S3Bucket_plug.py:57:80: E501 line too long (80 > 79 characters)
./sdt_dask/dataplugs/S3Bucket_plug.py:58:80: E501 line too long (80 > 79 characters)
./sdt_dask/dataplugs/S3Bucket_plug.py:75:80: E501 line too long (100 > 79 characters)
./sdt_dask/dataplugs/csv_plug.py:14:80: E501 line too long (81 > 79 characters)
./sdt_dask/dataplugs/csv_plug.py:48:80: E501 line too long (82 > 79 characters)
./sdt_dask/dataplugs/dataplug.py:12:80: E501 line too long (81 > 79 characters)
./sdt_dask/dataplugs/pvdb_plug.py:22:80: E501 line too long (81 > 79 characters)
...

2. I didn't find lint process in CI here, https://github.com/slacgismo/solar-data-tools/blob/792df3f325b87f11690e60848d1915422bf3fe12/.github/workflows/lint.yml#L4

A GitHub action might be useful for lint purpose and its integration in CI, https://github.com/marketplace/actions/lint-action

[pluflou]

@cdeline @jinningwang Thank you so much for reviewing the changes!

@jinningwang I am using ruff for formatting, which may have different settings than flake8 (we can control them and make them match, but I left them mostly at default). I set up linting up using pre-commit hooks (you can see the instructions here on step 7), but you can also install ruff and run ruff check and ruff format. The settings for the ruff checks are in here. The workflow is running the linting check on this line. What you are seeing is due to the fact that ruff does not enforce E501 by default, and I did not add it, but it would be straightforward to do so if that's your recommendation. Let me known if you have other questions/your thoughts.

[jinningwang]

Thanks for your clarification! Then I have no more questions. Thanks again for your excellent work! Regards, Jinning

…

On Tue, Jun 10, 2025 at 22:39 Sara A. Miskovich ***@***.***> wrote: *pluflou* left a comment (pyOpenSci/software-submission#210) <#210 (comment)> @cdeline <https://github.com/cdeline> @jinningwang <https://github.com/jinningwang> Thank you so much for reviewing the changes! @jinningwang <https://github.com/jinningwang> I am using ruff for formatting, which may have different settings than flake8 (we can control them and make them match, but I left them mostly at default). I set up linting up using pre-commit hooks (you can see the instructions here on step 7 <https://github.com/slacgismo/solar-data-tools/blob/main/CONTRIBUTING.md>), but you can also install ruff and run ruff check and ruff format. The settings for the ruff checks are in here <https://github.com/slacgismo/solar-data-tools/blob/792df3f325b87f11690e60848d1915422bf3fe12/.pre-commit-config.yaml#L20>. The workflow is running the linting check on this line <https://github.com/slacgismo/solar-data-tools/blob/792df3f325b87f11690e60848d1915422bf3fe12/.github/workflows/lint.yml#L38>. What you are seeing is due to the fact that ruff does not enforce E501 by default, and I did not add it, but it would be straightforward to do so if that's your recommendation. Let me known if you have other questions/your thoughts. — Reply to this email directly, view it on GitHub <#210 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AS4OJPM4QNS3D2FAR5BZLML3C6JGZAVCNFSM6AAAAABMVE3TOSVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDSNRRGA2TEOJSHE> . You are receiving this because you were mentioned.Message ID: ***@***.***>

[pluflou]

Thank you @jinningwang for your review! We really appreciate it.

@cmarmo Could you let me know what the next steps are? We also have a JOSS paper in the repo, but I'm not sure what the process is after this.

[cmarmo]

@pflou, as soon as @echedey-ls will finalise his answer, we can declare the package accepted and move forward with the JOSS submission.
Luckily we have a nice checklist for that too ... :)

[echedey-ls]

Everything's ok from my side. I had already seen those PRs, not the main code, due to my lack of free time lately. Good job!

[cmarmo]

Wonderful! I guess it's time to move to the next step then.

🎉 Solar Data Tools has been approved by pyOpenSci! Thank you @pluflou for submitting and many thanks to @cdeline, @echedey-ls and @jinningwang for reviewing this package! 😸

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It looks like you would like to submit this package to JOSS. Here are the next steps:

• Once the JOSS issue is opened for the package, we strongly suggest that you subscribe to issue updates. This will allow you to continue to update the issue labels on this review as it goes through the JOSS process.
• Login to the JOSS website and fill out the JOSS submission form using your Zenodo DOI. When you fill out the form, be sure to mention and link to the approved pyOpenSci review. JOSS will tag your package for expedited review if it is already pyOpenSci approved.
• Wait for a JOSS editor to approve the presubmission (which includes a scope check).
• Once the package is approved by JOSS, you will be given instructions by JOSS about updating the citation information in your README file.
• When the JOSS review is complete, add a comment to your review in the pyOpenSci software-review repo here that it has been approved by JOSS. An editor will then add the JOSS-approved label to this issue.

Editor Final Checks

Please complete the final steps to wrap up this review. Editor, please do the following:

• Make sure that the maintainers filled out the post-review survey
• Invite the maintainers to submit a blog post highlighting their package. Feel free to use / adapt language found in this comment to help guide the author.
• Change the status tag of the issue to 6/pyOS-approved6 🚀🚀🚀.
• Invite the package maintainer(s) and both reviewers to slack if they wish to join.
• If the author submits to JOSS, please continue to update the labels for JOSS on this issue until the author is accepted (do not remove the 6/pyOS-approved label). Once accepted add the label 9/joss-approved to the issue. Skip this check if the package is not submitted to JOSS.
• If the package is JOSS-accepted please add the JOSS doi to the YAML at the top of the issue.

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If you have any feedback for us about the review process please feel free to share it here. We are always looking to improve our process and documentation in the peer-review-guide.

[cmarmo]

@pluflou, @bmeyers, @cdeline, @echedey-ls and @jinningwang, please let me know if you are interested in an invite to the pyopensci Slack, I will be happy to provide you with it.

Also if the authors are interested in writing a blogpost about the review process pyopensci can provide the infrastructure to host it.

[jinningwang]

I can join it. Do I need to register it first? Regards, Jinning

…

On Fri, Jun 13, 2025 at 13:05 Chiara Marmo ***@***.***> wrote: *cmarmo* left a comment (pyOpenSci/software-submission#210) <#210 (comment)> @pluflou <https://github.com/pluflou>, @bmeyers <https://github.com/bmeyers>, @cdeline <https://github.com/cdeline>, @echedey-ls <https://github.com/echedey-ls> and @jinningwang <https://github.com/jinningwang>, please let me know if you are interested in an invite to the pyopensci Slack, I will be happy to provide you with it. Also if the authors are interested in writing a blogpost about the review process pyopensci can provide the infrastructure to host it. — Reply to this email directly, view it on GitHub <#210 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AS4OJPIOR5R75CERPWRYD433DMAEHAVCNFSM6AAAAABMVE3TOSVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDSNZQHE4DGNZQGU> . You are receiving this because you were mentioned.Message ID: ***@***.***>

[cmarmo]

I can join it. Do I need to register it first?

@jinningwang you are right, you are already in! No need for an invite! 🙂

[pluflou]

Thank you @cmarmo! Please add me to the Slack channel! I update the remaining tasks below, I will update as things progress with JOSS. Who submits the JOSS issue?

Author Wrap Up Tasks

• Activate Zenodo watching the repo if you haven't already done so.

• Tag and create a release to create a Zenodo version and DOI.

• Add the badge for pyOpenSci peer-review to the README.md of Solar Data Tools. The badge should be [![pyOpenSci Peer-Reviewed](https://pyopensci.org/badges/peer-reviewed.svg)](https://github.com/pyOpenSci/software-review/issues/issue-number).

• Please fill out the post-review survey. All maintainers and reviewers should fill this out.

• Once the JOSS issue is opened for the package, we strongly suggest that you subscribe to issue updates. This will allow you to continue to update the issue labels on this review as it goes through the JOSS process.

• Login to the JOSS website and fill out the JOSS submission form using your Zenodo DOI. When you fill out the form, be sure to mention and link to the approved pyOpenSci review. JOSS will tag your package for expedited review if it is already pyOpenSci approved.

• Wait for a JOSS editor to approve the presubmission (which includes a scope check).

• Once the package is approved by JOSS, you will be given instructions by JOSS about updating the citation information in your README file.

• When the JOSS review is complete, add a comment to your review in the pyOpenSci software-review repo here that it has been approved by JOSS. An editor will then add the JOSS-approved label to this issue.

[cmarmo]

Thank you @pluflou ! Do you mind creating a new release containing the modifications originated by the review? The 1.7.1 is dated back to April. The new one will be the version accepted by pyOpenSci.

Who submits the JOSS issue?

The authors / maintainers of the package take care of the submission: be sure to mention and link to the approved pyOpenSci review. Thanks a lot!
I will take care of the labelling of this issue while the JOSS submission moves forward.