[REVIEW]: GCol: A High-Performance Python Library for Graph Colouring

[editorialbot]

Submitting author: @Rhyd-Lewis (Rhyd Lewis)
Repository: https://github.com/Rhyd-Lewis/GCol
Branch with paper.md (empty if default branch): josspaper
Version: v 1.4.2
Editor: @vissarion
Reviewers: @paulbrodersen, @IvanIsCoding
Archive: Pending

Status

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Reviewers and authors:

Please avoid lengthy details of difficulties in the review thread. Instead, please create a new issue in the target repository and link to those issues (especially acceptance-blockers) by leaving comments in the review thread below. (For completists: if the target issue tracker is also on GitHub, linking the review thread in the issue or vice versa will create corresponding breadcrumb trails in the link target.)

Reviewer instructions & questions

@paulbrodersen & @IvanIsCoding, your review will be checklist based. Each of you will have a separate checklist that you should update when carrying out your review.
First of all you need to run this command in a separate comment to create the checklist:

@editorialbot generate my checklist

The reviewer guidelines are available here: https://joss.readthedocs.io/en/latest/reviewer_guidelines.html. Any questions/concerns please let @vissarion know.

✨ Please start on your review when you are able, and be sure to complete your review in the next six weeks, at the very latest ✨

Checklists

📝 Checklist for @paulbrodersen

📝 Checklist for @IvanIsCoding

[editorialbot]

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[editorialbot]

Software report:

github.com/AlDanial/cloc v 1.98  T=0.08 s (491.8 files/s, 276964.7 lines/s)
-------------------------------------------------------------------------------
Language                     files          blank        comment           code
-------------------------------------------------------------------------------
Text                            11              0              0           9198
Python                           8            708           2397           1991
Jupyter Notebook                 4              0           2547            813
reStructuredText                 7            760           1235            683
Markdown                         2             43              0            207
TeX                              1             17              0            132
YAML                             2              7             14             31
DOS Batch                        1              8              1             26
make                             1              4              7              9
-------------------------------------------------------------------------------
SUM:                            37           1547           6201          13090
-------------------------------------------------------------------------------

Commit count by author:

    66	Rhyd-Lewis
     1	Geraint Palmer

[editorialbot]

Paper file info:

⚠️ Wordcount for paper.md is 1443

✅ The paper includes a Statement of need section

[editorialbot]

License info:

✅ License found: MIT License (Valid open source OSI approved license)

[editorialbot]

Reference check summary (note 'MISSING' DOIs are suggestions that need verification):

✅ OK DOIs

- 10.21105/joss.01843 is OK
- 10.1137/0216048 is OK

🟡 SKIP DOIs

- No DOI given, and none found for title: Boost Graph Library
- No DOI given, and none found for title: ColPack
- No DOI given, and none found for title: Guide Coloring Methods
- No DOI given, and none found for title: Culberson’s Node Coloring Implementations
- No DOI given, and none found for title: DSatur
- No DOI given, and none found for title: GCol: A Library for Graph Coloring
- No DOI given, and none found for title: Goblin Graph Library
- No DOI given, and none found for title: A graph coloring algorithm for large scheduling pr...
- No DOI given, and none found for title: Lemon Graph Library
- No DOI given, and none found for title: Guide to Graph Colouring: Algorithms and Applicati...
- No DOI given, and none found for title: A Guide to Graph Colouring: User Guide
- No DOI given, and none found for title: NetworkX: Network Analysis in Python
- No DOI given, and none found for title: The Four Color Theorem
- No DOI given, and none found for title: SageMath: Graph Coloring
- No DOI given, and none found for title: COLOR.C: Easy code for graph coloring
- No DOI given, and none found for title: Vizing’s Theorem

❌ MISSING DOIs

- None

❌ INVALID DOIs

- None

[paulbrodersen]

Review checklist for @paulbrodersen

Conflict of interest

• I confirm that I have read the JOSS conflict of interest (COI) policy and that: I have no COIs with reviewing this work or that any perceived COIs have been waived by JOSS for the purpose of this review.

Code of Conduct

• I confirm that I read and will adhere to the JOSS code of conduct.

General checks

• Repository: Is the source code for this software available at the https://github.com/Rhyd-Lewis/GCol?
• License: Does the repository contain a plain-text LICENSE or COPYING file with the contents of an OSI approved software license?
• Contribution and authorship: Has the submitting author (@Rhyd-Lewis) made major contributions to the software? Does the full list of paper authors seem appropriate and complete?
• Substantial scholarly effort: Does this submission meet the scope eligibility described in the JOSS guidelines
• Data sharing: If the paper contains original data, data are accessible to the reviewers. If the paper contains no original data, please check this item.
• Reproducibility: If the paper contains original results, results are entirely reproducible by reviewers. If the paper contains no original results, please check this item.
• Human and animal research: If the paper contains original data research on humans subjects or animals, does it comply with JOSS's human participants research policy and/or animal research policy? If the paper contains no such data, please check this item.

Functionality

• Installation: Does installation proceed as outlined in the documentation?
• Functionality: Have the functional claims of the software been confirmed?
• Performance: If there are any performance claims of the software, have they been confirmed? (If there are no claims, please check off this item.)

Documentation

• A statement of need: Do the authors clearly state what problems the software is designed to solve and who the target audience is?
• Installation instructions: Is there a clearly-stated list of dependencies? Ideally these should be handled with an automated package management solution.
• Example usage: Do the authors include examples of how to use the software (ideally to solve real-world analysis problems).
• Functionality documentation: Is the core functionality of the software documented to a satisfactory level (e.g., API method documentation)?
• Automated tests: Are there automated tests or manual steps described so that the functionality of the software can be verified?
• Community guidelines: Are there clear guidelines for third parties wishing to 1. Contribute to the software 2. Report issues or problems with the software 3. Seek support

Software paper

• Summary: Has a clear description of the high-level functionality and purpose of the software for a diverse, non-specialist audience been provided?
• A statement of need: Does the paper have a section titled 'Statement of need' that clearly states what problems the software is designed to solve, who the target audience is, and its relation to other work?
• State of the field: Do the authors describe how this software compares to other commonly-used packages?
• Quality of writing: Is the paper well written (i.e., it does not require editing for structure, language, or writing quality)?
• References: Is the list of references complete, and is everything cited appropriately that should be cited (e.g., papers, datasets, software)? Do references in the text use the proper citation syntax?

[editorialbot]

👉📄 Download article proof 📄 View article proof on GitHub 📄 👈

[IvanIsCoding]

Review checklist for @IvanIsCoding

Conflict of interest

• I confirm that I have read the JOSS conflict of interest (COI) policy and that: I have no COIs with reviewing this work or that any perceived COIs have been waived by JOSS for the purpose of this review.

Code of Conduct

• I confirm that I read and will adhere to the JOSS code of conduct.

General checks

• Repository: Is the source code for this software available at the https://github.com/Rhyd-Lewis/GCol?
• License: Does the repository contain a plain-text LICENSE or COPYING file with the contents of an OSI approved software license?
• Contribution and authorship: Has the submitting author (@Rhyd-Lewis) made major contributions to the software? Does the full list of paper authors seem appropriate and complete?
• Substantial scholarly effort: Does this submission meet the scope eligibility described in the JOSS guidelines
• Data sharing: If the paper contains original data, data are accessible to the reviewers. If the paper contains no original data, please check this item.
• Reproducibility: If the paper contains original results, results are entirely reproducible by reviewers. If the paper contains no original results, please check this item.
• Human and animal research: If the paper contains original data research on humans subjects or animals, does it comply with JOSS's human participants research policy and/or animal research policy? If the paper contains no such data, please check this item.

Functionality

• Installation: Does installation proceed as outlined in the documentation?
• Functionality: Have the functional claims of the software been confirmed?
• Performance: If there are any performance claims of the software, have they been confirmed? (If there are no claims, please check off this item.)

Documentation

• A statement of need: Do the authors clearly state what problems the software is designed to solve and who the target audience is?
• Installation instructions: Is there a clearly-stated list of dependencies? Ideally these should be handled with an automated package management solution.
• Example usage: Do the authors include examples of how to use the software (ideally to solve real-world analysis problems).
• Functionality documentation: Is the core functionality of the software documented to a satisfactory level (e.g., API method documentation)?
• Automated tests: Are there automated tests or manual steps described so that the functionality of the software can be verified?
• Community guidelines: Are there clear guidelines for third parties wishing to 1. Contribute to the software 2. Report issues or problems with the software 3. Seek support

Software paper

• Summary: Has a clear description of the high-level functionality and purpose of the software for a diverse, non-specialist audience been provided?
• A statement of need: Does the paper have a section titled 'Statement of need' that clearly states what problems the software is designed to solve, who the target audience is, and its relation to other work?
• State of the field: Do the authors describe how this software compares to other commonly-used packages?
• Quality of writing: Is the paper well written (i.e., it does not require editing for structure, language, or writing quality)?
• References: Is the list of references complete, and is everything cited appropriately that should be cited (e.g., papers, datasets, software)? Do references in the text use the proper citation syntax?

[paulbrodersen]

@editorialbot generate pdf

[editorialbot]

👉📄 Download article proof 📄 View article proof on GitHub 📄 👈

[paulbrodersen]

Hi @Rhyd-Lewis, pleasure to make your acquaintance. W.r.t. General checks / item 3 on our checklists, could you expand a bit on the contributions of your co-author Geraint Palmer? None of the commits seem to list him as author or co-author (though I am aware that the software was developed offline and uploaded at a late stage in the development cycle).

[paulbrodersen]

W.r.t Documentation / item 5: Automated tests:

The test suite looks great, the selection of test cases is self-explanatory, and the whole suite passes without skipping any tests in a reasonable amount of time. Two comments though:

1. While anybody likely to execute the test suite will know how to execute a pytest test suite, please include instructions in the documentation how to execute the tests. It allows me to check that box, and it can help with trouble-shooting support requests in the future.
2. pytest should be listed as an optional dependency in setup.py:

setup(
    name="gcol",
    ...
    extras_require = {
        'testing':  ["pytest"]
    }
)

[paulbrodersen]

Ditto for pandas, which is used in some of the examples:

setup(
    name="gcol",
    ...
    extras_require = {
        'testing':  ["pytest"],
        'documentation' : ["pandas"],
    }
)

[paulbrodersen]

I don't have time to confirm the performance claims nor to look into the references now, but I will try to before the end of the week.

[Rhyd-Lewis]

Hi @paulbrodersen -- thank you for your comments and your time.

I have created a new branch with the above arguments added to the setup.py file. Once it's been tested, I'll merge it into main.

Regarding your other question, Geraint is my colleague at Cardiff university who has been very helpful in preparing this library. We pair programmed using my github account and he helped to oversee the packaging, paper preperation, linking to gitub, and conversion of my existing c++-based algorithms into python implementations.

Thanks

Rhyd