[REVIEW]: PyNumDiff 2.0: Practical Numerical Differentiation for Noisy Data

[editorialbot]

Submitting author: @pavelkomarov (Pavel Komarov)
Repository: https://github.com/florisvb/PyNumDiff
Branch with paper.md (empty if default branch): joss2.0
Version: v0.2.3
Editor: @prashjha
Reviewers: @alexzerg, @sidxz
Archive: Pending

Status

Status badge code:

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Markdown: [![status](https://joss.theoj.org/papers/3b87180224e98705b4312cc35aaa615b/status.svg)](https://joss.theoj.org/papers/3b87180224e98705b4312cc35aaa615b)

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

@alexzerg & @sidxz, 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 @prashjha know.

✨ Please start on your review when you are able; the expectation is that it will take 2-4 weeks to complete. ✨

Checklists

📝 Checklist for @sidxz

📝 Checklist for @alexzerg

[editorialbot]

Hello humans, I'm @editorialbot, a robot that can help you with some common editorial tasks.

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For example, to regenerate the paper pdf after making changes in the paper's md or bib files, type:

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[editorialbot]

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

✅ OK DOIs

- 10.21105/joss.04078 is OK
- 10.1109/ACCESS.2020.3034077 is OK
- 10.5402/2011/164564 is OK
- 10.1073/pnas.1517384113 is OK
- 10.1038/s41592-019-0686-2 is OK
- 10.1038/s41586-020-2649-2 is OK
- 10.1021/ac60214a047 is OK
- 10.2514/3.3166 is OK
- 10.1007/978-3-642-38398-4_8 is OK
- 10.1115/1.3662552 is OK
- 10.1016/j.cpc.2007.03.009 is OK
- 10.21105/joss.02104 is OK
- 10.21105/joss.01237 is OK

🟡 SKIP DOIs

- No DOI given, and none found for title: A Taxonomy of Numerical Differentiation Methods
- No DOI given, and none found for title: CVXPY: A Python-embedded modeling language for con...
- No DOI given, and none found for title: derivative: Numerical differentiation in Python

❌ MISSING DOIs

- None

❌ INVALID DOIs

- None

[editorialbot]

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

[editorialbot]

Repository Analysis Report

Code breakdown

github.com/AlDanial/cloc v 1.98  T=0.06 s (903.8 files/s, 117476.5 lines/s)
-------------------------------------------------------------------------------
Language                     files          blank        comment           code
-------------------------------------------------------------------------------
Python                          19            583           1177           1950
Jupyter Notebook                 7              0           2225            580
Markdown                         5            100              2            265
TeX                              1             15              0            152
YAML                             4              5              0             73
reStructuredText                17             36             70             65
TOML                             1              4              0             55
Text                             1              3              0             18
INI                              1              2              0              9
make                             1              4              7              9
-------------------------------------------------------------------------------
SUM:                            57            752           3481           3176
-------------------------------------------------------------------------------

Commit Count by Author

372	pavelkomarov
   177	Floris van Breugel
    53	luckystarufo
    18	dependabot[bot]
    15	Pavel Komarov
    11	Maria Protogerou
     7	Jake Stevens-Haas
     4	floris
     3	Yuying
     3	pavel
     2	Ashton Graves
     2	Daniel S. Katz
     2	Nimra-Fayaz
     2	asteppke
     1	fossabot

Repository History

Repository age: First commit on November 29, 2018

Code distribution (top 3 48-hour windows):

Period	Insertions	% of Total	Signal	View Changes
Jun 01, 2021 - Jun 03, 2021	427557	38.3%	🟡	View diff
Sep 01, 2020 - Sep 03, 2020	422948	37.9%	🟡	View diff
Oct 15, 2025 - Oct 17, 2025	109454	9.8%	🟢	View diff

GitHub Activity Metrics

Metric	Count
GitHub stars	135
Forks	24
GitHub contributors	11
Releases	9
Total issues	82
Total pull requests	120
Unique commenters/reviewers (excluding authors)	5

[editorialbot]

Paper file info:

📄 Wordcount for paper.md is 1447

✅ The paper includes a Statement of need section

✅ The paper includes a State of the field section

✅ The paper includes a Software design section

✅ The paper includes a Research impact statement section

✅ The paper includes an AI usage disclosure section

[editorialbot]

License info:

🟡 License found: Other (Check here for OSI approval)

[prashjha]

Hi @alexzerg, @sidxz, please read the first couple of comments in this thread and create your review checklist. You can read the reviewer guidelines here. Also, you can browse the closed "REVIEW" issues on the "joss-reviews" repository to get some ideas on how to complete the reviews.

For a software or a Joss article draft, you can directly create a GitHub issue on the repository (see the link at the top). When you create an issue, include the text #10630 to refer to this review.

[prashjha]

Hi @alexzerg, @sidxz, the authors have indicated that this is a second JOSS publication on the software pynumdiff and I asked for some clarification here and the authors response can be found here.

I will suggest accounting for this conversation in your reviews.

[editorialbot]

I'm sorry human, I don't understand that. You can see what commands I support by typing:

@editorialbot commands

[sidxz]

Review checklist for @sidxz

AI usage

• I confirm that I have read the JOSS AI policy and understand that:
  • AI may only be used for non-substantive assistance (e.g., grammar checking my review text, contextualizing public materials)
  • All evaluative decisions—including scoring, accept/reject recommendations, and assessments of originality, correctness, significance, and ethics compliance—must be made exclusively by me, not AI
  • I bear full responsibility for all judgments, recommendations, and technical claims in my review
  • I will disclose any AI assistance at the conclusion of my review

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/florisvb/PyNumDiff?
• 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 (@pavelkomarov) made major contributions to the software? Does the full list of paper authors seem appropriate and complete?
• Scope and significance: Does this submission demonstrate clear research impact or credible scholarly significance as 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.

Development history and open-source practice

• Development timeline: Does the project show evidence of sustained development over time (preferably months or years) rather than rapid, recent code generation?
• Open development: Was the software developed openly from early stages? For projects with recent public repositories, is there at least six months of public development history with evidence of releases, public issues/pull requests, and ideally external engagement?
• Collaborative effort: Does the project show evidence of community engagement — such as contributions from multiple developers, issues/discussions from external users, or community influence on development — in the repo or as described in the paper?
• Good practices: Does the project look like a reusable, non-throwaway research software project that follows good open-source practices (license, documentation, tests and/or verification processes, releases, and clear contribution/support pathways).

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 (required section): 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 (required section): 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 (required section): Do the authors describe how this software compares to other commonly-used packages? If related tools exist, do they provide a clear "build vs. contribute" justification explaining their unique scholarly contribution and why alternatives are insufficient?
• Software Design (required section): Does the paper include a "Software Design" section that explains the trade-offs weighed, the design/architecture chosen, and why it matters? Is the content compelling and does it demonstrate meaningful design thinking?
• Research Impact Statement (required section): Does the paper include a "Research Impact Statement" section providing evidence of realized impact (publications, external use, integrations) or credible near-term significance (benchmarks, reproducible materials, community-readiness signals)? Is the evidence presented compelling?
• AI usage disclosure (required section): Does the paper include an "AI usage disclosure" section that transparently discloses any use of generative AI in the software creation, documentation, or paper authoring?
• 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?

[alexzerg]

Review checklist for @alexzerg

AI usage

• I confirm that I have read the JOSS AI policy and understand that:
  • AI may only be used for non-substantive assistance (e.g., grammar checking my review text, contextualizing public materials)
  • All evaluative decisions—including scoring, accept/reject recommendations, and assessments of originality, correctness, significance, and ethics compliance—must be made exclusively by me, not AI
  • I bear full responsibility for all judgments, recommendations, and technical claims in my review
  • I will disclose any AI assistance at the conclusion of my review

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/florisvb/PyNumDiff?
• 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 (@pavelkomarov) made major contributions to the software? Does the full list of paper authors seem appropriate and complete?
• Scope and significance: Does this submission demonstrate clear research impact or credible scholarly significance as 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.

Development history and open-source practice

• Development timeline: Does the project show evidence of sustained development over time (preferably months or years) rather than rapid, recent code generation?
• Open development: Was the software developed openly from early stages? For projects with recent public repositories, is there at least six months of public development history with evidence of releases, public issues/pull requests, and ideally external engagement?
• Collaborative effort: Does the project show evidence of community engagement — such as contributions from multiple developers, issues/discussions from external users, or community influence on development — in the repo or as described in the paper?
• Good practices: Does the project look like a reusable, non-throwaway research software project that follows good open-source practices (license, documentation, tests and/or verification processes, releases, and clear contribution/support pathways).

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 (required section): 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 (required section): 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 (required section): Do the authors describe how this software compares to other commonly-used packages? If related tools exist, do they provide a clear "build vs. contribute" justification explaining their unique scholarly contribution and why alternatives are insufficient?
• Software Design (required section): Does the paper include a "Software Design" section that explains the trade-offs weighed, the design/architecture chosen, and why it matters? Is the content compelling and does it demonstrate meaningful design thinking?
• Research Impact Statement (required section): Does the paper include a "Research Impact Statement" section providing evidence of realized impact (publications, external use, integrations) or credible near-term significance (benchmarks, reproducible materials, community-readiness signals)? Is the evidence presented compelling?
• AI usage disclosure (required section): Does the paper include an "AI usage disclosure" section that transparently discloses any use of generative AI in the software creation, documentation, or paper authoring?
• 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?