[REVIEW]: Deep-River: A Deep Learning Library for Data Streams

editorialbot commented 1 month ago

Submitting author: !--author-handle-->@kulbachcedric@cheginit<!--end-editor-- Reviewers: @musabgultekin, @atanikan Archive: Pending

Status

Status badge code:

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Markdown: [![status](https://joss.theoj.org/papers/6a76784f55e8b041d71a7fa776eb386a/status.svg)](https://joss.theoj.org/papers/6a76784f55e8b041d71a7fa776eb386a)

Reviewers and authors:

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Reviewer instructions & questions

@musabgultekin & @atanikan, 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 @cheginit 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 @musabgultekin

📝 Checklist for @atanikan

editorialbot commented 1 month ago

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editorialbot commented 1 month ago

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

✅ OK DOIs

- 10.48550/arXiv.2405.17222 is OK
- 10.1007/978-3-031-26387-3_16 is OK
- 10.1016/j.knosys.2022.108632 is OK
- 10.1109/TKDE.2018.2876857 is OK

🟡 SKIP DOIs

- No DOI given, and none found for title: River: machine learning for streaming data in Pyth...
- No DOI given, and none found for title: Automatic differentiation in PyTorch

❌ MISSING DOIs

- None

❌ INVALID DOIs

- None

editorialbot commented 1 month ago

Software report:

github.com/AlDanial/cloc v 1.90  T=0.11 s (635.9 files/s, 341185.9 lines/s)
-------------------------------------------------------------------------------
Language                     files          blank        comment           code
-------------------------------------------------------------------------------
Markdown                         6            221              0          23669
Python                          32            654           1502           2625
CSV                              3              0              0           2103
Jupyter Notebook                13              0           4252           1015
CSS                              1             55             17            336
YAML                             5             35             15            218
HTML                             3             12             11             71
TeX                              1              0              0             58
TOML                             1              5              1             57
JSON                             1              0              0             43
JavaScript                       1              1              0             15
make                             1              6              0             14
Bourne Shell                     1              1              0              7
-------------------------------------------------------------------------------
SUM:                            69            990           5798          30231
-------------------------------------------------------------------------------

Commit count by author:

   414  Cedric Kulbach
    90  Lucas Cazzonelli
    34  kulbach
     4  Hoang-Anh Ngo
     2  LCa95
     2  Max Halford
     1  Lucas

editorialbot commented 1 month ago

Paper file info:

📄 Wordcount for paper.md is 1019

✅ The paper includes a Statement of need section

editorialbot commented 1 month ago

License info:

✅ License found: BSD 3-Clause "New" or "Revised" License (Valid open source OSI approved license)

cheginit commented 1 month ago

👋🏼 @@kulbachcedric, @musabgultekin, and @atanikan, this is the review thread for the paper. All of our communications will happen here from now on.

As a reviewer, the first step, as mentioned in the first comment of this issue, is to create a checklist for your review by entering

@editorialbot generate my checklist

as the top of a new comment in this thread.

These checklists contain the JOSS requirements. As you go over the submission, please check any items that you feel have been satisfied. The first comment in this thread also contains links to the JOSS reviewer guidelines.

The JOSS review is different from most other journals. Our goal is to work with the authors to help them meet our criteria instead of merely passing judgment on the submission. As such, the reviewers are encouraged to submit issues and pull requests on the software repository. When doing so, please mention openjournals/joss-reviews#7226 so that a link is created to this thread (and I can keep an eye on what is happening). Please also feel free to comment and ask questions on this thread. In my experience, it is better to post comments/questions/suggestions as you come across them, instead of waiting until you've reviewed the entire package.

We aim for reviews to be completed within about 2-4 weeks. Please notify me if any of you require some more time. We can also use EditorialBot (our bot) to set automatic reminders if you know you'll be away for a known period of time.

Please don't hesitate to ping me (@cheginit) if you have any questions/concerns.

editorialbot commented 1 month ago

:point_right::page_facing_up: Download article proof :page_facing_up: View article proof on GitHub :page_facing_up: :point_left:

musabgultekin commented 1 month ago

Review checklist for @musabgultekin

Conflict of interest

[x] 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

[x] I confirm that I read and will adhere to the JOSS code of conduct.

General checks

[x] Repository: Is the source code for this software available at the https://github.com/online-ml/deep-river?
[x] License: Does the repository contain a plain-text LICENSE or COPYING file with the contents of an OSI approved software license?
[x] Contribution and authorship: Has the submitting author (@kulbachcedric) made major contributions to the software? Does the full list of paper authors seem appropriate and complete?
[x] Substantial scholarly effort: Does this submission meet the scope eligibility described in the JOSS guidelines
[x] 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.
[x] Reproducibility: If the paper contains original results, results are entirely reproducible by reviewers. If the paper contains no original results, please check this item.
[x] 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?
[x] 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.
[x] 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

[x] Summary: Has a clear description of the high-level functionality and purpose of the software for a diverse, non-specialist audience been provided?
[x] 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?
[x] 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?

cheginit commented 1 month ago

@musabgultekin, and @atanikan, a friendly reminder for this review.

musabgultekin commented 1 month ago

Hi @kulbachcedric,

On the first quick start example, I'm getting

(venv) musab@musab v1 % python3 main.py 
Traceback (most recent call last):
  File "/Users/musab/projs/test/deep-river-review/v1/venv/lib/python3.12/site-packages/deep_river/base.py", line 22, in <module>
    from torchviz import make_dot
  File "/Users/musab/projs/test/deep-river-review/v1/venv/lib/python3.12/site-packages/torchviz/__init__.py", line 1, in <module>
    from .dot import make_dot, make_dot_from_trace
  File "/Users/musab/projs/test/deep-river-review/v1/venv/lib/python3.12/site-packages/torchviz/dot.py", line 2, in <module>
    from distutils.version import LooseVersion
ModuleNotFoundError: No module named 'distutils'

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/Users/musab/projs/test/deep-river-review/v1/main.py", line 2, in <module>
    from deep_river import classification
  File "/Users/musab/projs/test/deep-river-review/v1/venv/lib/python3.12/site-packages/deep_river/__init__.py", line 1, in <module>
    from . import anomaly, classification, regression, utils
  File "/Users/musab/projs/test/deep-river-review/v1/venv/lib/python3.12/site-packages/deep_river/anomaly/__init__.py", line 1, in <module>
    from .ae import Autoencoder
  File "/Users/musab/projs/test/deep-river-review/v1/venv/lib/python3.12/site-packages/deep_river/anomaly/ae.py", line 9, in <module>
    from deep_river.base import DeepEstimator
  File "/Users/musab/projs/test/deep-river-review/v1/venv/lib/python3.12/site-packages/deep_river/base.py", line 24, in <module>
    raise ValueError(
ValueError: You have to install graphviz to use the draw method

I tried "brew install graphviz", but still same error. I'm using MacOS 15.0 with python 3.12

musabgultekin commented 1 month ago

@kulbachcedric

Okay I find that python 3.12 and 3.13 is not supported. Could you clarify that in the installation or add support for 3.12 at least (by removing torchviz dependency?)?

musabgultekin commented 1 month ago

@kulbachcedric

Regarding the repo:

It would have been better if you could publish a new release with the latest commit. So we don't need to install with git. As the current "pip install deep-river" doesn't include all commits.
In the repo README, could you clearly state the library is designed to solve and who the target audience is? As we would like this to be clearly stated for people to understand if this repo is properly targeted for them.
As there are multiple ways to contribute an open-source project, it would be critical to have a way for people to see how to contribute to this project. You can check this guideline : https://docs.github.com/en/communities/setting-up-your-project-for-healthy-contributions/setting-guidelines-for-repository-contributors . So basically we need to add CONTRIBUTING file with instructions on it

musabgultekin commented 1 month ago

@kulbachcedric

Regarding the paper:

It lacks a section dedicated to comparing DeepRiver with other existing tools or libraries that address deep learning in streaming or online learning contexts. So we need to update the paper to include related work. Such as scikit-multiflow, Apache SAMOA etc
Also I see that citations are sometimes inconsistently formatted. could you format the citations consistently? See: https://pandoc.org/MANUAL.html#extension-citations

cheginit commented 2 weeks ago

@kulbachcedric please update us on how the review is going.

cheginit commented 2 weeks ago

@atanikan, a friendly reminder for the review.

kulbachcedric commented 5 days ago

Hi @all,

sorry for the late response, I was looking into the wrong thread.... However, SAMOA was not related to deep-river when it was created and focusses more on the integration of Python into the MOA Framework. The Package Sci-kit multiflow merged in 2021 with the package creme and was rebranded into river. In this case Sci-kit multiflow is not related any more and does not cover the deep learning part.

Regarding the consistancy, I will update the citations within the paper branch of the deep-river repository. Is that ok for you?

Thanks again for reviewing and kind regards Cedric

atanikan commented 4 days ago

Review checklist for @atanikan

Conflict of interest

[x] 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

[x] I confirm that I read and will adhere to the JOSS code of conduct.

General checks

[x] Repository: Is the source code for this software available at the https://github.com/online-ml/deep-river?
[x] License: Does the repository contain a plain-text LICENSE or COPYING file with the contents of an OSI approved software license?
[x] Contribution and authorship: Has the submitting author (@kulbachcedric) made major contributions to the software? Does the full list of paper authors seem appropriate and complete?
[x] Substantial scholarly effort: Does this submission meet the scope eligibility described in the JOSS guidelines
[x] 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.
[x] Reproducibility: If the paper contains original results, results are entirely reproducible by reviewers. If the paper contains no original results, please check this item.
[x] 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

[x] 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?

atanikan commented 4 days ago

Hi @kulbachcedric

I have opened an issue in your repos issues tracker #95. Please let me know if you need clarification.

musabgultekin commented 4 days ago

@kulbachcedric Could you mind adding a separate section for the related work that you think of appropriate related work. Also I'm waiting update on the other comments I made above. Thank you!

kulbachcedric commented 15 hours ago

Hi @kulbachcedric

I have opened an issue in your repos issues tracker #95. Please let me know if you need clarification.

Hi @atanikan, I'll work on the mentioned points within the branch 95-updates-to-installation. In the upcoming week there will be a PR :-)

@kulbachcedric Could you mind adding a separate section for the related work that you think of appropriate related work. Also I'm waiting update on the other comments I made above. Thank you!

Hi @musabgultekin, good point, I'll also work on that in the upcoming week within the paper branch. Based on your points already mentioned I made a few smaller changes within this branch. Is it in the way you thought of?

Thanks both of you for your feedback!

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