GALAssify submission

[Malclay]

Submitting Author: Manuel Alcázar-Laynez (@Manalclay)
All current maintainers: (@Manalclay, @andonij)
Package Name: GALAssify
One-Line Description of Package: A Python package for visually classifying astronomical objects
Repository Link: https://gitlab.com/astrogal/GALAssify/
Version submitted: v1.0.1
EiC: Szymon Moliński (@SimonMolinsky )
Editor: Avik Basu (@ab93)
Reviewer 1: Akhil Krishna R (@akhilkrishnar0)
Reviewer 2: Erik Whiting (@erik-whiting)
Archive: https://zenodo.org/records/17433197
JOSS DOI: N/A
Version accepted: v2.0.0
Date accepted (month/day/year): 11/16/2025

---

Code of Conduct & Commitment to Maintain Package

• I agree to abide by pyOpenSci's Code of Conduct during the review process and in maintaining my package after should it be accepted.
• I have read and will commit to package maintenance after the review as per the pyOpenSci Policies Guidelines.

Description

• Include a brief paragraph describing what your package does:
  We present GALAssify, a customisable graphical tool that allows the user to visually inspect and characterise properties of astronomical objects in a simple way. GALAssify allows the user to save the results of the visual classification into a file using a list of previously defined tags based on the user's interests. A priori, it has been initially developed to tackle astrophysical problems but, due to its versatility, it could be easily adapted. For instance, this tool can be used to classify microscopy images from biological studies or be used in any other discipline.
  

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

Community Partnerships

If your package is associated with an
existing community please check below:

• Astropy:My package adheres to Astropy community standards
• Pangeo: My package adheres to the Pangeo standards listed in the pyOpenSci peer review guidebook

• For all submissions, explain how and why the package falls under the categories you indicated above. In your explanation, please address the following points (briefly, 1-2 sentences for each):
  GALAssify allows the user to visualise and validate a large dataset of astronomical images (or of any other field) using a Graphical User Interface (GUI) to accomplish it using only a keyboard, a mouse or both. User can view the image of the object and a linked FITS image at time, and visually classify it with a previously-defined tags, or even discard the object if required.

  • Who is the target audience and what are scientific applications of this package?
    This package is designed for astronomers who need to manually classify large numbers of astronomical objects given their respective images using customizable labels.

  • Are there other Python packages that accomplish the same thing? If so, how does yours differ?
    Currently, we don't know any customizable GUI-based tool specific for astronomical objects. The most similar tools can be ML generic dataset-creation GUI tools such as image-sorter2 or DataTurks, but their functionality is limited for our use case. For example, our tool can display both RGB and FITS images of the same object at time to perform a better classification. Also, our tool can be used without mouse interaction -- all its functionality can be accessed using keyboard shortcuts, which is a essential speed-up in the workflow when classifying large datasets.

  • 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:
    Presubmission Inquiry for GALAssify: A Python package for visually classifying astronomical objects #189

Technical checks

For details about the pyOpenSci packaging requirements, see our packaging guide. Confirm each of the following by checking the box. This package:

• does not violate the Terms of Service of any service it interacts with.
• uses an OSI approved license.
• contains a README with instructions for installing the development version.
• includes documentation with examples for all functions.
• contains a tutorial with examples of its essential functions and uses.
• has a test suite.
• has continuous integration setup, such as GitHub Actions CircleCI, and/or others.

Publication Options

• Do you wish to automatically submit to the Journal of Open Source Software? If so:

JOSS Checks

• The package has an obvious research application according to JOSS's definition in their submission requirements. Be aware that completing the pyOpenSci review process does not guarantee acceptance to JOSS. Be sure to read their submission requirements (linked above) if you are interested in submitting to JOSS.
• The package is not a "minor utility" as defined by JOSS's submission requirements: "Minor ‘utility’ packages, including ‘thin’ API clients, are not acceptable." pyOpenSci welcomes these packages under "Data Retrieval", but JOSS has slightly different criteria.
• The package contains a paper.md matching JOSS's requirements with a high-level description in the package root or in inst/.
• The package is deposited in a long-term repository with the DOI:

Note: JOSS accepts our review as theirs. You will NOT need to go through another full review. JOSS will only review your paper.md file. Be sure to link to this pyOpenSci issue when a JOSS issue is opened for your package. Also be sure to tell the JOSS editor that this is a pyOpenSci reviewed package once you reach this step.

Are you OK with Reviewers Submitting Issues and/or pull requests to your Repo Directly?

This option will allow reviewers to open smaller issues that can then be linked to PR's rather than submitting a more dense text based review. It will also allow you to demonstrate addressing the issue via PR links.

• Yes I am OK with reviewers submitting requested changes as issues to my repo. Reviewers will then link to the issues in their submitted review.

Confirm each of the following by checking the box.

• I have read the author guide.
• I expect to maintain this package for at least 2 years and can help find a replacement for the maintainer (team) if needed.

Please fill out our survey

• Last but not least please fill out our pre-review survey. This helps us track
  submission and improve our peer review process. We will also ask our reviewers
  and editors to fill this out.

P.S. Have feedback/comments about our review process? Leave a comment here

Editor and Review Templates

The editor template can be found here.

The review template can be found here.

Footnotes

1. Please fill out a pre-submission inquiry before submitting a data visualization package. ↩

[Manalclay]

Dear pyOpenSci team,

I posted this submission with my other personal (non-scientific) GitHub account (@Malclay). I hope this won't be a problem. If so, please let me repost this submission with my scientific account (@Manalclay).

Thank you!

[hamogu]

Hi! Thanks for your submission @Manalclay! While we are waiting for our Editor-in-Chief to get started with the first look, I already wanted to ask you a question: I noticed that the purpose of your package is listed as "classifying astronomical objects" (though of course other science areas also look at images), so I thought that it might make sense to tick the "astropy" box under "partnerships", but I notice that you didn't do that. So I'm just checking if that's on purpose?

Any pyopensci package will be fully listed on pyopensci - astropy and pang are in addition, not instead of that. So, if your package deal with astronomical data, there really is no downside to also make it "astropy partnership" in this submission.

[hamogu]

Sorry, I just went back to #189 and saw that we already discussed this in #189 (comment) a few months ago. I'm sorry I forgot - please disregard my comment.

[SimonMolinsky]

Hi @Malclay !

I'm currently Editor-in-Chief, so I will start the review process. I need (max) one day for the initial check of your package. Expect the feedback tomorrow!

[Manalclay]

Hello again!

Sorry, I just went back to #189 and saw that we already discussed this in #189 (comment) a few months ago. I'm sorry I forgot - please disregard my comment.

No problem at all :) Thanks for check the presubmission!

Hi @Malclay !

I'm currently Editor-in-Chief, so I will start the review process. I need (max) one day for the initial check of your package. Expect the feedback tomorrow!

Take your time! Thanks for the fast response

[SimonMolinsky]

Editor in Chief checks

Hi there @Malclay ! 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).
  • The package imports properly into a standard Python environment import package.
• Fit The package meets criteria for fit and overlap.
• Documentation The package has sufficient online documentation to allow us to evaluate package function and scope without installing the package. This includes:
  • User-facing documentation that overviews how to install and start using the package.
  • Short tutorials that help a user understand how to use the package and what it can do for them.
  • API documentation (documentation for your code's functions, classes, methods and attributes): this includes clearly written docstrings with variables defined using a standard docstring format.
• Core GitHub repository Files
  • README The package has a README.md file with clear explanation of what the package does, instructions on how to install it, and a link to development instructions.
  • Contributing File The package has a CONTRIBUTING.md file that details how to install and contribute to the package.
  • Code of Conduct The package has a CODE_OF_CONDUCT.md file.
  • License The package has an OSI approved license.
    NOTE: We prefer that you have development instructions in your documentation too.
• Issue Submission Documentation All of the information is filled out in the YAML header of the issue (located at the top of the issue template).
• Automated tests Package has a testing suite and is tested via a Continuous Integration service.
• Repository The repository link resolves correctly.
• Package overlap The package doesn't entirely overlap with the functionality of other packages that have already been submitted to pyOpenSci.
• Archive (JOSS only, may be post-review): The repository DOI resolves correctly.
• Version (JOSS only, may be post-review): Does the release version given match the GitHub release (v1.0.0)?

---

• 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. 🙌

---

---

Editor comments

Hi @Malclay !

I've performed initial checks of your package. It's rather uncanny to see the package using QT here, but I know that image classification tasks need to be done manually, and PyQT is one of the best options for GUI programs in Python. I think creating user-facing software is a very hard task, and I'm impressed by your work!

I've encountered a few problems, and here are these with links to the Gitlab issues:

1. Problems with the installation: https://gitlab.com/astrogal/GALAssify/-/issues/13
2. Why does documentation refer to installation directly from the repository when your package is published on PyPI?
3. I couldn't find API docs. Have you written API documentation? In this context, tool customization is your user-facing API. However, you must also provide internal documentation of the project methods and classes for contributors (see point 4).
4. Usually, the package we review should have maintenance workflows documented. This means you should assume that other contributors will eventually join your project. Thus, the package should have a Contributing File as well as some documentation describing low-level API for programmers (see point 3.) The CONTRIBUTING.md file is a bare minimum. I've created an issue here for this point: https://gitlab.com/astrogal/GALAssify/-/issues/14
5. The same as above for Code of Conduct.
6. Do you plan to submit your package to JOSS?

[Manalclay]

Hello @SimonMolinsky !

First of all, thank you very much for your words and for your revision, which we really appreciate.

My colleague @andonij and me are addressing the points you listed. Currently, we added the code of conduct and the CONTRIBUITNG.md file, which points to a new developer guide located inside the doc/ folder.

We are trying to replicate the reported installation issues. All the progress is being reported at the link of the issue you already opened. Also, we are working now on the lack of the API documentation, which is being written using docstrings, as suggested.

Answering to 6th point: A paper of the package was already submitted to JOSS (see the related issue). Unfortunately, it was rejected due it did not pass the substantial scholarly effort criterion. I would have like this package to be published to JOSS, but I understand that it does not match the requisites. The reviewer recommended me to submit it to pyOpenSci, That's why I'm here :) I hope this does not represent an inconvenience to be able to publish with you. In that case, please let us know!

I have already filled the Initial onboarding survey, but I see this box is not checked in your report. There exist any problem locating my filled survey? I can fill it again if needed.

[SimonMolinsky]

Hi @Manalclay

Thanks for your effort. Contribution files and API docs are critical issues right now. Thanks for checking the macOS installation issue; I will test it now and let you know how it went in your repository.

I'm sorry that your package didn't meet the scholarly effort criteria in JOSS. JOSS review and decisions are not a problem for us, but I needed to know about the potential submission because it leads to additional package and documentation checks in pyOpenSci.

Yes, I see that you have completed the onboarding survey. Thanks!