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Published 20 hours ago • verified publisher icon pyOpenSci

MILESpy

Open isaac-aa opened this issue 5 months ago • 4 comments

Submitting Author: (@isaac-aa) All current maintainers: (@isaac-aa) Package Name: MILESpy One-Line Description of Package: Python wrapper for the MILES stellar library and Single Stellar Population models Repository Link: https://github.com/miles-iac/milespy Version submitted: 1.0rc3 EiC: TBD Editor: TBD
Reviewer 1: TBD
Reviewer 2: TBD
Archive: TBD JOSS DOI: TBD Version accepted: TBD Date accepted (month/day/year): TBD

Code of Conduct & Commitment to Maintain Package

Description

  • Include a brief paragraph describing what your package does:

MILESpy is a python interface to the MILES single stellar population (SSP) models and stellar library. This package aims to provide users an easy interface to access SSP models, navigate the stellar library or synthesize a spectrum given a star formation history (SFH). It automatically downloads all the needed data and includes utilities to post-process the resulting spectra, including computing photometry, rebinning, convolution and velocity shifts. MILESpy is fully integrated and builds upon previously existing tools, namely astropy and specutils.

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):

    • [x] Data retrieval
    • [ ] Data extraction
    • [x] Data processing/munging
    • [ ] Data deposition
    • [ ] Data validation and testing
    • [ ] Data visualization[^1]
    • [ ] 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:

[^1]: Please fill out a pre-submission inquiry before submitting a data visualization package.

  • 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):

    • Who is the target audience and what are scientific applications of this package?

MILESpy has the potential to be used by a wide range of fields in Astronomy and Astrophysics, for example, studies of unresolved stellar populations in galaxies, spectra generation from cosmological simulations, SED fitting. Although this fields have already been using the MILES SSP models and stellar library, MILESpy aims to reduce development times and increase scientific production by providing a ready-to-use tool for analysis and coupling with third-party codes (e.g., ppxf, PST, FSPS).

  • Are there other Python packages that accomplish the same thing? If so, how does yours differ?

To the best of our knowledge, the Population Synthesis Toolkit (PST) Python library is the only package that has a similar aim as MILESpy. For example, it provides an interface to E-MILES SSP models (one of several models in MILESpy), which are also available in MILESpy, but does not provide an interface to any stellar library. Overall, PST focuses on building Composite Stellar Populations (CSP) from different sets of SSP models. Thus, it could potentially even use MILESpy as a back-end to add more SSP models not readily presently in PST.

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https://github.com/pyOpenSci/software-submission/issues/237

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  • [x] contains a tutorial with examples of its essential functions and uses.
  • [x] has a test suite.
  • [x] has continuous integration setup, such as GitHub Actions CircleCI, and/or others.

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isaac-aa avatar Jun 10 '25 11:06 isaac-aa

Thanks for your submission @\isaac-aa! Sorry for the delays, I'll do the initial EiC checks in the next day or so👍🏽

eliotwrobson avatar Jul 15 '25 18:07 eliotwrobson

Editor in Chief checks

Hi there! 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.

  • [x] 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).
    • [x] The package imports properly into a standard Python environment import package.
  • [x] Fit The package meets criteria for fit and overlap.
  • [x] Documentation The package has sufficient online documentation to allow us to evaluate package function and scope without installing the package. This includes:
    • [x] User-facing documentation that overviews how to install and start using the package.
    • [x] Short tutorials that help a user understand how to use the package and what it can do for them.
    • [x] 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.
    • [x] Contributing File The package has a CONTRIBUTING.md file that details how to install and contribute to the package.
    • [x] Code of Conduct The package has a CODE_OF_CONDUCT.md file.
    • [x] License The package has an OSI approved license. NOTE: We prefer that you have development instructions in your documentation too.
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  • [x] Automated tests Package has a testing suite and is tested via a Continuous Integration service.
  • [x] Repository The repository link resolves correctly.
  • [x] 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. :raised_hands: Thank you authors in advance for setting aside five to ten minutes to do this. It truly helps our organization. :raised_hands:

Editor comments

From the above, my comments are the following:

  • You'll need to be in compliance with the README requirements, which you can find here before we can get a full review going.
  • It seems like some of the requirements are pretty out of date? This package doesn't support numpy 2.0. I think this could benefit from an uplift, along with possibly using newer developer tools like uv and ruff (instead of flake8).
  • It doesn't look like the existing lint checks run as part of the normal CI? You should add workflows that include this.

Those issues are pretty minor in the scheme of things. Aside from that, I'll check in with others and get the ball rolling 👍🏽

eliotwrobson avatar Jul 24 '25 17:07 eliotwrobson

Hello, thanks for the comments. I have updated the README to add links to the documentation and I think that now it adheres to the requirements that you linked.

Regarding to the use of other developers tools (uv and ruff), I have started the migration, as I'm already using them in other projects. The linting will also be added to the CI once this is done.

The requirement for numpy < 2.0 has been decided to allow for older versions of python to run milespy, as some packages for python 3.8 do not support numpy >= 2.0. In any case, I could check if this is still the case and update the requirements if I can.

isaac-aa avatar Jul 28 '25 15:07 isaac-aa

We have updated the requirements (and dropped support for python<3.10) so that we are compatible with the latest versions of our most critical dependencies, namely numpy, astropy and specutils.

isaac-aa avatar Jul 29 '25 16:07 isaac-aa