MontePy Submission

[MicahGale]

Submitting Author: @MicahGale
All current maintainers: @MicahGale, @tjlaboss
Package Name: MontePy
One-Line Description of Package: MontePy is a python library for reading, editing, and writing MCNP input files.
Repository Link: https://github.com/idaholab/MontePy
Version submitted: 0.2.10
EiC: @cmarmo
Editor: @kellyrowland
Reviewer 1: @munkm
Reviewer 2: @jpmorgan98
Archive:
JOSS DOI: https://joss.theoj.org/papers/10.21105/joss.07951
Version accepted: 0.5.5
Date accepted (month/day/year): 03/19/2025

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Description

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MontePy is a Python library for reading, editing, and writing MCNP input files. MCNP is the Monte Carlo N-Particle radiation transport code that supports 37 particle types, and is widely used in Nuclear Engineering, and Medical Physics. MontePy provides an object-oriented interface for MCNP input files. This allows for easy automation of many different tasks for working with MCNP input files. MontePy does not support MCNP output files

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  • Data retrieval
  • Data extraction
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    • Scientists and engineers who use MCNP and know python are the primary audience. This will be mostly nuclear engineers, and medical physicists. Use cases are:

    • Automating tedious updates of simulation models (e.g., renumbering all materials to merge two models)

    • Automating generating many permutations of the model for optimization, sensitivity analysis, etc.

    • Extracting information from an existing model in a more legible way.

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

    • There is also MCNPy, which reports to provide similar features. I have been unable to verify this as I have been unable to install it. MontePy is different by being written purely in python, and not java, and having a publicly accessible github, that anyone can open an issue for.

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[cmarmo]

Editor in Chief checks

Hi @MicahGale ! Thank you for submitting your package for pyOpenSci review.
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If some of these are missing, we will ask you to work on them before the review process begins.

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Editor comments

MontePy is in very good shape, congratulations to all the maintainers for your hard work!

Some comments about the checklist above.

• In the documentation about the installation of a specific version : I strongly recommend to remove any manual process creating symbolic links and installing requirements in a folder. Virtual environments should always be preferred and you can install specific versions/tags/branches or commit in them with

pip install git+https://github.com/idaholab/MontePy.git@<your-version/tag/branch/commit>

• The README.md redirects to the documentation for details about the installation: may I suggest to explicitely add the command pip install? This will clarify that the package is available from pypi but not from any conda channel.
• The code of conduct is linked in contributing.md (btw thanks for expliciting the contact e-mail) but the file is missing and the link gives a "404 not found".

Minor comments not needed to start the review:

• the documentation generally moves from more readable contents to more technical and detailed contents: I would have put the API at the end of the documentation.
• wearing my data processing engineer hat, I would be grateful to have a safe default option backupping original files when overwriting ... I was checking basic usage documentation and the behaviour of your writing function really scared me.... 😅

Final note: I enjoyed this quote from your documentation 🪄

Creating a new universe is very straight forward. You just need to initialize it with a new number

[MicahGale]

@cmarmo thank you for the feedback!

I have opened this PR: idaholab/MontePy#440 to address this feedback.

In the documentation about the installation of a specific version : I strongly recommend to remove any manual process creating symbolic links and installing requirements in a folder. Virtual environments should always be preferred and you can install specific versions/tags/branches or commit in them with

These directions are old and from when this was an internal tool. I just removed them and instead pointed to using pip install montepy==<version>. Most versions are on PyPI, and those that aren't, can't be because they don't have an OSS license yet. So if someone really wants that old of a version I think they will figure it out on their own how to manage.

The README.md redirects to the documentation for details about the installation: may I suggest to explicitely add the command pip install? This will clarify that the package is available from pypi but not from any conda channel.

Added the command.

The code of conduct is linked in contributing.md (btw thanks for expliciting the contact e-mail) but the file is missing and the link gives a "404 not found".

Corrected this and actually added a boilerplate code of conduct.

the documentation generally moves from more readable contents to more technical and detailed contents: I would have put the API at the end of the documentation.

Good point. I updated the index to list the API documentation last.

wearing my data processing engineer hat, I would be grateful to have a safe default option backupping original files when overwriting ... I was checking basic usage documentation and the behaviour of your writing function really scared me.... 😅

This warning was written when MontePy used to discard user formatting and comments, which is no longer the case. write_to_file has no default option that would override the original file. I think now the only real risk with overwriting the original file is having a script that is buggy and accidentally changing the model. I changed the warning to discourage this sort of workflow for making script development easier.

After more consideration (mostly from others) I think this behavior should be changed, and an issue has been opened: idaholab/MontePy#442.

Final note: I enjoyed this quote from your documentation 🪄

Creating a new universe is very straight forward. You just need to initialize it with a new number

I forget sometimes about how silly the concept of universes are in these models is sometimes especially when working with them.

[cmarmo]

Thank you @MicahGale for your prompt response to my comments.
Let me know when your PR is merged so I can start looking for an editor.

[MicahGale]

Ok this PR has been merged.

[cmarmo]

Thank you @MicahGale !
Your package looks ready for review to me.

I noticed that you submitted to JOSS independently (see openjournals/joss-reviews#6977): may I suggest to merge the two submissions, as pyOpenSci has a partnership with JOSS.
This will also lower the pression on our two communities, as both pyOpenSci and JOSS are based on volounteer engagement.
If you are ok with that I can comment on the related JOSS issue and we can follow up here.