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MontePy Submission #205
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Editor in Chief checksHi @MicahGale ! Thank you for submitting your package for pyOpenSci review. Please check our Python packaging guide for more information on the elements
Editor commentsMontePy is in very good shape, congratulations to all the maintainers for your hard work! Some comments about the checklist above.
Minor comments not needed to start the review:
Final note: I enjoyed this quote from your documentation 🪄
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@cmarmo thank you for the feedback! I have opened this PR: idaholab/MontePy#440 to address this feedback.
These directions are old and from when this was an internal tool. I just removed them and instead pointed to using
Added the command.
Corrected this and actually added a boilerplate code of conduct.
Good point. I updated the index to list the API documentation last.
This warning was written when MontePy used to discard user formatting and comments, which is no longer the case. After more consideration (mostly from others) I think this behavior should be changed, and an issue has been opened: idaholab/MontePy#442.
I forget sometimes about how silly the concept of universes are in these models is sometimes especially when working with them. |
Thank you @MicahGale for your prompt response to my comments. |
Ok this PR has been merged. |
Thank you @MicahGale ! 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. |
Yes let's merge them if that makes sense. I just did things in a bit of a different order. |
Hello @MicahGale , I'm glad to announce that @kellyrowland has accepted to be editor for the MontePy review. I'm letting her introduce herself here and I wish to all of you a happy review process! 🚀 : |
Hi - This is my first engagement with pyOpenSci, so thanks in advance for your patience. 😅 I've been an editor for JOSS for a few years, and that's how we've arrived here. @MicahGale before I get started on finding reviewers, I see there are a set of JOSS-related boxes to tick off - can you take a look at those and check them off/open PRs/etc. and let me know about the status of those items? Thanks for tagging some possible reviewers over in openjournals/joss-reviews#6977 - I'll ping folks in this issue and make a post with the editor template once we've got two reviewers on board. -Kelly |
Thank you for being willing to do this new role for this package. :) Ok I updated the JOSS section accordingly. The one concern I had was about getting a DOI for archiving the software. Under the JOSS guidelines it seems like that's a final step?
Are you alright with following the JOSS order for this? |
Good point, thanks. I think archiving the release and getting a DOI is a logical last step since it's often the case that changes are made to the software during the review process. |
@cmarmo it looks like the remaining "Core GitHub repository Files" item is set - could you please take a look and check that off at your earliest convenience? I think I should be set to ping potential reviewers at that point. |
Done! Thank you Kelly! |
hi @paulromano @munkm 👋 would you be interested in and available to review this pyOpenSci submission? the reviewer template that you would use can be seen at https://www.pyopensci.org/software-peer-review/appendices/templates.html#peer-review-template . if you're not available for the review, could you suggest other potential reviewers for the package? |
I would love to! But I won't be able to review until after September 15th. Will that be an issue? If it is, I'll suggest an alternate. |
@MicahGale does the above timeline work for you? |
Yes, @kellyrowland, @munkm that timeline works me. |
hello @jpmorgan98 @gwenchee 👋 would you be interested in and available to review this pyOpenSci submission? the reviewer template that you would use can be seen at https://www.pyopensci.org/software-peer-review/appendices/templates.html#peer-review-template . |
@kellyrowland I am willing! However, I will not be available until Sept. 31st. Let me know if that's an issue |
@jpmorgan98, I am fine with that. I understand end of the federal fiscal year crunch time. |
thanks all! I think we can assign the reviewers and then I'll check back in... @cmarmo is that something you could do, edit the anchor post to add the reviewers? I don't think I'm able to as a drop-in editor here. |
@MicahGale @munkm @jpmorgan98 @cmarmo just FYI I will be out of office starting September 30 and will return on October 21. |
@munkm, @jpmorgan98 I just wanted to check in with you both and see if you might have some time for this review now that we are in a new fiscal year. |
@MicahGale I had this penciled in for Monday of next week. If you'd like I can move some stuff around and start tomorrow evening, sorry about the delays and thanks for your understanding! |
No that's great. I just wanted to check in. |
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: 0.4.1
EiC: @cmarmo
Editor: @kellyrowland
Reviewer 1: @munkm
Reviewer 2: @jpmorgan98
Archive: TBD
JOSS DOI: TBD
Version accepted: TBD
Date accepted (month/day/year): TBD
Code of Conduct & Commitment to Maintain Package
Description
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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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.
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