RSTT Submission

[Ematrion]

Submitting Author: David Bucher (@Ematrion)
All current maintainers: (@Ematrion)
Package RSTT
One-Line Description of Package: Competition simulation tool to evaluate ranking
Repository Link: https://github.com/Ematrion/rstt
Version submitted: v0.6.7-alpha
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

• I agree to abide by pyOpenSci's Code of Conduct during the review process and in future interactions in spaces supported by pyOpenSci 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:

Package enable sport/games simulation providing different tournament format, state of the art rating system and probabilistic model. It is build around the interaction of a ranking, used to seed competition, and the resulting games, used to update the ranking. It allows users to compared trained ranking with the simulation model, and answer question such has 'Does the ranking have a unique stationary distribution'.

It aims at enabling simulation based research in the context of competition.

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):

I believe it fits the "Scope for packages that support analytics, statistics and modeling":
It helps producing well defined, yet complex synthetic dataset with a precise and short syntax, 20 lines of code or less for millions of games. It is possible to reproduce others research (check tutorial_3) in the field.

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

     - data scientist testing rating system for large video game title or sport leagues.
     - game developer who wants to make simple test.
     - teaching tool to illustrate ranking behaviour in an intuitive context.
     - mathematician studying Markov process and stationery distribution.
     - tournament organiser with care for matching and seeding methods
  

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

I know there is a paper on a tool call MMBench: https://dl.acm.org/doi/10.1145/3539597.3573023 . I could not access it. It seems limited to its own component while RSTT allows user to define and integrate custom model. It does not seems to address the interplay between ranking and game generation project. Does not seems to tune the initial ranking state.

• 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: RSTT #255

  @eliotwrobson

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:

https://doi.org/10.5281/zenodo.16926606

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. ↩