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https://github.com/jstrieb/poker-chipper

Optimally allocate poker chips using constrained, nonlinear optimization
https://github.com/jstrieb/poker-chipper

constraint-programming constraint-satisfaction-problem optimization poker scip svelte web-application web-assembly

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Optimally allocate poker chips using constrained, nonlinear optimization

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README 

        






Poker Chipper






Optimally

select poker chip denominations for cash games using constrained, nonlinear

optimization.



# About



Imagine hosting a small poker game. You know how many friends will attend, how

many chips you have, and the buy in. How do you pick chip denominations?



Without Poker Chipper, picking chip denominations is manual and error-prone.

You first try to pick values that divide each other nicely and are easy to

remember. (Alternatively, struggle to recall the values from the last time you

played.) You next try to find a way to make the chosen values sum to the buy

in. Then, you backtrack whenever there aren't enough chips for everyone, or

when there are too many chips left over. Finally, you settle for a suboptimal

chip allocation so that you can actually start playing.



With Poker Chipper, on the other hand, picking chip denominations is fast and

easy. Input the number of players, buy in, blinds, and number of chips. After

waiting a moment for the mathematically optimal results, you can save them for

next time, or share them with others. If you want to modify the results, adjust

the "advanced options," and the chip denominations will be recomputed

accordingly.



# How Poker Chipper Works



Poker Chipper uses mixed-integer nonlinear programming (MINLP), which is a form

of constrained, nonconvex optimization, to optimally pick poker chip

denominations. 



Optimization is performed using a "solver" – in this case,

[SCIP](https://www.scipopt.org/). Some inputs to Poker Chipper are translated

into solver constraints, which affect what denominations are admissible. Other

inputs influence the solver's objective function, which affects how candidate

denominations are evaluated, ranked, and chosen. In the user interface, inputs

affecting constraints, and inputs affecting the objective function are

described as influencing the "requirements" and "score," respectively, of

candidate solutions.



Poker Chipper is a fully static web application. In other words, all of the

processing involved in performing optimization occurs client-side – entirely in

the user's browser. The SCIP solver is designed to run natively, so Poker

Chipper bundles it for the browser by compiling SCIP to WebAssembly (WASM) with

[Emscripten](https://emscripten.org/).



## How to Read the Code



### Code Table of Contents



The links below are listed in the order the code should be read to understand

the application from the highest to lowest level.



- [`src/App.svelte`](src/App.svelte) – main high-level application

- [`src/*.svelte`](src/) – UI components

- [`src/solve.js`](src/solve.js) – convert user inputs to MINLP model and solve

  using WASM SCIP

- [`src/solveWorker.js`](src/solveWorker.js) – web worker to run solver in

  non-blocking thread

- [`public/serviceWorker.js`](public/serviceWorker.js) – service worker for

  caching and offline functionality

- [`public/*`](public/) – PWA manifest, global stylesheet, favicons, etc.

- [`experiments/*`](experiments/) – exploration of initial concept in Python

  (with both Z3, and later, SCIP), and Dockerfile for compiling SCIP with

  Emscripten

- [`src/compiled/*`](src/compiled/) – SCIP compiled to WASM via Emscripten,

  plus associated support files



### Application Architecture



In the diagram below, labeled arrows represent asynchronous fetch requests and

message passing.



``` mermaid

flowchart LR

    A[Svelte Front End] -->|Solve Requests| B["Web Worker

    (non-blocking thread)"]

    B -->|Solutions| A

    A <-->|Static Assets| C[Service Worker]

    B <-->|Solver Static Assets| C

    C -->|Cache| C

    C <-->|Static Assets| D[Web Server]

```



# Project Status & Contributing



Poker Chipper is actively maintained. If there are no recent commits,

everything is running smoothly! As of the initial release, the code is stable,

and there are no major, outstanding features that remain to be added.



Bug reports and feature requests via GitHub Issues are encouraged. Pull

requests with more than 20 lines of code are unlikely to be merged quickly,

unless associated with prior discussion or accompanied by substantial,

explanatory English prose. In other words, pull requests containing code

without context may be merged after much delay, or may not be merged at all.



Since Poker Chipper is a fully static web application with no server-side

processing (outside of serving unchanging files), it is extremely scalable, and

has a very low maintenance burden. As such, even if something were to happen to

me, and I could not continue to work on the project, the [public

version](https://jstrieb.github.io/poker-chipper/) should continue to remain

functional and available online as long as my GitHub account is open and the

[jstrieb.github.io](https://jstrieb.github.io) domain is active.



## Support the Project



The best ways to support the project are to:



- Share the project on sites like Twitter, Reddit, and Hacker News

- Report any bugs, glitches, errors, or shortcomings that you find

- Star the repository and follow me on GitHub

- Host a version of the code translated into another language



If you insist on spending money to show your support, please do so in a way

that is widely beneficial. In particular, donations to the following

organizations help me, in addition to the general, Internet-using public:



- [Electronic Frontier Foundation](https://supporters.eff.org/donate/)

- [The Internet Archive](https://archive.org/donate/index.php)

- [Signal Foundation](https://signal.org/donate/)

- [Mozilla](https://donate.mozilla.org/en-US/)



# Acknowledgments & Greetz



Poker Chipper would not have been possible without help and feedback from:



- [Logan Snow](https://github.com/lsnow99)

- [Amy Liu](https://www.linkedin.com/in/amyjl)

- [Chris Cherian](https://twitter.com/chrischerian)

- [Ani Chowdhury](https://www.linkedin.com/in/ani-chowdhury)

- Will Hooper