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PH Evaluator

GitHub Workflow Status

A Poker Hand Evaluator based on a Perfect Hash Algorithm

Overview

Efficiently evaluating a poker hand has been an interesting and challenging problem. Given two different poker hands, how to determine which one is stronger? Or more generally, given one poker hand, can we assign a score to it indicating its strength?

Cactus Kev once gave an answer for a five-card poker hand evaluation. With smart encoding, it ranks each hand to 7462 distinct values.

Still, Kev's solution is specific for a five-card hand. To evaluate a seven-card poker hand (which is more popular because of Texas Hold'em) using Kev's algorithm, one brute force solution is to iterate all 7 choose 5 combination, running his five-card evaluation algorithm 21 times to find the best answer, which is apparently too time-inefficient. Omaha poker would be even more complicated, as it requires picking exactly two cards from four player's cards, and exactly three cards from five community cards. Using brute force, it would take 60 iterations (5 choose 3 multiplied by 4 choose 2) of Kev's 5-card evaluation algorithm.

PH Evaluator is designed for evaluating poker hands with more than 5 cards. Instead of traversing all the combinations, it uses a perfect hash algorithm to get the hand strength from a pre-computed hash table, which only costs very few CPU cycles and considerably small memory (~100kb for the 7 card evaluation). With slight modification, the same algorithm can be also applied to evaluating Omaha poker hands.

Algorithm

This documentation has the description of the underlying algorithm.

C/C++ Implementation

The cpp subdirectory has the C/C++ implementation of the algorithm, offering evaluation from 5-card hands to 7-card hands, as well as Omaha poker hands, including PLO4, PLO5, and PLO6.

Time performance

One of the latest benchmark report generated by Google Benchmark:

$ ./benchmark_phevaluator
2023-09-02T11:51:57+10:00
Running ./benchmark_phevaluator
Run on (12 X 2600 MHz CPU s)
CPU Caches:
  L1 Data 32 KiB
  L1 Instruction 32 KiB
  L2 Unified 256 KiB (x6)
  L3 Unified 12288 KiB
Load Average: 2.17, 2.68, 2.67
-------------------------------------------------------------------
Benchmark                         Time             CPU   Iterations
-------------------------------------------------------------------
EvaluateAllFiveCards       33412347 ns     33377333 ns           21
EvaluateAllSixCards       286893486 ns    286658500 ns            2
EvaluateAllSevenCards    2229689783 ns   2224943000 ns            1
EvaluateRandomFiveCards        1376 ns         1375 ns       501339
EvaluateRandomSixCards         1550 ns         1549 ns       432192
EvaluateRandomSevenCards       1778 ns         1777 ns       379830
EvaluateRandomPlo4Cards        3054 ns         3014 ns       227197
EvaluateRandomPlo5Cards        3300 ns         3202 ns       221414
EvaluateRandomPlo6Cards        3441 ns         3313 ns       210607
Number of Hands Time Used Hands per Second
All 5-card Hands 2598960 33412347 ns 77 M/s
All 6-card Hands 20358520 286893486 ns 71 M/s
All 7-card Hands 133784560 2229689783 ns 60 M/s
Random 5-card Hands 100 1376 ns 72 M/s
Random 6-card Hands 100 1550 ns 64 M/s
Random 7-card Hands 100 1778 ns 56 M/s
Random PLO4 Hands 100 3054 ns 32 M/s
Random PLO5 Hands 100 3300 ns 30 M/s
Random PLO6 Hands 100 3441 ns 29 M/s
  • The performance on random samples are slightly worse due to the overhead of accessing the pre-generated random samples in the memory.

Memory performance

The memory usage is measured by pmap.

Library Memory Used
pheval5 60k
pheval6 84k
pheval7 144k
pheval 648k
phevalplo4 30516k
phevalplo5 112296k
phevalplo6 353484k

Python Implementation

GitHub Workflow Status PyPI version PyPI downloads Apache_2.0

The python subdirectory has the latest Python implementation.

Currently it supports 5-card, 6-card and 7-card poker hands evaluation, as well as Omaha poker hands evaluation.

You can install the library using pip:

pip3 install phevaluator

You can find more examples from here.

Thanks to the community for contributing to the Python implementations. Especially azriel1rf, ohwi, and bensi94.

Other Implementations

PHE is a Javascript port, developed by Thorsten Lorenz.

41Poker is another Javascript port, developed by 41semicolon.

poker is a Dart port, developed by Kohei.

ghais/poker contains a Haskell implementation of the evaluator.

gophe is a Go port, developed by mattlangl.

poker-handle has a TypeScript port, developed by pocketberserker.

PokerHandEvaluator.cs is a C# port, developed by travisstaloch.

poker_engine is a Rust port, developed by Alexander Leones.

Poker-Calculator contains a CUDA implementation of this evaluator.

Awesome Use Cases

A simple Hold'em pre-flop equity estimator

A reddit user coded a Hold'em pre-flop equity estimator in C++ using the PHEvaluator library.

https://www.reddit.com/r/poker/comments/okk5qn/i_ran_1m_runouts_of_random_play_to_get_a_sense_of/

The source code can be found in sim.cc.

pre-flop equity estimator

A Python example for Monte Carlo simulation

An article about Monte Carlo simulation of Texas Hold'em.

Estimating the outcome of a Texas hold’em game using Monte Carlo simulation

It's source code is in https://github.com/petrosDemetrakopoulos/TexasHoldemMonteCarloSimulation

Contributing to this repository

All contributions are welcome. A contribution can be as small as reporting a bug by creating an issue.

If you plan to create a Pull Request, please find more details in CONTRIBUTING.md.