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Texas Hold'em Poker Probability Calculator in Python

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PokerPy

A python module writen in C++ for caculating Texas Hold'em poker odds in under a second. The union between python and C++ is done with pybind11

Installation

To install this module use the following command.

pip install git+https://github.com/glpcc/PokerPy

Use Cases

In the test folder are some use cases of possibilities with this module

Documentation

Card Class

class Card:
    def __init__(self, card:str) -> None: ...
    @property
    def value(self) -> str: ...
    @property
    def color(self) -> str: ...

The Card class is used to represent a poker card, for the creation of a class you must pass a string with the form KD In which the first letter/s represent the value of the card i.e from 2 to A.Then the second letter represents the color of the card it can be passed as D-H-C-S or using the unicode characters ♣,♦,♥,♠.

Internally Card are stored as a struct with two int values, not accesible from the python interface.

Warning

At the time no checks for valid values of color and value are done so it is left to the user responsability. With undefined behaviour if done incorrectly.

Hand Class

class Hand:
    def __init__(self, hand_type: str, Cards: list[Card]) -> None: ...
    @property
    def hand_type(self) -> str: ...
    @property
    def Cards(self) -> list[Card]: ...

This is a class to represent a poker Hand with a list of 5 cards representing the 5 chosen cards of the Hand and the Hand_type property, a string representing the type of the Hand. The value of the hand_type can be one of the following,in order of value.

Royal Flush
Straight Flush
Poker
Full House
Flush
Straight
Triples
Double Pairs
Pairs
High Card

It is not recommended to create Hand Classes manually unless you want to calculate a specific Hand Heuristic. It should be mainly used as the return type of the get_best_hand function.

Warning

At the time no checks for valid values of hand_type or the number of hands are done so it is left to the user responsability. With undefined behaviour if done incorrectly.

Utility Functions

get_best_hand

def get_best_hand(cards: list[Card]) -> Hand: ...

It gets a list of 7 cards and returns the best possible Hand as a hand_type.

Internally it sorts the cards and perform different checks for different types of hands on a single for loop for performance. It is internally used in the calculate_hand_frequencies.

Warning

At the time it isn't checked if the correct number of cards is supplied or if there is any repeated cards. Any thing outside 7 valid,non repeated cards is undefined behaviour.

calculate_hand_frequency

def calculate_hand_frequency(cards: list[list[Card]]) -> list[dict[str,int]]: ...

Function that gets a list of players cards, and returns a list with all the hands frequencies for each player, taking into account the other players hands. It also calculates the win and draw frequency of each player, this is shown as the keys "Win" and "Draw" in each players dictionaries.

It is done by iterating for all the possibe combinations of cards and calculating the best hand.

Warning

The number of cards per player supplied must be between 2 and 6.And all players should have the same cards. However different players can repeat cards, for example the fold should be shared upon all players. Anything outside these bounds is UNDEFINED BEHAVIOUR.

nice_print_frequencies

def nice_print_frequencies(frecs: list[dict[str,int]]) -> None: ...

Function that gets a the frequencies of the calculate_hand_frequency function and prints them in a nice table format.

calculate_hand_heuristic

def calculate_hand_heuristic(hand: Hand) -> int: ...

Function that gets a hand and uses bitshifting to calculate a hand value efficienly. It ensures that if a hand is better than another in texas hold'em, this function returns a larger int for the better hand.

This is used internally in the calculate_hand_frequency function to calculate the win,draw chance of every possible combination of cards.

Limitations

Supports up to 10 players, and might run slower than a second in old hardware.

Contributing

Any performance increase or bugfix will be gladly welcomed.

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  • C++ 79.3%
  • Python 20.7%