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Description

Xtreys(eXtended treys) is a lightweight add-on to the library Treys. Xtreys uses integers created from Treys to rank hole cards, calculate equity, etc.

Installation

First, open your terminal and run:

pip install git+https://github.com/bingchiliingsacker-dot/Xtreys.git

or:

pip install xtreys

Note: If you run into any issues installing or using Xtreys, feel free to open a ticket on the Issues tab!

Usages

One of Xtreys' goals is to evaluate hole cards only. Cards are ranked from 1 to 91 with 'A-A' or pocket Ace's being the strongest and a '2-7' being the weakest hand

The function for this is preflop_eval.

Here is a quick test to see if Xtreys is working:

from treys import Deck
from xtreys import preflop_eval

d = Deck()
cards = d.draw(2)

rank = preflop_eval(cards)
print(f"Pre-flop hand rank:\t{rank}") #Output: Pre-flop hand rank:    1-91

Another usage of Xtreys is calculating the approximate and accurate equity of cards. approximate_equity gives an approximate equity from 0.1(lowest) to 0.9(highest).

Heres a quick test:

from xtreys import approximate_equity

d = Deck()

cards = d.draw(2)
flop_board = d.draw(3)
turn_card = d.draw(1)
river_card = d.draw(1)

turn_board = flop_board + turn_card
river_board = flop_board + river_card

flop_equity = approximate_equity(cards, flop_board)

print('---Flop---')
print(f'Approximate equity:\t{flop_equity}')
print('')

turn_equity = approximate_equity(cards, turn_board)

print('---Turn---')
print(f'Approximate equity:\t{turn_equity}')
print('')

river_equity = approximate_equity(cards, river_board)

print('---River---')
print(f'Approximate equity:\t{river_equity}')

'''
Output:
---Flop---
Approximate equity:     0.2

---Turn---
Approximate equity:     0.3

---River---
Approximate equity:     0.2
'''

Accurate equity outputs a much more pinpoint equity than approximate equity, it needs a cards variable of type list[int], a board variable of type list[int], and how many Monte-Carlo simulations you want to make(default=50).

Heres a quick test for accurate_equity:

from xtreys import accurate_equity
d = Deck()

cards = d.draw(2)
flop_board = d.draw(3)
turn_card = d.draw(1)
river_card = d.draw(1)

turn_board = flop_board + turn_card
river_board = flop_board + river_card

flop_equity = accurate_equity(cards, flop_board, 100)

print('---Flop---')
print(f'Accurate equity:\t{flop_equity:.2f}')
print('')

turn_equity = accurate_equity(cards, turn_board, 150)

print('---Turn---')
print(f'Accurate equity:\t{turn_equity:.2f}')
print('')

river_equity = accurate_equity(cards, river_board)

print('---River---')
print(f'Accurate equity:\t{river_equity:.2f}')

'''
Output:

---Flop---
Accurate equity:        0.54

---Turn---
Accurate equity:        0.39

---River---
Accurate equity:        0.30
'''

relative_equity outputs almost the same equity as accurate_equity, the only difference between the two is that relative_equity calculates the equity of the players hand based on behavior unlike accurate_equity which is accurate mathematically.

Here is a quick test for relative_equity:

from treys import Deck

for _ in range(5):
	deck = Deck()
	
	cards = deck.draw(2)
	board = deck.draw(3)
	
	opp_cards = [
	    deck.draw(2),
	    deck.draw(2),
	    deck.draw(2)
	]
	
	choice = ['bet', 'fold', 'check', 'call', 'raise', 'all_in']
	
	decision = choices(choice, k=3)
	
	equity = relative_equity(
	    cards=cards,
	    board=board,
	    opp_cards=opp_cards,
	    decision=decision,
	    average_aggression=uniform(0.0, 10.0)
	    )
	
	print('---Relative Equity Test---')
	print(f'cards:\t{cards}')
	print(f'Opponent cards:\t{opp_cards}')
	print(f'Board:\t{board}')
	print(f'Equity:\t{equity}')
	print('')

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