Skip to main content

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/XtreysPF.git

or:

pip install xtreyspf

Note: If you run into any issues installing or using XtreysPF, 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 pair

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, river_card = d.draw(1), 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, river_card = d.draw(1), d.draw(1)

turn_board = flop_board + turn_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}')
river_board = flop_board + river_card

'''
Output:

---Flop---
Accurate equity:        0.54

---Turn---
Accurate equity:        0.39

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

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

xtreys-0.2.0.tar.gz (3.8 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

xtreys-0.2.0-py3-none-any.whl (4.2 kB view details)

Uploaded Python 3

File details

Details for the file xtreys-0.2.0.tar.gz.

File metadata

  • Download URL: xtreys-0.2.0.tar.gz
  • Upload date:
  • Size: 3.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/7.0.0 CPython/3.13.13

File hashes

Hashes for xtreys-0.2.0.tar.gz
Algorithm Hash digest
SHA256 6d3ad00f465c52e73a09c83b1d533433eeb0447d8871ac731566baaa7c5898ac
MD5 3030a2382f0b49d9fd5adc729c1483b2
BLAKE2b-256 0ffdc5eae576d0c5c07035086d89e19e8a231eabbd1871a58bcc41a6ad2e7a65

See more details on using hashes here.

File details

Details for the file xtreys-0.2.0-py3-none-any.whl.

File metadata

  • Download URL: xtreys-0.2.0-py3-none-any.whl
  • Upload date:
  • Size: 4.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/7.0.0 CPython/3.13.13

File hashes

Hashes for xtreys-0.2.0-py3-none-any.whl
Algorithm Hash digest
SHA256 15bd6628db1f980bf545c700d3e6f0c33a9ba0e0184cea914f40bfaf7756b70d
MD5 b3148e4d14a8be428e35ba6f68646f36
BLAKE2b-256 d38ff5d577c28cc1aebf790b15ad1302c92d9701b2133bf5be1e6f98f44edf67

See more details on using hashes here.

Release history Release notifications | RSS feed

0.2.43

2 files

0.2.42

2 files

0.2.41

2 files

0.2.4

2 files

0.2.3

2 files

0.2.2

2 files

This release

0.2.0 This release

2 files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page