playerClass.py

from selenium.webdriver.common.by import By
from selenium.webdriver.common.keys import Keys
import dice_calculations as dc


# Class used to define each player and their message ids
class Player:
    def __init__(self, name, id):
        self.name = name
        self.id = id
        self.read_msg = []
        self.rolls = []
        self.cdf = []
        self.inv_cdf = []
        self.past_n_probabilities = []  # Store probabilities of last n rolls

    def check_roll(self, driver):
        try:
            rolls = driver.find_elements(By.XPATH, f'//div[@data-playerid="{self.id}"]')
        except:
            # If there are no rolls, just return with nothing
            self.read_msg = []
            return 0

        if len(self.read_msg) == 0:  # If it's the first time the program is called, don't read old messages
            for roll in rolls:
                self.read_msg.append(str(roll.get_attribute("data-messageid")))

        for roll in rolls:  # Go through all the messages
            m_id = str(roll.get_attribute("data-messageid"))  # message ID
            roll_message = str(roll.get_attribute("innerText"))  # Roll result

            # Check if this message has been read before
            if m_id in self.read_msg:
                continue
            # Save the message as read
            self.read_msg.append(m_id)

            # In case there are no rolls in the message
            if roll_message.split("rolling ")[-1].split("\n")[0].find("d") == -1:
                return 0

            # Go through the actual values of the dice
            print("calculating...")
            out = dc.ret_rolls(roll_message)  # Retrieve the statistical values
            if out != -1:
                roll_inp, result, mean, pmf, cdf, inv_cdf = out
                print(f'Player {self.name} rolls\nMean = {float(mean)}\npmf = {float(pmf)}\n cdf = {float(cdf)}\n inv_cdf = {float(inv_cdf)}')

                self.cdf.append(cdf)
                self.inv_cdf.append(inv_cdf)

                self.rolls.append(roll_inp)
                self.rolls.append(result)
                # Update the past_n_probabilities list with the new probability
                if len(self.past_n_probabilities) >= 10:
                    self.past_n_probabilities.pop(0)  # Remove the oldest probability if list size exceeds 10
                self.past_n_probabilities.append(float(pmf))

                return roll_inp, result, self.name
            else:  # If the message contains too many dice, the cdf and pdf will be skipped
                print(f'Not possible')
                return 0

    # Retrieve data from the object
    def curr_stats(self):  # Returns (rolls, average roll, best roll, best roll index)
        if len(self.inv_cdf) == 0:
            return ['no rolls', -1, -1, -1]
        avg_broll = sum(self.inv_cdf) / len(self.inv_cdf)
        #avg_wroll = sum(self.cdf) / len(self.cdf)
        #avg = (avg_broll+(1-avg_wroll))/2

        worst_roll = min(self.cdf)
        best_roll = min(self.inv_cdf)
        w_index = self.cdf.index(worst_roll)
        b_index = self.inv_cdf.index(best_roll)

        return self.rolls, avg_broll, [worst_roll, w_index], [best_roll, b_index]


# Function to find and write in the chat bar
def print20(driver, message):
    text_area = driver.find_element(By.XPATH, '// *[ @ id = "textchat-input"] / textarea')
    text_area.send_keys(message)
    text_area.send_keys(Keys.ENTER)


# Retrieve dice from the already gone through dice rolls
def ret_dice(message):
    import re
    d = []
    for roll in (re.findall(r'\d+d\d+', message)):
        roll = roll.split('d')
        for i in range(int(roll[0])):
            d.append(roll[1])
    return d, int(message.split('+')[-1])