petrosDemetrakopoulos

from dataclasses import dataclass
from typing import List
import datetime

@dataclass
class Order:
    date: datetime.datetime
    price: float = 0.0
 
@dataclass

petrosDemetrakopoulos

from dataclasses import dataclass

@dataclass
class User:
    email: str
    name: str = "First name"
    surname: str = "Last name"
    
    def fullName(self):
        return self.name + " " + self.surname

petrosDemetrakopoulos

from dataclasses import dataclass

@dataclass
class User:
    email: str
    name: str = "First name"
    surname: str = "Last name"
    

petrosDemetrakopoulos

from dataclasses import dataclass

@dataclass
class User:
    name: str
    surname: str
    email: str

user_instance = User('Petros', 'Demetrakopoulos', 'test@test.com')
print(user_instance)

petrosDemetrakopoulos

print(monte_carlo(['Ah','Ad'], ['Ac','2d','9s']))

petrosDemetrakopoulos

def monte_carlo(hand, table, players=2, samples=10000):
    dist = [0,0,0]

    for i in range(samples):
        outcome = simulate(hand, table, players)
        dist[outcome] += 1
    return list(map(lambda x: x/samples, dist))

petrosDemetrakopoulos

def simulate(hand, table, players):
    hands = []
    deck = random.sample(cards,len(cards)) #shuffle the deck
    hand = hand[:]
    table = table[:]

    full = table + hand
    deck = list(filter(lambda x: x not in full, deck))

    #deal cards to players

petrosDemetrakopoulos

from phevaluator import evaluate_cards
import random

suits = ['d','s','c','h']
ranks = ['A','2','3','4','5','6','7','8','9','T','J','Q','K']
cards = []
for r in ranks:
    for s in suits:
        cards.append(r+s)

petrosDemetrakopoulos

df['coin_toss'] = df['coin_toss'].map({'HEADS': True, 'TAILS': False})

petrosDemetrakopoulos

import pandas as pd
import random
age_column = [random.randrange(0,120) for x in range(1000)]
df = pd.DataFrame({'age':age_column})
print(df.info(memory_usage="deep"))