# WVLottopy: Matteo DiBiagio
from fractions import Fraction as frac
import pandas as pd
import requests
from collections import Counter

def get_data():
    df_old = pd.read_excel('./excel_lotto_records/lotto_america.xlsx')
    salvaged = df_old[['Date', 'Numbers', 'SB', 'All Star']]

    url = 'https://wvlottery.com/draw-games/lotto-america/?game-analyze=lotto-america&what-to-search=historysearch&date-range=-1'
    header = {
        "User-Agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/50.0.2661.75 Safari/537.36",
        "X-Requested-With": "XMLHttpRequest"
    }

    # Get web data
    r = requests.get(url, headers=header)
    dfs = pd.read_html(r.text)
    pd.set_option('display.max_rows', None)
    # Specifies no max rows, otherwise only shows 10 records
    df = dfs[0].append(salvaged, ignore_index=True)
    df2 = df[['Date', 'Numbers', 'SB', 'All Star']]
    date = list(df2['Date']) 
    nums = list(df2['Numbers'].astype('str')) 
    SBs = list(df2['SB'].astype('int'))
    return date, nums, SBs

date, nums, SBs = get_data()

# Formatting 
hyphenfree = []
for x in nums:
    hyphenfree.append(x.replace('–',', ')) 
splitlist = ", ".join(hyphenfree)
sep = splitlist.split(", ")

for n in range(0, 52):
    most_common= Counter(sep).most_common(5)
    likely_nums = [v[0] for v in most_common]
    frequency = [v[-1] for v in most_common]
    
for n in range(0, 10):
    most_common_sb = Counter(SBs).most_common(1)
    SB = [v[0] for v in most_common_sb]
    frequency_sb = [v[-1] for v in most_common_sb]

sorted_nums = sorted(likely_nums)
total_freq = sum(frequency + frequency_sb) 
Chance = frac(total_freq, 25989600) # Chance = number call freq / all possible numbers i.e. 25,989,600
Forecast = str("-".join(sorted_nums))

print(f"Likely numbers are . . .  {Forecast} SB: {SB}\n"
f"With percent chance of winning being {Chance}")