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from Source.Predict import predict | |
from flask import Flask, render_template, jsonify, request | |
import requests | |
import pickle as pkl | |
import pandas as pd | |
import numpy as np | |
pd.set_option('display.max_columns', None) | |
pd.set_option('display.expand_frame_repr', False) | |
import os | |
import json | |
with open('Source/Data/record.json','r') as f: | |
record = json.load(f) | |
# input the over/under lines here for quicker predictions! | |
lines = [44.5, | |
43, | |
38, | |
47, | |
41.5, | |
43.5, | |
47.5, | |
54.5, | |
35, | |
43, | |
42.5, | |
44, | |
48.5, | |
43.5, | |
45, | |
43.5] | |
# get week, season | |
week, season = predict.get_week() | |
app = Flask(__name__, template_folder="Templates", static_folder="Static", static_url_path="/Static") | |
app.secret_key = 'green-flounder' | |
games = predict.get_games(week)[['Date','Away Team','Home Team']] | |
def index(): | |
return render_template('index.html', **record) | |
def get_lines(): | |
return jsonify(lines) | |
def get_games(): | |
return jsonify(games.to_dict(orient='records')) | |
def submit_games(): | |
data = request.json | |
data = pd.DataFrame(data).replace('', np.nan).dropna() | |
print(data) | |
home_teams = data['HomeTeam'].values | |
away_teams = data['AwayTeam'].values | |
ou_lines = data['OverUnderLine'].values | |
row_indices = data['rowIndex'].values | |
moneylines = [] | |
over_unders = [] | |
for row_index,home,away,total in zip(row_indices,home_teams,away_teams,ou_lines): | |
game_id, moneyline, over_under = predict.predict(home,away,season,week,total) | |
moneyline['rowIndex'] = int(row_index) | |
over_under['rowIndex'] = int(row_index) | |
moneylines.append(moneyline) | |
over_unders.append(over_under) | |
print('MoneyLines') | |
print(moneylines) | |
print('OverUnders') | |
print(over_unders) | |
return jsonify({'moneylines': moneylines, | |
'over_unders': over_unders}) | |
if __name__ == '__main__': | |
app.run(host='0.0.0.0', port='7860') |