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| from Source.Predict import predict | |
| from flask import Flask, render_template, jsonify, request, session | |
| 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 json | |
| with open('Source/Data/record.json','r') as f: | |
| record = json.load(f) | |
| with open('Source/Data/lines.json','r') as f: | |
| lines = json.load(f) | |
| app = Flask(__name__, template_folder="Templates", static_folder="Static", static_url_path="/Static") | |
| app.config.update( | |
| SESSION_COOKIE_SECURE=True, | |
| SESSION_COOKIE_SAMESITE='None', | |
| ) | |
| app.secret_key = 'green-flounder' | |
| # get week, season | |
| current_week, season = predict.get_week() | |
| current_games = predict.get_games(current_week)[['Date','Away Team','Home Team']] | |
| available_weeks = list(range(current_week+1))[3:] | |
| available_weeks.reverse() | |
| # load current data by default | |
| def index(): | |
| print('Current Week', current_week) | |
| session['selected_week'] = current_week | |
| for week in available_weeks: | |
| session[f'games_week_{week}'] = None | |
| session[f'games_week_{current_week}'] = current_games.to_json() | |
| return render_template('index.html', **record) | |
| # send week list to front end | |
| def get_weeks(): | |
| return jsonify(available_weeks) | |
| # send lines to front end | |
| def get_lines(): | |
| try: | |
| return jsonify(lines[str(session.get('selected_week'))]) | |
| except: | |
| return jsonify(lines[str(current_week)]) | |
| # send games of selected week to front end | |
| def get_games(): | |
| requested_week = int(request.args.get('week')) | |
| session['selected_week'] = requested_week | |
| # If select a new week | |
| if requested_week and requested_week != current_week: | |
| print("Requested Week:", requested_week) | |
| # Check if that week's games are cached | |
| if session.get(f'games_week_{requested_week}'): | |
| print("Using cached games") | |
| print(session.get(f'games_week_{requested_week}')) | |
| games = session.get(f'games_week_{requested_week}') | |
| games = json.loads(games) | |
| return jsonify(games) | |
| else: | |
| games = predict.get_games(requested_week)[['Date','Away Team','Home Team']] | |
| session[f'games_week_{requested_week}'] = games.to_json(orient='records') | |
| return jsonify(games.to_dict(orient='records')) | |
| else: | |
| games = current_games | |
| return jsonify(games.to_dict(orient='records')) | |
| # make predictions | |
| def submit_games(): | |
| data = request.json | |
| data = pd.DataFrame(data).replace('', np.nan).dropna() | |
| 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): | |
| selected_week = session.get('selected_week') | |
| game_id, moneyline, over_under = predict.predict(home,away,season,selected_week,total) | |
| moneyline['rowIndex'] = int(row_index) | |
| over_under['rowIndex'] = int(row_index) | |
| moneylines.append(moneyline) | |
| over_unders.append(over_under) | |
| return jsonify({'moneylines': moneylines, | |
| 'over_unders': over_unders}) | |
| if __name__ == '__main__': | |
| app.run(host='0.0.0.0', port='7860', debug=True) |