Spaces:
Running
Running
Commit
·
e0391c1
1
Parent(s):
a575a22
Speed improvements
Browse files
Source/Build/update.py
CHANGED
@@ -26,6 +26,14 @@ year = dt.datetime.now().year
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month = dt.datetime.now().month
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current_season = year if month in [8,9,10,11,12] else year-1
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# update current season
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build.build_gbg_data(get_seasons=[current_season])
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#build.build_gbg_data(get_seasons=range(2014,2024))
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@@ -33,7 +41,6 @@ build.add_odds_data()
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# get winners
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pbp = build.get_pbp_data([current_season])
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-
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pbp = pbp.drop_duplicates(subset='game_id')
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pbp[['season','week','away','home']] = pbp['game_id'].str.split('_', expand=True)
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games = pbp[['game_id','away_score','home_score','season','week','away','home']]
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month = dt.datetime.now().month
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current_season = year if month in [8,9,10,11,12] else year-1
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# get schedule
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print('Getting schedule.\n')
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url = 'https://www.nbcsports.com/nfl/schedule'
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df = pd.read_html(url)
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file_path = os.path.join(pickle_directory, 'schedule.pkl')
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with open(file_path, 'wb') as f:
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pkl.dump(df, f)
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# update current season
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build.build_gbg_data(get_seasons=[current_season])
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#build.build_gbg_data(get_seasons=range(2014,2024))
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# get winners
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pbp = build.get_pbp_data([current_season])
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pbp = pbp.drop_duplicates(subset='game_id')
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pbp[['season','week','away','home']] = pbp['game_id'].str.split('_', expand=True)
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games = pbp[['game_id','away_score','home_score','season','week','away','home']]
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Source/Predict/__pycache__/predict.cpython-311.pyc
CHANGED
Binary files a/Source/Predict/__pycache__/predict.cpython-311.pyc and b/Source/Predict/__pycache__/predict.cpython-311.pyc differ
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Source/Predict/predict.py
CHANGED
@@ -31,6 +31,11 @@ file_path = os.path.join(pickle_directory, 'team_abbreviation_to_name.pkl')
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with open(file_path, 'rb') as f:
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team_abbreviation_to_name = pkl.load(f)
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# load models
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# moneyline
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model = 'xgboost_ML_no_odds_71.4%'
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@@ -67,8 +72,9 @@ def get_week():
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def get_games(week):
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# pull from NBC
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url = 'https://www.nbcsports.com/nfl/schedule'
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df = pd.read_html(url)[week-1]
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df['Away Team'] = [' '.join(i.split('\xa0')[1:]) for i in df['Away TeamAway Team']]
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df['Home Team'] = [' '.join(i.split('\xa0')[1:]) for i in df['Home TeamHome Team']]
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df['Date'] = pd.to_datetime(df['Game TimeGame Time'])
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@@ -121,7 +127,6 @@ def predict(home,away,season,week,total):
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# create game id
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game_id = str(season) + '_0' + str(int(week)) + '_' + away_abbrev + '_' + home_abbrev
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print(game_id)
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try:
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moneyline_result = results.loc[results['game_id']==game_id, 'winner'].item()
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with open(file_path, 'rb') as f:
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team_abbreviation_to_name = pkl.load(f)
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# get schedule
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file_path = os.path.join(pickle_directory, 'schedule.pkl')
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with open(file_path, 'rb') as f:
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schedule = pkl.load(f)
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# load models
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# moneyline
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model = 'xgboost_ML_no_odds_71.4%'
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def get_games(week):
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# pull from NBC
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#url = 'https://www.nbcsports.com/nfl/schedule'
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#df = pd.read_html(url)[week-1]
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df = schedule[week-1]
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df['Away Team'] = [' '.join(i.split('\xa0')[1:]) for i in df['Away TeamAway Team']]
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df['Home Team'] = [' '.join(i.split('\xa0')[1:]) for i in df['Home TeamHome Team']]
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df['Date'] = pd.to_datetime(df['Game TimeGame Time'])
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# create game id
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game_id = str(season) + '_0' + str(int(week)) + '_' + away_abbrev + '_' + home_abbrev
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try:
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moneyline_result = results.loc[results['game_id']==game_id, 'winner'].item()
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