def test_teams_string_representation(self):
expected = """Golden State Warriors (GSW)
Houston Rockets (HOU)
Denver Nuggets (DEN)
Cleveland Cavaliers (CLE)
Washington Wizards (WAS)
Los Angeles Clippers (LAC)
Boston Celtics (BOS)
Portland Trail Blazers (POR)
Phoenix Suns (PHO)
Toronto Raptors (TOR)
Oklahoma City Thunder (OKC)
Brooklyn Nets (BRK)
Minnesota Timberwolves (MIN)
San Antonio Spurs (SAS)
Indiana Pacers (IND)
Charlotte Hornets (CHO)
Los Angeles Lakers (LAL)
New Orleans Pelicans (NOP)
New York Knicks (NYK)
Milwaukee Bucks (MIL)
Miami Heat (MIA)
Atlanta Hawks (ATL)
Chicago Bulls (CHI)
Sacramento Kings (SAC)
Philadelphia 76ers (PHI)
Detroit Pistons (DET)
Orlando Magic (ORL)
Utah Jazz (UTA)
Memphis Grizzlies (MEM)
Dallas Mavericks (DAL)"""
teams = Teams()
assert teams.__repr__() == expected
def get_schedule(date):
teams = Teams()
df_full = pd.DataFrame()
for team in teams:
schedule = team.schedule
df = team.schedule.dataframe
df['team_abbr'] = team.abbreviation
df_full = pd.concat([df_full, df])
df_full = df_full[df_full['location'] == 'Away']
return df_full[df_full['datetime'].dt.date == date.date()]
def test_invalid_default_year_reverts_to_previous_year(
self, *args, **kwargs):
flexmock(utils) \
.should_receive('_find_year_for_season') \
.and_return(2022)
teams = Teams()
for team in teams:
assert team._year == '2021'
def test_nba_empty_page_returns_no_teams(self):
flexmock(utils) \
.should_receive('_no_data_found') \
.once()
flexmock(utils) \
.should_receive('_get_stats_table') \
.and_return(None)
teams = Teams()
assert len(teams) == 0
def setup_method(self, *args, **kwargs):
self.results = {
'rank': 26,
'abbreviation': 'DET',
'name': 'Detroit Pistons',
'games_played': 82,
'minutes_played': 19805,
'field_goals': 3269,
'field_goal_attempts': 7282,
'field_goal_percentage': .449,
'three_point_field_goals': 631,
'three_point_field_goal_attempts': 1915,
'three_point_field_goal_percentage': .330,
'two_point_field_goals': 2638,
'two_point_field_goal_attempts': 5367,
'two_point_field_goal_percentage': .492,
'free_throws': 1140,
'free_throw_attempts': 1586,
'free_throw_percentage': .719,
'offensive_rebounds': 908,
'defensive_rebounds': 2838,
'total_rebounds': 3746,
'assists': 1732,
'steals': 574,
'blocks': 310,
'turnovers': 973,
'personal_fouls': 1467,
'points': 8309,
'opp_field_goals': 3144,
'opp_field_goal_attempts': 6830,
'opp_field_goal_percentage': .460,
'opp_three_point_field_goals': 767,
'opp_three_point_field_goal_attempts': 2098,
'opp_three_point_field_goal_percentage': .366,
'opp_two_point_field_goals': 2377,
'opp_two_point_field_goal_attempts': 4732,
'opp_two_point_field_goal_percentage': .502,
'opp_free_throws': 1346,
'opp_free_throw_attempts': 1726,
'opp_free_throw_percentage': .780,
'opp_offensive_rebounds': 656,
'opp_defensive_rebounds': 2861,
'opp_total_rebounds': 3517,
'opp_assists': 1929,
'opp_steals': 551,
'opp_blocks': 339,
'opp_turnovers': 1046,
'opp_personal_fouls': 1434,
'opp_points': 8401
}
self.abbreviations = [
'BOS', 'CLE', 'TOR', 'WAS', 'ATL', 'MIL', 'IND', 'CHI', 'MIA',
'DET', 'CHO', 'NYK', 'ORL', 'PHI', 'BRK', 'GSW', 'SAS', 'HOU',
'LAC', 'UTA', 'OKC', 'MEM', 'POR', 'DEN', 'NOP', 'DAL', 'SAC',
'MIN', 'LAL', 'PHO'
]
flexmock(utils) \
.should_receive('_todays_date') \
.and_return(MockDateTime(YEAR, MONTH))
self.teams = Teams()
def setup_method(self, *args, **kwargs):
self.results = {
'rank': 27,
'abbreviation': 'DET',
'name': 'Detroit Pistons',
'games_played': 72,
'minutes_played': 17430,
'field_goals': 2783,
'field_goal_attempts': 6162,
'field_goal_percentage': .452,
'three_point_field_goals': 832,
'three_point_field_goal_attempts': 2370,
'three_point_field_goal_percentage': .351,
'two_point_field_goals': 1951,
'two_point_field_goal_attempts': 3792,
'two_point_field_goal_percentage': .515,
'free_throws': 1278,
'free_throw_attempts': 1683,
'free_throw_percentage': .759,
'offensive_rebounds': 694,
'defensive_rebounds': 2381,
'total_rebounds': 3075,
'assists': 1743,
'steals': 531,
'blocks': 371,
'turnovers': 1075,
'personal_fouls': 1477,
'points': 7676,
'opp_field_goals': 2980,
'opp_field_goal_attempts': 6260,
'opp_field_goal_percentage': .476,
'opp_three_point_field_goals': 817,
'opp_three_point_field_goal_attempts': 2260,
'opp_three_point_field_goal_percentage': .362,
'opp_two_point_field_goals': 2163,
'opp_two_point_field_goal_attempts': 4000,
'opp_two_point_field_goal_percentage': .541,
'opp_free_throws': 1221,
'opp_free_throw_attempts': 1607,
'opp_free_throw_percentage': .760,
'opp_offensive_rebounds': 717,
'opp_defensive_rebounds': 2475,
'opp_total_rebounds': 3192,
'opp_assists': 1785,
'opp_steals': 578,
'opp_blocks': 419,
'opp_turnovers': 1004,
'opp_personal_fouls': 1469,
'opp_points': 7998
}
self.abbreviations = [
'BOS', 'CLE', 'TOR', 'WAS', 'ATL', 'MIL', 'IND', 'CHI', 'MIA',
'DET', 'CHO', 'NYK', 'ORL', 'PHI', 'BRK', 'GSW', 'SAS', 'HOU',
'LAC', 'UTA', 'OKC', 'MEM', 'POR', 'DEN', 'NOP', 'DAL', 'SAC',
'MIN', 'LAL', 'PHO'
]
flexmock(utils) \
.should_receive('_todays_date') \
.and_return(MockDateTime(YEAR, MONTH))
self.teams = Teams()
def main():
year = 2021
TeamLists = pd.read_excel('data/TeamLists.xls', sheet_name=0, header=None)
TeamLists = TeamLists.to_numpy(dtype=object, copy=True)
if year > 2014:
TeamList = TeamLists[:, 2]
elif year == 2014:
TeamList = TeamLists[:, 1]
elif year < 2014:
TeamList = TeamLists[:, 0]
TeamList_Lines = TeamLists[:, 3]
now = datetime.datetime.now()
datestring = now.strftime("%m_%d_%Y")
today = (now - datetime.datetime(year - 1, 10, 12)).days
with open('pickles/NBA_Data_pickled/' + str(year) + 'NBAData.pkl',
'rb') as Data:
Data_Full = pickle.load(Data)
teams = Teams(year)
for team in teams:
print(team)
for i in range(30):
if team.name == TeamList[i]:
break
schedule = team.schedule
for game in schedule:
game_date = game.datetime
daynum = (game_date - datetime.datetime(year - 1, 10, 12)).days
if daynum >= today - 30:
box = game.boxscore
Data_Full[daynum, 7, i] = game.opponent_name
Data_Full[daynum, 8, i] = game.points_scored
Data_Full[daynum, 9, i] = game.points_allowed
Data_Full[daynum, 6, i] = game.location
Data_Full[daynum, 0, i] = game.game
Data_Full[daynum, 35, i] = game.playoffs
Data_Full[daynum, 34, i] = game.streak
if game.location == 'Home':
Data_Full[daynum, 10, i] = box.home_offensive_rating
Data_Full[daynum, 11, i] = box.home_defensive_rating
Data_Full[daynum, 12,
i] = box.home_effective_field_goal_percentage
Data_Full[daynum, 13, i] = box.home_assist_percentage
Data_Full[daynum, 14, i] = box.home_assists
Data_Full[daynum, 15, i] = box.home_block_percentage
Data_Full[daynum, 17,
i] = box.home_defensive_rebound_percentage
Data_Full[daynum, 18, i] = box.home_field_goal_percentage
Data_Full[daynum, 19, i] = box.home_field_goals
Data_Full[daynum, 20, i] = box.home_free_throw_attempt_rate
Data_Full[daynum, 21,
i] = box.home_offensive_rebound_percentage
Data_Full[daynum, 22, i] = box.home_steal_percentage
Data_Full[daynum, 23,
i] = box.home_three_point_field_goal_percentage
Data_Full[daynum, 24, i] = box.home_turnover_percentage
Data_Full[daynum, 26,
i] = box.home_true_shooting_percentage
Data_Full[daynum, 27, i] = box.home_free_throws
Data_Full[daynum, 28, i] = box.pace
elif game.location == 'Away':
Data_Full[daynum, 10, i] = box.away_offensive_rating
Data_Full[daynum, 11, i] = box.away_defensive_rating
Data_Full[daynum, 12,
i] = box.away_effective_field_goal_percentage
Data_Full[daynum, 13, i] = box.away_assist_percentage
Data_Full[daynum, 14, i] = box.away_assists
Data_Full[daynum, 15, i] = box.away_block_percentage
Data_Full[daynum, 17,
i] = box.away_defensive_rebound_percentage
Data_Full[daynum, 18, i] = box.away_field_goal_percentage
Data_Full[daynum, 19, i] = box.away_field_goals
Data_Full[daynum, 20, i] = box.away_free_throw_attempt_rate
Data_Full[daynum, 21,
i] = box.away_offensive_rebound_percentage
Data_Full[daynum, 22, i] = box.away_steal_percentage
Data_Full[daynum, 23,
i] = box.away_three_point_field_goal_percentage
Data_Full[daynum, 24, i] = box.away_turnover_percentage
Data_Full[daynum, 26,
i] = box.away_true_shooting_percentage
Data_Full[daynum, 27, i] = box.away_free_throws
Data_Full[daynum, 28, i] = box.pace
with open('pickles/NBA_Data_pickled/' + str(year) + 'NBAData.pkl',
'wb') as Data_in:
pickle.dump(Data_Full, Data_in)
pdb.set_trace()