def run():
logging.basicConfig(level=logging.INFO)
a = NBAComAgent(db=True, safe=False)
fla = FantasyLabsNBAAgent(db=True, safe=False)
# update players
logging.info('start update players')
a.commonallplayers('2015-16')
logging.info('completed update players')
# Update cs_player_gamelogs table through yesterday's games
logging.info('start update player_gamelogs')
a.cs_player_gamelogs('2015-16')
logging.info('end update player_gamelogs')
# Update cs_playerstats table through yesterday's games
logging.info('start update playerstats')
a.cs_playerstats('2015-16')
logging.info('end update playerstats')
# Update cs_team_gamelogs table through yesterday's games
logging.info('start update team_gamelogs')
a.cs_team_gamelogs('2015-16')
logging.info('end update team_gamelogs')
# Update cs_teamstats table through yesterday's games
logging.info('start update teamstats')
a.cs_teamstats('2015-16')
logging.info('end update teamstats')
# Get models and salaries from today's games
# insert salaries into database
logging.info('start update models')
players, pp_players = fla.today_models(insert_db=True)
logging.info('end update models')
# insert models into database
# TODO: preprocess_models + insert models code
return players, pp_players
class FantasyLabsNBAAgent_test(unittest.TestCase):
def setUp(self):
self.a = FantasyLabsNBAAgent(db=True, use_cache=True)
def test_init(self):
adb = FantasyLabsNBAAgent(db=True)
self.assertIsNotNone(adb.db)
asafe = FantasyLabsNBAAgent(safe=True)
self.assertIsNotNone(adb.safe)
asafe = FantasyLabsNBAAgent(use_cache=True)
self.assertIsNotNone(adb.scraper)
def test_past_day_models(self):
delta = random.choice(range(1,7))
d = dt.datetime.today() - dt.timedelta(delta)
fmt = site_format('fl')
models, pp_models = self.a.past_day_models(model_day=dt.datetime.strftime(d, fmt))
logging.debug('there are {0} models'.format(len(models)))
self.assertIsInstance(models, list)
self.assertTrue(len(models) > 0)
model = random.choice(models)
self.assertIsInstance(model, dict)
self.assertIn('Salary', model)
pp_model = random.choice(pp_models)
self.assertIsInstance(pp_model, dict)
self.assertIn('salary', pp_model)
def test_range_models(self):
fmt = site_format('fl')
delta = random.choice(range(7,14))
range_start = dt.datetime.today() - dt.timedelta(delta)
range_end = range_start + dt.timedelta(2)
models, pp_models = self.a.range_models(range_start=dt.datetime.strftime(range_start, fmt),
range_end=dt.datetime.strftime(range_end, fmt))
logging.debug('there are {0} models'.format(len(models)))
self.assertIsInstance(models, list)
self.assertTrue(len(models) > 0)
model = random.choice(models)
self.assertIsInstance(model, dict)
self.assertIn('Salary', model)
pp_model = random.choice(pp_models)
self.assertIsInstance(pp_model, dict)
self.assertIn('salary', pp_model)
def test_today_models(self):
models, pp_models = self.a.today_models()
logging.debug('there are {0} models'.format(len(models)))
self.assertIsInstance(models, list)
self.assertTrue(len(models) > 0)
model = random.choice(models)
self.assertIsInstance(model, dict)
self.assertIn('Salary', model)
pp_model = random.choice(pp_models)
self.assertIsInstance(pp_model, dict)
self.assertIn('salary', pp_model)
