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How to use get_random_number method in locust

Best Python code snippet using locust

ml_backend.py

Source:ml_backend.py

...23        'Pts5', 'OR1', 'OR2', 'OR3', 'OR4', 'OR5', 'DR1', 'DR2', 'DR3',24        'DR4', 'DR5', 'FG2Pct', 'FG3Pct', 'FTPct', 'BlockPct',25        'OppFG2Pct', 'OppFG3Pct', 'OppFTPct', 'OppBlockPct', 'F3GRate',26        'OppF3GRate', 'ARate', 'OppARate', 'StlRate', 'OppStlRate']27def get_random_number():28    """generate random number between -1 and 1."""29    rand = random.random()30    rand = (rand * 2) - 131    return rand32def prepare_data(year1, team1, year2, team2, mongo):33    """Prepare data for prediction."""34    data = []35    team_year_info = mongo.db.basketball.find_one(36        {'TeamName': str(team1), 'Season': int(year1)})37    for col in cols:38        data.append(team_year_info[col])39    tc1 = team_year_info['color1']40    team_year_info = mongo.db.basketball.find_one(41        {'TeamName': str(team2), 'Season': int(year2)})42    for col in cols:43        data.append(team_year_info[col])44    tc2 = team_year_info['color1']45    data.append(home_court.get(str(team1), 0))46    data = np.array(data)47    return data, tc1, tc248def randomize_data(year1, team1, year2, team2, data):49    """randomize data for bootstrap predictions."""50    data_std = year_team_std[year1].get(team1, year_team_std['all'])51    cols_len = len(cols)52    data_copy = data.copy()53    data_copy[0] += get_random_number() * data_std['Pace']54    data_copy[1] += get_random_number() * data_std['ORtg']55    data_copy[2] += get_random_number() * data_std['DRtg']56    data_copy[3] += get_random_number() * data_std['OeFG%'] * 10057    data_copy[4] += get_random_number() * data_std['DeFG%'] * 10058    data_copy[5] += get_random_number() * data_std['OTOV%']59    data_copy[6] += get_random_number() * data_std['DTOV%']60    data_copy[7] += get_random_number() * data_std['OORB%']61    data_copy[8] += get_random_number() * data_std['DDRB%']62    data_copy[9] += get_random_number() * data_std['OFT/FGA'] * 10063    data_copy[10] += get_random_number() * data_std['DFT/FGA'] * 10064    data_copy[42] += get_random_number() * data_std['h3P%'] * 10065    data_copy[43] += get_random_number() * data_std['hFT%'] * 10066    data_copy[44] += get_random_number() * data_std['BLK%']67    data_copy[51] += get_random_number() * data_std['AST%']68    data_copy[53] += get_random_number() * data_std['STL%'] / 10069    data_std = year_team_std[year2].get(team2, year_team_std['all'])70    data_copy[0 + cols_len] += get_random_number() * data_std['Pace']71    data_copy[1 + cols_len] += get_random_number() * data_std['ORtg']72    data_copy[2 + cols_len] += get_random_number() * data_std['DRtg']73    data_copy[3 + cols_len] += get_random_number() * data_std['OeFG%'] * 10074    data_copy[4 + cols_len] += get_random_number() * data_std['DeFG%'] * 10075    data_copy[5 + cols_len] += get_random_number() * data_std['OTOV%']76    data_copy[6 + cols_len] += get_random_number() * data_std['DTOV%']77    data_copy[7 + cols_len] += get_random_number() * data_std['OORB%']78    data_copy[8 + cols_len] += get_random_number() * data_std['DDRB%']79    data_copy[9 + cols_len] += get_random_number() * data_std['OFT/FGA'] * 10080    data_copy[10 + cols_len] += get_random_number() * data_std['DFT/FGA'] * 10081    data_copy[42 + cols_len] += get_random_number() * data_std['h3P%'] * 10082    data_copy[43 + cols_len] += get_random_number() * data_std['hFT%'] * 10083    data_copy[44 + cols_len] += get_random_number() * data_std['BLK%']84    data_copy[51 + cols_len] += get_random_number() * data_std['AST%']85    data_copy[53 + cols_len] += get_random_number() * data_std['STL%'] / 10086    return data_copy87def bootstrap(year1, team1, year2, team2, mongo):88    """predict 100 random games."""89    output = {}90    data, tc1, tc2 = prepare_data(year1, team1, year2, team2, mongo)91    data_df = pd.DataFrame(data.reshape(1, 111))92    data_copy = data.copy()93    num_trials = 9994    for i in range(num_trials):95        rand_data = randomize_data(year1, team1, year2, team2, data_copy)96        data_df.loc[len(data_df)] = rand_data97    data_df -= ml_stats_mean98    data_df = data_df / ml_stats_std99    global graph...

test_cached.py

Source:test_cached.py

2import pytest3import random4import warnings5@cached6def get_random_number(a, b, *args, **kwars):7    print(a, b)8    return random.randint(a, b)9@cached10def get_number(a, b, *args, **kwars):11    return (a + b) // 212class TestCached:13    def initialize(self):14        random.seed(42)15    def test_simple(self):16        self.initialize()17        for i in range(100):18            assert get_random_number(1, 2) == get_random_number(1, 2)19    def test_hashable_types(self):20        self.initialize()21        tpl = (1, 2.0, '123', None, True)22        for i in range(100):23            assert get_random_number(1, 2, tpl) == get_random_number(1, 2, tpl)24    def test_runtime_warning_unhashable_types(self):25        unhashable = {1: 2, 3: 4}26        with pytest.warns(RuntimeWarning):27            get_number(1, 2, unhashable)28    def test_unhashable_types(self):29        warnings.simplefilter("ignore")...

test_fixture.py

Source:test_fixture.py

...16#     assert os.path.exists(directory), 'dir not exist'171819@pytest.fixture(scope="session")20def get_random_number():21    number = random.randint(1, 100)22    print(number)23    return number242526def test_random_number(get_random_number):27    assert 0 < get_random_number <= 100282930def test_random_number_2(get_random_number):31    assert 0 < get_random_number <= 100323334class TestRandom:
...

test_2.py

Source:test_2.py

1import pytest2from proga import get_random_number3def test_get_random_number_1():4    assert isinstance(get_random_number(12), int)5def test_get_random_number_2():6    assert get_random_number(12) <= 127def test_get_random_number_3():8    assert isinstance(get_random_number(20), int)9def test_get_random_number_4():10    assert get_random_number(20) <= 2011def test_get_random_number_5():12    assert isinstance(get_random_number(123), int)13def test_get_random_number_6():...

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