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gil.py
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from .pandas_vb_common import *
from pandas.core import common as com
try:
from pandas.util.testing import test_parallel
have_real_test_parallel = True
except ImportError:
have_real_test_parallel = False
def test_parallel(num_threads=1):
def wrapper(fname):
return fname
return wrapper
class nogil_groupby_count_2(object):
goal_time = 0.2
def setup(self):
self.N = 1000000
self.ngroups = 1000
np.random.seed(1234)
self.df = DataFrame({'key': np.random.randint(0, self.ngroups, size=self.N), 'data': np.random.randn(self.N), })
if (not have_real_test_parallel):
raise NotImplementedError
def time_nogil_groupby_count_2(self):
self.pg2()
@test_parallel(num_threads=2)
def pg2(self):
self.df.groupby('key')['data'].count()
class nogil_groupby_last_2(object):
goal_time = 0.2
def setup(self):
self.N = 1000000
self.ngroups = 1000
np.random.seed(1234)
self.df = DataFrame({'key': np.random.randint(0, self.ngroups, size=self.N), 'data': np.random.randn(self.N), })
if (not have_real_test_parallel):
raise NotImplementedError
def time_nogil_groupby_last_2(self):
self.pg2()
@test_parallel(num_threads=2)
def pg2(self):
self.df.groupby('key')['data'].last()
class nogil_groupby_max_2(object):
goal_time = 0.2
def setup(self):
self.N = 1000000
self.ngroups = 1000
np.random.seed(1234)
self.df = DataFrame({'key': np.random.randint(0, self.ngroups, size=self.N), 'data': np.random.randn(self.N), })
if (not have_real_test_parallel):
raise NotImplementedError
def time_nogil_groupby_max_2(self):
self.pg2()
@test_parallel(num_threads=2)
def pg2(self):
self.df.groupby('key')['data'].max()
class nogil_groupby_mean_2(object):
goal_time = 0.2
def setup(self):
self.N = 1000000
self.ngroups = 1000
np.random.seed(1234)
self.df = DataFrame({'key': np.random.randint(0, self.ngroups, size=self.N), 'data': np.random.randn(self.N), })
if (not have_real_test_parallel):
raise NotImplementedError
def time_nogil_groupby_mean_2(self):
self.pg2()
@test_parallel(num_threads=2)
def pg2(self):
self.df.groupby('key')['data'].mean()
class nogil_groupby_min_2(object):
goal_time = 0.2
def setup(self):
self.N = 1000000
self.ngroups = 1000
np.random.seed(1234)
self.df = DataFrame({'key': np.random.randint(0, self.ngroups, size=self.N), 'data': np.random.randn(self.N), })
if (not have_real_test_parallel):
raise NotImplementedError
def time_nogil_groupby_min_2(self):
self.pg2()
@test_parallel(num_threads=2)
def pg2(self):
self.df.groupby('key')['data'].min()
class nogil_groupby_prod_2(object):
goal_time = 0.2
def setup(self):
self.N = 1000000
self.ngroups = 1000
np.random.seed(1234)
self.df = DataFrame({'key': np.random.randint(0, self.ngroups, size=self.N), 'data': np.random.randn(self.N), })
if (not have_real_test_parallel):
raise NotImplementedError
def time_nogil_groupby_prod_2(self):
self.pg2()
@test_parallel(num_threads=2)
def pg2(self):
self.df.groupby('key')['data'].prod()
class nogil_groupby_sum_2(object):
goal_time = 0.2
def setup(self):
self.N = 1000000
self.ngroups = 1000
np.random.seed(1234)
self.df = DataFrame({'key': np.random.randint(0, self.ngroups, size=self.N), 'data': np.random.randn(self.N), })
if (not have_real_test_parallel):
raise NotImplementedError
def time_nogil_groupby_sum_2(self):
self.pg2()
@test_parallel(num_threads=2)
def pg2(self):
self.df.groupby('key')['data'].sum()
class nogil_groupby_sum_4(object):
goal_time = 0.2
def setup(self):
self.N = 1000000
self.ngroups = 1000
np.random.seed(1234)
self.df = DataFrame({'key': np.random.randint(0, self.ngroups, size=self.N), 'data': np.random.randn(self.N), })
if (not have_real_test_parallel):
raise NotImplementedError
def time_nogil_groupby_sum_4(self):
self.pg4()
def f(self):
self.df.groupby('key')['data'].sum()
def g2(self):
for i in range(2):
self.f()
def g4(self):
for i in range(4):
self.f()
def g8(self):
for i in range(8):
self.f()
@test_parallel(num_threads=2)
def pg2(self):
self.f()
@test_parallel(num_threads=4)
def pg4(self):
self.f()
@test_parallel(num_threads=8)
def pg8(self):
self.f()
class nogil_groupby_sum_8(object):
goal_time = 0.2
def setup(self):
self.N = 1000000
self.ngroups = 1000
np.random.seed(1234)
self.df = DataFrame({'key': np.random.randint(0, self.ngroups, size=self.N), 'data': np.random.randn(self.N), })
if (not have_real_test_parallel):
raise NotImplementedError
def time_nogil_groupby_sum_8(self):
self.pg8()
def f(self):
self.df.groupby('key')['data'].sum()
def g2(self):
for i in range(2):
self.f()
def g4(self):
for i in range(4):
self.f()
def g8(self):
for i in range(8):
self.f()
@test_parallel(num_threads=2)
def pg2(self):
self.f()
@test_parallel(num_threads=4)
def pg4(self):
self.f()
@test_parallel(num_threads=8)
def pg8(self):
self.f()
class nogil_groupby_var_2(object):
goal_time = 0.2
def setup(self):
self.N = 1000000
self.ngroups = 1000
np.random.seed(1234)
self.df = DataFrame({'key': np.random.randint(0, self.ngroups, size=self.N), 'data': np.random.randn(self.N), })
if (not have_real_test_parallel):
raise NotImplementedError
def time_nogil_groupby_var_2(self):
self.pg2()
@test_parallel(num_threads=2)
def pg2(self):
self.df.groupby('key')['data'].var()
class nogil_take1d_float64(object):
goal_time = 0.2
def setup(self):
self.N = 1000000
self.ngroups = 1000
np.random.seed(1234)
self.df = DataFrame({'key': np.random.randint(0, self.ngroups, size=self.N), 'data': np.random.randn(self.N), })
if (not have_real_test_parallel):
raise NotImplementedError
self.N = 10000000.0
self.df = DataFrame({'int64': np.arange(self.N, dtype='int64'), 'float64': np.arange(self.N, dtype='float64'), })
self.indexer = np.arange(100, (len(self.df) - 100))
def time_nogil_take1d_float64(self):
self.take_1d_pg2_int64()
@test_parallel(num_threads=2)
def take_1d_pg2_int64(self):
com.take_1d(self.df.int64.values, self.indexer)
@test_parallel(num_threads=2)
def take_1d_pg2_float64(self):
com.take_1d(self.df.float64.values, self.indexer)
class nogil_take1d_int64(object):
goal_time = 0.2
def setup(self):
self.N = 1000000
self.ngroups = 1000
np.random.seed(1234)
self.df = DataFrame({'key': np.random.randint(0, self.ngroups, size=self.N), 'data': np.random.randn(self.N), })
if (not have_real_test_parallel):
raise NotImplementedError
self.N = 10000000.0
self.df = DataFrame({'int64': np.arange(self.N, dtype='int64'), 'float64': np.arange(self.N, dtype='float64'), })
self.indexer = np.arange(100, (len(self.df) - 100))
def time_nogil_take1d_int64(self):
self.take_1d_pg2_float64()
@test_parallel(num_threads=2)
def take_1d_pg2_int64(self):
com.take_1d(self.df.int64.values, self.indexer)
@test_parallel(num_threads=2)
def take_1d_pg2_float64(self):
com.take_1d(self.df.float64.values, self.indexer)
class nogil_kth_smallest(object):
number = 1
repeat = 5
def setup(self):
if (not have_real_test_parallel):
raise NotImplementedError
np.random.seed(1234)
self.N = 10000000
self.k = 500000
self.a = np.random.randn(self.N)
self.b = self.a.copy()
self.kwargs_list = [{'arr': self.a}, {'arr': self.b}]
def time_nogil_kth_smallest(self):
@test_parallel(num_threads=2, kwargs_list=self.kwargs_list)
def run(arr):
algos.kth_smallest(arr, self.k)
run()
class nogil_datetime_fields(object):
goal_time = 0.2
def setup(self):
self.N = 100000000
self.dti = pd.date_range('1900-01-01', periods=self.N, freq='D')
self.period = self.dti.to_period('D')
if (not have_real_test_parallel):
raise NotImplementedError
def time_datetime_field_year(self):
@test_parallel(num_threads=2)
def run(dti):
dti.year
run(self.dti)
def time_datetime_field_day(self):
@test_parallel(num_threads=2)
def run(dti):
dti.day
run(self.dti)
def time_datetime_field_daysinmonth(self):
@test_parallel(num_threads=2)
def run(dti):
dti.days_in_month
run(self.dti)
def time_datetime_field_normalize(self):
@test_parallel(num_threads=2)
def run(dti):
dti.normalize()
run(self.dti)
def time_datetime_to_period(self):
@test_parallel(num_threads=2)
def run(dti):
dti.to_period('S')
run(self.dti)
def time_period_to_datetime(self):
@test_parallel(num_threads=2)
def run(period):
period.to_timestamp()
run(self.period)