Parallel isin (#603)

Author: Rubtsowa

sdc/datatypes/hpat_pandas_series_functions.py

@@ -63,12 +63,14 @@
 from sdc.str_arr_type import (StringArrayType, string_array_type)
 from sdc.str_arr_ext import (str_arr_is_na, str_arr_set_na, num_total_chars,
                              pre_alloc_string_array, cp_str_list_to_array,
-                             create_str_arr_from_list, str_arr_set_na_by_mask)
+                             create_str_arr_from_list, str_arr_set_na_by_mask,
+                             str_list_to_array)
 from sdc.utilities.utils import to_array, sdc_overload, sdc_overload_method, sdc_overload_attribute
 from sdc import sdc_autogenerated
 from sdc.functions import numpy_like
 from sdc.hiframes.api import isna
 from sdc.datatypes.hpat_pandas_groupby_functions import init_series_groupby
+from sdc.utilities.prange_utils import parallel_chunks
 
 from .pandas_series_functions import apply
 from .pandas_series_functions import map as _map
@@ -2048,7 +2050,7 @@ def hpat_pandas_series_isin(self, values):
     Pandas Series method :meth:`pandas.Series.isin` implementation.
 
     .. only:: developer
-        Test: python -m sdc.runtests sdc.tests.test_series.TestSeries.test_series_isin_list1
+        Test: python -m sdc.runtests -k sdc.tests.test_series.TestSeries.test_series_isin*
     """
 
     _func_name = 'Method isin().'
@@ -2059,10 +2061,31 @@ def hpat_pandas_series_isin(self, values):
     if not isinstance(values, (types.Set, types.List)):
         ty_checker.raise_exc(values, 'set or list', 'values')
 
-    def hpat_pandas_series_isin_impl(self, values):
-        # TODO: replace with below line when Numba supports np.isin in nopython mode
-        # return pandas.Series(np.isin(self._data, values))
-        return pandas.Series(data=[(x in values) for x in self._data], index=self._index, name=self._name)
+    if isinstance(values.dtype, (types.UnicodeType, types.StringLiteral)):
+        def hpat_pandas_series_isin_impl(self, values):
+            # TODO: replace with below line when Numba supports np.isin in nopython mode
+            # return pandas.Series (np.isin (self._data, values))
+
+            values = str_list_to_array(list(values))
+            values = set(values)
+            data_len = len(self._data)
+            result = numpy.empty(data_len, dtype=numpy.bool_)
+            for i in prange(data_len):
+                result[i] = self._data[i] in values
+
+            return pandas.Series(data=result, index=self._index, name=self._name)
+    else:
+        def hpat_pandas_series_isin_impl(self, values):
+            # TODO: replace with below line when Numba supports np.isin in nopython mode
+            # return pandas.Series (np.isin (self._data, values))
+
+            values = set(values)
+            data_len = len(self._data)
+            result = numpy.empty(data_len, dtype=numpy.bool_)
+            for i in prange(data_len):
+                result[i] = self._data[i] in values
+
+            return pandas.Series(data=result, index=self._index, name=self._name)
 
     return hpat_pandas_series_isin_impl
 

sdc/tests/tests_perf/test_perf_series.py

@@ -107,7 +107,9 @@ def _test_case(self, pyfunc, name, total_data_length, input_data=None, data_num=
     TC(name='idxmin', size=[10 ** 8], check_skipna=True),
     TC(name='iloc', size=[10 ** 7], call_expr='data.iloc[100000]', usecase_params='data'),
     TC(name='index', size=[10 ** 7], call_expr='data.index', usecase_params='data'),
-    TC(name='isin', size=[10 ** 7], call_expr='data.isin([0])', usecase_params='data'),
+    TC(name='isin', size=[10 ** 7], params='values=[0]'),
+    TC(name='isin', size=[10 ** 7], call_expr='data.isin(["a", "q", "c", "q", "d", "q", "e"])', usecase_params='data',
+       input_data=[['a', 'b', 'q', 'w', 'c', 'd', 'e', 'r']]),
     TC(name='isna', size=[10 ** 7]),
     TC(name='isnull', size=[10 ** 7]),
     TC(name='le', size=[10 ** 7], params='other', data_num=2),