blob: bc9f36d8e50cbbb50991dfea5d7fff35db064146 [file] [log] [blame]
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
# cython: profile=False
# distutils: language = c++
# cython: embedsignature = True
import numpy as np
import multiprocessing
import os
cdef extern from 'arrow/python/init.h':
int arrow_init_numpy() except -1
cdef extern from 'arrow/python/config.h' namespace 'arrow::py':
void set_numpy_nan(object o)
arrow_init_numpy()
set_numpy_nan(np.nan)
cdef int CPU_COUNT = int(
os.environ.get('OMP_NUM_THREADS',
max(multiprocessing.cpu_count() // 2, 1)))
def cpu_count():
"""
Returns
-------
count : Number of CPUs to use by default in parallel operations. Default is
max(1, multiprocessing.cpu_count() / 2), but can be overridden by the
OMP_NUM_THREADS environment variable. For the default, we divide the CPU
count by 2 because most modern computers have hyperthreading turned on,
so doubling the CPU count beyond the number of physical cores does not
help.
"""
return CPU_COUNT
def set_cpu_count(count):
global CPU_COUNT
CPU_COUNT = max(int(count), 1)