在Python多处理库中，是否有支持多个参数的pool.map变体？
import multiprocessing
text = "test"
def harvester(text, case):
X = case[0]
text + str(X)
if __name__ == '__main__':
pool = multiprocessing.Pool(processes=6)
case = RAW_DATASET
pool.map(harvester(text, case), case, 1)
pool.close()
pool.join()
当前回答
对于Python 2，可以使用此技巧
def fun(a, b):
return a + b
pool = multiprocessing.Pool(processes=6)
b = 233
pool.map(lambda x:fun(x, b), range(1000))
其他回答
将所有参数存储为元组数组。
该示例表示，通常调用函数为：
def mainImage(fragCoord: vec2, iResolution: vec3, iTime: float) -> vec3:
而是传递一个元组并解压缩参数：
def mainImage(package_iter) -> vec3:
fragCoord = package_iter[0]
iResolution = package_iter[1]
iTime = package_iter[2]
预先使用循环构建元组：
package_iter = []
iResolution = vec3(nx, ny, 1)
for j in range((ny-1), -1, -1):
for i in range(0, nx, 1):
fragCoord: vec2 = vec2(i, j)
time_elapsed_seconds = 10
package_iter.append((fragCoord, iResolution, time_elapsed_seconds))
然后通过传递元组数组来执行所有using map：
array_rgb_values = []
with concurrent.futures.ProcessPoolExecutor() as executor:
for val in executor.map(mainImage, package_iter):
fragColor = val
ir = clip(int(255* fragColor.r), 0, 255)
ig = clip(int(255* fragColor.g), 0, 255)
ib = clip(int(255* fragColor.b), 0, 255)
array_rgb_values.append((ir, ig, ib))
我知道Python有*和**用于开箱，但我还没有尝试过。
使用高级库并发期货也比使用低级多处理库更好。
Python 2的更好解决方案：
from multiprocessing import Pool
def func((i, (a, b))):
print i, a, b
return a + b
pool = Pool(3)
pool.map(func, [(0,(1,2)), (1,(2,3)), (2,(3, 4))])
输出
2 3 4
1 2 3
0 1 2
out[]:
[3, 5, 7]
我认为以下内容会更好：
def multi_run_wrapper(args):
return add(*args)
def add(x,y):
return x+y
if __name__ == "__main__":
from multiprocessing import Pool
pool = Pool(4)
results = pool.map(multi_run_wrapper,[(1,2),(2,3),(3,4)])
print results
输出
[3, 5, 7]
对于Python 2，可以使用此技巧
def fun(a, b):
return a + b
pool = multiprocessing.Pool(processes=6)
b = 233
pool.map(lambda x:fun(x, b), range(1000))
如何获取多个参数：
def f1(args):
a, b, c = args[0] , args[1] , args[2]
return a+b+c
if __name__ == "__main__":
import multiprocessing
pool = multiprocessing.Pool(4)
result1 = pool.map(f1, [ [1,2,3] ])
print(result1)
