Python ctypedef在Cython和numpy中：什么是正确的约定？

在Cython中，当使用numpy时，写作的目的是什么：

cimport numpy as np
import numpy as np
ctypedef np.int_t DTYPE_t

---

然后到处使用

DTYPE\u t

，而不是只使用

np.int\u t

？

ctypedef

在此处生成的代码中是否实际执行了不同的操作？

您可以从中阅读注释，阅读注释他们解释了使用此符号的原因并导入

from __future__ import division
import numpy as np
# "cimport" is used to import special compile-time information
# about the numpy module (this is stored in a file numpy.pxd which is
# currently part of the Cython distribution).
cimport numpy as np
# We now need to fix a datatype for our arrays. I've used the variable
# DTYPE for this, which is assigned to the usual NumPy runtime
# type info object.
DTYPE = np.int
# "ctypedef" assigns a corresponding compile-time type to DTYPE_t. For
# every type in the numpy module there's a corresponding compile-time
# type with a _t-suffix.
ctypedef np.int_t DTYPE_t
# "def" can type its arguments but not have a return type. The type of the
# arguments for a "def" function is checked at run-time when entering the
# function.
#
# The arrays f, g and h is typed as "np.ndarray" instances. The only effect
# this has is to a) insert checks that the function arguments really are
# NumPy arrays, and b) make some attribute access like f.shape[0] much
# more efficient. (In this example this doesn't matter though.)

---

我想这没关系，但这会让以后换成另一种类型更容易。他是对的。在任何地方编写

unsigned long long

之类的东西也可能有点麻烦。但这只是我的观点。假设我有pxd和pyx文件，它们都使用如下函数参数：np.ndarray[DTYPE\u double\u t，ndim=1]weight，但两个文件（pyx和pxd）中的ctypedef都会出现：“DTYPE\u int\u t”重新声明