Linux中vectormath无法通过pip安装的解决办法

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博客讲述了vectormath安装时出现权限不足等报错情况，如‘Permission denied’等，还提示Python 2.7将不再被支持。给出的解决办法是去官网下载python文件，详细步骤包括下载文件、创建安装目录、移动vectormath文件以及测试test_vectormath.py。

在使用pip安装vectormath的时候

$ pip install vectormath

总是会报错

ERROR: Could not install packages due to an EnvironmentError: [Errno 13] Permission denied: /usr/local/lib/python2.7/dist-packages/vectormath

/home/kai/.local/lib/python2.7/site-packages/pip/_vendor/requests/init.py:83: RequestsDependencyWarning: Old version of cryptography ([1, 2, 3]) may cause slowdown.
warnings.warn(warning, RequestsDependencyWarning)
DEPRECATION: Python 2.7 will reach the end of its life on January 1st, 2020. Please upgrade your Python as Python 2.7 won’t be maintained after that date. A future version of pip will drop support for Python 2.7.
Collecting vectormath
Requirement already satisfied: numpy>=1.7 in ./.local/lib/python2.7/site-packages (from vectormath) (1.16.4)
Installing collected packages: vectormath
ERROR: Could not install packages due to an EnvironmentError: [Errno 13] Permission denied: ‘/usr/local/lib/python2.7/dist-packages/vectormath’
Consider using the --user option or check the permissions.

解决办法：

去官网直接下载python文件，然后使用suso拷贝/usr/local/lib/python2.7/dist-packages/vectormath到这个目录中

具体步骤如下：

step1：下载python文件

官网直达链接：vectormath · PyPI
https://pypi.org/project/vectormath/#files

在这里插入图片描述

step2：创建安装目录

$ cd /usr/local/lib/python2.7/dist-packages/
$ sudo mkdir vectormath

step3：移动vectormath文件

解压缩得到如下所示，这里的setup.py运行仍然是没有用的，很失望。
在这里插入图片描述

然后进入vectormath文件夹

在这里插入图片描述

将这两个文件移动到/usr/local/lib/python2.7/dist-packages/vectormath这个目录中

$ sudo cp __init__.py vector.py /usr/local/lib/python2.7/dist-packages/vectormath

step4：测试一个test_vectormath.py

$ gedit test_vectormath.py

输入

import numpy as np
import vectormath as vmath

# Single Vectors
v = vmath.Vector3(5, 0, 0)
v.normalize()
print(v)                          # >> [1, 0, 0]
print(v.x)                        # >> 1.0

# VectorArrays are much faster than a for loop over Vectors
v_array = vmath.Vector3Array([[4, 0, 0], [0, 2, 0], [0, 0, 3]])
print(v_array.x)                  # >> [4, 0, 0]
print(v_array.length)             # >> [4, 2, 3]
print(v_array.normalize())        # >> [[1, 0, 0], [0, 1, 0], [0, 0, 1]]
# Vectors can be accessed individually or in slices
print(type(v_array[1:]))          # >> vectormath.Vector3Array
print(type(v_array[2]))           # >> vectormath.Vector3

# All these classes are just numpy arrays
print(isinstance(v, np.ndarray))  # >> True
print(type(v_array[1:, 1:]))      # >> numpy.ndarray

然后关闭保存运行：

$ python test_vectormath.py

正常运行的话会显示这些：

[1. 0. 0.]
1.0
[4. 0. 0.]
[4. 2. 3.]
[[1. 0. 0.]
 [0. 1. 0.]
 [0. 0. 1.]]
<class 'vectormath.vector.Vector3Array'>
<class 'vectormath.vector.Vector3'>
True
<type 'numpy.ndarray'>