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kuailehaibin avatar kuailehaibin commented on June 12, 2024

@zhaoxu6666 你好!首先,非常感谢您提出的问题!针对您提出的问题,我们做了实际测试。实际测试脚本中引入了 pandasscikit-learn 机器学习库,通过 pip download <libpackage> 命令我们可以发现 pandasscikit-learn 的依赖如下:

pip download pandas
pip download scikit-learn

执行完后可以发现,pandas 主要依赖 numpydateutilpytzsix 等库;scikit-learn 主要依赖 numpyscipyjoblib 等库。

参考 文档,通常只要把下载的依赖库解压与测试脚本放在同一目录下,并以 package 形式引入即可。

但是,实际测试来看,在 Raspberry pi 4 model B 上的确出现了问题截图中的异常,经查询资料发现,pandasscikit-learn 安装使用除了上述已列出的第三方库外,还对与系统相关的 Cython 库有依赖(单独编译 pandasscikit-learn 库会有相应提示),需要在具备 Cython 环境的基础上才能正确使用;此外,scikit-learn 依赖的 scipy 的构建和安装需要依赖发行版系统。要在没有预编译所需库软件包的操作系统上构建 SciPynumpy 同理),必须先构建然后静态链接到 Fortran 库 BLASLAPACK

image

因此,对于 pandasscikit-learn 库的使用不能参考普通第三方库引入的方式。这里提供一个建议:可以在我们官方提供的 Python runtime Dockerfile 的基础上直接把所需要的特殊第三方库(如 pandasscikit-learn)在打包、构建的容器镜像时引入。

相关资料可参考:
[1] https://stackoverflow.com/questions/14570011/explain-why-numpy-should-not-be-imported-from-source-directory
[2] https://stackoverflow.com/questions/7496547/does-python-scipy-need-blas
[3] https://docs.scipy.org/doc/scipy-1.1.0/reference/building/linux.html

from baetyl.

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