mojo编程语言：编译后的mojo二进制执行文件调用python库报错——设置MOJO_PYTHON_LIBRARY变量

代码：

from python import Python

fn f() raises:
    # This is equivalent to Python's `import numpy as np`
    let np = Python.import_module("numpy")
    let a = np.array([1, 2, 3])
    print(a)

fn main() raises:
    f()

mojo编译后执行，报错：

Mojo/Python interoperability error: Unable to locate a suitable libpython, please set `MOJO_PYTHON_LIBRARY`

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参考：

https://github.com/modularml/mojo/issues/551

执行命令（查找当前python环境下的libpython位置）：

python3 -c 'import sysconfig; print(sysconfig.get_config_var("LIBDIR"))'

ls $(python3 -c 'import sysconfig; print(sysconfig.get_config_var("LIBDIR"))') | grep libpython

解决方法：

echo 'export MOJO_PYTHON_LIBRARY="<full_path_to_libpython.so>"' >> ~/.bashrc

source ~/.bashrc

因此在当前环境配置命令为：

export MOJO_PYTHON_LIBRARY=/home/devil/anaconda3/envs/mojo/lib/libpython3.so

也或者将命令写入 .bashrc 配置文件中：

配置后执行：

/home/devil/anaconda3/lib/python3.9/site-packages/numpy/__init__.py:143: UserWarning: mkl-service package failed to import, therefore Intel(R) MKL initialization ensuring its correct out-of-the box operation under condition when Gnu OpenMP had already been loaded by Python process is not assured. Please install mkl-service package, see http://github.com/IntelPython/mkl-service
from . import _distributor_init
Unhandled exception caught during execution: An error occurred in Python.

考虑到之前配置使当前的python环境失效，重新设置python解释器环境：

conda activate mojo

再次执行，成功：

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PS:

说明下上面配置的原理，mojo二进制执行程序调用python库其实可以分为编译和执行两个阶段，编译的时候指定libpython3.so的位置就是指定编译后的程序需要调用的lib库是哪个，执行的时候会在当前的lib库搜索路径下进行搜索，因此就需要保证编译时指定的libpython3.so文件和执行时候的搜索的当前python环境是同一个。

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