# 像Python一样玩C/C++ 在Python中我们可以使用`Jupyter Notebook`直接看到结果,例如: ```c l = [1,2] l ``` 直接输出: ``` [1,2] ``` 那当使用C++的时候,例如: ```cpp map mp{ {"one", 1}, {"two", 2}, {"three", 3}, {"four", 4} }; ``` 如果要输出,就得循环遍历,可否直接输出结果呢? so easy!!! `Jupyter Notebook`可以解决一切问题,哈哈~ ## 如何在Jupyter中玩C++? 在github上有一个仓库,如下所示: > https://github.com/QuantStack/xeus-cling `xeus-cling` 是一个用于C++的Jupyter内核,基于C++解释器和Jupyter协议xeus的原生实现。 目前,支持Mac与Linux,但不支持Windows。 安装也是非常简单,首先安装好Anaconda,在里面创建一个虚拟环境: ``` conda create -n cling ``` 切换进去: ``` conda activate cling ``` 给新环境安装`jupyter`和`notebook` ``` conda install jupyter notebook ``` 使用`conda-forge`安装`xeus-cling` ``` conda install xeus-cling -c conda-forge ``` 为了加速安装,请记得给Anaconda配置源! 检查是否安装好了内核(kernel): ``` jupyter kernelspec list ``` 输出: ```cpp python3 /home/xxx/anaconda3/envs/cling/share/jupyter/kernels/python3 xcpp11 /home/xxx/anaconda3/envs/cling/share/jupyter/kernels/xcpp11 xcpp14 /home/xxx/anaconda3/envs/cling/share/jupyter/kernels/xcpp14 xcpp17 /home/xxx/anaconda3/envs/cling/share/jupyter/kernels/xcpp17 ``` 打开`Jupyter Notebook`,就可以看到看到kernel了。 启动`Jupyter Notebook`: ``` jupyter-notebook ``` ## 如何在Jupyter中玩C? 只需要安装c kernel即可! 可以直接在当前环境中创建c kernel,也可以新开一个环境安装,下面是在当前环境中直接安装。 ``` pip install jupyter-c-kernel install_c_kernel jupyter kernelspec list ``` 此时,就输出: ```cpp c /home/light/anaconda3/envs/cling/share/jupyter/kernels/c python3 /home/light/anaconda3/envs/cling/share/jupyter/kernels/python3 xcpp11 /home/light/anaconda3/envs/cling/share/jupyter/kernels/xcpp11 xcpp14 /home/light/anaconda3/envs/cling/share/jupyter/kernels/xcpp14 xcpp17 /home/light/anaconda3/envs/cling/share/jupyter/kernels/xcpp17 ``` 启动`Jupyter Notebook`: ``` jupyter-notebook ```