像Python一样玩C/C++
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:
l = [1,2] l
直接输出:
[1,2]
那当使用C++的时候,例如:
map<string, int> 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:
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:
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:
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
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