python写法和c很像_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 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notebookconda install jupyter notebook

使用conda-forge安装xeus-clingconda 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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