118 lines
2.3 KiB
Markdown
118 lines
2.3 KiB
Markdown
# 像Python一样玩C/C++
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在Python中我们可以使用`Jupyter Notebook`直接看到结果，例如：
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```c
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l = [1,2]
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l
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```
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直接输出：
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```
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[1,2]
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```
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那当使用C++的时候，例如：
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```cpp
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map<string, int> mp{
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{"one", 1},
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{"two", 2},
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{"three", 3},
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{"four", 4}
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};
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```
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如果要输出，就得循环遍历，可否直接输出结果呢？
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so easy!!! `Jupyter Notebook`可以解决一切问题，哈哈～
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## 如何在Jupyter中玩C++？
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在github上有一个仓库，如下所示：
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> https://github.com/QuantStack/xeus-cling
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`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。
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目前，支持Mac与Linux，但不支持Windows。
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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：
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```
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conda create -n cling
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```
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切换进去：
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```
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conda activate cling
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```
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给新环境安装`jupyter`和`notebook`
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```
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conda install jupyter notebook
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```
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使用`conda-forge`安装`xeus-cling`
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```
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conda install xeus-cling -c conda-forge
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```
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为了加速安装，请记得给Anaconda配置源！
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检查是否安装好了内核(kernel)：
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```
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jupyter kernelspec list
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```
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输出：
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```cpp
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python3 /home/xxx/anaconda3/envs/cling/share/jupyter/kernels/python3
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xcpp11 /home/xxx/anaconda3/envs/cling/share/jupyter/kernels/xcpp11
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xcpp14 /home/xxx/anaconda3/envs/cling/share/jupyter/kernels/xcpp14
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xcpp17 /home/xxx/anaconda3/envs/cling/share/jupyter/kernels/xcpp17
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```
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打开`Jupyter Notebook`，就可以看到看到kernel了。
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启动`Jupyter Notebook`：
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```
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jupyter-notebook
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```
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## 如何在Jupyter中玩C？
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只需要安装c kernel即可！
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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。
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```
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pip install jupyter-c-kernel
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install_c_kernel
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jupyter kernelspec list
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```
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此时，就输出：
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```cpp
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c /home/light/anaconda3/envs/cling/share/jupyter/kernels/c
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python3 /home/light/anaconda3/envs/cling/share/jupyter/kernels/python3
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xcpp11 /home/light/anaconda3/envs/cling/share/jupyter/kernels/xcpp11
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xcpp14 /home/light/anaconda3/envs/cling/share/jupyter/kernels/xcpp14
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xcpp17 /home/light/anaconda3/envs/cling/share/jupyter/kernels/xcpp17
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```
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启动`Jupyter Notebook`：
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```
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jupyter-notebook
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```
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