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<blockquote>
<p>conda install jupyter notebook</p>
</blockquote>
<h3 id="修改主目录">修改主目录</h3>
<p>Jupyter Notebook 默认的主目录是“我的文档”，</p>
<blockquote>
<p>jupyter notebook --generate-config 显示配置文档所在位置</p>
</blockquote>
<blockquote>
<p>打开jupyter_notebook_config.py，查找NotebookApp.notebook_dir,后面文件夹改为指定目录。大概在393行</p>
</blockquote>
<blockquote>
<p>快捷方式属性，删除%USERPROFILE%</p>
</blockquote>
<h4 id="利用conda创建了虚拟环境，但是启动jupyter-notebook之后却找不到虚拟环境。实际上是由于在虚拟环境下缺少kernel-json文件。">利用conda创建了虚拟环境，但是启动jupyter notebook之后却找不到虚拟环境。实际上是由于在虚拟环境下缺少kernel.json文件。</h4>
<ol>
<li>使用anaconda安装ipykernel，很简单，只需执行一条命令：</li>
</ol>
<blockquote>
<p>$ conda install ipykernel</p>
</blockquote>
<ol start="2">
<li>添加配置好的环境到jupyter notebook的kernel中：</li>
</ol>
<blockquote>
<p>$ python -m ipykernel install --user --name env --display-name &quot;给kernel添加的名称</p>
</blockquote>
<p>如果经常用到jupyter notebook，可以在创建虚拟环境的时候安装好ipykernel：</p>
<blockquote>
<p>conda create -n 环境名称 python=3,9 ipykernel</p>
</blockquote>
<h3 id="jupyter-增加和删除kernel"><a target="_blank" rel="noopener" href="https://www.cnblogs.com/qiulinzhang/p/11023434.html">jupyter 增加和删除kernel</a></h3>
<ol>
<li>查看当前 jupyter 中有哪些 kernel</li>
</ol>
<figure class="highlight bash"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">jupyter kernelspec list</span><br></pre></td></tr></table></figure>
<hr>
<ol start="2">
<li>删除指定 kernel</li>
</ol>
<figure class="highlight bash"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">jupyter kernelspec remove kernel_name</span><br></pre></td></tr></table></figure>
<hr>
<ol start="3">
<li>增加指定 kernel</li>
</ol>
<ul>
<li>先进入相应的虚拟环境 <code>conda activate name</code></li>
<li>然后再用 <code>which python</code>找到当前虚拟环境下的 python 位置</li>
</ul>
<figure class="highlight bash"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br></pre></td><td class="code"><pre><span class="line">(pytorch) user-name@406:~$ <span class="built_in">which</span> python</span><br><span class="line">/home/user-name/anaconda3/envs/pytorch/bin/python</span><br></pre></td></tr></table></figure>
<ul>
<li>然后再输入，其中 XXXX 是你想要的 kernel name，由于权限问题可能要加 sudo</li>
</ul>
<figure class="highlight bash"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">sudo /home/user-name/anaconda3/envs/pytorch/bin/python -m ipykernel install --name XXXX</span><br></pre></td></tr></table></figure>
<p>注意：这里不能直接使用 <code>sudo python</code> 因为这样会对应到默认的python，而不是虚拟环境中的 python，因此直接输入虚拟环境的具体位置</p>
<h3 id="改指定工作目录">改指定工作目录</h3>
<p>右键属性, 目标后面的字串改成需要指定的工作空间路径</p>
<h3 id="魔法函数">魔法函数</h3>
<p>下面我们简单介绍几个最常见的魔法函数。<br>
<a target="_blank" rel="noopener" href="https://blog.csdn.net/u011213419/article/details/81299282">https://blog.csdn.net/u011213419/article/details/81299282</a></p>
<h4 id="lsmagic函数">%lsmagic函数</h4>
<p>%lsmagic函数可以列出（list，简写ls）所有魔法函数。如果我们想使用一个魔法函数，却忘记函数名如何写时，就可以使用%lsmagic来查询（在代码框内输入%lsmagic后按Shift+Enter组合键执行即可），如图1-29所示。<br>
<img src="https://imgs-1302910354.cos.ap-shanghai.myqcloud.com/images/jupyter_notebook%E7%9A%84%E4%BD%BF%E7%94%A8.-fig-0.png" alt="jupyter_notebook的使用.-fig-0.png">图1-29 Jupyter中的各种魔法函数</p>
<h4 id="matplotlib-inline函数">%matplotlib inline函数</h4>
<p>图1-22的第16行代码中出现过%matplotlib inline函数，它的含义就是告诉IPython，我们的绘图模式是内嵌（inline）模式，即将绘图直接显示在当前的网页上。<br>
有了这个魔法函数，图1-22所示代码的第21行plt.show()其实是可以省略的，读者朋友将其用注释形式去掉，然后尝试再次运行代码，可查看结果有无变化。<br>
其实，这个魔法函数的后置参数“inline”有一个“对标”参数—qt，如果我们使用这个参数，即%matplotlib qt，则表示代码构造的图形是通过独立窗口显示的。在独立窗口中可支持图形的缩放、拖曳及被另存为多种格式的图形文件（如.jpg、.png和.pdf等）。读者朋友可将图1-22中的第16行代码修改为的%matplotlib qt并再次运行，感性认识这两个参数带来的不同。</p>
<h4 id="timeit函数">%timeit函数</h4>
<p>魔法函数%timeit的功能是为某行代码的执行提供计时服务<a target="_blank" rel="noopener" href="https://zhuanlan.zhihu.com/p/142942524/edit#_ftn1">[1]</a>，这在评估机器学习算法的性能（特别是评估运行时间）时特别有用。例如，如果我们想对图1-22中的第14行代码的运行时间进行计时，则可以如下操作。</p>
<figure class="highlight plaintext"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">%timeit area = (40 * np.random.rand(20))**2</span><br></pre></td></tr></table></figure>
<p>按Shift+Enter组合键执行，结果如下。</p>
<figure class="highlight plaintext"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">6.6 µs ± 1.28 µs per loop (mean ± std. dev. of 7 runs, 100000 loops each)</span><br></pre></td></tr></table></figure>
<p>上述输出结果的意思是，对于代码“area = (40 * np.random.rand(20))**2”运行7轮，每轮运行1000个循环，然后求得均值为6.6微秒，方差为1.28微秒<a target="_blank" rel="noopener" href="https://zhuanlan.zhihu.com/p/142942524/edit#_ftn2">[2]</a>。<br>
如果我们想运行10轮而非7轮，该怎么办呢？这时就需要为魔法函数添加参数了，具体如下。</p>
<figure class="highlight plaintext"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">%timeit –n10 out = sess.run(a)</span><br></pre></td></tr></table></figure>
<p>需要注意的是，参数选项“-n10”中的“-n”和“10”中间并没有空格。图1-29列出了如此多魔法函数，我们怎么才能知道某个魔法函数的具体用法呢？最简单的办法就是在Jupyter中创建一个新的单元格，然后输入该魔法函数，最后追加一个问号（?），注意函数名和问号之间没有空格，如下所示。</p>
<figure class="highlight plaintext"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">%timeit?</span><br></pre></td></tr></table></figure>
<p>然后按Ctrl+Enter组合键运行这个单元格。<br>
假设某个代码块正好就是一个算法的实现，现在我们想对整个代码块的运行进行计时，而不是对某一行代码的运行计时，该如何做呢？<br>
这时，就需要利用%timeit的姊妹函数—块魔法函数%%timeit，即timeit前面有两个%。如前所述，它的适用范围是整个代码块，因此通常会把这个魔法函数放在某个代码块的首行。</p>
<h4 id="writefile函数">%%writefile函数</h4>
<p>我们知道，Jupyter是一个集才华（代码编写）和颜值（图文文档显示）于一身的编程工具。但有时，如在生产环境中，我们还想把调试好的Python代码单独拎出来操作，这时该怎么办呢？<br>
当然，我们可以采用复制的方式，把Jupyter代码块中的代码一块一块地复制到一个IDE（如Spyder）的新建文件中，然后保存为我们所需要的Python源文件。<br>
但实际上，Jupyter已经替我们考虑到这个需求。魔法函数%%writefile就是做这项工作的。见名知意，这个魔法函数的主要功能是把整个代码块中的Python代码保存为一个.py文件。<br>
通过该魔法函数前端的两个百分号（%%）就可以看出，这是一个作用域为整块代码的魔法函数。%%writefile后面跟的参数是一个具体的Python文件名。假设我们想保存图1-22所示的代码块中的Python代码，就可以在代码块的首行添加如下代码。</p>
<figure class="highlight plaintext"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">%%writefile myFirstBook.py # 这里，myFirstBook.py是任意你想保存的文件名</span><br></pre></td></tr></table></figure>
<p>然后，按Ctrl+Enter组合键运行单元格，这个myFirstBook.py源文件就默认保存在与*.ipynb（Jupyter文件）相同的路径下。当然，我们可以为其添加一个非默认路径，如%%writefile/Users/yhilly/ Documents/myFirstBook.py.<br>
在这种情况下，单元格执行之后，myFirstBook.py就被存储在“/Users/yhilly/Documents/”路径下。读者也可以单击Jupyter的菜单栏【File】-&gt;【Download as】，有多种文件格式可供选择，可将编写好的代码保存到本地。</p>
<h4 id="其他常用的魔法函数">其他常用的魔法函数</h4>
<p>下面我们列出其他常用的魔法函数，如表1-1所示，更多详细使用方法，可参阅IPython的官方文档。<br>
表1-1　其他常用的魔法函数<br>
<img src="https://imgs-1302910354.cos.ap-shanghai.myqcloud.com/images/jupyter_notebook%E7%9A%84%E4%BD%BF%E7%94%A8.-fig-1.png" alt="jupyter_notebook的使用.-fig-1.png"></p>
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href="#%E5%88%A9%E7%94%A8conda%E5%88%9B%E5%BB%BA%E4%BA%86%E8%99%9A%E6%8B%9F%E7%8E%AF%E5%A2%83%EF%BC%8C%E4%BD%86%E6%98%AF%E5%90%AF%E5%8A%A8jupyter-notebook%E4%B9%8B%E5%90%8E%E5%8D%B4%E6%89%BE%E4%B8%8D%E5%88%B0%E8%99%9A%E6%8B%9F%E7%8E%AF%E5%A2%83%E3%80%82%E5%AE%9E%E9%99%85%E4%B8%8A%E6%98%AF%E7%94%B1%E4%BA%8E%E5%9C%A8%E8%99%9A%E6%8B%9F%E7%8E%AF%E5%A2%83%E4%B8%8B%E7%BC%BA%E5%B0%91kernel-json%E6%96%87%E4%BB%B6%E3%80%82"><span class="toc-text">利用conda创建了虚拟环境，但是启动jupyter notebook之后却找不到虚拟环境。实际上是由于在虚拟环境下缺少kernel.json文件。</span></a></li></ol></li><li class="toc-item toc-level-3"><a class="toc-link" href="#jupyter-%E5%A2%9E%E5%8A%A0%E5%92%8C%E5%88%A0%E9%99%A4kernel"><span class="toc-text">jupyter 增加和删除kernel</span></a></li><li class="toc-item toc-level-3"><a class="toc-link" href="#%E6%94%B9%E6%8C%87%E5%AE%9A%E5%B7%A5%E4%BD%9C%E7%9B%AE%E5%BD%95"><span class="toc-text">改指定工作目录</span></a></li><li class="toc-item toc-level-3"><a class="toc-link" href="#%E9%AD%94%E6%B3%95%E5%87%BD%E6%95%B0"><span class="toc-text">魔法函数</span></a><ol class="toc-child"><li class="toc-item toc-level-4"><a class="toc-link" href="#lsmagic%E5%87%BD%E6%95%B0"><span class="toc-text">%lsmagic函数</span></a></li><li class="toc-item toc-level-4"><a class="toc-link" href="#matplotlib-inline%E5%87%BD%E6%95%B0"><span class="toc-text">%matplotlib inline函数</span></a></li><li class="toc-item toc-level-4"><a class="toc-link" href="#timeit%E5%87%BD%E6%95%B0"><span class="toc-text">%timeit函数</span></a></li><li class="toc-item toc-level-4"><a class="toc-link" href="#writefile%E5%87%BD%E6%95%B0"><span class="toc-text">%%writefile函数</span></a></li><li class="toc-item toc-level-4"><a class="toc-link" href="#%E5%85%B6%E4%BB%96%E5%B8%B8%E7%94%A8%E7%9A%84%E9%AD%94%E6%B3%95%E5%87%BD%E6%95%B0"><span class="toc-text">其他常用的魔法函数</span></a></li></ol></li></ol></div></div><div class="card-widget card-recent-post"><div class="item-headline"><i class="fas fa-history"></i><span>最新文章</span></div><div class="aside-list"><div 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