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<div id="toc"><ul><li><a class="toc-href" href="#ch1-10-ipython-essentials" title="ch1: 10 IPython essentials">ch1: 10 IPython essentials</a><ul><li><a class="toc-href" href="#magic-commands" title="magic commands">magic commands</a></li><li><a class="toc-href" href="#ipython-notebook" title="IPython Notebook">IPython Notebook</a></li><li><a class="toc-href" href="#customizing-ipython" title="customizing IPython">customizing IPython</a></li></ul></li><li><a class="toc-href" href="#ch2-interavtive-work-with-ipython_1" title="ch2: Interavtive Work with IPython">ch2: Interavtive Work with IPython</a><ul><li><a class="toc-href" href="#navigating-the-file-system" title="navigating the file system">navigating the file system</a></li><li><a class="toc-href" href="#accessing-system-shell-with-ipython" title="Accessing system shell with IPython">Accessing system shell with IPython</a></li><li><a class="toc-href" href="#the-extended-python-console" title="The Extended Python Console">The Extended Python Console</a><ul><li><a class="toc-href" href="#debug" title="debug">debug</a></li><li><a class="toc-href" href="#benchmarkingji-zhun-ce-shi" title='benchmarking("基准测试")'>benchmarking("基准测试")</a></li></ul></li><li><a class="toc-href" href="#using-the-ipython-notebook_1" title="Using the IPython notebook">Using the IPython notebook</a><ul><li><a class="toc-href" href="#notebookde-yi-xie-kuai-jie-jian" title="notebook的一些快捷键">notebook的一些快捷键</a></li></ul></li></ul></li></ul></div>
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<p><a href="http://www.packtpub.com/learning-ipython-for-interactive-computing-and-data-visualization/book">Learning IPython for Interactive Computing and Data Visualization</a>这本书的前两章的笔记, 这本书还被放在了IPython官网上, 虽然只有一百页多一点点, 但是讲的内容却很丰富, 介绍了IPython, numpy, pandas以及并行计算等方面. </p>
<p>(在开始系统学IPython之前简单使用过IPython, 那时候我还是更喜欢bpython的代码提示功能...)</p>
<h1 id="ch1-10-ipython-essentials">ch1: 10 IPython essentials</h1>
<ul>
<li>在任何变量后面加问号<code>?</code>或者双问号<code>??</code>, 将会输出详细的信息(按<code>q</code>退出), <code>??</code>的信息更加详细些</li>
<li>Tab Completion: 没啥好说的 没有bpython做的好 也凑合吧...</li>
<li><code>_, __, ___</code>保存最近三次的输出; <code>_i, __i, ___i</code>保存最近三次的输入(作为字符串保存)</li>
</ul>
<h2 id="magic-commands">magic commands</h2>
<ul>
<li>在IPython里面可以使用一些标准unix命令, 比如<code>cd</code>, <code>pwd,ls</code>等... </li>
</ul>
<p>这个太好了 否则还要<code>import os</code>, 然后再什么<code>os.chdir('...')</code></p>
<ul>
<li>其实这些unix命令是IPython的<strong>magic commands</strong>, 这些magic commands一般用<code>%</code>作为前缀.</li>
</ul>
<p>但是由于默认IPython开启了<strong>automagic system</strong>, 上面那些命令可以不用加前缀了(或者使用Tab自动给加上前缀)</p>
<ul>
<li><code>%run</code> 命令, 运行一个.py脚本, 但是好处是, 与运行完了以后这个.py文件里的变量都可以在Ipython里继续访问</li>
<li><code>%timeit</code> 命令, 可以用来做基准测试(<em>benchmarking</em>), 测试一个命令(或者一个函数)的运行时间</li>
</ul>
<p>ex. </p>
<div class="highlight"><pre><span class="code-line"><span></span><span class="nf">%timeit</span> <span class="p">[</span><span class="n">x</span><span class="o">*</span><span class="n">x</span> <span class="k">for</span> <span class="n">x</span> <span class="n">in</span> <span class="n">range</span><span class="p">(</span><span class="mi">1000</span><span class="p">)]</span></span>
<span class="code-line"><span class="mi">10000</span> <span class="n">loops</span><span class="p">,</span> <span class="n">best</span> <span class="n">of</span> <span class="mi">3</span><span class="o">:</span> <span class="mf">56.5</span> <span class="err">µ</span><span class="n">s</span> <span class="n">per</span> <span class="n">loop</span></span>
<span class="code-line"></span>
<span class="code-line"><span class="nf">%timeit</span> <span class="p">[</span><span class="n">x</span><span class="o">*</span><span class="n">x</span> <span class="k">for</span> <span class="n">x</span> <span class="n">in</span> <span class="n">xrange</span><span class="p">(</span><span class="mi">1000</span><span class="p">)]</span></span>
<span class="code-line"><span class="mi">10000</span> <span class="n">loops</span><span class="p">,</span> <span class="n">best</span> <span class="n">of</span> <span class="mi">3</span><span class="o">:</span> <span class="mf">51.7</span> <span class="err">µ</span><span class="n">s</span> <span class="n">per</span> <span class="n">loop</span></span>
</pre></div>
<ul>
<li><code>%debug</code> 命令: 当有exception的时候, 在console里输入<code>%debug</code>即可打开debugger. </li>
</ul>
<p>在debugger里, 输入<code>u,d</code>(up, down)查看stack, 输入<code>q</code>退出debugger</p>
<div class="highlight"><pre><span class="code-line"><span></span><span class="nf">%debug</span></span>
<span class="code-line"><span class="o">></span> <span class="o"><</span><span class="n">ipython</span><span class="o">-</span><span class="n">input</span><span class="o">-</span><span class="mi">34</span><span class="o">-</span><span class="mi">17</span><span class="n">c374156862</span><span class="o">></span><span class="p">(</span><span class="mi">2</span><span class="p">)</span><span class="o"><</span><span class="n">module</span><span class="o">></span><span class="p">()</span></span>
<span class="code-line"> <span class="mi">1</span> <span class="k">if</span> <span class="mi">1</span><span class="o"><</span><span class="mi">2</span><span class="o">:</span></span>
<span class="code-line"><span class="o">----></span> <span class="mi">2</span> <span class="n">raise</span> <span class="n">Exception</span></span>
<span class="code-line"> <span class="mi">3</span> </span>
<span class="code-line"><span class="n">ipdb</span><span class="o">></span> <span class="n">u</span></span>
<span class="code-line"><span class="o">***</span> <span class="n">Oldest</span> <span class="n">frame</span></span>
<span class="code-line"><span class="n">ipdb</span><span class="o">></span> <span class="n">d</span></span>
<span class="code-line"><span class="o">***</span> <span class="n">Newest</span> <span class="n">frame</span></span>
<span class="code-line"><span class="n">ipdb</span><span class="o">></span> <span class="n">q</span></span>
</pre></div>
<p>使用%pdb开启自动pdb模式</p>
<blockquote>
<p>%pdb<br/>
Automatic pdb calling has been turned ON</p>
</blockquote>
<ul>
<li>
<p><code>%pylab</code> 命令, 大杀器, 看一下都import了什么:</p>
<p>%pylab makes the following imports::
import numpy
import matplotlib
from matplotlib import pylab, mlab, pyplot
np = numpy
plt = pyplot
from IPython.display import display
from IPython.core.pylabtools import figsize, getfigs
from pylab import *
from numpy import *</p>
</li>
</ul>
<p>画图的时候可以不用非要加<code>plt.</code>前缀了, 直接<code>plot()</code>即可. 图像化出来的时候, 画图窗口并没有block, 可以动态(<em>interactively</em>)画图.</p>
<p>另外, qtconsole和notebook一样, 指定了<code>inline</code>选项以后可以直接在窗口里画图:</p>
<p><img alt="" class="img-responsive" src="../images/IPython上手学习笔记/pasted_image004.png"/></p>
<p>后来发现inline的图片貌似不能放大看, 所以有时候还是单独一个窗口比较好, 换到非inline模式只需要再输入以下%pylab, 加上选项qt:
<code>%pylab qt</code></p>
<h2 id="ipython-notebook">IPython Notebook</h2>
<p><strong>(重头戏)</strong></p>
<p>这个可以在浏览器里(!!)使用IPython, 并且可以使用多行编辑后再一并执行. </p>
<blockquote>
<p><em>The Notebook brings the functionality of IPython into the browser for multiline textediting features, interactive session reproducibility, and so on.</em></p>
</blockquote>
<p>在shell/cmd窗口里启动ipython的时候加上notebook:</p>
<p><code>$ipython notebook</code></p>
<p>看到浏览器打开了, 很神奇: </p>
<p><img alt="" class="img-responsive" src="../images/IPython上手学习笔记/pasted_image.png"/></p>
<p>新建一个notebook, 用用看: </p>
<p><img alt="" class="img-responsive" src="../images/IPython上手学习笔记/pasted_image001.png"/></p>
<p>使用的过程中渐渐理解了为什么书里说可以用来做"<em>multiline textediting features, interactive session reproducibility</em>"... 因为这不只是个编程的东西, 还可以作为一个笔记本 — 而且是一个交互式的笔记本! </p>
<p>(<em>注: 更多关于notebook的介绍在下面第二章的内容里.</em>)</p>
<ul>
<li>代码,或者段落, 按照cell(格子)进行组织, 一个cell里面的内容可以是code, 但是也同样可以是markdown的段落, 或者是一个标题(heading).</li>
<li>在一个代码的cell里, 写入多行代码, 就像在编辑器里写python程序一样, 按回车只会换行, 不会运行程序.</li>
</ul>
<p>写了一段程序代码以后, 按<code>ctrl+Enter</code>运行程序, 运行结果也是一个作为cell.
(<strong>注</strong>: 在qtconsole里面相反, 如果要输入多行程序的话, 按<code>Ctrl+Enter</code>换行(按一一次ctrl+enter即可进入多行编辑模式), 写了几行代码以后要运行的话, 就按两次回车, 或者按<code>Shift+Enter</code>)</p>
<ul>
<li>...还有好多快捷键, 按Esc以后再按h就可以看到... 这个还分编辑模式和命令模式呢... 真不能小看了IPython了!</li>
</ul>
<p><img alt="" class="img-responsive" src="../images/IPython上手学习笔记/pasted_image002.png"/></p>
<h2 id="customizing-ipython">customizing IPython</h2>
<p>保存自己的IPython配置文件, 只需要在shell/cmd里输入ipython profile create<code>,</code> 配置文件存储在 <code>~.ipython</code> 或者 <code>~/.config/ipython</code>目录里.</p>
<h1 id="ch2-interavtive-work-with-ipython_1">ch2: Interavtive Work with IPython</h1>
<p>IPython可以实现<strong>shell(OS)和python的交互</strong>. 这样做一些unix shell的操作的时候可以不必退出console了.</p>
<h2 id="navigating-the-file-system">navigating the file system</h2>
<p>例子: 完成下载压缩包, 解压缩, 以及打开解压后的文件这些操作...</p>
<p>在py变量前面加入$, 可以把这个变量共享给OS或者magic command:</p>
<div class="highlight"><pre><span class="code-line"><span></span><span class="n">folder</span><span class="o">=</span><span class="err">'</span><span class="n">data</span><span class="err">'</span></span>
<span class="code-line"><span class="nf">%mkdir</span> <span class="n">$folder</span></span>
</pre></div>
<p>这样就在当前目录下建立一个'data'文件夹 — 这可比py的命令好记多了啊... <code>%mkdir</code>的原理其实是给了shell命令一个别名(<code>alias</code>).</p>
<p>然后, <code>%bookmark</code>可以把当前的目录加入收藏夹 下次cd的时候方便直接跳到这里来:</p>
<p>ex.
<code>%bookmark bm</code>
那么以后可以直接用 <code>cd bm</code> 跳到这个目录下. <code>%bookmark -l</code> 可以列出收藏夹的目录内容.</p>
<p>然后发现原来IPython连文件名都是可以提示的啊!... </p>
<div class="highlight"><pre><span class="code-line"><span></span><span class="err">with open('0<TAB></span></span>
<span class="code-line"><span class="err">0.circles 0.edges</span></span>
</pre></div>
<h2 id="accessing-system-shell-with-ipython">Accessing system shell with IPython</h2>
<p>在IPython里调用系统的命令, 不用再使用<code>sys.exec('...')</code>之类冗长的方式了, 只需要在系统的命令前面加上一个感叹号<code>!</code>即可...</p>
<p>shell返回的结果可以作为一个string的列表保存在一个python variable里.</p>
<p>ex. </p>
<div class="highlight"><pre><span class="code-line"><span></span><span class="err">In [2]: files = !ls -1 -S | grep edges</span></span>
<span class="code-line"><span class="err">In [3]: files</span></span>
<span class="code-line"><span class="err">Out[3]: ['1912.edges',</span></span>
<span class="code-line"><span class="err"> '107.edges',</span></span>
<span class="code-line"><span class="err"> [...]</span></span>
<span class="code-line"><span class="err"> '3980.edges']</span></span>
</pre></div>
<p>(当然 上面这一行只能在unix系统下运行, 因为Windows的cmd没有ls 和 grep命令)</p>
<p>还可以把一条比较长的命令作为alias保存起来, 用<code>%alias</code>命令... (这个应该一般用不到)</p>
<p><code>%alias largest ls -1sSh | grep %s</code></p>
<h2 id="the-extended-python-console">The Extended Python Console</h2>
<ul>
<li><code>%history</code> 或者 <code>%hist</code> , 显示之前的记录, 有一些参数可用...</li>
<li><code>%store</code> 把python变量的内容保存下来, 以后的session可以用</li>
<li><code>%paste</code> 导入并执行剪贴板里面的内容</li>
<li><code>%run</code> 之前讲过了, 运行py文件, 运行后py文件里的变量可以在console里访问</li>
<li><code>%edit</code> 打开系统的文件编辑器, 并且在关闭这个编辑器时自动运行程序</li>
<li>介绍了一个包 networkx, 可以用来分析复杂网络(graph)的....</li>
</ul>
<h3 id="debug">debug</h3>
<ul>
<li>debug加入断点: <code>%run -d -b29 script.py</code> 运行script.py 并且在29行的时候暂停, 当输入<code>c</code>的时候再继续运行.</li>
<li>一些pdb(debugging环境)里常用的命令:<ul>
<li><code>u/d</code> for going up/down into the call stack</li>
<li><code>s</code> to step into the next statement</li>
<li><code>n</code> to continue execution until the next line in the current function</li>
<li><code>r</code> to continue execution until the current function returns</li>
<li><code>c</code> to continue execution until the next breakpoint or exception</li>
<li><code>p</code> to evaluate and print any expression</li>
<li><code>a</code> to obtain the arguments of the current functions</li>
<li>The <code>!</code> prefix to execute any Python command within the debugger</li>
</ul>
</li>
</ul>
<h3 id="benchmarkingji-zhun-ce-shi">benchmarking("基准测试")</h3>
<ul>
<li><code>%timeit fun()</code> 测试一个<strong>函数</strong>的执行速度</li>
<li><code>%run -t</code>和<code>%timeit</code>效果类似, 作用是测试一个py脚本<strong>文件</strong>的执行速度</li>
<li>更精细的运行时间测试, 可以用<strong>profile模块</strong></li>
</ul>
<blockquote>
<p><em>The profiler outputs details about calls of every Python function used directly or indirectly in this script.</em></p>
</blockquote>
<p>@@...好高级!!! 这样的话就更容易发现程序运行的瓶颈在哪里了!
方法是使用 <code>%run -p</code> 或者 <code>%prun</code></p>
<h2 id="using-the-ipython-notebook_1">Using the IPython notebook</h2>
<p>这个notebook的功能实在是很NB... 不仅可以加入代码/markdown段落, 还可以加入图片和视频... notebook的格式为.ipybn文件, 用JSON存储数据.</p>
<ul>
<li>
<p>输入 <code>ipython notebook</code>(或者在ipython里输入<code>!ipython notebook</code>)以后, 会在8888端口建立一个web server, 访问 <a href="http://localhost:8888/">http://localhost:8888/</a> 就可以看到上面的那个截图, 或者称之为<strong>notebook dashboard.</strong></p>
</li>
<li>
<p><strong>cell magics</strong>的作用域是整个cell(多行), 而magic command的作用域是一行, cell magics的前缀是两个百分号<code>%%</code>.</p>
</li>
<li>
<p>从一个py文件直接建立一个notebook, 只需要把文件拖入dashboard即可, 然后notebook也可以保存为文件. </p>
</li>
<li>
<p>编辑了Markdown以后, 还是<code>Ctrl+Enter/Shift+Enter</code> , 即可成为格式化的文本, 再双击就可以编辑!!</p>
</li>
<li>
<p>让plot的图片直接嵌入在notebook里面: 使用<code>ipython notebook --pylab inline</code>, 或者在notebook里面输入<code>%pylab inline</code></p>
</li>
</ul>
<p><img alt="" class="img-responsive" src="../images/IPython上手学习笔记/pasted_image003.png"/></p>
<h3 id="notebookde-yi-xie-kuai-jie-jian">notebook的一些快捷键</h3>
<ul>
<li>Esc从编辑模式(edit mode)退出到命令模式(command mode)</li>
<li>Enter从命令模式到编辑模式</li>
</ul>
<p><strong>(编辑模式下)</strong></p>
<ul>
<li>ctrl+Enter: 运行程序/markdown代码</li>
<li>shift+Enter: 运行程序, 并自动跳到下一个cell</li>
<li>alt+Enter: 运行程序, 并自动在后面新建一个cell在</li>
</ul>
<p><strong>(命令模式下)</strong></p>
<ul>
<li>c: 复制一个cell</li>
<li>x: 剪切一个cell</li>
<li>v: 粘贴cell</li>
<li>a: 在当前cell上面(<strong>a</strong>bove)新建一个cell</li>
<li>b: 在当前cell下面(<strong>b</strong>elow)新建一个cell</li>
<li>m: 让当前cell变成一个markdown的cell</li>
<li>y: 让当前cell变成code的cell</li>
<li>1,2,3...: n级标题</li>
<li>j,k: 上下移动选中的cell, vim风格..</li>
<li>dd(d按两下): 删除一个cell(vim 风格...)</li>
</ul>
<p>......爽到爆!!</p>
</div>
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<div id="toc"><ul><li><a class="toc-href" href="#ch1-10-ipython-essentials" title="ch1: 10 IPython essentials">ch1: 10 IPython essentials</a><ul><li><a class="toc-href" href="#magic-commands" title="magic commands">magic commands</a></li><li><a class="toc-href" href="#ipython-notebook" title="IPython Notebook">IPython Notebook</a></li><li><a class="toc-href" href="#customizing-ipython" title="customizing IPython">customizing IPython</a></li></ul></li><li><a class="toc-href" href="#ch2-interavtive-work-with-ipython_1" title="ch2: Interavtive Work with IPython">ch2: Interavtive Work with IPython</a><ul><li><a class="toc-href" href="#navigating-the-file-system" title="navigating the file system">navigating the file system</a></li><li><a class="toc-href" href="#accessing-system-shell-with-ipython" title="Accessing system shell with IPython">Accessing system shell with IPython</a></li><li><a class="toc-href" href="#the-extended-python-console" title="The Extended Python Console">The Extended Python Console</a><ul><li><a class="toc-href" href="#debug" title="debug">debug</a></li><li><a class="toc-href" href="#benchmarkingji-zhun-ce-shi" title='benchmarking("基准测试")'>benchmarking("基准测试")</a></li></ul></li><li><a class="toc-href" href="#using-the-ipython-notebook_1" title="Using the IPython notebook">Using the IPython notebook</a><ul><li><a class="toc-href" href="#notebookde-yi-xie-kuai-jie-jian" title="notebook的一些快捷键">notebook的一些快捷键</a></li></ul></li></ul></li></ul></div>
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