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<div class="tutorial-container" style="max-width: 960px; margin: 80px auto 40px; padding: 0 20px;"><div class="tutorial-sidebar"><h3>目录</h3><a href="0.html">1. 简介</a><a href="1.html">2. Python历史</a><a href="2.html">3. 安装Python</a><a href="3.html">3.1. Python解释器</a><a href="4.html">4. 第一个Python程序</a><a href="5.html">4.1. 使用文本编辑器</a><a href="6.html">4.2. 输入和输出</a><a href="7.html">5. Python基础</a><a href="8.html">5.1. 数据类型和变量</a><a href="9.html">5.2. 字符串和编码</a><a href="10.html">5.3. 使用list和tuple</a><a href="11.html">5.4. 条件判断</a><a href="12.html">5.5. 模式匹配</a><a href="13.html">5.6. 循环</a><a href="14.html">5.7. 使用dict和set</a><a href="15.html">6. 函数</a><a href="16.html">6.1. 调用函数</a><a href="17.html">6.2. 定义函数</a><a href="18.html">6.3. 函数的参数</a><a href="19.html">6.4. 递归函数</a><a href="20.html">7. 高级特性</a><a href="21.html">7.1. 切片</a><a href="22.html">7.2. 迭代</a><a href="23.html">7.3. 列表生成式</a><a href="24.html">7.4. 生成器</a><a href="25.html">7.5. 迭代器</a><a href="26.html">8. 函数式编程</a><a href="27.html">8.1. 高阶函数</a><a href="28.html">8.1.1. map/reduce</a><a href="29.html">8.1.2. filter</a><a href="30.html">8.1.3. sorted</a><a href="31.html">8.2. 返回函数</a><a href="32.html">8.3. 匿名函数</a><a href="33.html">8.4. 装饰器</a><a href="34.html">8.5. 偏函数</a><a href="35.html">9. 模块</a><a href="36.html">9.1. 使用模块</a><a href="37.html">9.2. 安装第三方模块</a><a href="38.html">10. 面向对象编程</a><a href="39.html">10.1. 类和实例</a><a href="40.html">10.2. 访问限制</a><a href="41.html">10.3. 继承和多态</a><a href="42.html">10.4. 获取对象信息</a><a href="43.html">10.5. 实例属性和类属性</a><a href="44.html">11. 面向对象高级编程</a><a href="45.html">11.1. 使用__slots__</a><a href="46.html">11.2. 使用@property</a><a href="47.html">11.3. 多重继承</a><a href="48.html">11.4. 定制类</a><a href="49.html">11.5. 使用枚举类</a><a href="50.html">11.6. 使用元类</a><a href="51.html">12. 错误、调试和测试</a><a href="52.html">12.1. 错误处理</a><a href="53.html">12.2. 调试</a><a href="54.html">12.3. 单元测试</a><a href="55.html">12.4. 文档测试</a><a href="56.html">13. IO编程</a><a href="57.html">13.1. 文件读写</a><a href="58.html">13.2. StringIO和BytesIO</a><a href="59.html">13.3. 操作文件和目录</a><a href="60.html">13.4. 序列化</a><a href="61.html">14. 进程和线程</a><a href="62.html">14.1. 多进程</a><a href="63.html">14.2. 多线程</a><a href="64.html">14.3. ThreadLocal</a><a href="65.html">14.4. 进程 vs. 线程</a><a href="66.html">14.5. 分布式进程</a><a href="67.html">15. 正则表达式</a><a href="68.html">16. 常用内建模块</a><a href="69.html">16.1. datetime</a><a href="70.html">16.2. collections</a><a href="71.html">16.3. argparse</a><a href="72.html">16.4. base64</a><a href="73.html">16.5. struct</a><a href="74.html">16.6. hashlib</a><a href="75.html">16.7. hmac</a><a href="76.html">16.8. itertools</a><a href="77.html">16.9. contextlib</a><a href="78.html">16.10. urllib</a><a href="79.html">16.11. XML</a><a href="80.html">16.12. HTMLParser</a><a href="81.html">16.13. venv</a><a href="82.html">17. 常用第三方模块</a><a href="83.html">17.1. Pillow</a><a href="84.html">17.2. requests</a><a href="85.html">17.3. chardet</a><a href="86.html">17.4. psutil</a><a href="87.html">18. 图形界面</a><a href="88.html">18.1. 海龟绘图</a><a href="89.html">19. 网络编程</a><a href="90.html">19.1. TCP/IP简介</a><a href="91.html">19.2. TCP编程</a><a href="92.html">19.3. UDP编程</a><a href="93.html">20. 电子邮件</a><a href="94.html">20.1. SMTP发送邮件</a><a href="95.html">20.2. POP3收取邮件</a><a href="96.html">21. 访问数据库</a><a href="97.html">21.1. 使用SQLite</a><a href="98.html">21.2. 使用MySQL</a><a href="99.html">21.3. 使用SQLAlchemy</a><a href="100.html">22. Web开发</a><a href="101.html">22.1. HTTP协议简介</a><a href="102.html">22.2. HTML简介</a><a href="103.html">22.3. WSGI接口</a><a href="104.html">22.4. 使用Web框架</a><a href="105.html">22.5. 使用模板</a><a href="106.html">23. 异步IO</a><a href="107.html">23.1. 协程</a><a href="108.html">23.2. 使用asyncio</a><a href="109.html">23.3. 使用aiohttp</a><a href="110.html">24. FAQ</a><a href="111.html">25. 期末总结</a></div><div class="tutorial-content"><h1>12.2. 调试</h1><div class="tutorial-body"><p>第一种方法简单直接粗暴有效，就是用<code>print()</code>把可能有问题的变量打印出来看看：</p>
<pre class="hljs"><code class="language-python"><span class="hljs-keyword">def</span> <span class="hljs-title function_">foo</span>(<span class="hljs-params">s</span>):
n = <span class="hljs-built_in">int</span>(s)
<span class="hljs-built_in">print</span>(<span class="hljs-string">'>>> n = %d'</span> % n)
<span class="hljs-keyword">return</span> <span class="hljs-number">10</span> / n
<span class="hljs-keyword">def</span> <span class="hljs-title function_">main</span>():
foo(<span class="hljs-string">'0'</span>)
main()
</code></pre>
<p>执行后在输出中查找打印的变量值：</p>
<pre class="hljs"><code class="language-plain">$ python err.py
>>> n = 0
Traceback (most recent call last):
...
ZeroDivisionError: integer division or modulo by zero
</code></pre>
<p>用<code>print()</code>最大的坏处是将来还得删掉它，想想程序里到处都是<code>print()</code>，运行结果也会包含很多垃圾信息。所以，我们又有第二种方法。</p>
<h3>断言</h3>
<p>凡是用<code>print()</code>来辅助查看的地方，都可以用断言（assert）来替代：</p>
<pre class="hljs"><code class="language-python"><span class="hljs-keyword">def</span> <span class="hljs-title function_">foo</span>(<span class="hljs-params">s</span>):
n = <span class="hljs-built_in">int</span>(s)
<span class="hljs-keyword">assert</span> n != <span class="hljs-number">0</span>, <span class="hljs-string">'n is zero!'</span>
<span class="hljs-keyword">return</span> <span class="hljs-number">10</span> / n
<span class="hljs-keyword">def</span> <span class="hljs-title function_">main</span>():
foo(<span class="hljs-string">'0'</span>)
</code></pre>
<p><code>assert</code>的意思是，表达式<code>n != 0</code>应该是<code>True</code>，否则，根据程序运行的逻辑，后面的代码肯定会出错。</p>
<p>如果断言失败，<code>assert</code>语句本身就会抛出<code>AssertionError</code>：</p>
<pre class="hljs"><code class="language-plain">$ python err.py
Traceback (most recent call last):
...
AssertionError: n is zero!
</code></pre>
<p>程序中如果到处充斥着<code>assert</code>，和<code>print()</code>相比也好不到哪去。不过，启动Python解释器时可以用<code>-O</code>参数来关闭<code>assert</code>：</p>
<pre class="hljs"><code class="language-plain">$ python -O err.py
Traceback (most recent call last):
...
ZeroDivisionError: division by zero
</code></pre>
<div class="alert alert-note">
<p><svg xmlns="http://www.w3.org/2000/svg" fill="none" viewBox="0 0 24 24" stroke-width="1.5" stroke="currentColor"><path stroke-linecap="round" stroke-linejoin="round" d="m11.25 11.25.041-.02a.75.75 0 0 1 1.063.852l-.708 2.836a.75.75 0 0 0 1.063.853l.041-.021M21 12a9 9 0 1 1-18 0 9 9 0 0 1 18 0Zm-9-3.75h.008v.008H12V8.25Z" /></svg> 注意<span></span></p>
<p>断言的开关“-O”是英文大写字母O，不是数字0。
</p></div>
<p>关闭后，你可以把所有的<code>assert</code>语句当成<code>pass</code>来看。</p>
<h3>logging</h3>
<p>把<code>print()</code>替换为<code>logging</code>是第3种方式，和<code>assert</code>比，<code>logging</code>不会抛出错误，而且可以输出到文件：</p>
<pre class="hljs"><code class="language-python"><span class="hljs-keyword">import</span> logging
s = <span class="hljs-string">'0'</span>
n = <span class="hljs-built_in">int</span>(s)
logging.info(<span class="hljs-string">'n = %d'</span> % n)
<span class="hljs-built_in">print</span>(<span class="hljs-number">10</span> / n)
</code></pre>
<p><code>logging.info()</code>就可以输出一段文本。运行，发现除了<code>ZeroDivisionError</code>，没有任何信息。怎么回事？</p>
<p>别急，在<code>import logging</code>之后添加一行配置再试试：</p>
<pre class="hljs"><code class="language-python"><span class="hljs-keyword">import</span> logging
logging.basicConfig(level=logging.INFO)
</code></pre>
<p>看到输出了：</p>
<pre class="hljs"><code class="language-plain">$ python err.py
INFO:root:n = 0
Traceback (most recent call last):
File "err.py", line 8, in <module>
print(10 / n)
ZeroDivisionError: division by zero
</code></pre>
<p>这就是<code>logging</code>的好处，它允许你指定记录信息的级别，有<code>debug</code>，<code>info</code>，<code>warning</code>，<code>error</code>等几个级别，当我们指定<code>level=INFO</code>时，<code>logging.debug</code>就不起作用了。同理，指定<code>level=WARNING</code>后，<code>debug</code>和<code>info</code>就不起作用了。这样一来，你可以放心地输出不同级别的信息，也不用删除，最后统一控制输出哪个级别的信息。</p>
<p><code>logging</code>的另一个好处是通过简单的配置，一条语句可以同时输出到不同的地方，比如console和文件。</p>
<h3>pdb</h3>
<p>第4种方式是启动Python的调试器pdb，让程序以单步方式运行，可以随时查看运行状态。我们先准备好程序：</p>
<pre class="hljs"><code class="language-python"><span class="hljs-comment"># err.py</span>
s = <span class="hljs-string">'0'</span>
n = <span class="hljs-built_in">int</span>(s)
<span class="hljs-built_in">print</span>(<span class="hljs-number">10</span> / n)
</code></pre>
<p>然后启动：</p>
<pre class="hljs"><code class="language-plain">$ python -m pdb err.py
> /Users/michael/Github/learn-python3/samples/debug/err.py(2)<module>()
-> s = '0'
</code></pre>
<p>以参数<code>-m pdb</code>启动后，pdb定位到下一步要执行的代码<code>-> s = '0'</code>。输入命令<code>l</code>来查看代码：</p>
<pre class="hljs"><code class="language-plain">(Pdb) l
1 # err.py
2 -> s = '0'
3 n = int(s)
4 print(10 / n)
</code></pre>
<p>输入命令<code>n</code>可以单步执行代码：</p>
<pre class="hljs"><code class="language-plain">(Pdb) n
> /Users/michael/Github/learn-python3/samples/debug/err.py(3)<module>()
-> n = int(s)
(Pdb) n
> /Users/michael/Github/learn-python3/samples/debug/err.py(4)<module>()
-> print(10 / n)
</code></pre>
<p>任何时候都可以输入命令<code>p 变量名</code>来查看变量：</p>
<pre class="hljs"><code class="language-plain">(Pdb) p s
'0'
(Pdb) p n
0
</code></pre>
<p>输入命令<code>q</code>结束调试，退出程序：</p>
<pre class="hljs"><code class="language-plain">(Pdb) q
</code></pre>
<p>这种通过pdb在命令行调试的方法理论上是万能的，但实在是太麻烦了，如果有一千行代码，要运行到第999行得敲多少命令啊。还好，我们还有另一种调试方法。</p>
<h3>pdb.set_trace()</h3>
<p>这个方法也是用pdb，但是不需要单步执行，我们只需要<code>import pdb</code>，然后，在可能出错的地方放一个<code>pdb.set_trace()</code>，就可以设置一个断点：</p>
<pre class="hljs"><code class="language-python"><span class="hljs-comment"># err.py</span>
<span class="hljs-keyword">import</span> pdb
s = <span class="hljs-string">'0'</span>
n = <span class="hljs-built_in">int</span>(s)
pdb.set_trace() <span class="hljs-comment"># 运行到这里会自动暂停</span>
<span class="hljs-built_in">print</span>(<span class="hljs-number">10</span> / n)
</code></pre>
<p>运行代码，程序会自动在<code>pdb.set_trace()</code>暂停并进入pdb调试环境，可以用命令<code>p</code>查看变量，或者用命令<code>c</code>继续运行：</p>
<pre class="hljs"><code class="language-plain">$ python err.py
> /Users/michael/Github/learn-python3/samples/debug/err.py(7)<module>()
-> print(10 / n)
(Pdb) p n
0
(Pdb) c
Traceback (most recent call last):
File "err.py", line 7, in <module>
print(10 / n)
ZeroDivisionError: division by zero
</code></pre>
<p>这个方式比直接启动pdb单步调试效率要高很多，但也高不到哪去。</p>
<h3>IDE</h3>
<p>如果要比较爽地设置断点、单步执行，就需要一个支持调试功能的IDE。目前比较好的Python IDE有：</p>
<p>Visual Studio Code：<a href="https://code.visualstudio.com/" target="_blank">https://code.visualstudio.com/</a>，需要安装Python插件。</p>
<p>PyCharm：<a href="http://www.jetbrains.com/pycharm/" target="_blank">http://www.jetbrains.com/pycharm/</a></p>
<p>另外，<a href="http://www.eclipse.org/" target="_blank">Eclipse</a>加上<a href="http://pydev.org/" target="_blank">pydev</a>插件也可以调试Python程序。</p>
<h3>小结</h3>
<p>写程序最痛苦的事情莫过于调试，程序往往会以你意想不到的流程来运行，你期待执行的语句其实根本没有执行，这时候，就需要调试了。</p>
<p>虽然用IDE调试起来比较方便，但是最后你会发现，logging才是终极武器。</p>
<h3>参考源码</h3>
<p><a href="do_assert.py">do_assert.py</a></p>
<p><a href="do_logging.py">do_logging.py</a></p>
<p><a href="do_pdb.py">do_pdb.py</a></p>
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