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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>3.1. Python解释器</h1><div class="tutorial-body"><p>由于整个Python语言从规范到解释器都是开源的，所以理论上，只要水平够高，任何人都可以编写Python解释器来执行Python代码（当然难度很大）。事实上，确实存在多种Python解释器。</p>
<h3>CPython</h3>
<p>当我们从<a href="https://www.python.org/" target="_blank">Python官方网站</a>下载并安装好Python 3.x后，我们就直接获得了一个官方版本的解释器：CPython。这个解释器是用C语言开发的，所以叫CPython。在命令行下运行<code>python</code>就是启动CPython解释器。</p>
<p>CPython是使用最广的Python解释器。教程的所有代码也都在CPython下执行。</p>
<h3>IPython</h3>
<p>IPython是基于CPython之上的一个交互式解释器，也就是说，IPython只是在交互方式上有所增强，但是执行Python代码的功能和CPython是完全一样的。</p>
<p>CPython用<code>>>></code>作为提示符，而IPython用<code>In [序号]:</code>作为提示符。</p>
<h3>PyPy</h3>
<p>PyPy是另一个Python解释器，它的目标是执行速度。PyPy采用<a href="http://en.wikipedia.org/wiki/Just-in-time_compilation" target="_blank">JIT技术</a>，对Python代码进行动态编译（注意不是解释），所以可以显著提高Python代码的执行速度。</p>
<p>绝大部分Python代码都可以在PyPy下运行，但是PyPy和CPython有一些是不同的，这就导致相同的Python代码在两种解释器下执行可能会有不同的结果。如果你的代码要放到PyPy下执行，就需要了解<a href="http://pypy.readthedocs.org/en/latest/cpython_differences.html" target="_blank">PyPy和CPython的不同点</a>。</p>
<h3>Jython</h3>
<p>Jython是运行在Java平台上的Python解释器，可以直接把Python代码编译成Java字节码执行。</p>
<h3>IronPython</h3>
<p>IronPython和Jython类似，只不过IronPython是运行在微软.Net平台上的Python解释器，可以直接把Python代码编译成.Net的字节码。</p>
<h3>小结</h3>
<p>Python的解释器很多，但使用最广泛的还是CPython。如果要和Java或.Net平台交互，最好的办法不是用Jython或IronPython，而是通过网络调用来交互，确保各程序之间的独立性。</p>
<p>本教程的所有代码只确保在CPython 3.x版本下运行。请务必在本地安装CPython（也就是从Python官方网站下载的安装程序）。</p>
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