最常用的情况下,我理解,比如
<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">5</span><span class="p">):</span> <span class="k">print</span> <span class="n">i</span>
回复内容:
关键词:迭代器简单来说,for in 语句是一个语法糖,具体是这样的:
- 调用一个对象的 __iter__ 方法,方法会返回一个迭代器,所谓迭代器就是实现了 __next__ 方法的对象,如果一个对象本身就实现了 __next__(Python 2 中是直接 “next” 方法,没有下划线) ,可以直接返回自身。
- 调用迭代器的 __next__ 返回迭代器中的“下一个”元素,比如说第一次调用会返回 0,第二次会返回 1,如此这般。
- 最后没有元素了,迭代器抛出一个异常来表明自己没有元素了。for 语句会捕获这个异常并停下来。

另外,还有一个销魂的东西叫做生成器,演示一下如何优雅地斐波那契:
(此后的代码为了简洁我都用 Python 3 来写,用 Python 2 能运行但是性能糟糕。)
<span class="k">def</span> <span class="nf">fib</span><span class="p">(</span><span class="n">n</span><span class="p">):</span>
<span class="n">a</span> <span class="o">=</span> <span class="mi">0</span>
<span class="n">b</span> <span class="o">=</span> <span class="mi">1</span>
<span class="k">for</span> <span class="n">_</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">n</span><span class="p">):</span>
<span class="n">a</span><span class="p">,</span> <span class="n">b</span> <span class="o">=</span> <span class="n">b</span><span class="p">,</span> <span class="n">a</span><span class="o">+</span><span class="n">b</span>
<span class="k">yield</span> <span class="n">a</span>
谢邀。刚看到问题以为楼主要问in是什么意思。这个for实际上就是迭代,使用的是迭代器(Iterator)。
<span class="c"># 以下代码在Python 2中运行</span>
<span class="k">for</span> <span class="n">row</span> <span class="ow">in</span> <span class="n">f</span><span class="p">:</span>
<span class="k">print</span> <span class="n">row</span>
<span class="c"># 完全等价于</span>
<span class="n">itr</span> <span class="o">=</span> <span class="n">f</span><span class="o">.</span><span class="n">__iter__</span><span class="p">()</span> <span class="c"># 获得新的迭代器</span>
<span class="k">while</span> <span class="bp">True</span><span class="p">:</span>
<span class="k">try</span><span class="p">:</span>
<span class="n">row</span> <span class="o">=</span> <span class="n">itr</span><span class="o">.</span><span class="n">next</span><span class="p">()</span>
<span class="k">except</span> <span class="ne">StopIteration</span><span class="p">:</span>
<span class="k">break</span>
<span class="k">print</span> <span class="n">row</span>
迭代器。将

用dis转成虚拟机的指令

in 关键字实现了一套python中的遍历协议.
- 协议A: __iter__ + next
循环时, 程序先使用__iter__ (相当于iter(instance))获取具有next方法的对象, 然后通过其返回的对象, 不断调用其next方法, 直到StopIteration错误抛出.
<span class="k">class</span> <span class="nc">A</span><span class="p">:</span>
<span class="k">def</span> <span class="nf">__iter__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="bp">self</span><span class="o">.</span><span class="n">limit</span> <span class="o">=</span> <span class="mi">4</span>
<span class="bp">self</span><span class="o">.</span><span class="n">times</span> <span class="o">=</span> <span class="mi">0</span>
<span class="bp">self</span><span class="o">.</span><span class="n">init</span> <span class="o">=</span> <span class="mi">1</span>
<span class="k">return</span> <span class="bp">self</span>
<span class="k">def</span> <span class="nf">next</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">times</span> <span class="o">>=</span> <span class="bp">self</span><span class="o">.</span><span class="n">limit</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">StopIteration</span><span class="p">()</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">x</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">init</span>
<span class="bp">self</span><span class="o">.</span><span class="n">times</span> <span class="o">+=</span> <span class="mi">1</span>
<span class="bp">self</span><span class="o">.</span><span class="n">init</span> <span class="o">+=</span> <span class="mi">1</span>
<span class="k">return</span> <span class="n">x</span>
<span class="k">print</span> <span class="s">'A>>>>>>'</span>
<span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">A</span><span class="p">():</span>
<span class="k">print</span> <span class="n">x</span>

Is it enough to learn Python for two hours a day? It depends on your goals and learning methods. 1) Develop a clear learning plan, 2) Select appropriate learning resources and methods, 3) Practice and review and consolidate hands-on practice and review and consolidate, and you can gradually master the basic knowledge and advanced functions of Python during this period.

Key applications of Python in web development include the use of Django and Flask frameworks, API development, data analysis and visualization, machine learning and AI, and performance optimization. 1. Django and Flask framework: Django is suitable for rapid development of complex applications, and Flask is suitable for small or highly customized projects. 2. API development: Use Flask or DjangoRESTFramework to build RESTfulAPI. 3. Data analysis and visualization: Use Python to process data and display it through the web interface. 4. Machine Learning and AI: Python is used to build intelligent web applications. 5. Performance optimization: optimized through asynchronous programming, caching and code

Python is better than C in development efficiency, but C is higher in execution performance. 1. Python's concise syntax and rich libraries improve development efficiency. 2.C's compilation-type characteristics and hardware control improve execution performance. When making a choice, you need to weigh the development speed and execution efficiency based on project needs.

Python's real-world applications include data analytics, web development, artificial intelligence and automation. 1) In data analysis, Python uses Pandas and Matplotlib to process and visualize data. 2) In web development, Django and Flask frameworks simplify the creation of web applications. 3) In the field of artificial intelligence, TensorFlow and PyTorch are used to build and train models. 4) In terms of automation, Python scripts can be used for tasks such as copying files.

Python is widely used in data science, web development and automation scripting fields. 1) In data science, Python simplifies data processing and analysis through libraries such as NumPy and Pandas. 2) In web development, the Django and Flask frameworks enable developers to quickly build applications. 3) In automated scripts, Python's simplicity and standard library make it ideal.

Python's flexibility is reflected in multi-paradigm support and dynamic type systems, while ease of use comes from a simple syntax and rich standard library. 1. Flexibility: Supports object-oriented, functional and procedural programming, and dynamic type systems improve development efficiency. 2. Ease of use: The grammar is close to natural language, the standard library covers a wide range of functions, and simplifies the development process.

Python is highly favored for its simplicity and power, suitable for all needs from beginners to advanced developers. Its versatility is reflected in: 1) Easy to learn and use, simple syntax; 2) Rich libraries and frameworks, such as NumPy, Pandas, etc.; 3) Cross-platform support, which can be run on a variety of operating systems; 4) Suitable for scripting and automation tasks to improve work efficiency.

Yes, learn Python in two hours a day. 1. Develop a reasonable study plan, 2. Select the right learning resources, 3. Consolidate the knowledge learned through practice. These steps can help you master Python in a short time.


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