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class="container" id="main-content" tabindex="-1"><div class="post"><article class="post-block h-entry"><div class="post-meta p-author h-card visually-hidden"><img class="author-avatar u-photo" src="../favicon.png" alt="Cytrogen"><span class="p-name">Cytrogen</span><a class="u-url" href="https://cytrogen.icu">https://cytrogen.icu</a></div><a class="post-permalink u-url u-uid visually-hidden" href="https://cytrogen.icu/posts/224a.html">永久链接</a><div class="p-summary visually-hidden"><p>近期在学习 IBM 全栈应用开发微学士课程，故此记录学习笔记。</p></div><div class="visually-hidden"><a class="p-category" href="../categories/%E7%BC%96%E7%A8%8B%E7%AC%94%E8%AE%B0/">编程笔记</a><a class="p-category" href="../tags/Python/">Python</a><a class="p-category" href="../tags/IBM/">IBM</a></div><h1 class="post-title p-name">IBM 全栈开发【8】：用于人工智能和开发项目的 Python</h1><div class="post-info"><time class="post-date dt-published" datetime="2024-05-19T22:49:00.000Z">5/19/2024</time><time class="dt-updated visually-hidden" datetime="2026-02-09T17:16:54.721Z"></time></div><div class="post-content e-content"><html><head></head><body><p>近期在学习 IBM 全栈应用开发微学士课程，故此记录学习笔记。</p>
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<h1 id="1-python编码实践和打包概念"><a class="markdownIt-Anchor" href="#1-python编码实践和打包概念"></a> 1. Python 编码实践和打包概念</h1>
<h2 id="11-开发生命周期"><a class="markdownIt-Anchor" href="#11-开发生命周期"></a> 1.1. 开发生命周期</h2>
<p>应用程序开发生命周期分为七个阶段，包括：</p>
<ul>
<li>收集需求： 收集应用程序的用户、业务和技术需求。</li>
<li>分析： 分析需求。</li>
<li>设计： 设计完整的解决方案。</li>
<li>编码和测试： 构建和测试应用程序的不同组件。</li>
<li>用户和系统测试： 用户测试应用程序的可用性，进行系统集成测试和性能测试。</li>
<li>生产： 应用程序可供所有最终用户使用。</li>
<li>维护： 升级或修复任何用户或系统问题。</li>
</ul>
<h2 id="12-pep8"><a class="markdownIt-Anchor" href="#12-pep8"></a> 1.2. PEP8</h2>
<p>PEP8 关于代码可读性的指导原则包括以下内容：</p>
<ul>
<li>缩进四个空格。</li>
<li>空行用于分隔函数和类。</li>
<li>操作符周围和逗号后的空格。</li>
</ul>
<p>PEP8 的编码规范具有一致性和可管理性，其中包括：</p>
<ul>
<li>在函数内添加较大的代码块。</li>
<li>使用带下划线的小写字母命名函数和文件。</li>
<li>使用驼峰大写为类命名。</li>
<li>用大写字母命名常量，单词之间用下划线分隔。</li>
</ul>
<h2 id="13-单元测试"><a class="markdownIt-Anchor" href="#13-单元测试"></a> 1.3. 单元测试</h2>
<p>单元测试是一种验证代码单元是否按设计运行的方法。在与最终代码库集成之前，必须测试每个单元。</p>
<h4 id="131-例子"><a class="markdownIt-Anchor" href="#131-例子"></a> 1.3.1. 例子</h4>
<figure class="highlight python"><table><tbody><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br></pre></td><td class="code"><pre><span class="line"><span class="keyword">def</span> <span class="title function_">add</span>(<span class="params">a,b</span>):</span><br><span class="line"> <span class="keyword">return</span> a + b</span><br><span class="line"></span><br><span class="line"><span class="keyword">def</span> <span class="title function_">substract</span>(<span class="params">a,b</span>):</span><br><span class="line"> <span class="keyword">return</span> a - b</span><br></pre></td></tr></tbody></table></figure>
<figure class="highlight python"><table><tbody><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br></pre></td><td class="code"><pre><span class="line"><span class="keyword">import</span> unittest</span><br><span class="line"><span class="keyword">from</span> math <span class="keyword">import</span> add, substract</span><br><span class="line"></span><br><span class="line"><span class="keyword">class</span> <span class="title class_">TestMain</span>(unittest.TestCase):</span><br><span class="line"> <span class="keyword">def</span> <span class="title function_">test_add</span>(<span class="params">self</span>):</span><br><span class="line"> <span class="variable language_">self</span>.assertEqual(add(<span class="number">6</span>,<span class="number">4</span>),<span class="number">10</span>)</span><br><span class="line"> </span><br><span class="line"> <span class="keyword">def</span> <span class="title function_">test_substract</span>(<span class="params">self</span>):</span><br><span class="line"> <span class="variable language_">self</span>.assertEqual(substract(<span class="number">6</span>,<span class="number">4</span>),<span class="number">3</span>)</span><br></pre></td></tr></tbody></table></figure>
<h2 id="14-创建包"><a class="markdownIt-Anchor" href="#14-创建包"></a> 1.4. 创建包</h2>
<ol>
<li>以软件包名称创建文件夹。</li>
<li>创建一个空的 <code>__init__.py</code> 文件。</li>
<li>创建所需的模块。</li>
<li>在 <code>__init__.py</code> 文件中，添加代码以引用软件包中需要的模块。</li>
</ol>
<p>可以在 Python shell 中通过 bash 终端验证软件包。</p>
<h2 id="15-其他"><a class="markdownIt-Anchor" href="#15-其他"></a> 1.5. 其他</h2>
<p>关于网络应用程序，以下两种说法是正确的：</p>
<blockquote>
<p>所有网络应用程序都是 API。</p>
<p>网络应用支持 CRUD 操作。</p>
</blockquote>
<p>在哪个测试阶段验证应用程序在更大框架内的功能？：</p>
<blockquote>
<p>集成测试。</p>
</blockquote>
<p>PyLint 是一款 Python 静态代码分析工具。</p>
<p>在为一个管理活动的应用程序收集需求时，客户提到项目的目标是提高客户保留率。<br>
<strong>业务需求</strong> 描述了上述情况。</p>
<h1 id="2-使用flask部署网络应用程序"><a class="markdownIt-Anchor" href="#2-使用flask部署网络应用程序"></a> 2. 使用 Flask 部署网络应用程序</h1>
<h2 id="21-flask"><a class="markdownIt-Anchor" href="#21-flask"></a> 2.1. Flask</h2>
<p>Flask 是一个微型框架，只需最少的依赖即可运行。Flask 具有调试服务器、路由、模板和错误处理等功能，可用于构建网站。Flask 可以作为 python 软件包安装。与 Flask 相比，Django 是一个全栈框架。你可以通过实例化 Flask 类来创建服务器。</p>
<p>Flask 为每次客户端调用提供一个请求和一个响应对象。可以从 Flask 请求中获取更多信息，如标题。您可以解析请求对象，获取查询参数、正文和其他参数。您甚至可以在将响应发送回客户端之前，在响应对象上设置状态。</p>
<p>可以使用动态路由创建 RESTful 端点。</p>
<p>HTTP 状态代码有多种类型，分别显示成功、用户错误或服务器错误。Flask 在响应时会隐式返回成功代码 200。您也可以明确提供状态代码。Flask 还提供应用程序级的错误处理程序。</p>
<p>Flask 支持 CRUD。</p>
<p>可以使用 Flask 渲染静态和动态模板。</p>
<h4 id="211-代码案例"><a class="markdownIt-Anchor" href="#211-代码案例"></a> 2.1.1. 代码案例</h4>
<p>实例化 Flask：</p>
<figure class="highlight python"><table><tbody><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br></pre></td><td class="code"><pre><span class="line"><span class="keyword">from</span> flask <span class="keyword">import</span> Flask</span><br><span class="line"></span><br><span class="line">app = Flask(__name__)</span><br></pre></td></tr></tbody></table></figure>
<p><code>@app.route</code> 装饰器：</p>
<figure class="highlight python"><table><tbody><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br></pre></td><td class="code"><pre><span class="line"><span class="meta">@app.route(<span class="params"><span class="string">'/'</span></span>)</span></span><br><span class="line"><span class="keyword">def</span> <span class="title function_">hello_world</span>():</span><br><span class="line"> <span class="keyword">return</span> <span class="string">"<b>My first Flask application in action!</b>"</span></span><br></pre></td></tr></tbody></table></figure>
<p>400 错误：</p>
<figure class="highlight python"><table><tbody><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br></pre></td><td class="code"><pre><span class="line"><span class="meta">@app.route(<span class="params"><span class="string">'/'</span></span>)</span></span><br><span class="line"><span class="keyword">def</span> <span class="title function_">search_response</span>():</span><br><span class="line"> query = request.args.get(<span class="string">'q'</span>)</span><br><span class="line"> <span class="keyword">if</span> <span class="keyword">not</span> query:</span><br><span class="line"> <span class="keyword">return</span> {<span class="string">"error_message"</span>: <span class="string">"Input parameter missing"</span>}, <span class="number">422</span></span><br><span class="line"> resource = fetch_from_database(query)</span><br><span class="line"> <span class="keyword">if</span> resource:</span><br><span class="line"> <span class="keyword">return</span> {<span class="string">"message"</span>: resource}</span><br><span class="line"> <span class="keyword">else</span>:</span><br><span class="line"> <span class="keyword">return</span> {<span class="string">"error_message"</span>: <span class="string">"Resource not found"</span>}, <span class="number">404</span></span><br></pre></td></tr></tbody></table></figure>
<h1 id="3-使用flask创建人工智能应用并进行部署"><a class="markdownIt-Anchor" href="#3-使用flask创建人工智能应用并进行部署"></a> 3. 使用 Flask 创建人工智能应用并进行部署</h1>
<div class="danger">
<p><code>Watson NLP</code> 库被嵌入到实验网页中，外部工具无法访问。</p>
</div>
<h2 id="31-项目概述"><a class="markdownIt-Anchor" href="#31-项目概述"></a> 3.1. 项目概述</h2>
<p>在这个同行评分的毕业设计中，你将扮演一名软件工程师，需要开发一款基于人工智能的网络应用程序。您将分析情景并执行以下任务：</p>
<ol>
<li>克隆项目资源库。</li>
<li>使用 <code>Watson NLP</code> 库创建一个情绪检测应用程序。</li>
<li>格式化应用程序的输出。</li>
<li>打包应用程序。</li>
<li>在应用程序上运行单元测试。</li>
<li>使用 Flask 对应用程序进行网络部署。</li>
<li>纳入错误处理。</li>
<li>运行静态代码分析。</li>
</ol>
<div class="github-card" data-github="ibm-developer-skills-network/oaqjp-final-project-emb-ai" data-width="400" data-height="150" data-theme="default"></div>
<script src="//cdn.jsdelivr.net/github-cards/latest/widget.js"></script>
<p>在这个项目中，您将开发一个集成了 Embeddable Watson 人工智能库的网络应用程序。然后，您将提交相关截图供同行评审。</p>
<h2 id="32-情景"><a class="markdownIt-Anchor" href="#32-情景"></a> 3.2. 情景</h2>
<p>你被一家电子商务公司聘为软件工程师，负责创建一个基于人工智能的网络应用程序，对其特色产品的客户反馈进行分析。为实现这一要求，您将创建一个情感检测系统，处理客户以文本格式提供的反馈，并解读相关的情感表达。</p>
<blockquote>
<p>情感检测扩展了情感分析的概念，从语句中提取更细微的情感，如喜悦、悲伤、愤怒等，而不是情感分析所提供的简单极性。这使得情感检测成为一个非常重要的研究分支，企业将此类系统广泛用于基于人工智能的推荐系统、自动聊天机器人等。</p>
</blockquote>
<h4 id="321-详情"><a class="markdownIt-Anchor" href="#321-详情"></a> 3.2.1. 详情</h4>
<p><code>Watson NLP</code> 库是预装在 Cloud IDE 框架中的可嵌入库。因此，无需将它们导入到你的代码中。你只需向库中的正确函数发送 post 请求，然后接收输出。</p>
<p>这些可嵌入的人工智能库基于流行的人工智能模型，提供了各种基于 NLP 和语音的功能。</p>
<p>使用 <code>Watson NLP</code> 库的 <code>Emotion Predict</code> 方法。访问该功能的 URL、Headers 和 Input json 格式如下。</p>
<figure class="highlight plaintext"><table><tbody><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br></pre></td><td class="code"><pre><span class="line">URL: 'https://sn-watson-emotion.labs.skills.network/v1/watson.runtime.nlp.v1/NlpService/EmotionPredict'</span><br><span class="line">Headers: {"grpc-metadata-mm-model-id": "emotion_aggregated-workflow_lang_en_stock"}</span><br><span class="line">Input json: { "raw_document": { "text": text_to_analyse } }</span><br></pre></td></tr></tbody></table></figure>
<blockquote>
<p><code>text_to_analyze</code> 被用作一个变量，用于保存需要分析的实际书面文本。</p>
</blockquote>
<ol>
<li>
<p>在项目根目录创建 <code>emotion_detection.py</code> 文件。</p>
</li>
<li>
<p>创建 <code>emotion_detector</code> 方法用于运行情感检测。</p>
<ul>
<li>用于分析的文本会被存储在 <code>text_to_analyze</code> 变量中，并会被作为参数传入该方法内。</li>
</ul>
<figure class="highlight python"><table><tbody><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br></pre></td><td class="code"><pre><span class="line"><span class="keyword">import</span> requests</span><br><span class="line"> </span><br><span class="line"><span class="keyword">def</span> <span class="title function_">emotion_detector</span>(<span class="params">text_to_analyse: <span class="built_in">str</span></span>):</span><br><span class="line">URL = <span class="string">'https://sn-watson-emotion.labs.skills.network/v1/watson.runtime.nlp.v1/NlpService/EmotionPredict'</span></span><br><span class="line">Headers = { <span class="string">"grpc-metadata-mm-model-id"</span>: <span class="string">"emotion_aggregated-workflow_lang_en_stock"</span> }</span><br><span class="line">Input_Json = { <span class="string">"raw_document"</span>: { <span class="string">"text"</span>: text_to_analyse } }</span><br><span class="line">response = requests.post(url=URL, json=Input_Json, headers=Headers)</span><br><span class="line"><span class="keyword">return</span> response.json()</span><br></pre></td></tr></tbody></table></figure>
<p>返回的内容：</p>
<figure class="highlight json"><table><tbody><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br><span class="line">15</span><br><span class="line">16</span><br><span class="line">17</span><br><span class="line">18</span><br><span class="line">19</span><br><span class="line">20</span><br><span class="line">21</span><br><span class="line">22</span><br><span class="line">23</span><br><span class="line">24</span><br><span class="line">25</span><br><span class="line">26</span><br><span class="line">27</span><br><span class="line">28</span><br><span class="line">29</span><br><span class="line">30</span><br><span class="line">31</span><br><span class="line">32</span><br><span class="line">33</span><br><span class="line">34</span><br></pre></td><td class="code"><pre><span class="line"><span class="punctuation">{</span></span><br><span class="line"> <span class="attr">"emotionPredictions"</span><span class="punctuation">:</span> <span class="punctuation">[</span></span><br><span class="line"> <span class="punctuation">{</span></span><br><span class="line"> <span class="attr">"emotion"</span><span class="punctuation">:</span> <span class="punctuation">{</span></span><br><span class="line"> <span class="attr">"anger"</span><span class="punctuation">:</span> <span class="number">0.0132405795</span><span class="punctuation">,</span></span><br><span class="line"> <span class="attr">"disgust"</span><span class="punctuation">:</span> <span class="number">0.0020517302</span><span class="punctuation">,</span></span><br><span class="line"> <span class="attr">"fear"</span><span class="punctuation">:</span> <span class="number">0.009090992</span><span class="punctuation">,</span></span><br><span class="line"> <span class="attr">"joy"</span><span class="punctuation">:</span> <span class="number">0.9699522</span><span class="punctuation">,</span></span><br><span class="line"> <span class="attr">"sadness"</span><span class="punctuation">:</span> <span class="number">0.054984167</span></span><br><span class="line"> <span class="punctuation">}</span><span class="punctuation">,</span></span><br><span class="line"> <span class="attr">"target"</span><span class="punctuation">:</span> <span class="string">""</span><span class="punctuation">,</span></span><br><span class="line"> <span class="attr">"emotionMentions"</span><span class="punctuation">:</span> <span class="punctuation">[</span></span><br><span class="line"> <span class="punctuation">{</span></span><br><span class="line"> <span class="attr">"span"</span><span class="punctuation">:</span> <span class="punctuation">{</span></span><br><span class="line"> <span class="attr">"begin"</span><span class="punctuation">:</span> <span class="number">0</span><span class="punctuation">,</span></span><br><span class="line"> <span class="attr">"end"</span><span class="punctuation">:</span> <span class="number">26</span><span class="punctuation">,</span></span><br><span class="line"> <span class="attr">"text"</span><span class="punctuation">:</span> <span class="string">"i love this new technology"</span></span><br><span class="line"> <span class="punctuation">}</span><span class="punctuation">,</span></span><br><span class="line"> <span class="attr">"emotion"</span><span class="punctuation">:</span> <span class="punctuation">{</span></span><br><span class="line"> <span class="attr">"anger"</span><span class="punctuation">:</span> <span class="number">0.0132405795</span><span class="punctuation">,</span></span><br><span class="line"> <span class="attr">"disgust"</span><span class="punctuation">:</span> <span class="number">0.0020517302</span><span class="punctuation">,</span></span><br><span class="line"> <span class="attr">"fear"</span><span class="punctuation">:</span> <span class="number">0.009090992</span><span class="punctuation">,</span></span><br><span class="line"> <span class="attr">"joy"</span><span class="punctuation">:</span> <span class="number">0.9699522</span><span class="punctuation">,</span></span><br><span class="line"> <span class="attr">"sadness"</span><span class="punctuation">:</span> <span class="number">0.054984167</span></span><br><span class="line"> <span class="punctuation">}</span></span><br><span class="line"> <span class="punctuation">}</span></span><br><span class="line"> <span class="punctuation">]</span></span><br><span class="line"> <span class="punctuation">}</span></span><br><span class="line"> <span class="punctuation">]</span><span class="punctuation">,</span></span><br><span class="line"> <span class="attr">"producerId"</span><span class="punctuation">:</span> <span class="punctuation">{</span></span><br><span class="line"> <span class="attr">"name"</span><span class="punctuation">:</span> <span class="string">"Ensemble Aggregated Emotion Workflow"</span><span class="punctuation">,</span> </span><br><span class="line"> <span class="attr">"version"</span><span class="punctuation">:</span> <span class="string">"0.0.1"</span></span><br><span class="line"> <span class="punctuation">}</span></span><br><span class="line"><span class="punctuation">}</span></span><br></pre></td></tr></tbody></table></figure>
</li>
<li>
<p>调整输出，使其返回以下格式的内容：</p>
<figure class="highlight json"><table><tbody><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br></pre></td><td class="code"><pre><span class="line"><span class="punctuation">{</span></span><br><span class="line"> <span class="attr">"anger"</span><span class="punctuation">:</span> anger_score<span class="punctuation">,</span></span><br><span class="line"> <span class="attr">"disgust"</span><span class="punctuation">:</span> disgust_score<span class="punctuation">,</span></span><br><span class="line"> <span class="attr">"fear"</span><span class="punctuation">:</span> fear_score<span class="punctuation">,</span></span><br><span class="line"> <span class="attr">"joy"</span><span class="punctuation">:</span> joy_score<span class="punctuation">,</span></span><br><span class="line"> <span class="attr">"sadness"</span><span class="punctuation">:</span> sadness_score<span class="punctuation">,</span></span><br><span class="line"> <span class="attr">"dominant_emotion"</span><span class="punctuation">:</span> <span class="string">"<name of dominant emotion>"</span></span><br><span class="line"><span class="punctuation">}</span></span><br></pre></td></tr></tbody></table></figure>
<figure class="highlight python"><table><tbody><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br></pre></td><td class="code"><pre><span class="line"><span class="keyword">def</span> <span class="title function_">emotion_detector</span>(<span class="params">text_to_analyse: <span class="built_in">str</span></span>):</span><br><span class="line"> URL = <span class="string">'https://sn-watson-emotion.labs.skills.network/v1/watson.runtime.nlp.v1/NlpService/EmotionPredict'</span></span><br><span class="line"> Headers = { <span class="string">"grpc-metadata-mm-model-id"</span>: <span class="string">"emotion_aggregated-workflow_lang_en_stock"</span> }</span><br><span class="line"> Input_Json = { <span class="string">"raw_document"</span>: { <span class="string">"text"</span>: text_to_analyse } }</span><br><span class="line"> response = requests.post(url=URL, json=Input_Json, headers=Headers)</span><br><span class="line"> emotions = response.json()[<span class="string">'emotionPredictions'</span>][<span class="number">0</span>][<span class="string">'emotion'</span>]</span><br><span class="line"> items = emotions.items()</span><br><span class="line"> max_item = <span class="built_in">max</span>(items, key=<span class="keyword">lambda</span> x: x[<span class="number">1</span>])</span><br><span class="line"> emotions[<span class="string">'dominant_emotion'</span>] = max_item[<span class="number">0</span>]</span><br><span class="line"> <span class="keyword">return</span> emotions</span><br></pre></td></tr></tbody></table></figure>
</li>
<li>
<p>创建 <code>EmotionDetection</code> Python 包。</p>
<ol>
<li>创建文件夹，命名为 <code>EmotionDetection</code>。</li>
<li>创建 <code>__init__.py</code> 文件。</li>
<li>在包的根目录下创建 <code>emotion_detector.py</code> 文件，其中包含我们之前创建的 <code>emotion_detector</code> 函数。</li>
</ol>
</li>
<li>
<p>在应用程序上运行单元测试。</p>
<ol>
<li>创建新文件 <code>test_emotion_detection.py</code>，调用包中的函数，并针对以下语句和主要情绪进行测试：
<table>
<thead>
<tr>
<th>语句</th>
<th>主要情绪</th>
</tr>
</thead>
<tbody>
<tr>
<td>I am glad this happened</td>
<td>joy</td>
</tr>
<tr>
<td>I am really mad about this</td>
<td>anger</td>
</tr>
<tr>
<td>I feel disgusted just hearing about this</td>
<td>disgust</td>
</tr>
<tr>
<td>I am so sad about this</td>
<td>sadness</td>
</tr>
<tr>
<td>I am really afraid that this will happen</td>
<td>fear</td>
</tr>
</tbody>
</table>
<figure class="highlight python"><table><tbody><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br><span class="line">15</span><br><span class="line">16</span><br><span class="line">17</span><br><span class="line">18</span><br></pre></td><td class="code"><pre><span class="line"><span class="keyword">import</span> pytest</span><br><span class="line"><span class="keyword">from</span> EmotionDetection <span class="keyword">import</span> emotion_detector</span><br><span class="line"></span><br><span class="line"><span class="keyword">def</span> <span class="title function_">test_emotion_detector</span>():</span><br><span class="line"> test_cases = [</span><br><span class="line"> (<span class="string">"I am glad this happened"</span>, <span class="string">"joy"</span>),</span><br><span class="line"> (<span class="string">"I am really mad about this"</span>, <span class="string">"anger"</span>),</span><br><span class="line"> (<span class="string">"I feel disgusted just hearing about this"</span>, <span class="string">"disgust"</span>),</span><br><span class="line"> (<span class="string">"I am so sad about this"</span>, <span class="string">"sadness"</span>),</span><br><span class="line"> (<span class="string">"I am really afraid that this will happen"</span>, <span class="string">"fear"</span>),</span><br><span class="line"> ]</span><br><span class="line"></span><br><span class="line"> <span class="keyword">for</span> text, expected_emotion <span class="keyword">in</span> test_cases:</span><br><span class="line"> result = emotion_detector(text)</span><br><span class="line"> <span class="keyword">assert</span> result[<span class="string">'dominant_emotion'</span>] == expected_emotion, <span class="string">f"For text: <span class="subst">{text}</span>, expected: <span class="subst">{expected_emotion}</span>, but got: <span class="subst">{result[<span class="string">'dominant_emotion'</span>]}</span>"</span></span><br><span class="line"></span><br><span class="line"><span class="keyword">if</span> __name__ == <span class="string">"__main__"</span>:</span><br><span class="line"> pytest.main()</span><br></pre></td></tr></tbody></table></figure>
</li>
<li>检查单元测试输出，验证单元测试是否通过。<figure class="highlight bash"><table><tbody><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">python3.11 test_emotion_detection.py</span><br></pre></td></tr></tbody></table></figure>
</li>
</ol>
</li>
</ol>
<p>使用 Flask 进行应用程序的网络部署：</p>
<div class="danger">
<p>注意：模板文件夹中的 <code>index.html</code> 文件和静态文件夹中的 <code>mywebscript.js</code> 文件已作为仓库的一部分提供。本项目无需对这些文件进行改动。</p>
</div>
<ol>
<li>在项目根目录下创建 <code>server.py</code>。确保应用程序调用函数的 Flask 装饰器是 <code>\emotionDetector</code>。客户要求以下面示例中的格式显示输出结果（假设是对 "I love my life" 这句话进行评价）：<figure class="highlight json"><table><tbody><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br></pre></td><td class="code"><pre><span class="line"><span class="punctuation">{</span></span><br><span class="line"> <span class="attr">"anger"</span><span class="punctuation">:</span> <span class="number">0.006274985</span><span class="punctuation">,</span></span><br><span class="line"> <span class="attr">"disgust"</span><span class="punctuation">:</span> <span class="number">0.0025598293</span><span class="punctuation">,</span></span><br><span class="line"> <span class="attr">"fear"</span><span class="punctuation">:</span> <span class="number">0.009251528</span><span class="punctuation">,</span></span><br><span class="line"> <span class="attr">"joy"</span><span class="punctuation">:</span> <span class="number">0.9680386</span><span class="punctuation">,</span></span><br><span class="line"> <span class="attr">"sadness"</span><span class="punctuation">:</span> <span class="number">0.049744144</span><span class="punctuation">,</span></span><br><span class="line"> <span class="attr">"dominant_emotion"</span><span class="punctuation">:</span><span class="string">"joy"</span></span><br><span class="line"><span class="punctuation">}</span></span><br></pre></td></tr></tbody></table></figure>
响应应当被格式化为：<figure class="highlight plaintext"><table><tbody><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">For the given statement, the system response is 'anger': 0.006274985, 'disgust': 0.0025598293, 'fear': 0.009251528, 'joy': 0.9680386 and 'sadness': 0.049744144. The dominant emotion is joy.</span><br></pre></td></tr></tbody></table></figure>
应用程序需要部署在 <code>localhost:5000</code> 上。</li>
<li>在函数 <code>emotion_detector</code> 中加入错误处理功能，以管理用户的空白条目，即在没有任何输入的情况下运行应用程序。
<ul>
<li>访问服务器响应的 <code>status_code</code> 属性，以正确显示空白条目的系统响应。</li>
<li>对于 <code>status_code = 400</code>，函数将返回相同的字典，但所有键的值均为 <code>None</code>。</li>
</ul>
</li>
<li>修改 <code>server.py</code>，在 <code>dominant_emotion</code> 为 <code>None</code> 时加入错误处理。在这种情况下，响应应显示 <code>Invalid text! Please try again!.</code>。</li>
</ol>
<p><code>EmotionDetection/__init__.py</code>：</p>
<figure class="highlight python"><table><tbody><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br><span class="line">15</span><br><span class="line">16</span><br><span class="line">17</span><br><span class="line">18</span><br></pre></td><td class="code"><pre><span class="line"><span class="keyword">import</span> requests</span><br><span class="line"></span><br><span class="line"><span class="keyword">def</span> <span class="title function_">emotion_detector</span>(<span class="params">text_to_analyse: <span class="built_in">str</span></span>):</span><br><span class="line"> <span class="keyword">if</span> <span class="keyword">not</span> text_to_analyse:</span><br><span class="line"> <span class="keyword">return</span> {<span class="string">'anger'</span>: <span class="literal">None</span>, <span class="string">'disgust'</span>: <span class="literal">None</span>, <span class="string">'fear'</span>: <span class="literal">None</span>, <span class="string">'joy'</span>: <span class="literal">None</span>, <span class="string">'sadness'</span>: <span class="literal">None</span>, <span class="string">'dominant_emotion'</span>: <span class="literal">None</span>}</span><br><span class="line"> </span><br><span class="line"> URL = <span class="string">'https://sn-watson-emotion.labs.skills.network/v1/watson.runtime.nlp.v1/NlpService/EmotionPredict'</span></span><br><span class="line"> Headers = { <span class="string">"grpc-metadata-mm-model-id"</span>: <span class="string">"emotion_aggregated-workflow_lang_en_stock"</span> }</span><br><span class="line"> Input_Json = { <span class="string">"raw_document"</span>: { <span class="string">"text"</span>: text_to_analyse } }</span><br><span class="line"> response = requests.post(url=URL, json=Input_Json, headers=Headers)</span><br><span class="line"> <span class="keyword">if</span> response.status_code == <span class="number">400</span>:</span><br><span class="line"> <span class="keyword">return</span> {<span class="string">'anger'</span>: <span class="literal">None</span>, <span class="string">'disgust'</span>: <span class="literal">None</span>, <span class="string">'fear'</span>: <span class="literal">None</span>, <span class="string">'joy'</span>: <span class="literal">None</span>, <span class="string">'sadness'</span>: <span class="literal">None</span>, <span class="string">'dominant_emotion'</span>: <span class="literal">None</span>}</span><br><span class="line"></span><br><span class="line"> emotions = response.json()[<span class="string">'emotionPredictions'</span>][<span class="number">0</span>][<span class="string">'emotion'</span>]</span><br><span class="line"> items = emotions.items()</span><br><span class="line"> max_item = <span class="built_in">max</span>(items, key=<span class="keyword">lambda</span> x: x[<span class="number">1</span>])</span><br><span class="line"> emotions[<span class="string">'dominant_emotion'</span>] = max_item[<span class="number">0</span>]</span><br><span class="line"> <span class="keyword">return</span> emotions</span><br></pre></td></tr></tbody></table></figure>
<p><code>server.py</code>：</p>
<figure class="highlight python"><table><tbody><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br><span class="line">15</span><br><span class="line">16</span><br><span class="line">17</span><br><span class="line">18</span><br><span class="line">19</span><br><span class="line">20</span><br><span class="line">21</span><br><span class="line">22</span><br><span class="line">23</span><br><span class="line">24</span><br><span class="line">25</span><br><span class="line">26</span><br><span class="line">27</span><br><span class="line">28</span><br><span class="line">29</span><br><span class="line">30</span><br><span class="line">31</span><br><span class="line">32</span><br><span class="line">33</span><br><span class="line">34</span><br><span class="line">35</span><br><span class="line">36</span><br><span class="line">37</span><br><span class="line">38</span><br></pre></td><td class="code"><pre><span class="line"><span class="string">"""</span></span><br><span class="line"><span class="string">This module defines a Flask application that provides an emotion detection API.</span></span><br><span class="line"><span class="string">"""</span></span><br><span class="line"></span><br><span class="line"><span class="keyword">from</span> flask <span class="keyword">import</span> Flask, request, render_template</span><br><span class="line"><span class="keyword">from</span> EmotionDetection <span class="keyword">import</span> emotion_detector</span><br><span class="line"></span><br><span class="line">app = Flask(__name__)</span><br><span class="line"></span><br><span class="line"><span class="meta">@app.route(<span class="params"><span class="string">'/emotionDetector'</span></span>)</span></span><br><span class="line"><span class="keyword">def</span> <span class="title function_">handle_emotion_detector</span>():</span><br><span class="line"> <span class="string">"""</span></span><br><span class="line"><span class="string"> This function handles GET requests to the /emotionDetector route. It</span></span><br><span class="line"><span class="string"> expects a textToAnalyze arg that contains the text to analyze. It returns</span></span><br><span class="line"><span class="string"> a string with all predicted emotions.</span></span><br><span class="line"><span class="string"> """</span></span><br><span class="line"> predicted_emotions = emotion_detector(request.args.get(<span class="string">'textToAnalyze'</span>))</span><br><span class="line"> <span class="keyword">if</span> predicted_emotions[<span class="string">'dominant_emotion'</span>] <span class="keyword">is</span> <span class="literal">None</span>:</span><br><span class="line"> <span class="keyword">return</span> <span class="string">'Invalid text! Please try again!'</span></span><br><span class="line"></span><br><span class="line"> response_text = (<span class="string">"For the given statement, "</span> +</span><br><span class="line"> <span class="string">f"the system response is 'anger': <span class="subst">{predicted_emotions[<span class="string">'anger'</span>]}</span>, "</span></span><br><span class="line"> <span class="string">f"'disgust': <span class="subst">{predicted_emotions[<span class="string">'disgust'</span>]}</span>, "</span> +</span><br><span class="line"> <span class="string">f"'fear': <span class="subst">{predicted_emotions[<span class="string">'fear'</span>]}</span>, "</span></span><br><span class="line"> <span class="string">f"'joy': <span class="subst">{predicted_emotions[<span class="string">'joy'</span>]}</span> "</span> +</span><br><span class="line"> <span class="string">f"and 'sadness': <span class="subst">{predicted_emotions[<span class="string">'sadness'</span>]}</span>. "</span></span><br><span class="line"> <span class="string">f"The dominant emotion is <span class="subst">{predicted_emotions[<span class="string">'dominant_emotion'</span>]}</span>."</span>)</span><br><span class="line"> <span class="keyword">return</span> response_text</span><br><span class="line"></span><br><span class="line"><span class="meta">@app.route(<span class="params"><span class="string">"/"</span></span>)</span></span><br><span class="line"><span class="keyword">def</span> <span class="title function_">render_index_page</span>():</span><br><span class="line"> <span class="string">"""</span></span><br><span class="line"><span class="string"> This function renders index.html to the / route.</span></span><br><span class="line"><span class="string"> """</span></span><br><span class="line"> <span class="keyword">return</span> render_template(<span class="string">'index.html'</span>)</span><br><span class="line"></span><br><span class="line"><span class="keyword">if</span> __name__ == <span class="string">'__main__'</span>:</span><br><span class="line"> app.run(host=<span class="string">'localhost'</span>, port=<span class="number">5000</span>)</span><br></pre></td></tr></tbody></table></figure>
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