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atom.xml
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<?xml version="1.0" encoding="utf-8"?>
<feed xmlns="http://www.w3.org/2005/Atom">
<title>Jack博客</title>
<icon>https://www.gravatar.com/avatar/95f3e37cb3152e52109b4fbb1cf72e17</icon>
<subtitle>Jack博客</subtitle>
<link href="https://jackgithubtest.github.io/atom.xml" rel="self"/>
<link href="https://jackgithubtest.github.io/"/>
<updated>2021-11-10T09:54:37.887Z</updated>
<id>https://jackgithubtest.github.io/</id>
<author>
<name>Jack</name>
<email>[email protected]</email>
</author>
<generator uri="https://hexo.io/">Hexo</generator>
<entry>
<title>centos编译安装Git</title>
<link href="https://jackgithubtest.github.io/2021/11/10/centos%E7%BC%96%E8%AF%91%E5%AE%89%E8%A3%85Git/"/>
<id>https://jackgithubtest.github.io/2021/11/10/centos%E7%BC%96%E8%AF%91%E5%AE%89%E8%A3%85Git/</id>
<published>2021-11-10T09:49:42.000Z</published>
<updated>2021-11-10T09:54:37.887Z</updated>
<content type="html"><![CDATA[<p>centos安装Git有两种方式，一种通过源安装，通过如下命今，即可一键安装成功：</p><figure class="highlight shell"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">yum -y install git</span><br></pre></td></tr></table></figure><p>但是通过源安装的Git，目前最高版本是1.7，想要使用更多新功能、更新版本的Git，就只能通过编译安装的方式来进行安装了，下面就来具体介绍这种安装过程。</p><h5 id="1、先安装依赖包"><a href="#1、先安装依赖包" class="headerlink" title="1、先安装依赖包"></a><strong>1、先安装依赖包</strong></h5><figure class="highlight shell"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">yum install curl-devel expat-devel gettext-devel openssl-devel zlib-devel</span><br></pre></td></tr></table></figure><h5 id="2、下载Git源码包，并解压"><a href="#2、下载Git源码包，并解压" class="headerlink" title="2、下载Git源码包，并解压"></a><strong>2、下载Git源码包，并解压</strong></h5><figure class="highlight shell"><table><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">cd /usr/local/src</span><br><span class="line">wget https://github.com/git/git/archive/v1.9.5.tar.gz</span><br><span class="line">tar -zxvf git-1.9.5.tar.gz</span><br></pre></td></tr></table></figure><h5 id="3、编译并安装"><a href="#3、编译并安装" class="headerlink" title="3、编译并安装"></a><strong>3、编译并安装</strong></h5><figure class="highlight shell"><table><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></pre></td><td class="code"><pre><span class="line">cd git-1.9.5</span><br><span class="line">make configure</span><br><span class="line">./configure --prefix=/usr/local/ --with-iconv=/usr/local/libiconv/</span><br><span class="line">make && make install</span><br></pre></td></tr></table></figure><p><strong>4、make过程中可能有如下错误</strong></p><figure class="highlight shell"><table><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></pre></td><td class="code"><pre><span class="line">make configure</span><br><span class="line">GIT_VERSION = 1.9.5</span><br><span class="line"> GEN configure</span><br><span class="line">/bin/sh: autoconf: command not found</span><br><span class="line">make: *** [configure] Error 127</span><br><span class="line"><span class="meta">#</span><span class="bash"> 解决方案</span></span><br><span class="line">yum install install autoconf automake libtool</span><br></pre></td></tr></table></figure><h5 id="5、查看Git版本"><a href="#5、查看Git版本" class="headerlink" title="5、查看Git版本"></a><strong>5、查看Git版本</strong></h5><figure class="highlight shell"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">git --version</span><br></pre></td></tr></table></figure><p><strong>问题</strong></p><figure class="highlight shell"><table><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">Can't locate ExtUtils/MakeMaker.pm in @INC (@INC contains: /usr/local/lib64/perl5 /usr/local/share/perl5 /usr/lib64/perl5/vendor_perl /usr/share/perl5/vendor_perl /usr/lib64/perl5 /usr/share/perl5 .) at Makefile.PL line 3.</span><br><span class="line">BEGIN failed--compilation aborted at Makefile.PL line 3.</span><br><span class="line">make[1]: *** [perl.mak] Error 2</span><br><span class="line">make: *** [perl/perl.mak] Error 2</span><br><span class="line"><span class="meta">#</span><span class="bash"> make可能会有如下报错，不需要管，只需要git --version能显示git版本就是成功</span></span><br></pre></td></tr></table></figure>]]></content>
<summary type="html"><p>centos安装Git有两种方式，一种通过源安装，通过如下命今，即可一键安装成功：</p>
<figure class="highlight shell"><table><tr><td class="gutter"><pre><span class="line">1</sp</summary>
</entry>
<entry>
<title></title>
<link href="https://jackgithubtest.github.io/2021/10/09/guanmai-%E8%87%AA%E5%8A%A8%E5%8C%96%E5%B7%A5%E7%A8%8B%E6%89%80%E9%81%87%E5%88%B0%E7%9A%84%E9%97%AE%E9%A2%98/"/>
<id>https://jackgithubtest.github.io/2021/10/09/guanmai-%E8%87%AA%E5%8A%A8%E5%8C%96%E5%B7%A5%E7%A8%8B%E6%89%80%E9%81%87%E5%88%B0%E7%9A%84%E9%97%AE%E9%A2%98/</id>
<published>2021-10-09T02:32:14.943Z</published>
<updated>2021-10-09T09:02:45.195Z</updated>
<content type="html"><![CDATA[<p>1、参数化</p><p>2、断言</p><p>3、update更新数据</p><p>4、用例关联</p><p>5、cert证书</p><ul><li>cert证书升级，导致无法链接grpc服务</li><li>解决方案：</li></ul>]]></content>
<summary type="html"><p>1、参数化</p>
<p>2、断言</p>
<p>3、update更新数据</p>
<p>4、用例关联</p>
<p>5、cert证书</p>
<ul>
<li>cert证书升级，导致无法链接grpc服务</li>
<li>解决方案：</li>
</ul>
</summary>
</entry>
<entry>
<title>语雀配置钉钉和企业微信webhook</title>
<link href="https://jackgithubtest.github.io/2021/09/30/%E8%AF%AD%E9%9B%80%E9%85%8D%E7%BD%AE%E9%92%89%E9%92%89%E5%92%8C%E4%BC%81%E4%B8%9A%E5%BE%AE%E4%BF%A1webhook/"/>
<id>https://jackgithubtest.github.io/2021/09/30/%E8%AF%AD%E9%9B%80%E9%85%8D%E7%BD%AE%E9%92%89%E9%92%89%E5%92%8C%E4%BC%81%E4%B8%9A%E5%BE%AE%E4%BF%A1webhook/</id>
<published>2021-09-30T02:52:53.000Z</published>
<updated>2021-09-30T03:44:31.065Z</updated>
<content type="html"><![CDATA[<h2 id="语雀如何配置钉钉或者企业微信机器人教程和坑"><a href="#语雀如何配置钉钉或者企业微信机器人教程和坑" class="headerlink" title="语雀如何配置钉钉或者企业微信机器人教程和坑"></a>语雀如何配置钉钉或者企业微信机器人教程和坑</h2><h6 id="1、首先需要钉钉新建一个机器人，钉钉机器人选择关键字选项，不要选择签名选项，不然无法推送"><a href="#1、首先需要钉钉新建一个机器人，钉钉机器人选择关键字选项，不要选择签名选项，不然无法推送" class="headerlink" title="1、首先需要钉钉新建一个机器人，钉钉机器人选择关键字选项，不要选择签名选项，不然无法推送"></a>1、首先需要钉钉新建一个机器人，钉钉机器人选择关键字选项，不要选择签名选项，不然无法推送</h6><h5 id="2、语雀端设置-在知识库-gt-设置-gt-消息推送-gt-添加webhook-钉钉webhook选择钉钉选项，若其他渠道机器人请选择其他渠道，支持企业微信和微信机器人"><a href="#2、语雀端设置-在知识库-gt-设置-gt-消息推送-gt-添加webhook-钉钉webhook选择钉钉选项，若其他渠道机器人请选择其他渠道，支持企业微信和微信机器人" class="headerlink" title="2、语雀端设置 在知识库->设置->消息推送->添加webhook 钉钉webhook选择钉钉选项，若其他渠道机器人请选择其他渠道，支持企业微信和微信机器人"></a>2、语雀端设置 在知识库->设置->消息推送->添加webhook 钉钉webhook选择钉钉选项，若其他渠道机器人请选择其他渠道，支持企业微信和微信机器人</h5><p><img src="https://gitee.com/Jack_Gitee_Code/Ptoho_Iamge/raw/master/image/2021/09/30/70136_image-20210930110153975.png" alt="image-20210930110153975"></p><p><img src="https://gitee.com/Jack_Gitee_Code/Ptoho_Iamge/raw/master/image/2021/09/30/97397_image-20210930110106441.png" alt="image-20210930110106441"></p><p><img src="https://gitee.com/Jack_Gitee_Code/Ptoho_Iamge/raw/master/image/2021/09/30/77290_image-20210930110135762.png" alt="image-20210930110135762"></p><h5 id="3、语雀推送消息到企业微信-配置和钉钉是一致的，如果不知道如何添加企业微信机器人，可以自行百度"><a href="#3、语雀推送消息到企业微信-配置和钉钉是一致的，如果不知道如何添加企业微信机器人，可以自行百度" class="headerlink" title="3、语雀推送消息到企业微信 配置和钉钉是一致的，如果不知道如何添加企业微信机器人，可以自行百度"></a>3、语雀推送消息到企业微信 配置和钉钉是一致的，如果不知道如何添加企业微信机器人，可以自行百度</h5><p><a href="https://zhuanlan.zhihu.com/p/92349571">企业微信机器人的快捷制作 - 知乎 (zhihu.com)</a></p><p>填写机器人名字和webhook地址后，点击添加就ok</p><p><img src="https://gitee.com/Jack_Gitee_Code/Ptoho_Iamge/raw/master/image/2021/09/30/17083_image-20210930110620413.png" alt="image-20210930110620413"></p><h4 id="配置webhook所遇到的坑"><a href="#配置webhook所遇到的坑" class="headerlink" title="配置webhook所遇到的坑"></a>配置webhook所遇到的坑</h4><p>问题：配置了webhook为什么无法推送消息，但是点击测试却能通过消息能发送，但是更新文章或发布文章却无法推送？</p><p>原因：在语雀未发布【开启自动发布】这个功能的时候其实这个问题是不会出现的，但是因为这个功能上线，导致了无法推送消息，仔细看官方的这个功能介绍，找到了这个问题所在，哦原来开启了自动发布功能就不会发送动态或消息</p><p><img src="https://gitee.com/Jack_Gitee_Code/Ptoho_Iamge/raw/master/image/2021/09/30/39682_image-20210930111216521.png" alt="image-20210930111216521"></p><p><img src="https://gitee.com/Jack_Gitee_Code/Ptoho_Iamge/raw/master/image/2021/09/30/49450_image-20210930113854852.png" alt="image-20210930113854852"></p><p><a href="https://www.yuque.com/yuque/blog/nyb4v9">https://www.yuque.com/yuque/blog/nyb4v9</a></p><p>解决方案：关闭开启自动发布的功能，消息推送成功，注：企业微信的webhook点击测试是无反应的，需要自动更新文章或者发布文章触发</p><h4 id="最后效果："><a href="#最后效果：" class="headerlink" title="最后效果："></a>最后效果：</h4><p><img src="https://gitee.com/Jack_Gitee_Code/Ptoho_Iamge/raw/master/image/2021/09/30/42522_image-20210930111321412.png" alt="image-20210930111321412"></p><p><img src="https://gitee.com/Jack_Gitee_Code/Ptoho_Iamge/raw/master/image/2021/09/30/83308_image-20210930111344233.png" alt="image-20210930111344233"></p>]]></content>
<summary type="html"><h2 id="语雀如何配置钉钉或者企业微信机器人教程和坑"><a href="#语雀如何配置钉钉或者企业微信机器人教程和坑" class="headerlink" title="语雀如何配置钉钉或者企业微信机器人教程和坑"></a>语雀如何配置钉钉或者企业微信机器人教程和坑</</summary>
<category term="webhook" scheme="https://jackgithubtest.github.io/tags/webhook/"/>
</entry>
<entry>
<title>自动化多进程下问题</title>
<link href="https://jackgithubtest.github.io/2021/09/27/%E8%87%AA%E5%8A%A8%E5%8C%96%E5%A4%9A%E8%BF%9B%E7%A8%8B%E4%B8%8B%E9%97%AE%E9%A2%98/"/>
<id>https://jackgithubtest.github.io/2021/09/27/%E8%87%AA%E5%8A%A8%E5%8C%96%E5%A4%9A%E8%BF%9B%E7%A8%8B%E4%B8%8B%E9%97%AE%E9%A2%98/</id>
<published>2021-09-27T03:53:30.000Z</published>
<updated>2021-10-09T09:01:46.072Z</updated>
<content type="html"><![CDATA[<p>自动化痛点</p><ul><li>异步接口需要定时获取结果【未想到最优解决方式】</li><li>运行速度慢</li><li>容错性差，维护性差</li><li>不能很好的兼容多进程方式运行</li><li>多进程下运行session块被重复运行，初始化代码被多次初始化覆盖删除，多个session的文件锁</li><li>多进程下api层单例所遇问题</li><li>多进程下token的设计</li><li>多进程下数据共享问题</li></ul><p>解决：</p><p>1、运行速度慢，我们可以采用多进程方式下去执行自动化，有pytest提供的常用插件pytest-xsdit 插件，插件用法就是一条命令这里就不过多解释了</p><figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">pytest -n <span class="number">2</span> <span class="built_in">dir</span></span><br></pre></td></tr></table></figure><p>采用此插件就能很好的解决多进程吗？答案是肯定是不是的：相信大家都知道session是一个进程是一个会话，那多个进程相比是有多个会话了？我们来验证我们的想法</p><p>目录结构为</p><figure class="highlight python"><table><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">comm</span><br><span class="line">__init__.py</span><br><span class="line">testcase</span><br><span class="line">test_*.py</span><br><span class="line">export</span><br><span class="line">allure</span><br><span class="line">html</span><br><span class="line">conftest.py</span><br><span class="line">run.py</span><br></pre></td></tr></table></figure><p>conftest.py</p><p><img src="https://gitee.com/Jack_Gitee_Code/Ptoho_Iamge/raw/master/image/2021/09/27/93034_image-20210927143425947.png" alt="image-20210927143425947"></p><p>pytest-xdist自动分配了四个进程来执行我们的自动化，注：pytest-xdist的auto会根据电脑的内核自动分配进程【明明我的电脑是8核，明天就提刀去联想官方店，希望给我一个完美的解释】</p><p><img src="https://gitee.com/Jack_Gitee_Code/Ptoho_Iamge/raw/master/image/2021/09/27/36702_image-20210927143220236.png" alt="image-20210927143220236"></p><p>由此可见，我们session级别的conftest被执行多次，说明session确实会存在问题，那要如何解决呢？</p><p><img src="https://gitee.com/Jack_Gitee_Code/Ptoho_Iamge/raw/master/image/2021/09/27/70973_image-20210927144512429.png" alt="image-20210927144512429"></p><p>看到了pytest-xdist官方解决方案</p><figure class="highlight python"><table><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></pre></td><td class="code"><pre><span class="line"><span class="keyword">import</span> json</span><br><span class="line"></span><br><span class="line"><span class="keyword">import</span> pytest</span><br><span class="line"><span class="keyword">from</span> filelock <span class="keyword">import</span> FileLock</span><br><span class="line"></span><br><span class="line"></span><br><span class="line"><span class="meta">@pytest.fixture(<span class="params">scope=<span class="string">"session"</span></span>)</span></span><br><span class="line"><span class="function"><span class="keyword">def</span> <span class="title">session_data</span>(<span class="params">tmp_path_factory, worker_id</span>):</span></span><br><span class="line"> <span class="keyword">if</span> worker_id == <span class="string">"master"</span>:</span><br><span class="line"> <span class="comment"># not executing in with multiple workers, just produce the data and let</span></span><br><span class="line"> <span class="comment"># pytest's fixture caching do its job</span></span><br><span class="line"> <span class="keyword">return</span> produce_expensive_data()</span><br><span class="line"></span><br><span class="line"> <span class="comment"># get the temp directory shared by all workers</span></span><br><span class="line"> root_tmp_dir = tmp_path_factory.getbasetemp().parent</span><br><span class="line"></span><br><span class="line"> fn = root_tmp_dir / <span class="string">"data.json"</span></span><br><span class="line"> <span class="keyword">with</span> FileLock(<span class="built_in">str</span>(fn) + <span class="string">".lock"</span>):</span><br><span class="line"> <span class="keyword">if</span> fn.is_file():</span><br><span class="line"> data = json.loads(fn.read_text())</span><br><span class="line"> <span class="keyword">else</span>:</span><br><span class="line"> data = produce_expensive_data()</span><br><span class="line"> fn.write_text(json.dumps(data))</span><br><span class="line"> <span class="keyword">return</span> data</span><br></pre></td></tr></table></figure><p>看到官方给的解决方案其实是采用FileLock文件锁的方式进行解决，亲测，完全可以解决此问题</p><p>2、第二种多进程方案multprocessing Pool</p><p><img src="https://gitee.com/Jack_Gitee_Code/Ptoho_Iamge/raw/master/image/2021/09/27/52247_image-20210927145749854.png" alt="image-20210927145749854"></p><p><img src="https://gitee.com/Jack_Gitee_Code/Ptoho_Iamge/raw/master/image/2021/09/27/45210_image-20210927145740377.png" alt="image-20210927145740377"></p><p>自动化是按照模块进行多进程执行，有多少模块启动多少个进程</p><p>为什么要用apply_async呢？因为他是非阻塞异步的, 他不会等待子进程执行完毕, 主进程会继续执行, 他会根据系统调度来进行进程切换</p><p>有不懂的吗？</p><p>不懂的话自己去敲代码吧，算了解释一下吧，我们来看一个栗子【比较好吃的那种】</p><p>首先我们看一下apply()阻塞异步</p><figure class="highlight python"><table><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></pre></td><td class="code"><pre><span class="line"><span class="keyword">import</span> time</span><br><span class="line"><span class="keyword">from</span> multiprocessing <span class="keyword">import</span> Pool</span><br><span class="line"></span><br><span class="line"></span><br><span class="line"><span class="function"><span class="keyword">def</span> <span class="title">doIt</span>(<span class="params">num</span>):</span></span><br><span class="line"> <span class="built_in">print</span>(<span class="string">"Process num is : %s"</span> % num)</span><br><span class="line"> time.sleep(<span class="number">1</span>)</span><br><span class="line"> <span class="built_in">print</span>(<span class="string">'process %s end'</span> % num)</span><br><span class="line"></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"> <span class="built_in">print</span>(<span class="string">'mainProcess start'</span>)</span><br><span class="line"> <span class="comment"># 记录一下开始执行的时间</span></span><br><span class="line"> start_time = time.time()</span><br><span class="line"> <span class="comment"># 创建三个子进程</span></span><br><span class="line"> pool = Pool(<span class="number">3</span>)</span><br><span class="line"> <span class="built_in">print</span>(<span class="string">'Child start'</span>)</span><br><span class="line"> <span class="keyword">for</span> i <span class="keyword">in</span> <span class="built_in">range</span>(<span class="number">3</span>):</span><br><span class="line"> pool.apply(doIt, [i])</span><br><span class="line"> <span class="built_in">print</span>(<span class="string">'mainProcess done time:%s s'</span> % (time.time() - start_time))</span><br></pre></td></tr></table></figure><p><img src="https://gitee.com/Jack_Gitee_Code/Ptoho_Iamge/raw/master/image/2021/09/27/67631_image-20210927151339788.png" alt="image-20210927151339788"></p><p><strong>执行结果</strong> 我们可以看到, 主进程开始执行之后, 创建的三个子进程也随即开始执行, 主进程被阻塞, 这里跟上一篇文章介绍的<code>join()</code> 很类似, 而且接下来三个子进程是一个接一个按顺序地执行, 等到子进程全部执行完毕之后, 主进程就会继续执行, 打印出最后一句,</p><p>接下来我们看看apply_asyn()</p><figure class="highlight python"><table><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></pre></td><td class="code"><pre><span class="line"><span class="keyword">import</span> time</span><br><span class="line"><span class="keyword">from</span> multiprocessing <span class="keyword">import</span> Pool</span><br><span class="line"></span><br><span class="line"></span><br><span class="line"><span class="function"><span class="keyword">def</span> <span class="title">doIt</span>(<span class="params">num</span>):</span></span><br><span class="line"> <span class="built_in">print</span>(<span class="string">"Process num is : %s"</span> % num)</span><br><span class="line"> time.sleep(<span class="number">1</span>)</span><br><span class="line"> <span class="built_in">print</span>(<span class="string">'process %s end'</span> % num)</span><br><span class="line"></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"> <span class="built_in">print</span>(<span class="string">'mainProcess start'</span>)</span><br><span class="line"> <span class="comment"># 记录一下开始执行的时间</span></span><br><span class="line"> start_time = time.time()</span><br><span class="line"> <span class="comment"># 创建三个子进程</span></span><br><span class="line"> pool = Pool(<span class="number">3</span>)</span><br><span class="line"> <span class="built_in">print</span>(<span class="string">'Child start'</span>)</span><br><span class="line"> <span class="keyword">for</span> i <span class="keyword">in</span> <span class="built_in">range</span>(<span class="number">3</span>):</span><br><span class="line"> pool.apply_async(doIt, [i])</span><br><span class="line"> <span class="built_in">print</span>(<span class="string">'mainProcess done time:%s s'</span> % (time.time() - start_time))</span><br></pre></td></tr></table></figure><p><img src="https://gitee.com/Jack_Gitee_Code/Ptoho_Iamge/raw/master/image/2021/09/27/21256_image-20210927151549546.png" alt="image-20210927151549546"></p><p>OMG发生了什么，怎么之有一个主进程执行了？我的子进程呢？</p><p>我们来看看运行结果 , 可以看出来, 截图的第一句是上一个程序的执行消耗时间, 最后一句是使用<strong>apply_async()</strong> 所消耗的时间, 在这里, 主进程没有被阻塞, 验证了他是非阻塞的, 子进程没有执行, 验证了他是根据系统调度完成的, 为什么会这样呢?<br>原因是, 进程的切换时操作系统控制的, 我们首先运行的是主进程, 而CPU运行得又很快, 快到还没等系统调度到子线程, 主线程就已经运行完毕了, 并且退出程序. 所以子进程就没有运行了.</p><p>那我 调用了apply_async() 是不是就不能运行子进程了吗？ 肯定可以呀!!小老弟,想啥呢??</p><p>还记得**join()**告诉主进程老子要运行子进程就好呀, 还记得 join()的作用吗, 他可以阻塞主进程, 等待所有子进程结束之后再运行, 我们在</p><figure class="highlight plaintext"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">print('mainProcess done time:%s s' % (time.time() - start_time))</span><br></pre></td></tr></table></figure><p> 执行之前加入两句代码</p><figure class="highlight plaintext"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br></pre></td><td class="code"><pre><span class="line">pool.close()</span><br><span class="line">pool.join()</span><br></pre></td></tr></table></figure><p>我们先要 close()一下子进程, 而且要先在 join() 前运行它,不逼逼赖赖，上代码</p><figure class="highlight python"><table><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></pre></td><td class="code"><pre><span class="line"><span class="keyword">import</span> time</span><br><span class="line"><span class="keyword">from</span> multiprocessing <span class="keyword">import</span> Pool</span><br><span class="line"></span><br><span class="line"></span><br><span class="line"><span class="function"><span class="keyword">def</span> <span class="title">doIt</span>(<span class="params">num</span>):</span></span><br><span class="line"> <span class="built_in">print</span>(<span class="string">"Process num is : %s"</span> % num)</span><br><span class="line"> time.sleep(<span class="number">1</span>)</span><br><span class="line"> <span class="built_in">print</span>(<span class="string">'process %s end'</span> % num)</span><br><span class="line"></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"> <span class="built_in">print</span>(<span class="string">'mainProcess start'</span>)</span><br><span class="line"> <span class="comment"># 记录一下开始执行的时间</span></span><br><span class="line"> start_time = time.time()</span><br><span class="line"> <span class="comment"># 创建三个子进程</span></span><br><span class="line"> pool = Pool(<span class="number">3</span>)</span><br><span class="line"> <span class="built_in">print</span>(<span class="string">'Child start'</span>)</span><br><span class="line"> <span class="keyword">for</span> i <span class="keyword">in</span> <span class="built_in">range</span>(<span class="number">3</span>):</span><br><span class="line"> pool.apply_async(doIt, [i])</span><br><span class="line"> pool.close()</span><br><span class="line"> pool.join()</span><br><span class="line"> <span class="built_in">print</span>(<span class="string">'mainProcess done time:%s s'</span> % (time.time() - start_time))</span><br></pre></td></tr></table></figure><p><img src="https://gitee.com/Jack_Gitee_Code/Ptoho_Iamge/raw/master/image/2021/09/27/13250_image-20210927152537833.png" alt="image-20210927152537833"></p><p>这是什么速度，这也太快了，比**apply()**快了六倍？</p><p>我们看看加入这两句的运行结果, 首先我们可以看到即使是使用了非阻塞主进程的apply_async() 也能让子进程运行了, 在这里子进程按顺序交替运行了,<br>CPU在执行第一个子进程的时候, 还没等第一个子进程结束, 系统调度到了按顺序调度到了第二个子进程, 以此类推, 一直调度运行子进程, 一个接一个地结束子进程的运行, 最后运行主进程, 而且我们可以看到使用apply_async()的执行效力会更高, 你看一下他们各自执行结果最后一句的执行消耗时间就知道了, 这也是官方推荐我们使用apply_async()的主要原因吧</p><h4 id="还有一个非常重要的原因win上multprocessing和linux下的multprocessing的区别-相当于说为什么windows下需要freeze-support"><a href="#还有一个非常重要的原因win上multprocessing和linux下的multprocessing的区别-相当于说为什么windows下需要freeze-support" class="headerlink" title="还有一个非常重要的原因win上multprocessing和linux下的multprocessing的区别,相当于说为什么windows下需要freeze_support()"></a>还有一个非常重要的原因win上multprocessing和linux下的multprocessing的区别,相当于说为什么windows下需要freeze_support()</h4><p>Windows下面的multiprocessing跟Linux下面略有不同，Linux下面的multiprocessing基于fork，fork之后所有的本地变量都复制一份，因此可以使用任意的全局变量；<br>在Windows下面，多进程是通过启动新进程完成的，所有的全局变量都是重新初始化的，在运行过程中动态生成、修改过的全局变量是不能使用的。</p><p>multiprocessing内部使用pickling传递map的参数到不同的进程，当传递一个函数或类时，pickling将函数或者类用所在模块+函数/类名的方式表示，<br>如果对端的Python进程无法在对应的模块中找到相应的函数或者类，就会出错。<br>当你在Interactive Console当中创建函数的时候，这个函数是动态添加到__main__模块中的，在重新启动的新进程当中不存在，所以会出错。<br>当不在Console中，而是在独立Python文件中运行时，你会遇到另一个问题：由于你下面调用multiprocessing的代码没有保护，<br>在新进程加载这个模块的时候会重新执行这段代码，创建出新的multiprocessing池，无限调用下去。</p><p><img src="https://gitee.com/Jack_Gitee_Code/Ptoho_Iamge/raw/master/image/2021/09/27/34716_image-20210927153035952.png" alt="image-20210927153035952"></p><h5 id="好了扯了一大堆没有用的言归正传"><a href="#好了扯了一大堆没有用的言归正传" class="headerlink" title="好了扯了一大堆没有用的言归正传"></a>好了扯了一大堆没有用的言归正传</h5><p>那我们自己实现的多进程是不是也会有conftest的session问题呢？答案是肯定的，当然有了怎么会没有，自己去按照思路去实现一下吧</p><p>那既然官方解释是说通过FileLock来实现，那我们是不是也可以自己实现一个FileLock呢？最笨方法的那种，话不多说，说干就干</p><p><strong>conftest.py修改为</strong></p><figure class="highlight python"><table><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></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> loguru <span class="keyword">import</span> logger</span><br><span class="line"></span><br><span class="line"><span class="function"><span class="keyword">def</span> <span class="title">log</span>():</span></span><br><span class="line"> logger.add(<span class="string">"aa.log"</span>, encoding=<span class="string">"UTF-8"</span>)</span><br><span class="line"> logger.info(<span class="string">"我是一个fixture，session级别的"</span>)</span><br><span class="line"></span><br><span class="line"><span class="meta">@pytest.fixture(<span class="params">scope=<span class="string">"session"</span></span>)</span></span><br><span class="line"><span class="function"><span class="keyword">def</span> <span class="title">fixture_print</span>(<span class="params">request</span>):</span></span><br><span class="line"> <span class="keyword">import</span> inspect</span><br><span class="line"> call_name = inspect.stack()[<span class="number">1</span>].function</span><br><span class="line"> <span class="keyword">with</span> <span class="built_in">open</span>(<span class="string">"FileLock.lock"</span>, <span class="string">"r+"</span>, encoding=<span class="string">"UTF-8"</span>) <span class="keyword">as</span> f:</span><br><span class="line"> <span class="keyword">if</span> call_name <span class="keyword">in</span> f.read():</span><br><span class="line"> <span class="keyword">return</span> <span class="literal">False</span></span><br><span class="line"> <span class="keyword">else</span>:</span><br><span class="line"> f.write(call_name)</span><br><span class="line"> request.addfinalizer(log)</span><br><span class="line"> <span class="comment"># log()</span></span><br><span class="line"> <span class="keyword">return</span> <span class="literal">True</span></span><br></pre></td></tr></table></figure><figure class="highlight python"><table><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><span class="line">39</span><br><span class="line">40</span><br><span class="line">41</span><br><span class="line">42</span><br><span class="line">43</span><br><span class="line">44</span><br><span class="line">45</span><br><span class="line">46</span><br><span class="line">47</span><br></pre></td><td class="code"><pre><span class="line"><span class="keyword">import</span> json</span><br><span class="line"><span class="keyword">import</span> os</span><br><span class="line"><span class="keyword">import</span> pytest</span><br><span class="line"><span class="keyword">from</span> random <span class="keyword">import</span> random</span><br><span class="line"><span class="keyword">from</span> filelock <span class="keyword">import</span> FileLock</span><br><span class="line"></span><br><span class="line"><span class="meta">@pytest.fixture(<span class="params">scope=<span class="string">"session"</span></span>)</span></span><br><span class="line"><span class="function"><span class="keyword">def</span> <span class="title">test</span>(<span class="params">tmp_path_factory, worker_id</span>):</span></span><br><span class="line"> <span class="comment"># 如果是单机运行 则运行这里的代码块【不可删除、修改】</span></span><br><span class="line"> <span class="keyword">if</span> worker_id == <span class="string">"master"</span>:</span><br><span class="line"> <span class="string">"""</span></span><br><span class="line"><span class="string"> 【自定义代码块】</span></span><br><span class="line"><span class="string"> 这里就写你要本身应该要做的操作，比如：登录请求、新增数据、清空数据库历史数据等等</span></span><br><span class="line"><span class="string"> """</span></span><br><span class="line"> token = <span class="built_in">str</span>(random())</span><br><span class="line"> <span class="built_in">print</span>(<span class="string">"fixture:请求登录接口，获取token"</span>, token)</span><br><span class="line"> os.environ[<span class="string">'token'</span>] = token</span><br><span class="line"></span><br><span class="line"> <span class="comment"># 如果测试用例有需要，可以返回对应的数据，比如 token</span></span><br><span class="line"> <span class="keyword">return</span> token</span><br><span class="line"></span><br><span class="line"> <span class="comment"># 如果是分布式运行</span></span><br><span class="line"> <span class="comment"># 获取所有子节点共享的临时目录，无需修改【不可删除、修改】</span></span><br><span class="line"> root_tmp_dir = tmp_path_factory.getbasetemp().parent</span><br><span class="line"> <span class="comment"># 【不可删除、修改】</span></span><br><span class="line"> fn = root_tmp_dir / <span class="string">"data.json"</span></span><br><span class="line"> <span class="comment"># 【不可删除、修改】</span></span><br><span class="line"> <span class="keyword">with</span> FileLock(<span class="built_in">str</span>(fn) + <span class="string">".lock"</span>):</span><br><span class="line"> <span class="comment"># 【不可删除、修改】</span></span><br><span class="line"> <span class="keyword">if</span> fn.is_file():</span><br><span class="line"> <span class="comment"># 缓存文件中读取数据，像登录操作的话就是 token 【不可删除、修改】</span></span><br><span class="line"> token = json.loads(fn.read_text())</span><br><span class="line"> <span class="built_in">print</span>(<span class="string">f"读取缓存文件，token 是<span class="subst">{token}</span> "</span>)</span><br><span class="line"> <span class="keyword">else</span>:</span><br><span class="line"> <span class="string">"""</span></span><br><span class="line"><span class="string"> 【自定义代码块】</span></span><br><span class="line"><span class="string"> 跟上面 if 的代码块一样就行</span></span><br><span class="line"><span class="string"> """</span></span><br><span class="line"> token = <span class="built_in">str</span>(random())</span><br><span class="line"> <span class="built_in">print</span>(<span class="string">"fixture:请求登录接口，获取token"</span>, token)</span><br><span class="line"> <span class="comment"># 【不可删除、修改】</span></span><br><span class="line"> fn.write_text(json.dumps(token))</span><br><span class="line"> <span class="built_in">print</span>(<span class="string">f"首次执行，token 是<span class="subst">{token}</span> "</span>)</span><br><span class="line"></span><br><span class="line"> <span class="comment"># 最好将后续需要保留的数据存在某个地方，比如这里是 os 的环境变量</span></span><br><span class="line"> os.environ[<span class="string">'token'</span>] = token</span><br><span class="line"> <span class="keyword">return</span> token</span><br></pre></td></tr></table></figure><p>main.py修改为：</p><p><img src="https://gitee.com/Jack_Gitee_Code/Ptoho_Iamge/raw/master/image/2021/09/27/84579_image-20210927154156807.png" alt="image-20210927154308215"></p><p>结果：意外的惊喜，session只运行了一次</p><p><img src="https://gitee.com/Jack_Gitee_Code/Ptoho_Iamge/raw/master/image/2021/09/27/74105_image-20210927154802299.png" alt="image-20210927154802299"></p><p>注：我们只需要限制pytest的hook函数执行conftest的session，千万不能限制自定义的函数去调用session，否在会出现异常</p><h4 id="session问题二：如果我有多个session呢？你看这代码，得到pytest的hook都是call-fixture-func啊这要怎么搞？"><a href="#session问题二：如果我有多个session呢？你看这代码，得到pytest的hook都是call-fixture-func啊这要怎么搞？" class="headerlink" title="session问题二：如果我有多个session呢？你看这代码，得到pytest的hook都是call_fixture_func啊这要怎么搞？"></a>session问题二：如果我有多个session呢？你看这代码，得到pytest的hook都是call_fixture_func啊这要怎么搞？</h4><p>call_fixture_limit.py限制一下就好了啊，<strong>注：采用a+方式去写入文件的时候，需要调整指针</strong></p><figure class="highlight python"><table><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></pre></td><td class="code"><pre><span class="line"><span class="function"><span class="keyword">def</span> <span class="title">call_limit</span>():</span></span><br><span class="line"> <span class="string">"""限制多进程下fixture重复调用"""</span></span><br><span class="line"> <span class="keyword">import</span> inspect</span><br><span class="line"> call_name = inspect.stack()[<span class="number">1</span>].function</span><br><span class="line"> <span class="keyword">with</span> <span class="built_in">open</span>(<span class="string">"FileLock.lock"</span>, <span class="string">"a+"</span>, encoding=<span class="string">"UTF-8"</span>) <span class="keyword">as</span> f:</span><br><span class="line"> f.seek(<span class="number">0</span>)</span><br><span class="line"> CALL_LIST = f.read().split(<span class="string">","</span>)</span><br><span class="line"> <span class="keyword">if</span> call_name <span class="keyword">in</span> CALL_LIST:</span><br><span class="line"> <span class="keyword">return</span> <span class="literal">False</span></span><br><span class="line"> <span class="keyword">else</span>:</span><br><span class="line"> f.seek(<span class="number">2</span>)</span><br><span class="line"> f.write(<span class="string">f"<span class="subst">{call_name}</span>,"</span>)</span><br><span class="line"> <span class="keyword">return</span> <span class="literal">True</span></span><br></pre></td></tr></table></figure><p><img src="https://gitee.com/Jack_Gitee_Code/Ptoho_Iamge/raw/master/image/2021/09/27/49993_image-20210927173555822.png" alt="image-20210927173555822"></p><h4 id="问题三：多进程下执行失败会出现Cache问题，如何解决呢？不要慌，不是在报错就是在报错的路上"><a href="#问题三：多进程下执行失败会出现Cache问题，如何解决呢？不要慌，不是在报错就是在报错的路上" class="headerlink" title="问题三：多进程下执行失败会出现Cache问题，如何解决呢？不要慌，不是在报错就是在报错的路上"></a>问题三：多进程下执行失败会出现Cache问题，如何解决呢？不要慌，不是在报错就是在报错的路上</h4><figure class="highlight python"><table><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></pre></td><td class="code"><pre><span class="line"><span class="function"><span class="keyword">def</span> <span class="title">run</span>(<span class="params">index</span>):</span></span><br><span class="line"> <span class="keyword">import</span> time</span><br><span class="line"> pytest.main([<span class="string">"-v"</span>, <span class="string">f"<span class="subst">{index}</span>"</span>, <span class="string">"--cache-clear"</span>, <span class="string">"--alluredir=reports/allure"</span>])</span><br><span class="line"> time.sleep(<span class="number">1</span>)</span><br></pre></td></tr></table></figure><p>官方提供了专门的清除缓存的命令，是不是很银杏，但是用了这个命令又有问题了，有人就问了，这会有什么问题，怎么那么多问题，是的不要慌</p><p>采用了–cache-clear后呢会出现–lf命令的问题，因为lf失败重跑他是在缓存中去收集的，现在你把我缓存清掉了我怎么跑是吧，就很头疼了，所以呢可以提供一种解决思路，那就是手动去控制是否需要清除，如果不重跑呢？就清除，如果重跑呢？就不清除了，当然了有更好的解决方案可以提供一下给我</p><h4 id="问题四：多进程下多个session级别的fixtures文件之间互相调用问题，都说了不是在报错就是在报错的路上"><a href="#问题四：多进程下多个session级别的fixtures文件之间互相调用问题，都说了不是在报错就是在报错的路上" class="headerlink" title="问题四：多进程下多个session级别的fixtures文件之间互相调用问题，都说了不是在报错就是在报错的路上"></a>问题四：多进程下多个session级别的fixtures文件之间互相调用问题，都说了不是在报错就是在报错的路上</h4><p>问题：多个session级别的fixtures下会存在拿不到已经调用的fixtures文件的result，导致了获取不到值直接报错</p><p>解决方案：可以采用os.envircon来进行数据共享，记住，os.envircon只能设置字符串，一定要进行解析</p><h4 id="问题五：多进程下数据共享问题，会导致数据共享反射无法生效"><a href="#问题五：多进程下数据共享问题，会导致数据共享反射无法生效" class="headerlink" title="问题五：多进程下数据共享问题，会导致数据共享反射无法生效"></a>问题五：多进程下数据共享问题，会导致数据共享反射无法生效</h4><p>问题：参数化反射无法生效</p><p>解决方案：</p><p>可以写入整个系统的环境变量，例如os.environ[key]=value</p><p>思路就是重写object对象和metaclass元类的__setattr__魔术方法和__getattribute__方法</p><p>话不多说，完整代码</p><figure class="highlight python"><table><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><span class="line">39</span><br></pre></td><td class="code"><pre><span class="line"><span class="keyword">import</span> os</span><br><span class="line"></span><br><span class="line"></span><br><span class="line"><span class="class"><span class="keyword">class</span> <span class="title">ParamsPoolMetaClass</span>(<span class="params"><span class="built_in">type</span></span>):</span></span><br><span class="line"></span><br><span class="line"> <span class="function"><span class="keyword">def</span> <span class="title">__new__</span>(<span class="params">cls, *args, **kwargs</span>):</span></span><br><span class="line"> <span class="keyword">return</span> <span class="built_in">super</span>().__new__(cls, *args, **kwargs)</span><br><span class="line"></span><br><span class="line"> <span class="function"><span class="keyword">def</span> <span class="title">__getattribute__</span>(<span class="params">self, item</span>):</span></span><br><span class="line"> <span class="keyword">try</span>:</span><br><span class="line"> result = <span class="built_in">super</span>().__getattribute__(item)</span><br><span class="line"> <span class="keyword">except</span> (AttributeError, RecursionError) <span class="keyword">as</span> AE:</span><br><span class="line"> <span class="keyword">try</span>:</span><br><span class="line"> result = <span class="built_in">eval</span>(os.environ.get(item.upper()))</span><br><span class="line"> <span class="keyword">except</span> (SyntaxError, TypeError) <span class="keyword">as</span> SE:</span><br><span class="line"> result = os.environ.get(item.upper())</span><br><span class="line"></span><br><span class="line"> <span class="keyword">return</span> result</span><br><span class="line"></span><br><span class="line"> <span class="function"><span class="keyword">def</span> <span class="title">__setattr__</span>(<span class="params">self, key, value</span>):</span></span><br><span class="line"> <span class="built_in">super</span>().__setattr__(key, value)</span><br><span class="line"> os.environ[key] = <span class="built_in">str</span>(value)</span><br><span class="line"></span><br><span class="line"></span><br><span class="line"><span class="class"><span class="keyword">class</span> <span class="title">TestParamsPool</span>(<span class="params">metaclass=ParamsPoolMetaClass</span>):</span></span><br><span class="line"></span><br><span class="line"> <span class="function"><span class="keyword">def</span> <span class="title">__getattribute__</span>(<span class="params">self, item</span>):</span></span><br><span class="line"> <span class="keyword">try</span>:</span><br><span class="line"> result = <span class="built_in">super</span>().__getattribute__(item)</span><br><span class="line"> <span class="keyword">except</span> (AttributeError, RecursionError) <span class="keyword">as</span> AE:</span><br><span class="line"> <span class="keyword">try</span>:</span><br><span class="line"> result = <span class="built_in">eval</span>(os.environ.get(item.upper()))</span><br><span class="line"> <span class="keyword">except</span> (SyntaxError, TypeError) <span class="keyword">as</span> SE:</span><br><span class="line"> result = os.environ.get(item.upper())</span><br><span class="line"> <span class="keyword">return</span> result</span><br><span class="line"></span><br><span class="line"> <span class="function"><span class="keyword">def</span> <span class="title">__setattr__</span>(<span class="params">self, key: <span class="built_in">str</span>, value</span>):</span></span><br><span class="line"> <span class="built_in">super</span>().__setattr__(key, value)</span><br><span class="line"> os.environ[key.upper()] = <span class="built_in">str</span>(value)</span><br></pre></td></tr></table></figure><h2 id="多进程下API层单例问题"><a href="#多进程下API层单例问题" class="headerlink" title="多进程下API层单例问题"></a>多进程下API层单例问题</h2><p>疑问：不就是多进程吗？我直接一个multprocessing.Pool()一顿操作就好了，不就是把我的代码给不同得人一起跑吗？还会有那么多花里胡哨的问题？你搁这搁这搁这呢？</p><p>如你所愿啊，多进程下单例确实会有问题，虽然是单例，但是在多进程下单例是无法挡住的，会重新申请开辟地址并且返回对象，啊这么神奇</p><p>那么如何解决呢？当然是加锁了，铐起来，叉出去，获取了枷锁是不是就跑不了了。【又不是人人都是武松，只是想不想的问题】</p><figure class="highlight python"><table><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></pre></td><td class="code"><pre><span class="line"><span class="keyword">import</span> threading</span><br><span class="line"></span><br><span class="line"></span><br><span class="line"><span class="function"><span class="keyword">def</span> <span class="title">synchronized</span>(<span class="params">func</span>):</span></span><br><span class="line"> func.__lock__ = threading.Lock()</span><br><span class="line"></span><br><span class="line"> <span class="function"><span class="keyword">def</span> <span class="title">lock_func</span>(<span class="params">*args, **kwargs</span>):</span></span><br><span class="line"> <span class="keyword">with</span> func.__lock__:</span><br><span class="line"> <span class="keyword">return</span> func(*args, **kwargs)</span><br><span class="line"></span><br><span class="line"> <span class="keyword">return</span> lock_func</span><br><span class="line"></span><br><span class="line"></span><br><span class="line"><span class="class"><span class="keyword">class</span> <span class="title">Singleton</span>(<span class="params"><span class="built_in">object</span></span>):</span></span><br><span class="line"> isstance = <span class="literal">None</span></span><br><span class="line"></span><br><span class="line"><span class="meta"> @synchronized</span></span><br><span class="line"> <span class="function"><span class="keyword">def</span> <span class="title">__new__</span>(<span class="params">cls, *args, **kwargs</span>):</span></span><br><span class="line"> <span class="keyword">if</span> cls.isstance <span class="keyword">is</span> <span class="literal">None</span>:</span><br><span class="line"> cls.isstance = <span class="built_in">super</span>().__new__(cls)</span><br><span class="line"> <span class="keyword">return</span> cls.isstance</span><br><span class="line"> <span class="function"><span class="keyword">def</span> <span class="title">printf</span>(<span class="params">self</span>):</span></span><br><span class="line"> <span class="built_in">print</span>(<span class="built_in">id</span>(self))</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"> <span class="keyword">from</span> multiprocessing <span class="keyword">import</span> Pool</span><br><span class="line"></span><br><span class="line"> p = Pool(<span class="number">4</span>)</span><br><span class="line"> <span class="keyword">for</span> i <span class="keyword">in</span> <span class="built_in">range</span>(<span class="number">4</span>):</span><br><span class="line"> p.apply_async(Singleton().printf)</span><br><span class="line"> p.close()</span><br><span class="line"> p.join()</span><br></pre></td></tr></table></figure><p>运行结果：发现id都一样，是不是就实现了单例，这玩意竟然那么神奇</p><p><img src="https://gitee.com/Jack_Gitee_Code/Ptoho_Iamge/raw/master/image/2021/09/27/55784_image-20210927161824853.png" alt="image-20210927161824853"></p><h2 id="3、多进程下Token的设计"><a href="#3、多进程下Token的设计" class="headerlink" title="3、多进程下Token的设计"></a>3、多进程下Token的设计</h2><p>还是可以基于单例的思想进行设计Token，Token类去继承单例类，实例化一个Token对象，这样在整个过程采用的Token都是相同不会出现Token问题</p><h2 id="4、用例执行过慢，维护性差"><a href="#4、用例执行过慢，维护性差" class="headerlink" title="4、用例执行过慢，维护性差"></a>4、用例执行过慢，维护性差</h2><h4 id="疑问：为什么要选择多进程，为什么不选择多线程呢？是不是大家都有这种疑问"><a href="#疑问：为什么要选择多进程，为什么不选择多线程呢？是不是大家都有这种疑问" class="headerlink" title="疑问：为什么要选择多进程，为什么不选择多线程呢？是不是大家都有这种疑问"></a>疑问：为什么要选择多进程，为什么不选择多线程呢？是不是大家都有这种疑问</h4><p>其实多进程和多线程都可以，问题是，多线程的bug无法解决啊，所以曲线救国，那就用高资源来换取bug吧</p>]]></content>
<summary type="html"><p>自动化痛点</p>
<ul>
<li>异步接口需要定时获取结果【未想到最优解决方式】</li>
<li>运行速度慢</li>
<li>容错性差，维护性差</li>
<li>不能很好的兼容多进程方式运行</li>
<li>多进程下运行session块被重复运行，初始化代码被多</summary>
<category term="work,工作" scheme="https://jackgithubtest.github.io/tags/work-%E5%B7%A5%E4%BD%9C/"/>
</entry>
<entry>
<title>数据库乐观锁和悲观锁</title>
<link href="https://jackgithubtest.github.io/2021/09/03/%E6%95%B0%E6%8D%AE%E5%BA%93%E4%B9%90%E8%A7%82%E9%94%81%E5%92%8C%E6%82%B2%E8%A7%82%E9%94%81/"/>
<id>https://jackgithubtest.github.io/2021/09/03/%E6%95%B0%E6%8D%AE%E5%BA%93%E4%B9%90%E8%A7%82%E9%94%81%E5%92%8C%E6%82%B2%E8%A7%82%E9%94%81/</id>
<published>2021-09-03T03:52:39.000Z</published>
<updated>2021-09-30T03:36:03.104Z</updated>
</entry>
<entry>
<title>hexo+github搭建博客教程</title>
<link href="https://jackgithubtest.github.io/2021/09/01/hexo-github%E6%90%AD%E5%BB%BA%E5%8D%9A%E5%AE%A2%E6%95%99%E7%A8%8B/"/>
<id>https://jackgithubtest.github.io/2021/09/01/hexo-github%E6%90%AD%E5%BB%BA%E5%8D%9A%E5%AE%A2%E6%95%99%E7%A8%8B/</id>
<published>2021-09-01T02:43:01.000Z</published>
<updated>2021-09-30T03:36:03.102Z</updated>
<content type="html"><![CDATA[<p>阅读须知：</p><h1 id="GitHub-Pages是什么？"><a href="#GitHub-Pages是什么？" class="headerlink" title="GitHub Pages是什么？"></a>GitHub Pages是什么？</h1><p>GitHub Pages 是由 GitHub 官方提供的一种免费的静态站点托管服务，让我们可以在 GitHub 仓库里托管和发布自己的静态网站页面。</p><h1 id="Hexo是什么"><a href="#Hexo是什么" class="headerlink" title="Hexo是什么"></a>Hexo是什么</h1><p>Hexo 是一个快速、简洁且高效的静态博客框架，它基于 Node.js 运行，可以将我们撰写的 Markdown 文档解析渲染成静态的 HTML 网页。</p><h1 id="Hexo-GitHub发布原理"><a href="#Hexo-GitHub发布原理" class="headerlink" title="Hexo + GitHub发布原理"></a>Hexo + GitHub发布原理</h1><p><img src="https://gitee.com/Jack_Gitee_Code/Ptoho_Iamge/raw/master/image/2021/09/01/73214_image-20210901110630384.png" alt="image-20210901110630384"></p><h1 id="优点和不足"><a href="#优点和不足" class="headerlink" title="优点和不足"></a>优点和不足</h1><p><strong>优点：</strong>完全免费；静态站点，轻量快速；可按需求自由定制改造；托管在 GitHub，安全省心；迁移方便……</p><p><strong>不足：</strong>发文不便，依赖于本地环境；更适合个人博客使用；GitHub 在国内访问速度有点不快。【可以采用hosts文件修改github.com dns解析到对应的ip加快访问速度，Google浏览器可以下载IGG谷歌访问助手插件免费代理】</p><h1 id="环境安装"><a href="#环境安装" class="headerlink" title="环境安装"></a>环境安装</h1><p>Hexo 基于 Node.js，搭建过程中还需要使用 npm（Node.js 已带） 和 git，因此先搭建本地操作环境，安装 Node.js 和 Git。</p><ul><li>Node.js：<a href="https://link.zhihu.com/?target=https://nodejs.org/zh-cn">https://nodejs.org/zh-cn</a></li><li>Git：<a href="https://link.zhihu.com/?target=https://git-scm.com/downloads">https://git-scm.com/downloads</a></li></ul><p>下载 Node.js 和 Git 程序并安装，一路点 “下一步” 按默认配置完成安装。</p><p>进入cmd可以验证是否安装成功 node -v , npm -v 和git –version</p><p><img src="https://gitee.com/Jack_Gitee_Code/Ptoho_Iamge/raw/master/image/2021/09/01/22030_image-20210901111037848.png" alt="image-20210901111037848"></p><h2 id="Git链接GitHub"><a href="#Git链接GitHub" class="headerlink" title="Git链接GitHub"></a>Git链接GitHub</h2><p>使用邮箱注册GItHub 账户，选择免费账户，并完成邮件验证。</p><p>进入Git bash here</p><figure class="highlight plaintext"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br></pre></td><td class="code"><pre><span class="line">git config --global user.name "GitHub 用户名"</span><br><span class="line">git config --global user.email "GitHub 邮箱"</span><br></pre></td></tr></table></figure><h5 id="创建SSH密钥："><a href="#创建SSH密钥：" class="headerlink" title="创建SSH密钥："></a>创建SSH密钥：</h5><p>ssh-keygen -t rsa -C “GitHub 邮箱” Github邮箱为你注册的邮箱</p><h5 id="添加密钥："><a href="#添加密钥：" class="headerlink" title="添加密钥："></a>添加密钥：</h5><p>进入你的家目录下找到隐藏文件.ssh把 id_rsa.pub 内容到 Key 中，点击 Add SSH key 完成添加。</p><h5 id="创建GitHub仓库"><a href="#创建GitHub仓库" class="headerlink" title="创建GitHub仓库"></a>创建GitHub仓库</h5><p>GitHub 主页右上角加号 -> New repository：</p><ul><li>Repository name 中输入 <code>用户名.github.io</code></li><li>勾选 “Initialize this repository with a README”</li><li>Description 选填</li></ul><p>填好后点击 Create repository 创建。</p>]]></content>
<summary type="html"><p>阅读须知：</p>
<h1 id="GitHub-Pages是什么？"><a href="#GitHub-Pages是什么？" class="headerlink" title="GitHub Pages是什么？"></a>GitHub Pages是什么？</h1><p>G</summary>
<category term="hexo+github" scheme="https://jackgithubtest.github.io/tags/hexo-github/"/>
</entry>
<entry>
<title>解决github.io无法打开的经历</title>
<link href="https://jackgithubtest.github.io/2021/08/30/%E8%A7%A3%E5%86%B3github-io%E6%97%A0%E6%B3%95%E6%89%93%E5%BC%80%E7%9A%84%E7%BB%8F%E5%8E%86/"/>
<id>https://jackgithubtest.github.io/2021/08/30/%E8%A7%A3%E5%86%B3github-io%E6%97%A0%E6%B3%95%E6%89%93%E5%BC%80%E7%9A%84%E7%BB%8F%E5%8E%86/</id>
<published>2021-08-30T06:13:31.000Z</published>
<updated>2021-09-30T03:36:03.108Z</updated>
<content type="html"><![CDATA[<p>记得之前有 github.com 打不开或者打开很慢的解决方案，现在轮到了 github.io，哈哈。我的 github.io 很久开始就打不开了，当时从网上试了几种方法没成功就放弃了，今天查资料需要打开 github.io，又有点时间，所以主要针对这个解决了一下。从本文您可以了解到：</p><ol><li><p>碰到这种dns的问题该怎么排查？</p></li><li><p>怎么解决打不开github.io的问题？</p><p>ping命令其实很强大，不仅可以知道能不能链接，延时是多少，还可以知道dns解析的ip地址是多少，例如我们ping <a href="http://www.github.com/">www.github.com</a></p><figure class="highlight plaintext"><table><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></pre></td><td class="code"><pre><span class="line">ping www.github.com</span><br><span class="line"></span><br><span class="line">正在 Ping github.com [52.74.223.119] 具有 32 字节的数据:</span><br><span class="line">来自 52.74.223.119 的回复: 字节=32 时间=208ms TTL=42</span><br><span class="line">来自 52.74.223.119 的回复: 字节=32 时间=198ms TTL=42</span><br><span class="line">来自 52.74.223.119 的回复: 字节=32 时间=202ms TTL=42</span><br><span class="line">来自 52.74.223.119 的回复: 字节=32 时间=207ms TTL=42</span><br><span class="line"></span><br><span class="line">52.74.223.119 的 Ping 统计信息:</span><br><span class="line"> 数据包: 已发送 = 4，已接收 = 4，丢失 = 0 (0% 丢失)，</span><br><span class="line">往返行程的估计时间(以毫秒为单位):</span><br><span class="line"> 最短 = 198ms，最长 = 208ms，平均 = 203ms</span><br></pre></td></tr></table></figure><p>可以看到，后面小括号里面的 52.74.223.119 就是 ip 地址了。</p></li></ol><p>ping github.io </p><blockquote><p>ping github.io</p></blockquote><figure class="highlight plaintext"><table><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></pre></td><td class="code"><pre><span class="line">PING github.io (127.0.0.1): 56 data bytes</span><br><span class="line">64 bytes from 127.0.0.1: icmp_seq=0 ttl=64 time=0.030 ms</span><br><span class="line">64 bytes from 127.0.0.1: icmp_seq=1 ttl=64 time=0.105 ms</span><br><span class="line">64 bytes from 127.0.0.1: icmp_seq=2 ttl=64 time=0.084 ms</span><br></pre></td></tr></table></figure><p>上面显示 ip 地址为<code>127.0.0.1</code>，这个就是本机地址嘛，然后我去<code>/etc/hosts</code>里面查看hosts文件有没有被意外修改过，没看到github.io被解析到<code>127.0.0.1</code>的记录，这就表示，<strong>电脑上的dns解析是完好的，但是远程的 dns 解析很可能惨遭网络运营商的污染了</strong>，从而导致解析的时候被解析到了<code>127.0.0.1</code>。</p><p>修改本机dns</p><p>修改dns的服务器地址，如下：如果【1】不行就试试【2】</p><p><img src="https://gitee.com/Jack_Gitee_Code/Ptoho_Iamge/raw/master/image/2021/08/30/40194_image-20210830142139831.png" alt="image-20210830142139831"></p><p><img src="https://gitee.com/Jack_Gitee_Code/Ptoho_Iamge/raw/master/image/2021/08/30/89065_image-20210830142211754.png" alt="image-20210830142211754"></p><p>【1】修改dns为<code>114.114.114.114</code></p><p><img src="https://gitee.com/Jack_Gitee_Code/Ptoho_Iamge/raw/master/image/2021/08/30/60336_image-20210830142112590.png" alt="image-20210830142112590"></p><p>【2】修改dns为<code>223.5.5.5</code>与<code>223.6.6.6</code></p><p><img src="https://gitee.com/Jack_Gitee_Code/Ptoho_Iamge/raw/master/image/2021/08/30/34216_image-20210830142238446.png" alt="image-20210830142238446"></p><p>7、刷新DNS<br>【1】<code>win+r</code>：输入cmd,<br>【2】在命令提示符中键入<code>ipconfig/flushdns</code></p><p>8、即可访问地址中带<code>github.io</code>的网址。</p>]]></content>
<summary type="html"><p>记得之前有 github.com 打不开或者打开很慢的解决方案，现在轮到了 github.io，哈哈。我的 github.io 很久开始就打不开了，当时从网上试了几种方法没成功就放弃了，今天查资料需要打开 github.io，又有点时间，所以主要针对这个解决了一下。从本文您</summary>
<category term="碰到这种dns的问题该怎么排查？" scheme="https://jackgithubtest.github.io/categories/%E7%A2%B0%E5%88%B0%E8%BF%99%E7%A7%8Ddns%E7%9A%84%E9%97%AE%E9%A2%98%E8%AF%A5%E6%80%8E%E4%B9%88%E6%8E%92%E6%9F%A5%EF%BC%9F/"/>
<category term="怎么解决打不开github.io的问题？" scheme="https://jackgithubtest.github.io/categories/%E7%A2%B0%E5%88%B0%E8%BF%99%E7%A7%8Ddns%E7%9A%84%E9%97%AE%E9%A2%98%E8%AF%A5%E6%80%8E%E4%B9%88%E6%8E%92%E6%9F%A5%EF%BC%9F/%E6%80%8E%E4%B9%88%E8%A7%A3%E5%86%B3%E6%89%93%E4%B8%8D%E5%BC%80github-io%E7%9A%84%E9%97%AE%E9%A2%98%EF%BC%9F/"/>
<category term="GitHub" scheme="https://jackgithubtest.github.io/tags/GitHub/"/>
<category term="GitHub.io" scheme="https://jackgithubtest.github.io/tags/GitHub-io/"/>
</entry>
</feed>