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一种精确从文本中提取URL的思路及实现

在今年三四月份,我接受了一个需求:从文本中提取URL。这样的需求,可能算是非常小众的需求了。大概只有QQ、飞信、阿里旺旺等之类的即时通讯软件存在这样的需求。在研究这个之前,我测试了这些软件这块功能,发现它们这块的功能还是非常弱的。这类软件往往也是恶意URL传播的媒介,如果不能准确识别出URL,相应的URL安全检测也无从谈起。而且网上也有很多使用正则表达式的方法,可是我看了下,方法简单但是不够精确,对于要求不高的情况可以胜任,但是如果“坏人”想绕过这种提取也是很方便的。(转载请指明出处)下面也是我在公司内部做的一次分享的内容:

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图论--差分约束--POJ 1364 King

Once, in one kingdom, there was a queen and that queen was expecting a baby. The queen prayed: ``If my child was a son and if only he was a sound king.'' After nine months her child was born, and indeed, she gave birth to a nice son. Unfortunately, as it used to happen in royal families, the son was a little retarded. After many years of study he was able just to add integer numbers and to compare whether the result is greater or less than a given integer number. In addition, the numbers had to be written in a sequence and he was able to sum just continuous subsequences of the sequence. The old king was very unhappy of his son. But he was ready to make everything to enable his son to govern the kingdom after his death. With regards to his son's skills he decided that every problem the king had to decide about had to be presented in a form of a finite sequence of integer numbers and the decision about it would be done by stating an integer constraint (i.e. an upper or lower limit) for the sum of that sequence. In this way there was at least some hope that his son would be able to make some decisions. After the old king died, the young king began to reign. But very soon, a lot of people became very unsatisfied with his decisions and decided to dethrone him. They tried to do it by proving that his decisions were wrong. Therefore some conspirators presented to the young king a set of problems that he had to decide about. The set of problems was in the form of subsequences Si = {aSi, aSi+1, ..., aSi+ni} of a sequence S = {a1, a2, ..., an}. The king thought a minute and then decided, i.e. he set for the sum aSi + aSi+1 + ... + aSi+ni of each subsequence Si an integer constraint ki (i.e. aSi + aSi+1 + ... + aSi+ni < ki or aSi + aSi+1 + ... + aSi+ni > ki resp.) and declared these constraints as his decisions. After a while he realized that some of his decisions were wrong. He could not revoke the declared constraints but trying to save himself he decided to fake the sequence that he was given. He ordered to his

02

转录组差异分析这样做能行吗?

前段时间,我们分享了转录组三种常见差异分析的推文以及单样本1V1进行差异分析的推文。对单个样本进行差异分析时,我们能获得相应的差异基因。在转录组三种常见差异分析的推文中,我们利用取交集的方式看了下三种方法获得共同差异基因的交集情况。曾老师提出了一个有趣的猜想,试想如果我们将3V3的样本拆分成3次1V1进行差异分析,是否会出现什么有趣的现象呢。为了让结果可比,我们就用上次的数据集GSE190114吧。此次,我们除了关注3次1V1差异分析上调与下调差异基因分别共同的交集情况之外,还将关注3种常见分析方法的上调与下调差异基因分别与拆分成3次1V1差异分析的上调与下调差异基因的共同交集情况,「用于探究是否能够拆分成3次1V1后进行差异分析」。话不多说,由于此次所使用的数据与上次一样,对此次的探究描述与数据集介绍感兴趣的小伙伴,请移驾至三种转录组差异分析方法及区别你会了吗?。

01

kubelet 配置资源预留的姿势

当我们在线上使用 Kubernetes 集群的时候,如果没有对节点配置正确的资源预留,我们可以考虑一个场景,由于某个应用无限制的使用节点的 CPU 资源,导致节点上 CPU 使用持续100%运行,而且压榨到了 kubelet 组件的 CPU 使用,这样就会导致 kubelet 和 apiserver 的心跳出问题,节点就会出现 Not Ready 状况了。默认情况下节点 Not Ready 过后,5分钟后会驱逐应用到其他节点,当这个应用跑到其他节点上的时候同样100%的使用 CPU,是不是也会把这个节点搞挂掉,同样的情况继续下去,也就导致了整个集群的雪崩,集群内的节点一个一个的 Not Ready 了,后果是非常严重的,或多或少的人遇到过 Kubernetes 集群雪崩的情况,这个问题也是面试的时候经常询问的问题。

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