[
](https://developer.aliyun.com/...)

一、Serverless函数计算

什么是Serverless？

在《Serverless Architectures》中对 Serverless 是这样子定义的：

Serverless was first used to describe applications that significantly or fully incorporate third-party, cloud-hosted applications and services, to manage server-side logic and state. These are typically “rich client” applications—think single-page web apps, or mobile apps—that use the vast ecosystem of cloud-accessible databases (e.g., Parse, Firebase), authentication services(e.g., Auth0, AWS Cognito), and so on. These types of services have been previously described as “(Mobile) Backend as a service", and I use “BaaS” as shorthand in the rest of this article. Serverless can also mean applications where server-side logic is still written by the application developer, but, unlike traditional architectures, it’s run in stateless compute containers that are event-triggered, ephemeral (may only last for one invocation), and fully managed by a third party. One way to think of this is “Functions as a Service” or “FaaS”.(Note: The original source for this name—a tweet by @marak—isno longer publicly available.) AWS Lambda is one of the most popular implementations of a Functions-as-a-Service platform at present, but there are many others, too.

这样的形容我置信有很多小伙伴不明确，咱们能够这样子来了解Serverless：
它的中文直译就是【无服务器】

目前对于 Serverless 有几种解读办法：

  • 在某些场景能够解读为一种软件系统架构办法，通常称为 Serverless 架构
  • 而在另一些状况下，又能够代表一种产品状态，称为 Serverless 产品

能够了解为Severless=FAAS+BAAS 即函数即服务 (Function as a Service)+后端即服务 (Backend as a Service)

阿里云函数计算

阿里云函数计算是事件驱动的全托管计算服务。应用函数计算，您无需洽购与治理服务器等基础设施，只需编写并上传代码。函数计算为您筹备好计算资源，弹性地、牢靠地运行工作，并提供日志查问、性能监控和报警等性能。
借助函数计算，您能够疾速构建任何类型的利用和服务，并且只需为工作理论耗费的资源付费。

阿里云也为开发者敌人们提供了每月收费额度！

二、成绩介绍

疫情数据统计推送基于Python和阿里云Serverless函数计算开发。实现了应用Python爬取取得疫情数据并进行整顿，应用函数计算配合定时触发器，每天定时推送全国疫情数据到企业微信。

三、背景意义

疫情防控常态化，在寰球疫情一直减速蔓延态势下在短期内齐全完结是不可能的，很有可能较长期间处于疫情防控的状态，这要求咱们时刻保持警惕，及时理解疫情状况。疫情数据统计推送我的项目，适应了此背景。企业员工每天关上手机微信就能够收到一条简洁的推送，理解当日的疫情状况。

四、劣势和有余

劣势：绝对各大媒体每日推送的疫情状况相比，此疫情数据统计推送更加简介，能够更快的获取到无效信息。应用了阿里云函数FC开发，保护不便，无需关注服务器等基础设施，能够依据企业微信推送的需求量主动扩缩容，而且老本极低。应用定时触发器，每天定时的触发程序，发送数据推送，无需人为干涉。
有余：文字枯燥，将在前期推出数据可视化版本。

五、作品展现

我的项目代码：

import requests,random,json url = "https://c.m.163.com/ug/api/wuhan/app/data/list-total"def UserAgent(): #随机获取申请头    user_agent_list = ['Mozilla/5.0 (Windows NT 6.2) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/28.0.1464.0 Safari/537.36',                   'Mozilla/5.0 (Windows NT 5.1) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/31.0.1650.16 Safari/537.36',                   'Mozilla/5.0 (Windows NT 5.1) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/35.0.3319.102 Safari/537.36',                   'Mozilla/5.0 (X11; CrOS i686 3912.101.0) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/27.0.1453.116 Safari/537.36',                   'Mozilla/5.0 (Windows NT 6.2; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/27.0.1453.93 Safari/537.36',                   'Mozilla/5.0 (Windows NT 6.2; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/32.0.1667.0 Safari/537.36',                   'Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:17.0) Gecko/20100101 Firefox/17.0.6',                   'Mozilla/5.0 (Windows NT 6.1) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/28.0.1468.0 Safari/537.36',                   'Mozilla/5.0 (Windows NT 5.1) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/41.0.2224.3 Safari/537.36',                   'Mozilla/5.0 (X11; CrOS i686 3912.101.0) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/27.0.1453.116 Safari/537.36']    UserAgent={'User-Agent': random.choice(user_agent_list)}    return UserAgent  def Get(arg1,arg2): #获取疫情    url_json = requests.get(url=url,headers=UserAgent()).json()     today_confirm = str(url_json['data']['chinaTotal']['today']['confirm'])#全国累计确诊较昨日新增    today_input =str(url_json['data']['chinaTotal']['today']['input'])#全国较昨日新增境外输出    today_storeConfirm = str(url_json['data']['chinaTotal']['today']['storeConfirm'])#全国现有确诊较昨日    today_dead =str(url_json['data']['chinaTotal']['today']['dead'])#累计死亡较昨日新增    today_heal = str(url_json['data']['chinaTotal']['today']['heal'])#累计治愈较昨日新增    today_incrNoSymptom = str(url_json['data']['chinaTotal']['extData']['incrNoSymptom'])#无症状感染者较昨日     total_confirm = str(url_json['data']['chinaTotal']['total']['confirm'])  # 全国累计确诊    total_input = str(url_json['data']['chinaTotal']['total']['input'])  # 境外输出    total_dead = str(url_json['data']['chinaTotal']['total']['dead'])  # 累计死亡    total_heal = str(url_json['data']['chinaTotal']['total']['heal'])  # 累计治愈    total_storeConfirm = str(url_json['data']['chinaTotal']['total']['confirm'] - url_json['data']['chinaTotal']['total']['dead'] - url_json['data']['chinaTotal']['total']['heal'])  # 全国现有确诊    total_noSymptom = str(url_json['data']['chinaTotal']['extData']['noSymptom'])#无症状感染者     lastUpdateTime = url_json['data']['lastUpdateTime']#截止工夫     data ='-' * 6 +'全国疫情数据实时统计' + '-' * 5 + '\n统计截至工夫：'+ lastUpdateTime +'\n' + '-' * 27 + '\n' + \          '  累计确诊：' + total_confirm + ' ; ' + '较昨日：' + today_confirm + \          '\n  现有确诊：' + total_storeConfirm + ' ; ' + '较昨日：' + today_storeConfirm + \          '\n  累计死亡：' + total_dead + ' ; ' + '较昨日：' + today_dead + \          '\n  累计治愈：' + total_heal + ' ; ' + '较昨日：' + today_heal + \          '\n  境外输出：' + total_input + ' ; ' + '较昨日：' + today_input + \          '\n  无症状感染者：' + total_noSymptom + ' ; ' + '较昨日：' + today_incrNoSymptom    print(data)    HtmlPuch_server(data)  def HtmlPuch_server(data):    url_wx = "https://qyapi.weixin.qq.com/cgi-bin/webhook/send?key=3b4bd7fa-4063-477f-bbc6-0fe767c52fdf"    headers = {"Content-Type": "text/plain"}    push_data ={                "msgtype": "text",                "text": {                    "content":data                    }                }    html = requests.post(url_wx,headers=headers,json=push_data)    print(html.text)

应用阿里云函数计算FC服务：

应用定时触发器：

最终成果：

六、总结

通过Serverless咱们不再须要关注务器等基础设施，只需编写并上传代码，只有为工作理论耗费的资源付费，每月的收费额度能够满足开发者的根本应用。当初函数计算FC为开发者提供一站式 Serverless 利用治理，从一键创立利用到疾速体验。

更多内容关注 Serverless 微信公众号（ID：serverlessdevs），会集 Serverless 技术最全内容，定期举办 Serverless 流动、直播，用户最佳实际。