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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.
这样的描述我相信有很多小伙伴不明白，我们可以这样子来理解Serverless：
它的中文直译就是【无服务器】
目前对于 Serverless 有几种解读方法：
- 在某些场景可以解读为一种软件系统架构方法，通常称为 Serverless 架构
- 而在另一些情况下，又可以代表一种产品形态，称为 Serverless 产品
可以理解为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。使用函数计算，您无需采购与管理服务器等基础设施，只需编写并上传代码。函数计算为您准备好计算资源，弹性地、可靠地运行任务，并提供日志查询、性能监控和报警等功能。
借助函数计算，您可以快速构建任何类型的应用和服务，并且只需为任务实际消耗的资源付费。
阿里云也为开发者朋友们提供了每月免费额度！
二、成果介绍
疫情数据统计推送基于Python和阿里云Serverless函数计算开发。实现了使用Python爬取获得疫情数据并进行整理，使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，在全球疫情不断加速蔓延态势下在短期内完全结束是不可能的，很有可能较长时期处于疫情防控的状态，这要求我们时刻保持警惕，及时了解疫情情况。疫情数据统计推送项目，顺应了此背景。企业员工每天打开手机微信就可以收到一条简约的推送，了解当日的疫情情况。
四、优势和不足
优势：相对各大媒体每日推送的疫情情况相比，此疫情数据统计推送更加简介，可以更快的获取到有效信息。使用了阿里云函数FC开发，维护方便，无需关注服务器等基础设施，可以根据企业微信推送的需求量自动扩缩容，而且成本极低。使用定时触发器，每天定时的触发程序，发送数据推送，无需人为干预。
不足：文字单调，将在后期推出数据可视化版本。
五、作品展示
项目代码：
import requests,random,json
url = "https://c.m.163.com/ug/api/wuhan/app/data/list-total"
def UserAgent(): #随机获取请求头
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入
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']) # 境外输入
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']#截止时间
data ='-' * 6 +'全国疫情数据实时统计' + '-' * 5 + '\n统计截至时间：'+ 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 境外输入：' + 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)使用阿里云函数计算FC服务：
使用定时触发器：
最终效果：
六、总结
通过Serverless我们不再需要关注务器等基础设施，只需编写并上传代码，只要为任务实际消耗的资源付费，每月的免费额度可以满足开发者的基本使用。现在函数计算FC为开发者提供一站式 Serverless 应用管理，从一键创建应用到快速体验。
更多内容关注 Serverless 微信公众号（ID：serverlessdevs），汇集 Serverless 技术最全内容，定期举办 Serverless 活动、直播，用户最佳实践。
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