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How to use Serverless to quickly build a survey questionnaire in APP, many novices are not very clear about this, in order to help you solve this problem, the following editor will explain in detail, people with this need can come to learn, I hope you can gain something.

Preface

Serverless computing enables developers to build modern applications with greater flexibility and lower cost. Developers do not need to configure and manage infrastructure such as servers, and can devote all their energies to the core business.

Serverless is essentially different from traditional serverful development methods:

Decoupling of computing and storage; they are expanded and priced independently

Code execution no longer requires manual allocation of resources

Charge by usage.

Rapid Construction of Serverless and APP questionnaire Survey

As the core computing component of Serverless architecture, functional services can be applied to all kinds of Serverless architectures, including two categories: Web, mobile, IoT, AI and other serverless back-end and data processing system back-end.

Among them, the typical scenarios of Web and mobile serverless backend are the most widely used. This document describes how to use functional services + API gateway to build user questionnaires in Jingdong Cloud APP minute by minute.

The construction of APP questionnaire can be accomplished by two simple functions: obtaining the content of the questionnaire and submitting the answer.

Step1: creating Stora

Create a database or object storage bucket for storing questionnaire questions and users' answers. In this example, create a cloud cache Redis instance (master / slave 4GB).

Step2: create function

Create and test two functions in the function service (runtime: Python2.7)

Create function 1

Create the function jcloud-app-survey-topic: request the user PIN, the questionnaire version version, obtain the questionnaire content from the database, and package the entry file index.py and the dependent library redis SDK to the function service. The index.py code is as follows:

# coding=utf-8import jsonimport redis''' download questionnaire''def handler (event,context): if not bool (event): result = {' statusCode': 200, 'headers': {},' body': ",} return result body = event ['detail'] [' body'] body = json.loads (body) pin = body.get ('pin') "") version = body.get ('version', ") print (pin) print (version) r = redis.Redis (host='redis-v214pzrgiicq-proxy-nlb.jvessel-open-hb.jdcloud.com', port=6379, db=0) topic = r.hget (' topic_' + version, version) data = {'pin': pin,' version': version, 'topic': topic} data = json.dumps (data) result = {' statusCode': 200 'headers': {}, 'body': data,} return result

Function test

Create function 2

Create function 2jcloud-app-survey-submit: request user PIN, questionnaire version version, user answer submit, upload to database, package entry file index.py and dependent library redis SDK to function service. The index.py code is as follows.

# def handler (event,context): if not bool (event): result = {'statusCode': 200,' headers': {}, 'body': ",} return result body = event [' detail'] ['body'] body = json.loads (body) pin = body.get (' pin') "") version = body.get ('version', ") submit = body.get (' submit',") print (pin) print (version) print (submit) r = redis.Redis (host='*.jdcloud.com', port=6379, db=0) old = r.hget ('submit_' + version, pin) if old! = None: data = {' code': 1 'desc':' user have submitted'} data = json.dumps (data) result = {'statusCode': 200,' headers': {}, 'body': data,} return result r.hset (' submit_' + version, pin, submit) data = {'code': 0,' desc': 'success'} data = json.dumps (data) result = {' statusCode': 'headers': {}, 'body': data,} return result

Function test

Step 3: create a publish API

Create two API in the API gateway, bind to the corresponding function as triggers, respond to the API request through function, and publish the API to the test environment. The jcloud-app-survey-topic function binds the API trigger as follows:

The jcloud-app-survey-submit function binds the API trigger as follows:

Step 4: verify launch

Verify the correctness of the API interface through the local API interface test tool, which can be debugged with the front-end H5 page development. After the test is completed, it can be iteratively released through the function version and alias function management online function.

Above, quickly complete the launch of the APP backend, just wait for the event to be launched

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