Discussion on the technical solution for realizing real-time questionnaire survey by docking with DingTalk interface

Discussion on the technical solution for realizing real-time questionnaire survey by docking with DingTalk interface

With the continuous development of office scenes, communication and collaboration within enterprises have become more and more convenient and efficient. As one of the most popular enterprise-level communication tools currently, DingTalk provides a wealth of interfaces and functions, making information transfer within the enterprise more convenient. In many companies, questionnaires are a common method of communication. In order to implement real-time questionnaires, we can quickly build an intelligent questionnaire system by docking with the DingTalk interface.

1. Overview of technical solutions

Our technical solution is based on DingTalk’s robot interface and message push function. It receives user messages through the robot, parses the questionnaire commands, and then sends the user’s The answer results are stored in the database, and finally the results of the questionnaire are fed back to the user through the message push function.

2. Detailed explanation of the technical solution

1. Create a robot
   Create a robot on the DingTalk developer platform and obtain its Webhook address to receive and send messages.
2. Create database
   Create a questionnaire database, including questionnaire table, question table and answer table, to save the basic information of the questionnaire, questions and user's answer results.
3. Message analysis
   When the user sends a questionnaire command to the robot, the robot will receive the corresponding message. We can obtain the ID of the questionnaire that the user needs to fill in by parsing the content of the message. Then, the corresponding questions are queried from the database according to the ID and sent to the user in order.
4. Question Answer
   After the user receives the question, he or she can choose to answer the question and send it to the robot. The robot will save the answers in the answer table of the database and record the user's unique identification for subsequent results statistics.
5. Message push
   When the user completes the questionnaire, the robot will push the results of the questionnaire to the user. We can send the results of the questionnaire to users in the form of text, graphics, etc. through message push.
6. Result Statistics
   After the questionnaire survey is completed, the results of the questionnaire can be counted based on the answer table in the database. We can analyze user responses and generate statistical charts or reports for reference and analysis by relevant personnel.

3. Code Example

The following is a simple example, using Python language as an example, to demonstrate how to implement a simple questionnaire system through the DingTalk robot interface.

import requests
import json

# 创建机器人并获取Webhook地址
webhook_url = "https://oapi.dingtalk.com/robot/send?access_token=xxxxxxxxxxxxxx"

# 定义发送消息的函数
def send_message(content):
    headers = {'Content-Type': 'application/json'}
    data = {
        "msgtype": "text",
        "text": {
            "content": content
        }
    }
    r = requests.post(webhook_url, headers=headers, data=json.dumps(data))
    return r.json()

# 解析消息并回复
def parse_message(message):
    if message == "问卷调查":
        send_message("请回答问题一：")
    elif message == "问题一答案":
        send_message("请回答问题二：")
    elif message == "问题二答案":
        send_message("问卷调查结束，谢谢参与！")

# 接收用户消息
def receive_message(message):
    parse_message(message)

# 测试代码
if __name__ == "__main__":
    receive_message("问卷调查")
    receive_message("问题一答案")
    receive_message("问题二答案")

The above code demonstrates how to trigger a questionnaire by sending a message to the robot, and respond accordingly based on the questions answered by the user. In actual projects, we need to combine database operations and message push to implement a complete questionnaire system.

Summary:
By connecting with the DingTalk interface, we can quickly build a real-time questionnaire survey system. This solution uses the message interface and message push function of DingTalk robot, combined with database operation and message analysis, to realize the functions of sending, answering, saving and pushing results of questionnaires. At the same time, we also provide a simple code example that demonstrates how to implement the system through the Python language. Using this technical solution, companies can more conveniently conduct real-time questionnaire surveys and conduct data analysis and decision-making based on the survey results.

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