How to use Python to implement the user survey function of CMS system

How to use Python to implement the user survey function of the CMS system

Introduction:
Content management system (CMS) is a tool widely used in website construction. It can help website administrators conveniently Create, modify and manage website content. In many websites, user survey feedback is an important part, which can help website administrators understand user needs and improve website experience. This article will introduce how to use Python language to implement the user survey function in CMS system, and attach code examples.

1. System Design
   The user survey function mainly includes four main steps: creating questionnaires, displaying questionnaires, collecting user feedback and generating statistical reports. We will use Python's web framework Flask to build and develop the website.
2. Create a questionnaire
   First, we need to create a questionnaire form to collect user feedback. Questionnaires can be created using HTML form elements, such as radio buttons, check boxes, text input boxes, etc. Use Flask's form extension package wtforms to process form data and validate input more conveniently. The following is a code example for a simple questionnaire form:

from flask_wtf import FlaskForm
from wtforms import StringField, SubmitField, RadioField

class SurveyForm(FlaskForm):
    name = StringField('姓名')
    gender = RadioField('性别', choices=[('男', '男'), ('女', '女')])
    feedback = StringField('反馈')
    submit = SubmitField('提交')

3. Display questionnaire
   Displaying the questionnaire on the website can be achieved by using Flask's route decorator. We can create a routing function to pass the questionnaire form as a parameter to the template and display it in the template. The following is a simple code example showing the routing function of the questionnaire:

from flask import render_template

@app.route('/survey', methods=['GET', 'POST'])
def survey():
    form = SurveyForm()
    if form.validate_on_submit():
        # 处理用户提交的问卷数据
        return '谢谢参与！'
    return render_template('survey.html', form=form)

4. Collecting user feedback
   For the questionnaire data submitted by the user, we can save it to the database for convenience Follow-up analysis and reporting. You can use Python's database operation modules such as SQLAlchemy or MongoDB to complete data storage. The following is a code example that uses SQLAlchemy to save user feedback data:

from flask_sqlalchemy import SQLAlchemy

app = Flask(__name__)
app.config['SQLALCHEMY_DATABASE_URI'] = 'mysql://username:password@localhost/mydatabase'
db = SQLAlchemy(app)

class Feedback(db.Model):
    id = db.Column(db.Integer, primary_key=True)
    name = db.Column(db.String(50))
    gender = db.Column(db.String(10))
    feedback = db.Column(db.String(100))

    def save(self):
        db.session.add(self)
        db.session.commit()

In the routing function of questionnaire submission, we can save the user's feedback data to the database:

@app.route('/survey', methods=['GET', 'POST'])
def survey():
    # ...
    if form.validate_on_submit():
        feedback = Feedback(name=form.name.data, gender=form.gender.data, feedback=form.feedback.data)
        feedback.save()
        return '谢谢参与！'
    # ...

5. Generate statistical report
   In order to better understand user needs and evaluations, we can perform statistics and analysis on the collected user feedback data and generate statistical reports. Python comes with many libraries for processing data and generating charts, such as pandas, matplotlib and seaborn. The following is a simple code example for generating statistical reports:

import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns

# 从数据库中读取反馈数据
feedbacks = Feedback.query.all()

# 将反馈数据转换为DataFrame
df = pd.DataFrame([(f.name, f.gender, f.feedback) for f in feedbacks], columns=['姓名', '性别', '反馈'])

# 统计性别比例
gender_counts = df['性别'].value_counts()
plt.pie(gender_counts, labels=gender_counts.index, autopct='%1.1f%%')
plt.title('参与用户性别比例')
plt.show()

# 分析反馈内容
word_counts = df['反馈'].str.lower().str.split().explode().value_counts().head(10)
sns.barplot(x=word_counts.index, y=word_counts.values)
plt.title('反馈内容常用词统计')
plt.show()

Conclusion:
By using the Python language and corresponding libraries, we can easily implement the user survey function in the CMS system, and Better understand user needs and reviews through statistical analysis. This article shows an implementation method based on the Flask framework and attaches corresponding code examples. I hope it will be helpful to readers.

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