后端代码

Roll_Call_Flask.py

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+import io
+from flask import Flask, request, jsonify, render_template, send_file
+import pandas as pd
+import os
+import random
+from flask_cors import CORS
+
+app = Flask(__name__)
+CORS(app)
+
+# 学生类，包含姓名、学号和积分
+class Student:
+    def __init__(self, id, name, score=0.0):
+        self.id = id
+        self.name = name
+        self.score = score
+
+# 从Excel文件中读取学生名单
+def Original_Reading(file):
+    df = pd.read_excel(file)
+
+    # 检查是否存在“积分”列，如果不存在则初始化一个积分列并设置为0
+    if '积分' not in df.columns:
+        df['积分'] = 0.0
+
+    students = []
+    for i, row in df.iterrows():
+        students.append(Student(row['学号'], row['姓名'], row['积分']))
+    return students
+
+# 从排行榜文件中读取学生名单
+def Leaderboard_Reading(file):
+    if not os.path.exists(file):
+        return None
+    df = pd.read_excel(file)
+    s = []
+    for i, row in df.iterrows():
+        s.append(Student(row['学号'], row['姓名'], row['积分']))
+    return s
+
+# 随机选择一个学生
+def Select_Student(students):
+    total = sum(s.score for s in students)
+    if total == 0:
+        # 如果总积分为零，所有学生的权重都为1
+        w = [1] * len(students)
+    else:
+        w = [(total - student.score + 1) for student in students]
+    selected_student = random.choices(students, weights=w, k=1)[0]
+    return selected_student
+
+# 更新学生的积分
+def update_score(s, arrived, repeated, correct):
+    if arrived == 1:
+        s.score += 1.0
+    if repeated == 1:
+        s.score += 0.5
+    elif repeated == 2:
+        s.score -= 1.0
+    if correct:
+        s.score += correct
+
+
+# 将学生列表转换为DataFrame并按积分从大到小排序
+def students_to_dataframe(students):
+    total = sum(s.score for s in students)
+    if total == 0:
+        # 如果总积分为零，所有学生的权重都为1
+        weights = [1] * len(students)
+    else:
+        weights = [(total - s.score + 1) for s in students]
+
+    total_weight = sum(weights)
+    pro = [weight / total_weight * 100 for weight in weights]
+
+    data = {'学号': [s.id for s in students],
+            '姓名': [s.name for s in students],
+            '积分': [s.score for s in students],
+            '抽取概率(%)': pro}
+    df = pd.DataFrame(data)
+    df = df.sort_values(by='积分', ascending=False).reset_index(drop=True)
+    return df
+
+# 主程序
+students = []
+
+@app.route('/')
+def index():
+    return render_template('index.html')
+
+@app.route('/upload', methods=['POST'])
+def upload_file():
+    global students
+    file = request.files['file']
+    if file and file.filename.endswith('.xlsx'):
+        students = Original_Reading(file)
+        return jsonify({'success': True})
+    return jsonify({'success': False})
+
+@app.route('/select_student', methods=['GET'])
+def select_student():
+    global students
+    if not students:
+        return jsonify({'error': 'No students available'})
+    selected_student = Select_Student(students)
+    return jsonify({'name': selected_student.name, 'id': selected_student.id, 'score': selected_student.score})
+
+@app.route('/update_score', methods=['POST'])
+def update_student_score():
+    global students
+    data = request.json
+    student_id = data.get('id')
+    arrived = data.get('arrived')
+    repeated = data.get('repeated')
+    correct = data.get('correct')
+
+    student = next((s for s in students if s.id == student_id), None)
+    if student:
+        update_score(student, arrived, repeated, correct)
+        return jsonify({'success': True, 'score': student.score})
+    return jsonify({'success': False, 'error': '未找到该学生'})
+
+@app.route('/export_file', methods=['GET'])
+def export_file():
+    global students
+    if not students:
+        return jsonify({'error': 'No students available'})
+
+    df = students_to_dataframe(students)
+    output = io.BytesIO()
+    with pd.ExcelWriter(output, engine='xlsxwriter') as writer:
+        df.to_excel(writer, sheet_name='students', index=False)
+    output.seek(0)
+    return send_file(output, download_name='students.xlsx', as_attachment=True)
+
+@app.route('/check_probability', methods=['GET'])
+def check_probability():
+    global students
+    student_id = request.args.get('id')
+    student = next((s for s in students if s.id == student_id), None)
+    if student:
+        total = sum(s.score for s in students)
+        if total == 0:
+            probability = 1 / len(students)
+        else:
+            probability = (total - student.score + 1) / total
+        return jsonify({'probability': probability})
+    return jsonify({'error': 'Student not found'})
+
+@app.route('/select_ten_students', methods=['GET'])
+def select_ten_students():
+    global students
+    if not students:
+        return jsonify({'error': 'No students available'})
+
+    selected_students = []
+    for _ in range(10):
+        selected_student = Select_Student(students)
+        selected_students.append({
+            'name': selected_student.name,
+            'id': selected_student.id,
+            'score': selected_student.score
+        })
+
+    return jsonify({'students': selected_students})
+
+
+if __name__ == '__main__':
+    app.run(debug=True)