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@ -1,55 +1,153 @@
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from models import Database
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from utils import ProbabilityCalculator, ScoreCalculator, ExcelService
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class RollCallService:
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def __init__(self):
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self.db = Database()
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self.probability_calculator = ProbabilityCalculator()
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def random_roll_call(self, class_name):
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"""随机点名"""
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students = self.db.get_students_by_class(class_name)
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if not students:
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return None
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selected_student = self.probability_calculator.weighted_random_selection(students)
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# 记录点名
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self.db.add_roll_call_record(
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selected_student.student_id,
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selected_student.name
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)
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return selected_student
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def update_student_score(self, student_id, answer_type, performance):
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"""更新学生积分"""
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score_delta = ScoreCalculator.calculate_score(answer_type, performance)
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success = self.db.update_student_score(student_id, score_delta)
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if success and score_delta != 0:
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student = next((s for s in self.db.get_all_students()
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if s.student_id == student_id), None)
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if student:
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self.db.add_roll_call_record(
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student_id,
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student.name,
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score_delta
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)
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return success, score_delta
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class ScoreService:
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def __init__(self):
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self.db = Database()
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self.excel_service = ExcelService()
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def get_class_ranking(self, class_name):
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"""获取班级积分排名"""
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students = self.db.get_students_by_class(class_name)
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return sorted(students, key=lambda x: x.total_score, reverse=True)
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def export_scores_excel(self, class_name):
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"""导出积分Excel"""
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students = self.db.get_students_by_class(class_name)
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return self.excel_service.export_scores(students)
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from models import get_db, Student, RollCallRecord, OrderCallStatus
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from utils import ProbabilityCalculator, ScoreCalculator, ExcelService
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import pandas as pd
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from sqlalchemy import desc
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import matplotlib.pyplot as plt
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import io
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import base64
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class RollCallService:
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def __init__(self):
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self.probability_calculator = ProbabilityCalculator()
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def import_students_from_excel(self, excel_file):
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db = next(get_db())
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try:
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df = pd.read_excel(excel_file, engine='openpyxl')
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required_cols = ['学号', '姓名', '专业', '班级']
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if not all(col in df.columns for col in required_cols):
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return False, "Excel缺少必填列（学号、姓名、专业、班级）"
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for _, row in df.iterrows():
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student = Student(
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student_id=str(row['学号']),
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name=str(row['姓名']),
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major=str(row['专业']),
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class_name=str(row['班级'])
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)
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existing = db.query(Student).filter_by(student_id=student.student_id).first()
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if existing:
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existing.name = student.name
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existing.major = student.major
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existing.class_name = student.class_name
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else:
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db.add(student)
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db.commit()
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return True, f"成功导入 {len(df)} 名学生"
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except Exception as e:
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db.rollback()
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return False, f"导入失败：{str(e)}"
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finally:
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db.close()
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def roll_call(self, class_name, call_mode='random'):
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db = next(get_db())
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try:
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students = db.query(Student).filter_by(class_name=class_name).order_by(Student.student_id).all()
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if not students:
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return None, "没有找到该班级学生"
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if call_mode == 'random':
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selected = self.probability_calculator.weighted_random_selection(students)
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else:
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status = db.query(OrderCallStatus).filter_by(class_name=class_name).first()
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if not status:
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status = OrderCallStatus(class_name=class_name, current_index=0)
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db.add(status)
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db.commit()
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selected = students[status.current_index % len(students)]
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status.current_index += 1
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db.commit()
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selected.call_count += 1
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db.commit()
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return selected, ""
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except Exception as e:
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db.rollback()
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return None, f"点名失败：{str(e)}"
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finally:
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db.close()
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def update_student_score(self, student_id, answer_type, performance, status='present'):
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db = next(get_db())
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try:
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student = db.query(Student).filter_by(student_id=student_id).first()
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if not student:
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return False, 0
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score_delta = ScoreCalculator.calculate_score(answer_type, performance)
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if status == 'present':
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score_delta += 1
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student.total_score += score_delta
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record = RollCallRecord(
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student_id=student_id,
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call_mode='random',
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status=status,
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answer_type=answer_type,
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performance=performance,
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score_delta=score_delta
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)
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db.add(record)
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db.commit()
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return True, score_delta
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except Exception as e:
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db.rollback()
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return False, 0
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finally:
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db.close()
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class ScoreService:
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def __init__(self):
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# 不在初始化时获取db连接
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self.excel_service = ExcelService()
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def get_class_ranking(self, class_name):
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db = next(get_db())
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try:
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return db.query(Student).filter_by(class_name=class_name).order_by(desc(Student.total_score)).all()
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finally:
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db.close()
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def generate_score_chart(self, class_name, top_n=5):
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db = next(get_db())
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try:
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students = self.get_class_ranking(class_name)[:top_n]
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if not students:
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return None
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plt.rcParams['font.sans-serif'] = ['SimHei']
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plt.rcParams['axes.unicode_minus'] = False
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fig, ax = plt.subplots(figsize=(8, 5))
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names = [s.name for s in students]
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scores = [s.total_score for s in students]
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call_counts = [s.call_count for s in students]
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x = range(len(names))
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ax.bar(x, scores, alpha=0.7, label='总积分', color='#3498db')
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ax2 = ax.twinx()
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ax2.plot(x, call_counts, color='#e74c3c', marker='o', label='点名次数')
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ax.set_xlabel('学生姓名')
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ax.set_ylabel('总积分', color='#3498db')
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ax2.set_ylabel('点名次数', color='#e74c3c')
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ax.set_title(f'{class_name} 积分TOP{top_n}及点名次数')
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ax.set_xticks(x)
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ax.set_xticklabels(names, rotation=45)
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buffer = io.BytesIO()
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plt.tight_layout()
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plt.savefig(buffer, format='png', dpi=100, bbox_inches='tight')
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buffer.seek(0)
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img_base64 = base64.b64encode(buffer.getvalue()).decode('utf-8')
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buffer.close()
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plt.close()
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return img_base64
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finally:
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db.close()
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def export_scores_excel(self, class_name):
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students = self.get_class_ranking(class_name)
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return self.excel_service.export_detailed_scores(students)
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