447 lines
14 KiB
Python
447 lines
14 KiB
Python
# app/controllers/statistics.py
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from flask import Blueprint, render_template, jsonify, request
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from flask_login import login_required, current_user
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from app.models.book import Book, db
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from app.models.borrow import BorrowRecord
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from app.models.user import User
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from app.utils.auth import admin_required
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from app.models.log import Log # 导入日志模型
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from sqlalchemy import func, case, desc, and_
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from datetime import datetime, timedelta
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import calendar
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statistics_bp = Blueprint('statistics', __name__, url_prefix='/statistics')
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@statistics_bp.route('/')
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@login_required
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@admin_required
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def index():
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"""统计分析首页"""
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# 记录访问统计分析首页的日志
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Log.add_log(
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action="访问统计分析",
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user_id=current_user.id,
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target_type="statistics",
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description="访问统计分析首页"
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)
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return render_template('statistics/index.html')
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@statistics_bp.route('/book-ranking')
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@login_required
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@admin_required
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def book_ranking():
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"""热门图书排行榜页面"""
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# 记录访问热门图书排行的日志
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Log.add_log(
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action="查看统计数据",
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user_id=current_user.id,
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target_type="statistics",
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description="查看热门图书排行榜"
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)
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return render_template('statistics/book_ranking.html')
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@statistics_bp.route('/api/book-ranking')
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@login_required
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@admin_required
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def api_book_ranking():
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"""获取热门图书排行数据API"""
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time_range = request.args.get('time_range', 'month')
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limit = request.args.get('limit', 10, type=int)
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# 记录获取热门图书排行数据的日志
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Log.add_log(
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action="获取数据",
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user_id=current_user.id,
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target_type="statistics",
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description=f"获取热门图书排行数据(时间范围:{time_range}, 数量:{limit})"
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)
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# 根据时间范围设置过滤条件
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if time_range == 'week':
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start_date = datetime.now() - timedelta(days=7)
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elif time_range == 'month':
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start_date = datetime.now() - timedelta(days=30)
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elif time_range == 'year':
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start_date = datetime.now() - timedelta(days=365)
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else: # all time
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start_date = datetime(1900, 1, 1)
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# 查询借阅次数最多的图书
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popular_books = db.session.query(
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Book.id, Book.title, Book.author, Book.cover_url,
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func.count(BorrowRecord.id).label('borrow_count')
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).join(
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BorrowRecord, Book.id == BorrowRecord.book_id
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).filter(
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BorrowRecord.borrow_date >= start_date
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).group_by(
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Book.id
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).order_by(
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desc('borrow_count')
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).limit(limit).all()
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result = [
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{
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'id': book.id,
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'title': book.title,
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'author': book.author,
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'cover_url': book.cover_url,
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'borrow_count': book.borrow_count
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} for book in popular_books
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]
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return jsonify(result)
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@statistics_bp.route('/borrow-statistics')
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@login_required
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@admin_required
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def borrow_statistics():
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"""借阅统计分析页面"""
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# 记录访问借阅统计分析的日志
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Log.add_log(
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action="查看统计数据",
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user_id=current_user.id,
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target_type="statistics",
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description="查看借阅统计分析"
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)
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return render_template('statistics/borrow_statistics.html')
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@statistics_bp.route('/api/borrow-trend')
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@login_required
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@admin_required
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def api_borrow_trend():
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"""获取借阅趋势数据API"""
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time_range = request.args.get('time_range', 'month')
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# 记录获取借阅趋势数据的日志
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Log.add_log(
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action="获取数据",
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user_id=current_user.id,
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target_type="statistics",
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description=f"获取借阅趋势数据(时间范围:{time_range})"
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)
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if time_range == 'week':
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# 获取过去7天每天的借阅和归还数量
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start_date = datetime.now() - timedelta(days=6)
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results = []
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for i in range(7):
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day = start_date + timedelta(days=i)
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day_start = day.replace(hour=0, minute=0, second=0, microsecond=0)
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day_end = day.replace(hour=23, minute=59, second=59, microsecond=999999)
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# 查询当天借阅量
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borrow_count = BorrowRecord.query.filter(
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BorrowRecord.borrow_date >= day_start,
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BorrowRecord.borrow_date <= day_end
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).count()
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# 查询当天归还量
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return_count = BorrowRecord.query.filter(
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BorrowRecord.return_date >= day_start,
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BorrowRecord.return_date <= day_end
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).count()
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# 当天逾期未还的数量
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overdue_count = BorrowRecord.query.filter(
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BorrowRecord.due_date < day_end,
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BorrowRecord.return_date.is_(None)
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).count()
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results.append({
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'date': day.strftime('%m-%d'),
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'borrow': borrow_count,
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'return': return_count,
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'overdue': overdue_count
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})
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return jsonify(results)
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elif time_range == 'month':
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# 获取过去30天每天的借阅和归还数量
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start_date = datetime.now() - timedelta(days=29)
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results = []
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for i in range(30):
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day = start_date + timedelta(days=i)
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day_start = day.replace(hour=0, minute=0, second=0, microsecond=0)
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day_end = day.replace(hour=23, minute=59, second=59, microsecond=999999)
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# 查询当天借阅量
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borrow_count = BorrowRecord.query.filter(
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BorrowRecord.borrow_date >= day_start,
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BorrowRecord.borrow_date <= day_end
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).count()
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# 查询当天归还量
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return_count = BorrowRecord.query.filter(
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BorrowRecord.return_date >= day_start,
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BorrowRecord.return_date <= day_end
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).count()
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# 当天逾期未还的数量
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overdue_count = BorrowRecord.query.filter(
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BorrowRecord.due_date < day_end,
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BorrowRecord.return_date.is_(None)
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).count()
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results.append({
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'date': day.strftime('%m-%d'),
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'borrow': borrow_count,
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'return': return_count,
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'overdue': overdue_count
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})
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return jsonify(results)
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elif time_range == 'year':
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# 获取过去12个月每月的借阅和归还数量
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current_month = datetime.now().month
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current_year = datetime.now().year
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results = []
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for i in range(12):
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# 计算月份和年份
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month = (current_month - i) % 12
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if month == 0:
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month = 12
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year = current_year - ((i - (current_month - 1)) // 12)
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# 计算该月的开始和结束日期
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days_in_month = calendar.monthrange(year, month)[1]
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month_start = datetime(year, month, 1)
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month_end = datetime(year, month, days_in_month, 23, 59, 59, 999999)
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# 查询当月借阅量
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borrow_count = BorrowRecord.query.filter(
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BorrowRecord.borrow_date >= month_start,
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BorrowRecord.borrow_date <= month_end
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).count()
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# 查询当月归还量
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return_count = BorrowRecord.query.filter(
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BorrowRecord.return_date >= month_start,
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BorrowRecord.return_date <= month_end
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).count()
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# 当月逾期未还的数量
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overdue_count = BorrowRecord.query.filter(
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BorrowRecord.due_date < month_end,
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BorrowRecord.return_date.is_(None)
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).count()
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results.append({
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'date': f'{year}-{month:02d}',
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'borrow': borrow_count,
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'return': return_count,
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'overdue': overdue_count
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})
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# 按时间顺序排序
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results.reverse()
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return jsonify(results)
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return jsonify([])
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@statistics_bp.route('/api/category-distribution')
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@login_required
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@admin_required
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def api_category_distribution():
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"""获取图书分类分布数据API"""
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# 记录获取图书分类分布数据的日志
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Log.add_log(
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action="获取数据",
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user_id=current_user.id,
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target_type="statistics",
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description="获取图书分类分布数据"
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)
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# 计算每个分类的总借阅次数
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category_stats = db.session.query(
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Book.category_id,
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func.count(BorrowRecord.id).label('borrow_count')
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).join(
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BorrowRecord, Book.id == BorrowRecord.book_id
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).group_by(
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Book.category_id
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).all()
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# 获取分类名称
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from app.models.book import Category
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categories = {cat.id: cat.name for cat in Category.query.all()}
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# 准备结果
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result = [
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{
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'category': categories.get(stat.category_id, '未分类'),
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'count': stat.borrow_count
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} for stat in category_stats if stat.category_id is not None
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]
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# 添加未分类数据
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uncategorized = next((stat for stat in category_stats if stat.category_id is None), None)
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if uncategorized:
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result.append({'category': '未分类', 'count': uncategorized.borrow_count})
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return jsonify(result)
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@statistics_bp.route('/user-activity')
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@login_required
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@admin_required
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def user_activity():
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"""用户活跃度分析页面"""
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# 记录访问用户活跃度分析的日志
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Log.add_log(
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action="查看统计数据",
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user_id=current_user.id,
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target_type="statistics",
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description="查看用户活跃度分析"
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)
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return render_template('statistics/user_activity.html')
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@statistics_bp.route('/api/user-activity')
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@login_required
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@admin_required
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def api_user_activity():
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"""获取用户活跃度数据API"""
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# 记录获取用户活跃度数据的日志
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Log.add_log(
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action="获取数据",
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user_id=current_user.id,
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target_type="statistics",
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description="获取用户活跃度数据"
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)
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# 查询最活跃的用户(借阅量最多)
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active_users = db.session.query(
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User.id, User.username, User.nickname,
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func.count(BorrowRecord.id).label('borrow_count')
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).join(
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BorrowRecord, User.id == BorrowRecord.user_id
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).group_by(
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User.id
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).order_by(
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desc('borrow_count')
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).limit(10).all()
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result = [
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{
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'id': user.id,
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'username': user.username,
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'nickname': user.nickname or user.username,
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'borrow_count': user.borrow_count
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} for user in active_users
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]
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return jsonify(result)
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@statistics_bp.route('/overdue-analysis')
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@login_required
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@admin_required
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def overdue_analysis():
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"""逾期分析页面"""
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# 记录访问逾期分析的日志
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Log.add_log(
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action="查看统计数据",
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user_id=current_user.id,
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target_type="statistics",
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description="查看借阅逾期分析"
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)
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return render_template('statistics/overdue_analysis.html')
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@statistics_bp.route('/api/overdue-statistics')
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@login_required
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@admin_required
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def api_overdue_statistics():
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"""获取逾期统计数据API"""
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# 记录获取逾期统计数据的日志
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Log.add_log(
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action="获取数据",
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user_id=current_user.id,
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target_type="statistics",
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description="获取借阅逾期统计数据"
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)
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now = datetime.now()
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# 计算总借阅量
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total_borrows = BorrowRecord.query.count()
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# 计算已归还的逾期借阅
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returned_overdue = BorrowRecord.query.filter(
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BorrowRecord.return_date.isnot(None),
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BorrowRecord.return_date > BorrowRecord.due_date
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).count()
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# 计算未归还的逾期借阅
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current_overdue = BorrowRecord.query.filter(
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BorrowRecord.return_date.is_(None),
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BorrowRecord.due_date < now
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).count()
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# 计算总逾期率
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overdue_rate = round((returned_overdue + current_overdue) / total_borrows * 100, 2) if total_borrows > 0 else 0
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# 计算各逾期时长区间的数量
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overdue_range_data = []
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# 1-7天逾期
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range1 = BorrowRecord.query.filter(
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and_(
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BorrowRecord.return_date.is_(None),
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BorrowRecord.due_date < now,
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BorrowRecord.due_date >= now - timedelta(days=7)
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)
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).count()
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overdue_range_data.append({'range': '1-7天', 'count': range1})
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# 8-14天逾期
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range2 = BorrowRecord.query.filter(
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and_(
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BorrowRecord.return_date.is_(None),
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BorrowRecord.due_date < now - timedelta(days=7),
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BorrowRecord.due_date >= now - timedelta(days=14)
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)
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).count()
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overdue_range_data.append({'range': '8-14天', 'count': range2})
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# 15-30天逾期
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range3 = BorrowRecord.query.filter(
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and_(
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BorrowRecord.return_date.is_(None),
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BorrowRecord.due_date < now - timedelta(days=14),
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BorrowRecord.due_date >= now - timedelta(days=30)
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)
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).count()
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overdue_range_data.append({'range': '15-30天', 'count': range3})
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# 30天以上逾期
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range4 = BorrowRecord.query.filter(
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and_(
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BorrowRecord.return_date.is_(None),
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BorrowRecord.due_date < now - timedelta(days=30)
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)
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).count()
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overdue_range_data.append({'range': '30天以上', 'count': range4})
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result = {
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'total_borrows': total_borrows,
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'returned_overdue': returned_overdue,
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'current_overdue': current_overdue,
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'overdue_rate': overdue_rate,
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'overdue_ranges': overdue_range_data
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}
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return jsonify(result)
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