370 lines
14 KiB
Python
370 lines
14 KiB
Python
import pandas as pd
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import io
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from datetime import date, datetime
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from typing import Optional, Dict, List, Any
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from sqlalchemy.orm import Session
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from sqlalchemy import func, and_
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from app.models import Employee, SecondaryAgent, ProductCategory, PerformanceRecord, User
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from app.services.calculate_service import (
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calculate_employee_income, calculate_company_profit,
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get_period_dates, get_rebate_rate_by_period
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)
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def export_employee_report(
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db: Session,
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employee_id: int,
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period: str,
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year: int,
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month: Optional[int] = None
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) -> tuple:
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"""
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导出员工收益明细Excel
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Returns:
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tuple: (excel_bytes, filename)
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"""
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# 计算员工收益
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result = calculate_employee_income(db, employee_id, period, year, month, save_result=False)
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# 获取周期日期范围
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start_date, end_date, period_key = get_period_dates(period, year, month)
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# 获取业绩明细
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personal_records = db.query(PerformanceRecord).filter(
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and_(
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PerformanceRecord.employee_id == employee_id,
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PerformanceRecord.record_type == "employee",
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PerformanceRecord.record_date >= start_date,
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PerformanceRecord.record_date < end_date
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)
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).all()
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agent_records = db.query(PerformanceRecord).filter(
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and_(
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PerformanceRecord.employee_id == employee_id,
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PerformanceRecord.record_type == "agent",
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PerformanceRecord.record_date >= start_date,
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PerformanceRecord.record_date < end_date
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)
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).all()
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# 创建Excel writer
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output = io.BytesIO()
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with pd.ExcelWriter(output, engine='openpyxl') as writer:
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# Sheet 1: 收益汇总
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summary_data = {
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'项目': [
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'员工姓名',
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'计算周期',
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'业绩总额',
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'目标金额',
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'完成率(%)',
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'底薪',
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'绩效奖金',
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'个人提成',
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'代理提成',
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'总收入',
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'公司返点',
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'公司成本',
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'公司利润'
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],
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'金额': [
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result['employee_name'],
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result['period_key'],
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result['total_performance'],
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result['target_amount'],
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f"{result['completion_rate']:.2f}",
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result['base_salary'],
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result['performance_bonus'],
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result['personal_commission'],
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result['agent_commission'],
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result['total_income'],
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result['company_rebate'],
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result['company_cost'],
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result['company_profit']
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]
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}
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df_summary = pd.DataFrame(summary_data)
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df_summary.to_excel(writer, sheet_name='收益汇总', index=False)
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# Sheet 2: 个人业绩明细
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if personal_records:
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personal_data = []
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for record in personal_records:
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personal_data.append({
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'日期': record.record_date,
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'客户名称': record.customer_name or '',
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'订单号': record.order_no or '',
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'产品分类': record.category.name if record.category else '',
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'业绩金额': float(record.amount or 0),
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'提成比例': float(record.category.commission_rate or 0) if record.category else 0,
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'提成金额': float(record.amount or 0) * float(record.category.commission_rate or 0) if record.category else 0
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})
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df_personal = pd.DataFrame(personal_data)
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df_personal.to_excel(writer, sheet_name='个人业绩明细', index=False)
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else:
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pd.DataFrame({'提示': ['该周期内无个人业绩记录']}).to_excel(writer, sheet_name='个人业绩明细', index=False)
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# Sheet 3: 代理业绩明细
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if agent_records:
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agent_data = []
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for record in agent_records:
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agent = record.agent
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agent_data.append({
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'日期': record.record_date,
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'代理公司': agent.company_name if agent else '',
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'客户名称': record.customer_name or '',
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'订单号': record.order_no or '',
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'产品分类': record.category.name if record.category else '',
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'业绩金额': float(record.amount or 0),
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'分佣比例': float(agent.profit_share_rate or 0.6) if agent else 0.6,
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'分佣金额': float(record.amount or 0) * float(agent.profit_share_rate or 0.6) if agent else float(record.amount or 0) * 0.6
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})
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df_agent = pd.DataFrame(agent_data)
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df_agent.to_excel(writer, sheet_name='代理业绩明细', index=False)
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else:
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pd.DataFrame({'提示': ['该周期内无代理业绩记录']}).to_excel(writer, sheet_name='代理业绩明细', index=False)
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# Sheet 4: 提成明细
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if result.get('detail') and result['detail'].get('personal_performance'):
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commission_data = []
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for item in result['detail']['personal_performance'].get('by_category', []):
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commission_data.append({
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'产品分类': item['category_name'],
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'业绩金额': item['amount'],
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'提成比例': item['commission_rate'],
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'提成金额': item['commission']
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})
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if commission_data:
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df_commission = pd.DataFrame(commission_data)
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df_commission.to_excel(writer, sheet_name='提成明细', index=False)
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output.seek(0)
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filename = f"employee_report_{employee_id}_{period_key}.xlsx"
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return output.getvalue(), filename
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def export_company_report(
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db: Session,
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period: str,
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year: int,
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month: Optional[int] = None
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) -> tuple:
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"""
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导出公司收益汇总Excel
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Returns:
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tuple: (excel_bytes, filename)
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"""
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# 计算公司收益
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result = calculate_company_profit(db, period, year, month)
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# 获取周期日期范围
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start_date, end_date, period_key = get_period_dates(period, year, month)
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# 创建Excel writer
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output = io.BytesIO()
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with pd.ExcelWriter(output, engine='openpyxl') as writer:
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# Sheet 1: 公司收益汇总
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summary_data = {
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'项目': [
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'计算周期',
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'员工数量',
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'总返点收入',
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'员工成本',
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'代理分成',
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'总成本',
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'公司利润'
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],
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'金额': [
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result['period_key'],
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result['employee_count'],
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result['total_rebate'],
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result['total_employee_cost'],
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result['total_agent_share'],
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result['total_cost'],
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result['company_profit']
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]
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}
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df_summary = pd.DataFrame(summary_data)
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df_summary.to_excel(writer, sheet_name='公司收益汇总', index=False)
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# Sheet 2: 返点明细
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if result.get('rebate_details'):
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rebate_data = []
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for item in result['rebate_details']:
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rebate_data.append({
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'产品分类': item['category_name'],
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'业绩金额': item['amount'],
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'返点比例': item['rebate_rate'],
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'返点金额': item['rebate']
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})
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df_rebate = pd.DataFrame(rebate_data)
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df_rebate.to_excel(writer, sheet_name='返点明细', index=False)
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# Sheet 3: 员工成本明细
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if result.get('employee_details'):
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emp_data = []
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for item in result['employee_details']:
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emp_data.append({
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'员工ID': item['employee_id'],
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'员工姓名': item['employee_name'],
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'员工收入': item['total_income'],
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'代理分成': item['agent_share']
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})
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df_emp = pd.DataFrame(emp_data)
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df_emp.to_excel(writer, sheet_name='员工成本明细', index=False)
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output.seek(0)
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filename = f"company_report_{period_key}.xlsx"
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return output.getvalue(), filename
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def export_performance_report(
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db: Session,
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filters: Dict[str, Any]
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) -> tuple:
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"""
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导出业绩报表Excel
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Args:
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filters: 筛选条件
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- start_date: 开始日期
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- end_date: 结束日期
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- employee_id: 员工ID（可选）
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- agent_id: 代理ID（可选）
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- category_id: 分类ID（可选）
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- record_type: 记录类型（employee/agent）
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Returns:
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tuple: (excel_bytes, filename)
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"""
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# 构建查询
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query = db.query(PerformanceRecord)
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# 应用筛选条件
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if filters.get('start_date'):
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query = query.filter(PerformanceRecord.record_date >= filters['start_date'])
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if filters.get('end_date'):
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query = query.filter(PerformanceRecord.record_date <= filters['end_date'])
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if filters.get('employee_id'):
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query = query.filter(PerformanceRecord.employee_id == filters['employee_id'])
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if filters.get('agent_id'):
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query = query.filter(PerformanceRecord.agent_id == filters['agent_id'])
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if filters.get('category_id'):
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query = query.filter(PerformanceRecord.category_id == filters['category_id'])
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if filters.get('record_type'):
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query = query.filter(PerformanceRecord.record_type == filters['record_type'])
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records = query.order_by(PerformanceRecord.record_date.desc()).all()
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# 创建Excel writer
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output = io.BytesIO()
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with pd.ExcelWriter(output, engine='openpyxl') as writer:
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# Sheet 1: 业绩明细
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if records:
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data = []
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total_amount = 0
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for record in records:
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amount = float(record.amount or 0)
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total_amount += amount
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employee_name = ""
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if record.employee and record.employee.user:
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employee_name = record.employee.user.name
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agent_name = ""
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if record.agent:
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agent_name = record.agent.company_name
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category_name = ""
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if record.category:
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category_name = record.category.name
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data.append({
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'ID': record.id,
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'记录类型': '员工业绩' if record.record_type == 'employee' else '代理业绩',
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'日期': record.record_date,
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'员工': employee_name,
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'代理': agent_name,
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'产品分类': category_name,
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'客户名称': record.customer_name or '',
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'订单号': record.order_no or '',
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'业绩金额': amount,
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'备注': record.remark or ''
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})
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df = pd.DataFrame(data)
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df.to_excel(writer, sheet_name='业绩明细', index=False)
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# Sheet 2: 汇总统计
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summary_data = {
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'统计项': [
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'记录总数',
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'业绩总额',
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'平均单笔业绩',
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'员工业绩笔数',
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'代理业绩笔数'
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],
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'数值': [
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len(records),
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total_amount,
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round(total_amount / len(records), 2) if records else 0,
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len([r for r in records if r.record_type == 'employee']),
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len([r for r in records if r.record_type == 'agent'])
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]
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}
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df_summary = pd.DataFrame(summary_data)
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df_summary.to_excel(writer, sheet_name='汇总统计', index=False)
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# Sheet 3: 按员工汇总
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emp_summary = {}
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for record in records:
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emp_name = record.employee.user.name if record.employee and record.employee.user else '未知'
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if emp_name not in emp_summary:
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emp_summary[emp_name] = {'count': 0, 'amount': 0}
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emp_summary[emp_name]['count'] += 1
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emp_summary[emp_name]['amount'] += float(record.amount or 0)
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emp_data = []
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for name, stats in emp_summary.items():
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emp_data.append({
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'员工': name,
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'业绩笔数': stats['count'],
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'业绩总额': stats['amount']
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})
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df_emp = pd.DataFrame(emp_data)
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df_emp.to_excel(writer, sheet_name='按员工汇总', index=False)
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# Sheet 4: 按分类汇总
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cat_summary = {}
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for record in records:
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cat_name = record.category.name if record.category else '未知'
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if cat_name not in cat_summary:
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cat_summary[cat_name] = {'count': 0, 'amount': 0}
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cat_summary[cat_name]['count'] += 1
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cat_summary[cat_name]['amount'] += float(record.amount or 0)
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cat_data = []
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for name, stats in cat_summary.items():
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cat_data.append({
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'产品分类': name,
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'业绩笔数': stats['count'],
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'业绩总额': stats['amount']
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})
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df_cat = pd.DataFrame(cat_data)
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df_cat.to_excel(writer, sheet_name='按分类汇总', index=False)
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else:
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pd.DataFrame({'提示': ['无业绩记录']}).to_excel(writer, sheet_name='业绩明细', index=False)
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output.seek(0)
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# 生成文件名
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date_str = datetime.now().strftime('%Y%m%d')
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filename = f"performance_report_{date_str}.xlsx"
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return output.getvalue(), filename
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