306 lines
9.8 KiB
Python
306 lines
9.8 KiB
Python
"""仪表盘路由
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仪表盘数据相关的 API 接口
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"""
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from datetime import datetime, date, timedelta
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from typing import Optional
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from fastapi import APIRouter, Depends, Query
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from sqlalchemy import select, func, and_
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from sqlalchemy.ext.asyncio import AsyncSession
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from app.database import get_db
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from app.models import (
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Project,
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ProjectCostSummary,
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Competitor,
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CompetitorPrice,
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PricingPlan,
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ProfitSimulation,
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OperationLog,
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)
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from app.schemas.common import ResponseModel
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from app.schemas.dashboard import (
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DashboardSummaryResponse,
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ProjectOverview,
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CostOverview,
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CostProjectInfo,
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MarketOverview,
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PricingOverview,
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StrategiesDistribution,
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AIUsageOverview,
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RecentActivity,
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CostTrendResponse,
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MarketTrendResponse,
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TrendDataPoint,
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)
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router = APIRouter()
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@router.get("/dashboard/summary", response_model=ResponseModel[DashboardSummaryResponse])
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async def get_dashboard_summary(
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db: AsyncSession = Depends(get_db),
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):
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"""获取仪表盘概览数据"""
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# 项目概览
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total_projects_result = await db.execute(
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select(func.count(Project.id))
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)
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total_projects = total_projects_result.scalar() or 0
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active_projects_result = await db.execute(
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select(func.count(Project.id)).where(Project.is_active == True)
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)
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active_projects = active_projects_result.scalar() or 0
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projects_with_pricing_result = await db.execute(
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select(func.count(func.distinct(PricingPlan.project_id)))
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)
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projects_with_pricing = projects_with_pricing_result.scalar() or 0
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project_overview = ProjectOverview(
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total_projects=total_projects,
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active_projects=active_projects,
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projects_with_pricing=projects_with_pricing,
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)
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# 成本概览
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avg_cost_result = await db.execute(
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select(func.avg(ProjectCostSummary.total_cost))
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)
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avg_project_cost = float(avg_cost_result.scalar() or 0)
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# 最高成本项目
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highest_cost_result = await db.execute(
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select(ProjectCostSummary).options(
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).order_by(ProjectCostSummary.total_cost.desc()).limit(1)
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)
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highest_cost_summary = highest_cost_result.scalar_one_or_none()
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highest_cost_project = None
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if highest_cost_summary:
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project_result = await db.execute(
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select(Project).where(Project.id == highest_cost_summary.project_id)
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)
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project = project_result.scalar_one_or_none()
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if project:
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highest_cost_project = CostProjectInfo(
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id=project.id,
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name=project.project_name,
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cost=float(highest_cost_summary.total_cost),
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)
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# 最低成本项目
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lowest_cost_result = await db.execute(
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select(ProjectCostSummary).where(
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ProjectCostSummary.total_cost > 0
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).order_by(ProjectCostSummary.total_cost.asc()).limit(1)
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)
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lowest_cost_summary = lowest_cost_result.scalar_one_or_none()
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lowest_cost_project = None
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if lowest_cost_summary:
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project_result = await db.execute(
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select(Project).where(Project.id == lowest_cost_summary.project_id)
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)
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project = project_result.scalar_one_or_none()
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if project:
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lowest_cost_project = CostProjectInfo(
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id=project.id,
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name=project.project_name,
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cost=float(lowest_cost_summary.total_cost),
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)
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cost_overview = CostOverview(
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avg_project_cost=round(avg_project_cost, 2),
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highest_cost_project=highest_cost_project,
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lowest_cost_project=lowest_cost_project,
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)
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# 市场概览
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competitors_result = await db.execute(
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select(func.count(Competitor.id)).where(Competitor.is_active == True)
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)
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competitors_tracked = competitors_result.scalar() or 0
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# 本月价格记录数
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this_month_start = date.today().replace(day=1)
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price_records_result = await db.execute(
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select(func.count(CompetitorPrice.id)).where(
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CompetitorPrice.collected_at >= this_month_start
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)
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)
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price_records_this_month = price_records_result.scalar() or 0
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# 市场平均价
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avg_market_price_result = await db.execute(
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select(func.avg(CompetitorPrice.original_price))
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)
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avg_market_price = avg_market_price_result.scalar()
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market_overview = MarketOverview(
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competitors_tracked=competitors_tracked,
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price_records_this_month=price_records_this_month,
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avg_market_price=float(avg_market_price) if avg_market_price else None,
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)
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# 定价概览
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pricing_plans_result = await db.execute(
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select(func.count(PricingPlan.id))
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)
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pricing_plans_count = pricing_plans_result.scalar() or 0
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avg_margin_result = await db.execute(
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select(func.avg(PricingPlan.target_margin))
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)
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avg_target_margin = avg_margin_result.scalar()
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# 策略分布
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traffic_count_result = await db.execute(
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select(func.count(PricingPlan.id)).where(PricingPlan.strategy_type == "traffic")
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)
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profit_count_result = await db.execute(
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select(func.count(PricingPlan.id)).where(PricingPlan.strategy_type == "profit")
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)
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premium_count_result = await db.execute(
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select(func.count(PricingPlan.id)).where(PricingPlan.strategy_type == "premium")
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)
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pricing_overview = PricingOverview(
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pricing_plans_count=pricing_plans_count,
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avg_target_margin=float(avg_target_margin) if avg_target_margin else None,
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strategies_distribution=StrategiesDistribution(
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traffic=traffic_count_result.scalar() or 0,
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profit=profit_count_result.scalar() or 0,
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premium=premium_count_result.scalar() or 0,
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),
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)
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# 最近活动（从操作日志获取）
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recent_logs_result = await db.execute(
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select(OperationLog).order_by(
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OperationLog.created_at.desc()
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).limit(10)
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)
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recent_logs = recent_logs_result.scalars().all()
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recent_activities = []
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for log in recent_logs:
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recent_activities.append(RecentActivity(
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type=f"{log.module}_{log.action}",
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project_name=log.target_type,
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user=None, # 简化处理
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time=log.created_at,
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))
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return ResponseModel(data=DashboardSummaryResponse(
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project_overview=project_overview,
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cost_overview=cost_overview,
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market_overview=market_overview,
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pricing_overview=pricing_overview,
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ai_usage_this_month=None, # AI 使用统计需要从 ai_call_logs 表获取
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recent_activities=recent_activities,
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))
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@router.get("/dashboard/cost-trend", response_model=ResponseModel[CostTrendResponse])
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async def get_cost_trend(
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period: str = Query("month", description="统计周期：week/month/quarter"),
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db: AsyncSession = Depends(get_db),
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):
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"""获取成本趋势数据"""
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# 根据周期确定时间范围
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today = date.today()
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if period == "week":
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start_date = today - timedelta(days=7)
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elif period == "quarter":
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start_date = today - timedelta(days=90)
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else: # month
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start_date = today - timedelta(days=30)
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# 按日期分组统计平均成本
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# 简化实现：返回最近的成本汇总数据
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result = await db.execute(
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select(ProjectCostSummary).order_by(
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ProjectCostSummary.calculated_at.desc()
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).limit(30)
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)
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summaries = result.scalars().all()
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# 按日期聚合
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date_costs = {}
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for summary in summaries:
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# 检查 calculated_at 是否为 None
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if summary.calculated_at is None:
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continue
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day = summary.calculated_at.strftime("%Y-%m-%d")
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if day not in date_costs:
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date_costs[day] = []
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date_costs[day].append(float(summary.total_cost))
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data = []
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total_cost = 0
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for day in sorted(date_costs.keys()):
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avg = sum(date_costs[day]) / len(date_costs[day])
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data.append(TrendDataPoint(date=day, value=round(avg, 2)))
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total_cost += avg
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avg_cost = total_cost / len(data) if data else 0
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return ResponseModel(data=CostTrendResponse(
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period=period,
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data=data,
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avg_cost=round(avg_cost, 2),
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))
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@router.get("/dashboard/market-trend", response_model=ResponseModel[MarketTrendResponse])
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async def get_market_trend(
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period: str = Query("month", description="统计周期：week/month/quarter"),
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db: AsyncSession = Depends(get_db),
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):
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"""获取市场价格趋势数据"""
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# 根据周期确定时间范围
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today = date.today()
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if period == "week":
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start_date = today - timedelta(days=7)
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elif period == "quarter":
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start_date = today - timedelta(days=90)
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else: # month
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start_date = today - timedelta(days=30)
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# 获取价格记录
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result = await db.execute(
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select(CompetitorPrice).where(
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CompetitorPrice.collected_at >= start_date
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).order_by(CompetitorPrice.collected_at.desc())
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)
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prices = result.scalars().all()
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# 按日期聚合
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date_prices = {}
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for price in prices:
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# 检查 collected_at 是否为 None
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if price.collected_at is None:
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continue
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day = price.collected_at.strftime("%Y-%m-%d")
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if day not in date_prices:
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date_prices[day] = []
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date_prices[day].append(float(price.original_price))
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data = []
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total_price = 0
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for day in sorted(date_prices.keys()):
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avg = sum(date_prices[day]) / len(date_prices[day])
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data.append(TrendDataPoint(date=day, value=round(avg, 2)))
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total_price += avg
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avg_price = total_price / len(data) if data else 0
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return ResponseModel(data=MarketTrendResponse(
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period=period,
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data=data,
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avg_price=round(avg_price, 2),
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))
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