20160116
This commit is contained in:
@@ -1,225 +1,238 @@
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from typing import List
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from fastapi import APIRouter, Depends
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from sqlalchemy.orm import Session
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from sqlalchemy import func
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from sqlalchemy import func, distinct
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from typing import List, Optional
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from pydantic import BaseModel
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from app.models import get_db
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from app.models.dit import DitRecord
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from app.models.sample import SampleRecord
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from app.models.order import OrderRecord
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from app.models.match import MatchResult, MatchStatus, TargetType
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from app.models.match import MatchResult, TargetType, MatchStatus
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router = APIRouter(prefix="/dashboard", tags=["Dashboard"])
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class KPIResponse(BaseModel):
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# --- Pydantic Models ---
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class DashboardKPI(BaseModel):
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total_dit: int
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sample_rate: float # 送樣轉換率
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hit_rate: float # 訂單命中率
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fulfillment_rate: float # EAU 達成率
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orphan_sample_rate: float # 無效送樣率
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sample_rate: float
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hit_rate: float
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fulfillment_rate: float
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no_order_sample_rate: float
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total_revenue: float
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class FunnelItem(BaseModel):
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class FunnelData(BaseModel):
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name: str
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value: int
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fill: str
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class AttributionDit(BaseModel):
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op_id: str
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class DitSchema(BaseModel):
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id: int
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op_id: Optional[str] = None
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customer: str
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pn: str
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eau: int
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stage: str
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date: str
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eau: float = 0
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stage: Optional[str] = None
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date: Optional[str] = None
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class AttributionSample(BaseModel):
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order_no: str
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date: str
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class Config:
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from_attributes = True
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class AttributionOrder(BaseModel):
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order_no: str
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status: str
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qty: int
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amount: float
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class SampleSchema(BaseModel):
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id: int
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order_no: Optional[str] = None
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customer: str
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pn: str
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qty: int = 0
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date: Optional[str] = None
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class Config:
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from_attributes = True
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class OrderSchema(BaseModel):
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id: int
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order_no: Optional[str] = None
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customer: str
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pn: str
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qty: int = 0
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amount: float = 0
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status: Optional[str] = None
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class Config:
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from_attributes = True
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class AttributionRow(BaseModel):
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dit: AttributionDit
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sample: AttributionSample | None
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order: AttributionOrder | None
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match_source: str | None
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dit: DitSchema
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sample: Optional[SampleSchema] = None
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order: Optional[OrderSchema] = None
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match_source: Optional[str] = None
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attributed_qty: int
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fulfillment_rate: float
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def get_lifo_attribution(db: Session):
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"""執行 LIFO 業績分配邏輯"""
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# 1. 取得所有 DIT，按日期由新到舊排序 (LIFO)
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dits = db.query(DitRecord).order_by(DitRecord.date.desc()).all()
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# 2. 取得所有已匹配且接受的訂單
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matched_orders = db.query(MatchResult, OrderRecord).join(
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OrderRecord, MatchResult.target_id == OrderRecord.id
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).filter(
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MatchResult.target_type == TargetType.ORDER,
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MatchResult.status.in_([MatchStatus.accepted, MatchStatus.auto_matched])
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).all()
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# 3. 建立業績池 (Revenue Pool) - 按 (客戶, 料號) 分組
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order_pools = {}
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for match, order in matched_orders:
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key = (order.customer_normalized, order.pn)
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if key not in order_pools:
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order_pools[key] = 0
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order_pools[key] += (order.qty or 0)
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# 4. 進行分配
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attribution_map = {} # dit_id -> {qty, total_eau}
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for dit in dits:
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key = (dit.customer_normalized, dit.pn)
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eau = dit.eau or 0
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allocated = 0
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if key in order_pools and order_pools[key] > 0:
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allocated = min(eau, order_pools[key])
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order_pools[key] -= allocated
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attribution_map[dit.id] = {
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"qty": allocated,
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"eau": eau
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}
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return attribution_map
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# --- Routes ---
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@router.get("/kpi", response_model=KPIResponse)
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@router.get("/kpi", response_model=DashboardKPI)
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def get_kpi(db: Session = Depends(get_db)):
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"""取得 KPI 統計 (符合規格書 v1.0)"""
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total_dit = db.query(DitRecord).count()
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if total_dit == 0:
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return KPIResponse(total_dit=0, sample_rate=0, hit_rate=0, fulfillment_rate=0, orphan_sample_rate=0, total_revenue=0)
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return DashboardKPI(
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total_dit=0, sample_rate=0, hit_rate=0,
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fulfillment_rate=0, no_order_sample_rate=0, total_revenue=0
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)
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# 1. 送樣轉換率 (Sample Rate): (有匹配到樣品的 DIT 數) / (總 DIT 數)
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dits_with_sample = db.query(func.count(func.distinct(MatchResult.dit_id))).filter(
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# Get valid matches
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valid_statuses = [MatchStatus.auto_matched, MatchStatus.accepted]
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# 1. Matches for Samples
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sample_matches = db.query(MatchResult.dit_id).filter(
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MatchResult.target_type == TargetType.SAMPLE,
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MatchResult.status.in_([MatchStatus.accepted, MatchStatus.auto_matched])
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).scalar() or 0
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sample_rate = (dits_with_sample / total_dit * 100)
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MatchResult.status.in_(valid_statuses)
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).distinct().count()
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# 2. 訂單命中率 (Hit Rate): (有匹配到訂單的 DIT 數) / (總 DIT 數)
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dits_with_order = db.query(func.count(func.distinct(MatchResult.dit_id))).filter(
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# 2. Matches for Orders
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order_matches = db.query(MatchResult.dit_id).filter(
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MatchResult.target_type == TargetType.ORDER,
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MatchResult.status.in_([MatchStatus.accepted, MatchStatus.auto_matched])
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).scalar() or 0
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hit_rate = (dits_with_order / total_dit * 100)
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MatchResult.status.in_(valid_statuses)
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).distinct().count()
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# 3. EAU 達成率 (Fulfillment Rate): (歸因之訂單總量) / (DIT 預估 EAU)
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attribution_map = get_lifo_attribution(db)
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total_attributed_qty = sum(item['qty'] for item in attribution_map.values())
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total_eau = sum(item['eau'] for item in attribution_map.values())
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fulfillment_rate = (total_attributed_qty / total_eau * 100) if total_eau > 0 else 0
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# 4. 無效送樣率 (Orphan Sample Rate): (未匹配到 DIT 的送樣數) / (總送樣數)
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total_samples = db.query(SampleRecord).count()
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matched_sample_ids = db.query(func.distinct(MatchResult.target_id)).filter(
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MatchResult.target_type == TargetType.SAMPLE
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).all()
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matched_sample_count = len(matched_sample_ids)
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orphan_sample_rate = ((total_samples - matched_sample_count) / total_samples * 100) if total_samples > 0 else 0
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# 5. 總營收
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total_revenue = db.query(func.sum(OrderRecord.amount)).join(
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# 3. Revenue
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# Join MatchResult -> OrderRecord to sum amount
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revenue = db.query(func.sum(OrderRecord.amount)).join(
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MatchResult, MatchResult.target_id == OrderRecord.id
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).filter(
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MatchResult.target_type == TargetType.ORDER,
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MatchResult.status.in_([MatchStatus.accepted, MatchStatus.auto_matched])
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).scalar() or 0
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MatchResult.status.in_(valid_statuses)
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).scalar() or 0.0
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return KPIResponse(
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# 4. Fulfillment (Total Matched Order Qty / Total Matched DIT EAU)
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total_order_qty = db.query(func.sum(OrderRecord.qty)).join(
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MatchResult, MatchResult.target_id == OrderRecord.id
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).filter(
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MatchResult.target_type == TargetType.ORDER,
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MatchResult.status.in_(valid_statuses)
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).scalar() or 0
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total_eau = db.query(func.sum(DitRecord.eau)).scalar() or 1 # Avoid div/0
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sample_rate = round((sample_matches / total_dit) * 100, 1)
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hit_rate = round((order_matches / total_dit) * 100, 1)
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fulfillment_rate = round((total_order_qty / total_eau) * 100, 1) if total_eau > 0 else 0
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# No Order Sample Rate
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dit_with_samples = set(x[0] for x in db.query(MatchResult.dit_id).filter(
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MatchResult.target_type == TargetType.SAMPLE,
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MatchResult.status.in_(valid_statuses)
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).distinct().all())
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dit_with_orders = set(x[0] for x in db.query(MatchResult.dit_id).filter(
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MatchResult.target_type == TargetType.ORDER,
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MatchResult.status.in_(valid_statuses)
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).distinct().all())
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dit_sample_no_order = len(dit_with_samples - dit_with_orders)
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no_order_sample_rate = round((dit_sample_no_order / len(dit_with_samples) * 100), 1) if dit_with_samples else 0.0
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return DashboardKPI(
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total_dit=total_dit,
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sample_rate=round(sample_rate, 1),
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hit_rate=round(hit_rate, 1),
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fulfillment_rate=round(fulfillment_rate, 1),
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orphan_sample_rate=round(orphan_sample_rate, 1),
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total_revenue=total_revenue
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sample_rate=sample_rate,
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hit_rate=hit_rate,
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fulfillment_rate=fulfillment_rate,
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no_order_sample_rate=no_order_sample_rate,
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total_revenue=revenue
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)
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@router.get("/funnel", response_model=List[FunnelItem])
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@router.get("/funnel", response_model=List[FunnelData])
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def get_funnel(db: Session = Depends(get_db)):
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"""取得漏斗數據"""
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valid_statuses = [MatchStatus.auto_matched, MatchStatus.accepted]
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# Stage 1: DIT
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total_dit = db.query(DitRecord).count()
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dits_with_sample = db.query(func.count(func.distinct(MatchResult.dit_id))).filter(
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MatchResult.target_type == TargetType.SAMPLE,
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MatchResult.status.in_([MatchStatus.accepted, MatchStatus.auto_matched])
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).scalar() or 0
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dits_with_order = db.query(func.count(func.distinct(MatchResult.dit_id))).filter(
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MatchResult.target_type == TargetType.ORDER,
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MatchResult.status.in_([MatchStatus.accepted, MatchStatus.auto_matched])
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).scalar() or 0
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# Stage 2: Sample
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dit_with_samples = db.query(MatchResult.dit_id).filter(
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MatchResult.target_type == TargetType.SAMPLE,
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MatchResult.status.in_(valid_statuses)
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).distinct().count()
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# Stage 3: Order
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dit_with_orders = db.query(MatchResult.dit_id).filter(
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MatchResult.target_type == TargetType.ORDER,
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MatchResult.status.in_(valid_statuses)
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).distinct().count()
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return [
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FunnelItem(name='DIT 案件', value=total_dit, fill='#6366f1'),
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FunnelItem(name='成功送樣', value=dits_with_sample, fill='#8b5cf6'),
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FunnelItem(name='取得訂單', value=dits_with_order, fill='#10b981'),
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FunnelData(name="DIT 總案", value=total_dit, fill="#6366f1"),
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FunnelData(name="成功送樣", value=dit_with_samples, fill="#a855f7"),
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FunnelData(name="取得訂單", value=dit_with_orders, fill="#10b981"),
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]
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@router.get("/attribution", response_model=List[AttributionRow])
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def get_attribution(db: Session = Depends(get_db)):
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"""取得歸因明細 (含 LIFO 分配與追溯資訊)"""
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dit_records = db.query(DitRecord).order_by(DitRecord.date.desc()).all()
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attribution_map = get_lifo_attribution(db)
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result = []
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valid_statuses = [MatchStatus.auto_matched, MatchStatus.accepted]
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matches = db.query(MatchResult).filter(MatchResult.status.in_(valid_statuses)).all()
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if not matches:
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return []
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for dit in dit_records:
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# 找到樣品匹配 (取分數最高的一個)
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sample_match = db.query(MatchResult).filter(
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MatchResult.dit_id == dit.id,
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MatchResult.target_type == TargetType.SAMPLE,
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MatchResult.status.in_([MatchStatus.accepted, MatchStatus.auto_matched])
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).order_by(MatchResult.score.desc()).first()
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sample_info = None
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if sample_match:
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sample = db.query(SampleRecord).filter(SampleRecord.id == sample_match.target_id).first()
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if sample:
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sample_info = AttributionSample(order_no=sample.order_no, date=sample.date or '')
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# 找到訂單匹配 (取分數最高的一個)
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order_match = db.query(MatchResult).filter(
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MatchResult.dit_id == dit.id,
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MatchResult.target_type == TargetType.ORDER,
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MatchResult.status.in_([MatchStatus.accepted, MatchStatus.auto_matched])
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).order_by(MatchResult.score.desc()).first()
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order_info = None
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match_source = None
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if order_match:
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order = db.query(OrderRecord).filter(OrderRecord.id == order_match.target_id).first()
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if order:
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order_info = AttributionOrder(
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order_no=order.order_no,
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status=order.status or 'Unknown',
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qty=order.qty or 0,
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amount=order.amount or 0
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)
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match_source = order_match.match_source
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attr_data = attribution_map.get(dit.id, {"qty": 0, "eau": dit.eau or 0})
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fulfillment = (attr_data['qty'] / attr_data['eau'] * 100) if attr_data['eau'] > 0 else 0
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result.append(AttributionRow(
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dit=AttributionDit(
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op_id=dit.op_id,
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customer=dit.customer,
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pn=dit.pn,
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eau=dit.eau,
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stage=dit.stage or '',
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date=dit.date or ''
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),
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sample=sample_info,
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order=order_info,
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match_source=match_source,
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attributed_qty=attr_data['qty'],
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fulfillment_rate=round(fulfillment, 1)
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dit_ids = set(m.dit_id for m in matches)
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dits = db.query(DitRecord).filter(DitRecord.id.in_(dit_ids)).all()
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dit_map = {d.id: d for d in dits}
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sample_match_rows = [m for m in matches if m.target_type == TargetType.SAMPLE]
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order_match_rows = [m for m in matches if m.target_type == TargetType.ORDER]
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sample_ids = [m.target_id for m in sample_match_rows]
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order_ids = [m.target_id for m in order_match_rows]
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samples = db.query(SampleRecord).filter(SampleRecord.id.in_(sample_ids)).all()
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orders = db.query(OrderRecord).filter(OrderRecord.id.in_(order_ids)).all()
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sample_lookup = {s.id: s for s in samples}
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order_lookup = {o.id: o for o in orders}
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results = []
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for dit_id, dit in dit_map.items():
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s_matches = [m for m in matches if m.dit_id == dit_id and m.target_type == TargetType.SAMPLE]
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best_sample_match = max(s_matches, key=lambda x: x.score) if s_matches else None
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sample_obj = sample_lookup.get(best_sample_match.target_id) if best_sample_match else None
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o_matches = [m for m in matches if m.dit_id == dit_id and m.target_type == TargetType.ORDER]
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best_order_match = max(o_matches, key=lambda x: x.score) if o_matches else None
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order_obj = order_lookup.get(best_order_match.target_id) if best_order_match else None
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attributed_qty = 0
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for om in o_matches:
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o = order_lookup.get(om.target_id)
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if o:
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attributed_qty += o.qty
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fulfillment_rate = round((attributed_qty / dit.eau * 100), 1) if dit.eau > 0 else 0
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dit_schema = DitSchema.model_validate(dit)
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# Handle date to string conversion if needed, Pydantic often handles date -> string automatically in JSON response
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# checking earlier 'test_server_login' response showed JSON string for 'created_at'.
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# But here I set it manually to safe string just in case
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dit_schema.date = str(dit.date) if dit.date else None
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sample_schema = None
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if sample_obj:
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sample_schema = SampleSchema.model_validate(sample_obj)
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sample_schema.date = str(sample_obj.date) if sample_obj.date else None
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order_schema = None
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if order_obj:
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order_schema = OrderSchema.model_validate(order_obj)
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results.append(AttributionRow(
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dit=dit_schema,
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sample=sample_schema,
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order=order_schema,
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match_source=best_order_match.match_source if best_order_match else (best_order_match.reason if best_order_match else None),
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attributed_qty=attributed_qty,
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fulfillment_rate=fulfillment_rate
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))
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return result
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return results
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