'commit'

Controller/YltAnalyticsController.py

@@ -0,0 +1,453 @@
+import math
+import asyncio
+import json
+from typing import List, Optional, Dict, Any
+
+from fastapi import APIRouter, HTTPException
+from fastapi.responses import StreamingResponse
+
+from DbKit.Db import Db
+from Config.Config import DB_URL
+from Util.LlmUtil import get_llm_response
+from Model.YltAnalyticsModel import (
+    StationBase,
+    CompetitorStation,
+    GeoCompetitionResponse,
+    GeoCompetitionSummary,
+    PriceSeries,
+    PriceComparisonResponse,
+    PriceComparisonSummary,
+)
+
+
+router = APIRouter()
+
+db = Db(db_url=DB_URL)
+
+
+async def init_db():
+    await db.init_db()
+
+
+async def close_db():
+    await db.close()
+
+
+@router.get("/api/ylt/stations", response_model=List[StationBase])
+async def list_ylt_stations(q: Optional[str] = None):
+    base_sql = """
+    SELECT
+        p.station_hash,
+        p.operator,
+        p.station_name,
+        p.address,
+        p.coord_x,
+        p.coord_y,
+        s.current_price
+    FROM t_station_profile_scd p
+    LEFT JOIN t_station_status_scd s
+        ON p.station_hash = s.station_hash AND s.is_current = 1
+    WHERE p.is_current = 1
+      AND p.operator = '驿来特'
+    """
+    params: Dict[str, Any] = {}
+    if q:
+        base_sql += " AND (p.station_name LIKE :kw OR p.address LIKE :kw)"
+        params["kw"] = f"%{q}%"
+    base_sql += " ORDER BY p.station_name"
+    rows = await db.find(base_sql, params)
+    result: List[StationBase] = []
+    for r in rows:
+        result.append(
+            StationBase(
+                station_hash=r.get("station_hash"),
+                operator=r.get("operator"),
+                station_name=r.get("station_name"),
+                address=r.get("address"),
+                coord_x=r.get("coord_x"),
+                coord_y=r.get("coord_y"),
+                current_price=r.get("current_price"),
+            )
+        )
+    return result
+
+
+def haversine_km(lon1: float, lat1: float, lon2: float, lat2: float) -> float:
+    r = 6371.0
+    phi1 = math.radians(lat1)
+    phi2 = math.radians(lat2)
+    d_phi = math.radians(lat2 - lat1)
+    d_lambda = math.radians(lon2 - lon1)
+    a = math.sin(d_phi / 2) ** 2 + math.cos(phi1) * math.cos(phi2) * math.sin(d_lambda / 2) ** 2
+    c = 2 * math.atan2(math.sqrt(a), math.sqrt(1 - a))
+    return r * c
+
+
+async def fetch_current_stations() -> List[dict]:
+    sql = """
+    SELECT
+        p.station_hash,
+        p.operator,
+        p.station_name,
+        p.address,
+        p.coord_x,
+        p.coord_y,
+        s.current_price
+    FROM t_station_profile_scd p
+    LEFT JOIN t_station_status_scd s
+        ON p.station_hash = s.station_hash AND s.is_current = 1
+    WHERE p.is_current = 1
+    """
+    return await db.find(sql, {})
+
+
+async def build_geo_competition(station_hash: str, radius_km: float = 3.0) -> GeoCompetitionResponse:
+    rows = await fetch_current_stations()
+    if not rows:
+        raise HTTPException(status_code=404, detail="no station data")
+    base_row = None
+    for r in rows:
+        if r.get("station_hash") == station_hash and r.get("operator") == "驿来特":
+            base_row = r
+            break
+    if base_row is None:
+        raise HTTPException(status_code=404, detail="base station not found for 驿来特")
+    base_lon = base_row.get("coord_x")
+    base_lat = base_row.get("coord_y")
+    if base_lon is None or base_lat is None:
+        raise HTTPException(status_code=400, detail="base station has no coordinates")
+    competitors: List[CompetitorStation] = []
+    ylt_price = base_row.get("current_price")
+    cheaper = 0
+    same = 0
+    more_expensive = 0
+    min_price: Optional[float] = None
+    max_price: Optional[float] = None
+    for r in rows:
+        if r.get("operator") == "驿来特":
+            continue
+        lon = r.get("coord_x")
+        lat = r.get("coord_y")
+        if lon is None or lat is None:
+            continue
+        dist = haversine_km(base_lon, base_lat, lon, lat)
+        if dist > radius_km:
+            continue
+        price = r.get("current_price")
+        competitors.append(
+            CompetitorStation(
+                station_hash=r.get("station_hash"),
+                operator=r.get("operator"),
+                station_name=r.get("station_name"),
+                distance_km=round(dist, 3),
+                current_price=price,
+            )
+        )
+        if price is not None:
+            if min_price is None or price < min_price:
+                min_price = price
+            if max_price is None or price > max_price:
+                max_price = price
+            if ylt_price is not None:
+                if price < ylt_price:
+                    cheaper += 1
+                elif price > ylt_price:
+                    more_expensive += 1
+                else:
+                    same += 1
+    base_station = StationBase(
+        station_hash=base_row.get("station_hash"),
+        operator=base_row.get("operator"),
+        station_name=base_row.get("station_name"),
+        address=base_row.get("address"),
+        coord_x=base_lon,
+        coord_y=base_lat,
+        current_price=ylt_price,
+    )
+    return GeoCompetitionResponse(
+        base_station=base_station,
+        competitors=competitors,
+        ylt_price=ylt_price,
+        min_competitor_price=min_price,
+        max_competitor_price=max_price,
+        cheaper_count=cheaper,
+        same_count=same,
+        more_expensive_count=more_expensive,
+    )
+
+
+async def fetch_station_schedule_json(station_hash: str) -> Optional[str]:
+    sql = """
+    SELECT schedule_json
+    FROM t_station_price_schedule_scd
+    WHERE station_hash = :h AND is_current = 1
+    ORDER BY valid_start_time DESC
+    LIMIT 1
+    """
+    rows = await db.find(sql, {"h": station_hash})
+    if not rows:
+        return None
+    value = rows[0].get("schedule_json")
+    if value is None:
+        return None
+    if isinstance(value, str):
+        return value
+    try:
+        return json.dumps(value, ensure_ascii=False)
+    except Exception:
+        return None
+
+
+def extract_price_from_item(item: Dict[str, Any]) -> Optional[float]:
+    if not isinstance(item, dict):
+        return None
+    for key in ("price", "price_kwh", "priceKwh", "total_price", "totalPrice"):
+        v = item.get(key)
+        if isinstance(v, (int, float)):
+            return float(v)
+    elec = item.get("elec_price")
+    service = item.get("service_price")
+    if isinstance(elec, (int, float)) and isinstance(service, (int, float)):
+        return float(elec) + float(service)
+    elec2 = item.get("electric_fee_kwh")
+    service2 = item.get("service_fee_kwh")
+    if isinstance(elec2, (int, float)) and isinstance(service2, (int, float)):
+        return float(elec2) + float(service2)
+    elec3 = item.get("ele_fee")
+    service3 = item.get("ser_fee")
+    if isinstance(elec3, (int, float)) and isinstance(service3, (int, float)):
+        return float(elec3) + float(service3)
+    return None
+
+
+def parse_hour_from_item(item: Dict[str, Any], default_index: int) -> Optional[int]:
+    start = item.get("start")
+    if isinstance(start, str) and ":" in start:
+        parts = start.split(":")
+        try:
+            h = int(parts[0])
+            if 0 <= h <= 23:
+                return h
+        except Exception:
+            pass
+    end = item.get("end")
+    if isinstance(end, str) and ":" in end:
+        parts = end.split(":")
+        try:
+            h2 = int(parts[0])
+            if 0 < h2 <= 24:
+                return h2 - 1
+        except Exception:
+            pass
+    if 0 <= default_index <= 23:
+        return default_index
+    return None
+
+
+def extract_hourly_prices(schedule_json_str: str) -> List[Optional[float]]:
+    series: List[Optional[float]] = [None] * 24
+    if not schedule_json_str:
+        return series
+    try:
+        data = json.loads(schedule_json_str)
+    except Exception:
+        return series
+    if not isinstance(data, list):
+        return series
+    for idx, item in enumerate(data):
+        price = extract_price_from_item(item)
+        if price is None:
+            continue
+        hour_idx = parse_hour_from_item(item, idx)
+        if hour_idx is None or not (0 <= hour_idx < 24):
+            continue
+        series[hour_idx] = float(price)
+    return series
+
+
+async def build_price_comparison(station_hash: str) -> PriceComparisonResponse:
+    geo = await build_geo_competition(station_hash)
+    base_station = geo.base_station
+    base_schedule_str = await fetch_station_schedule_json(base_station.station_hash)
+    if base_schedule_str is None:
+        raise HTTPException(status_code=404, detail="no price schedule for YLT station")
+    ylt_series = extract_hourly_prices(base_schedule_str)
+    hours = list(range(24))
+    operator_series_sum: Dict[str, List[float]] = {}
+    operator_series_count: Dict[str, List[int]] = {}
+    for comp in geo.competitors:
+        schedule_str = await fetch_station_schedule_json(comp.station_hash)
+        if not schedule_str:
+            continue
+        series = extract_hourly_prices(schedule_str)
+        op = comp.operator
+        if op not in operator_series_sum:
+            operator_series_sum[op] = [0.0] * 24
+            operator_series_count[op] = [0] * 24
+        sums = operator_series_sum[op]
+        counts = operator_series_count[op]
+        for i in range(24):
+            v = series[i]
+            if v is None:
+                continue
+            sums[i] += v
+            counts[i] += 1
+    competitors_series: List[PriceSeries] = []
+    for op, sums in operator_series_sum.items():
+        counts = operator_series_count[op]
+        avg_series: List[Optional[float]] = []
+        for i in range(24):
+            c = counts[i]
+            if c > 0:
+                avg_series.append(sums[i] / c)
+            else:
+                avg_series.append(None)
+        competitors_series.append(PriceSeries(operator=op, series=avg_series))
+    diffs: List[float] = []
+    for i in range(24):
+        y = ylt_series[i]
+        if y is None:
+            continue
+        competitor_prices: List[float] = []
+        for s in competitors_series:
+            v = s.series[i]
+            if v is not None:
+                competitor_prices.append(float(v))
+        if not competitor_prices:
+            continue
+        min_comp = min(competitor_prices)
+        diffs.append(y - min_comp)
+    min_diff = min(diffs) if diffs else None
+    max_diff = max(diffs) if diffs else None
+    avg_diff = sum(diffs) / len(diffs) if diffs else None
+    ylt_price_series = PriceSeries(operator=base_station.operator, series=ylt_series)
+    return PriceComparisonResponse(
+        hours=hours,
+        ylt=ylt_price_series,
+        competitors=competitors_series,
+        min_diff=min_diff,
+        max_diff=max_diff,
+        avg_diff=avg_diff,
+    )
+
+
+@router.get("/health")
+async def health():
+    return {"status": "ok"}
+
+
+@router.get("/api/ylt/geo/competitors/{station_hash}", response_model=GeoCompetitionResponse)
+async def get_geo_competitors(station_hash: str):
+    return await build_geo_competition(station_hash)
+
+
+@router.get("/api/ylt/geo/competitors/{station_hash}/summary", response_model=GeoCompetitionSummary)
+async def get_geo_competitors_summary(station_hash: str):
+    data = await build_geo_competition(station_hash)
+    base = data.base_station
+    total_comp = len(data.competitors)
+    cheaper = data.cheaper_count
+    same = data.same_count
+    more_expensive = data.more_expensive_count
+    ylt_price = data.ylt_price
+    min_price = data.min_competitor_price
+    max_price = data.max_competitor_price
+    summary_input = {
+        "station_name": base.station_name,
+        "operator": base.operator,
+        "ylt_price": ylt_price,
+        "competitor_count": total_comp,
+        "cheaper_count": cheaper,
+        "same_count": same,
+        "more_expensive_count": more_expensive,
+        "min_competitor_price": min_price,
+        "max_competitor_price": max_price,
+    }
+    text = (
+        "请作为驿来特价格策略分析顾问，用简明中文解释当前场站在3公里范围内的价格竞争情况，"
+        "给出可操作的价格调整或产品策略建议，控制在300字以内。以下是结构化数据：\n"
+        f"{summary_input}"
+    )
+    chunks: List[str] = []
+    async for chunk in get_llm_response(
+        text,
+        stream=False,
+        system_prompt="你是驿来特电价和选址策略顾问。",
+    ):
+        chunks.append(chunk)
+    summary_text = "".join(chunks)
+    return GeoCompetitionSummary(summary=summary_text)
+
+
+@router.get("/api/ylt/pricing/comparison/{station_hash}", response_model=PriceComparisonResponse)
+async def get_price_comparison(station_hash: str):
+    return await build_price_comparison(station_hash)
+
+
+@router.get("/api/ylt/pricing/comparison/{station_hash}/summary", response_model=PriceComparisonSummary)
+async def get_price_comparison_summary(station_hash: str):
+    data = await build_price_comparison(station_hash)
+    ylt_series = data.ylt.series
+    text_data = {
+        "hours": data.hours,
+        "ylt_prices": ylt_series,
+        "competitors": [
+            {"operator": s.operator, "series": s.series} for s in data.competitors
+        ],
+        "min_diff": data.min_diff,
+        "max_diff": data.max_diff,
+        "avg_diff": data.avg_diff,
+    }
+    text = (
+        "请作为驿来特价格策略分析顾问，对下列分时电价数据进行比较分析：\n"
+        "1) 解释驿来特与三家竞品在一天24小时内的价格差距特征；\n"
+        "2) 指出在哪些时间段我们明显偏贵、在哪些时间段有优势；\n"
+        "3) 给出2到3条可执行的调价或营销策略建议；\n"
+        "控制在400字以内。数据如下：\n"
+        f"{text_data}"
+    )
+    chunks: List[str] = []
+    async for chunk in get_llm_response(
+        text,
+        stream=False,
+        system_prompt="你是驿来特电价策略分析顾问。",
+    ):
+        chunks.append(chunk)
+    summary_text = "".join(chunks)
+    return PriceComparisonSummary(summary=summary_text)
+
+
+@router.get("/api/ylt/pricing/comparison/{station_hash}/sse")
+async def stream_price_comparison_summary(station_hash: str):
+    data = await build_price_comparison(station_hash)
+    text_data = {
+        "hours": data.hours,
+        "ylt_prices": data.ylt.series,
+        "competitors": [
+            {"operator": s.operator, "series": s.series} for s in data.competitors
+        ],
+        "min_diff": data.min_diff,
+        "max_diff": data.max_diff,
+        "avg_diff": data.avg_diff,
+    }
+    text = (
+        "请作为驿来特价格策略分析顾问，对下列分时电价数据进行比较分析：\n"
+        "1) 解释驿来特与三家竞品在一天24小时内的价格差距特征；\n"
+        "2) 指出在哪些时间段我们明显偏贵、在哪些时间段有优势；\n"
+        "3) 给出2到3条可执行的调价或营销策略建议；\n"
+        "控制在400字以内。数据如下：\n"
+        f"{text_data}"
+    )
+
+    async def event_generator():
+        async for chunk in get_llm_response(
+            text,
+            stream=True,
+            system_prompt="你是驿来特电价策略分析顾问。",
+        ):
+            if chunk is None:
+                continue
+            yield f"data: {chunk}\n\n"
+        yield "event: end\ndata: [DONE]\n\n"
+
+    return StreamingResponse(event_generator(), media_type="text/event-stream")