feat: Implement new bot architecture including handlers, services, analysis modules, and comprehensive tests.

src/bot/analysis/__init__.py

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+"""Bot analysis services."""
+

src/bot/analysis/city_analysis_service.py

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+from __future__ import annotations
+
+from typing import Any
+
+
+class CityAnalysisService:
+    """City analysis adapter with lazy imports to trim cold startup."""
+
+    def __init__(self, weather: Any):
+        self.weather = weather
+
+    def resolve_city(self, city_input: str):
+        from src.analysis.city_query_service import resolve_city_name
+
+        return resolve_city_name(city_input)
+
+    def build_city_report(self, city_name: str, city_query_cost: int) -> str:
+        coords = self.weather.get_coordinates(city_name)
+        if not coords:
+            raise ValueError(f"未找到城市坐标: {city_name}")
+
+        weather_data = self.weather.fetch_all_sources(
+            city_name,
+            lat=coords["lat"],
+            lon=coords["lon"],
+            force_refresh=True,
+        )
+
+        from src.analysis.city_query_service import build_city_query_report
+
+        return build_city_query_report(
+            city_name=city_name,
+            weather_data=weather_data,
+            city_query_cost=city_query_cost,
+        )
+

src/bot/analysis/deb_analysis_service.py

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+from __future__ import annotations
+
+import os
+from datetime import datetime as _dt
+from datetime import timedelta as _td
+
+
+class DebAnalysisService:
+    """DEB analytics adapter with lazy imports to trim cold startup."""
+
+    def __init__(self, project_root: str):
+        self.project_root = project_root
+        self.history_file = os.path.join(project_root, "data", "daily_records.json")
+
+    @staticmethod
+    def _load_aliases() -> dict[str, str]:
+        from src.data_collection.city_registry import ALIASES
+
+        return ALIASES
+
+    @staticmethod
+    def _load_deb_module_api():
+        from src.analysis.deb_algorithm import (
+            _is_excluded_model_name,
+            load_history,
+            reconcile_recent_actual_highs,
+        )
+
+        return _is_excluded_model_name, load_history, reconcile_recent_actual_highs
+
+    def resolve_city(self, city_input: str) -> str:
+        aliases = self._load_aliases()
+        city_input_norm = city_input.strip().lower()
+        return aliases.get(city_input_norm, city_input_norm)
+
+    def has_history(self, city_name: str) -> bool:
+        _is_excluded_model_name, load_history, reconcile_recent_actual_highs = (
+            self._load_deb_module_api()
+        )
+        del _is_excluded_model_name, reconcile_recent_actual_highs
+        data = load_history(self.history_file)
+        city_data = data.get(city_name)
+        return isinstance(city_data, dict) and bool(city_data)
+
+    def build_deb_accuracy_report(self, city_name: str, deb_query_cost: int) -> str:
+        _is_excluded_model_name, load_history, reconcile_recent_actual_highs = (
+            self._load_deb_module_api()
+        )
+        data = load_history(self.history_file)
+        if city_name not in data or not data[city_name]:
+            raise ValueError(f"暂无 {city_name} 的历史数据。")
+
+        reconcile_info = reconcile_recent_actual_highs(city_name, lookback_days=7)
+        data = load_history(self.history_file)
+        city_data = data[city_name]
+        today = _dt.now().date()
+        today_str = today.strftime("%Y-%m-%d")
+        cutoff_date = today - _td(days=6)
+
+        recent_items = []
+        for date_str, record in city_data.items():
+            try:
+                row_date = _dt.strptime(date_str, "%Y-%m-%d").date()
+            except Exception:
+                continue
+            if row_date >= cutoff_date:
+                recent_items.append((date_str, record, row_date))
+
+        recent_items.sort(key=lambda item: item[0])
+
+        lines = [
+            f"📊 <b>DEB 准确率报告 - {city_name.title()}</b>",
+            "",
+            "📅 <b>近日记录：</b>",
+        ]
+        if (
+            isinstance(reconcile_info, dict)
+            and reconcile_info.get("ok")
+            and int(reconcile_info.get("updated") or 0) > 0
+        ):
+            lines.extend(
+                [
+                    f"🔁 已用 METAR 历史回填修正 {int(reconcile_info.get('updated'))} 天实测最高温",
+                    "",
+                ]
+            )
+        total_days = 0
+        hits = 0
+        deb_errors = []
+        signed_errors = []
+        model_errors: dict[str, list[float]] = {}
+
+        for date_str, record, _row_date in recent_items:
+            actual = record.get("actual_high")
+            deb_pred = record.get("deb_prediction")
+            forecasts = record.get("forecasts", {}) or {}
+
+            if actual is None:
+                continue
+
+            try:
+                actual = float(actual)
+                if deb_pred is not None:
+                    deb_pred = float(deb_pred)
+            except Exception:
+                continue
+
+            if deb_pred is None and forecasts:
+                valid_preds = [
+                    float(v)
+                    for k, v in forecasts.items()
+                    if v is not None and not _is_excluded_model_name(k)
+                ]
+                if valid_preds:
+                    deb_pred = round(sum(valid_preds) / len(valid_preds), 1)
+
+            actual_wu = round(actual)
+
+            if date_str == today_str:
+                lines.append(f"  {date_str}: 📍 今天进行中 (实测暂 {actual:.1f})")
+            elif deb_pred is not None:
+                total_days += 1
+                deb_wu = round(deb_pred)
+                hit = deb_wu == actual_wu
+                if hit:
+                    hits += 1
+                err = deb_pred - actual
+                deb_errors.append(abs(err))
+                signed_errors.append(err)
+
+                if hit:
+                    result_icon = "✅"
+                    err_text = f"偏差{abs(err):.1f}°"
+                elif err < 0:
+                    result_icon = "❌"
+                    err_text = f"低估{abs(err):.1f}°"
+                else:
+                    result_icon = "❌"
+                    err_text = f"高估{abs(err):.1f}°"
+
+                retro = "≈" if "deb_prediction" not in record else ""
+                lines.append(
+                    f"  {date_str}: DEB {retro}{deb_pred:.1f}→{deb_wu} vs 实测 {actual:.1f}→{actual_wu} "
+                    f"{result_icon} {err_text}"
+                )
+
+            if date_str != today_str and actual is not None:
+                for model, pred in forecasts.items():
+                    if _is_excluded_model_name(model):
+                        continue
+                    if pred is None:
+                        continue
+                    try:
+                        model_errors.setdefault(model, []).append(abs(float(pred) - actual))
+                    except Exception:
+                        continue
+
+        if total_days > 0:
+            hit_rate = hits / total_days * 100
+            deb_mae = sum(deb_errors) / len(deb_errors)
+            lines.append("")
+            lines.append(
+                f"🏁 <b>DEB 总战绩：</b>WU命中 {hits}/{total_days} (<b>{hit_rate:.0f}%</b>) | MAE: {deb_mae:.1f}°"
+            )
+
+            if model_errors:
+                lines.append("")
+                lines.append("📈 <b>模型 MAE 对比：</b>")
+                model_maes = {m: sum(e) / len(e) for m, e in model_errors.items() if e}
+                sorted_models = sorted(model_maes.items(), key=lambda item: item[1])
+                for model, mae in sorted_models:
+                    tag = " ⭐" if mae <= deb_mae else ""
+                    lines.append(f"  {model}: {mae:.1f}°{tag}")
+                lines.append(f"  <b>DEB融合: {deb_mae:.1f}°</b>")
+
+            mean_bias = sum(signed_errors) / len(signed_errors)
+            underest = sum(1 for e in signed_errors if e < -0.3)
+            overest = sum(1 for e in signed_errors if e > 0.3)
+            accurate = total_days - underest - overest
+
+            lines.append("")
+            lines.append("🔍 <b>偏差分析：</b>")
+            if abs(mean_bias) > 0.3:
+                bias_label = "系统性低估" if mean_bias < 0 else "系统性高估"
+                lines.append(f"  ⚠️ {bias_label}：平均偏差 {mean_bias:+.1f}°")
+            else:
+                lines.append(f"  ✅ 整体无明显系统偏差：平均偏差 {mean_bias:+.1f}°")
+            lines.append(f"  (低估 {underest} 次 | 高估 {overest} 次 | 准确 {accurate} 次)")
+
+            lines.append("")
+            lines.append("💡 <b>建议：</b>")
+            if underest > overest and abs(mean_bias) > 0.5:
+                lines.append(
+                    f"  该城市模型集体低估趋势明显（{mean_bias:+.1f}°），实际最高温可能比 DEB 融合值高 "
+                    f"{abs(mean_bias):.0f}-{abs(mean_bias) + 0.5:.0f}°。交易时建议适当看高。"
+                )
+            elif overest > underest and abs(mean_bias) > 0.5:
+                lines.append(
+                    f"  该城市模型集体高估趋势明显（{mean_bias:+.1f}°），实际最高温可能低于 DEB 融合值。交易时注意追高风险。"
+                )
+            elif deb_mae > 1.5:
+                lines.append(
+                    f"  近期模型波动较大（MAE {deb_mae:.1f}°），建议降低对单一日预测的信任度。"
+                )
+            elif hit_rate >= 60:
+                lines.append("  DEB 近期表现稳定，可继续作为主要参考。")
+            else:
+                lines.append("  近期准确率一般，建议结合主站实测与周边站点共同判断。")
+
+            lines.append("")
+            lines.append("📝 MAE = 平均绝对误差，越小越准。⭐ = 优于 DEB 融合。")
+            lines.append("📅 统计窗口：近7天滚动样本。")
+        else:
+            lines.append("")
+            lines.append("🔔 近 7 天尚无完整的 DEB 预测记录。")
+
+        lines.append("")
+        lines.append(f"💸 本次消耗 <code>{deb_query_cost}</code> 积分。")
+        return "\n".join(lines)
+