diff --git a/routes/daily_sales_routes.py b/routes/daily_sales_routes.py
index 35f433d..929f1ed 100644
--- a/routes/daily_sales_routes.py
+++ b/routes/daily_sales_routes.py
@@ -17,6 +17,12 @@ import pandas as pd
 from config import BASE_DIR
 from database.manager import DatabaseManager
 from services.logger_manager import SystemLogger
+from utils.df_helpers import find_col
+from services.daily_sales_service import (
+    get_taiwan_holiday,
+    prepare_calendar_data,
+    prepare_marketing_summary,
+)
 
 # 時區設定
 TAIPEI_TZ = timezone(timedelta(hours=8))
@@ -68,15 +74,6 @@ def _is_cache_valid(cache_key):
 # 輔助函數
 # ==========================================
 
-def find_col(df_cols, keywords):
-    """從欄位列表中，根據關鍵字列表找出最匹配的欄位名稱"""
-    for k in keywords:
-        for col in df_cols:
-            if k in str(col):
-                return col
-    return None
-
-
 def validate_table_name(table_name):
     """驗證表名（防止 SQL Injection）"""
     import re
@@ -360,239 +357,6 @@ def prepare_category_summary(df, date_str=None, is_month_view=False, month_start
     return category_df.to_dict('records')
 
 
-def prepare_marketing_summary(df, selected_date=None, is_month_view=False, month_start=None, month_end=None, sort_by='revenue'):
-    """準備行銷活動業績貢獻數據"""
-    if is_month_view and month_start is not None and month_end is not None:
-        target_df = df[(df['snapshot_date'] >= month_start) & (df['snapshot_date'] <= month_end)]
-    elif selected_date is not None:
-        target_df = df[df['snapshot_date'] == selected_date]
-    else:
-        target_df = df
-
-    if target_df.empty:
-        return {'coupon': [], 'discount': [], 'bonus': [], 'click': []}
-
-    cols = target_df.columns.tolist()
-    col_amount = find_col(cols, ['銷售金額', '業績', '金額', '總業績'])
-    col_qty = find_col(cols, ['銷售數量', '銷量', '數量', 'Qty'])
-    col_profit = find_col(cols, ['毛利', 'Profit', '利潤'])
-    col_cost = find_col(cols, ['成本', 'Cost', '總成本'])
-
-    if not col_amount:
-        return {'coupon': [], 'discount': [], 'bonus': [], 'click': []}
-
-    marketing_cols = {
-        'coupon': '折價券活動名稱',
-        'discount': '折扣活動名稱',
-        'bonus': '滿額再折扣活動名稱',
-        'click': '點我再折扣'
-    }
-
-    result = {}
-    actual_sort_key = sort_by if sort_by in ['revenue', 'qty', 'profit'] else 'revenue'
-
-    for key, col_name in marketing_cols.items():
-        if col_name not in cols:
-            result[key] = []
-            continue
-
-        activity_df = target_df[
-            (target_df[col_name].notna()) &
-            (target_df[col_name] != '') &
-            (target_df[col_name] != '0') &
-            (target_df[col_name] != 0)
-        ]
-
-        if activity_df.empty:
-            result[key] = []
-            continue
-
-        agg_args = {
-            'revenue': (col_amount, 'sum'),
-            'order_count': (col_amount, 'count')
-        }
-        if col_qty:
-            agg_args['qty'] = (col_qty, 'sum')
-        if col_profit:
-            agg_args['profit'] = (col_profit, 'sum')
-
-        grouped = activity_df.groupby(col_name).agg(**agg_args).reset_index()
-
-        if 'profit' not in agg_args and col_cost:
-            cost_agg = activity_df.groupby(col_name)[col_cost].sum().reset_index()
-            grouped = grouped.merge(cost_agg, on=col_name)
-            grouped['profit'] = grouped['revenue'] - grouped[col_cost]
-
-        grouped = grouped.rename(columns={col_name: 'name'})
-
-        sort_col = actual_sort_key if actual_sort_key in grouped.columns else 'revenue'
-        grouped = grouped.sort_values(sort_col, ascending=False).head(15)
-
-        records = []
-        for _, row in grouped.iterrows():
-            record = {
-                'name': str(row['name'])[:50],
-                'revenue': float(row['revenue']),
-                'order_count': int(row['order_count'])
-            }
-            if 'qty' in row:
-                record['qty'] = float(row['qty'])
-            if 'profit' in row:
-                record['profit'] = float(row['profit'])
-            records.append(record)
-
-        result[key] = records
-
-    return result
-
-
-def get_taiwan_holiday(date):
-    """判斷是否為台灣國定假日"""
-    year = date.year
-    month = date.month
-    day = date.day
-
-    holidays_2026 = {
-        (1, 1): '元旦',
-        (2, 14): '春節連假', (2, 15): '小年夜', (2, 16): '除夕',
-        (2, 17): '春節 (初一)', (2, 18): '春節 (初二)', (2, 19): '春節 (初三)',
-        (2, 20): '春節連假', (2, 21): '春節連假', (2, 22): '春節連假',
-        (2, 28): '和平紀念日', (3, 2): '和平紀念日補假',
-        (4, 3): '兒童節補假', (4, 4): '清明節', (4, 5): '清明節連假', (4, 6): '清明節補假',
-        (5, 1): '勞動節',
-        (6, 19): '端午節',
-        (9, 25): '中秋節', (9, 28): '教師節',
-        (10, 9): '國慶日補假', (10, 10): '國慶日',
-        (10, 25): '臺灣光復節', (10, 26): '光復節補假',
-        (12, 25): '行憲紀念日',
-    }
-
-    holidays_2027 = {
-        (1, 1): '元旦',
-        (2, 11): '春節 (除夕)', (2, 12): '春節 (初一)', (2, 13): '春節 (初二)',
-        (2, 14): '春節 (初三)', (2, 15): '春節 (初四)', (2, 16): '春節 (初五)', (2, 17): '春節 (初六)',
-        (2, 28): '和平紀念日',
-        (4, 4): '清明節', (4, 5): '清明節連假',
-        (6, 14): '端午節',
-        (9, 21): '中秋節',
-        (10, 10): '國慶日', (10, 11): '國慶日連假',
-    }
-
-    holidays = holidays_2026 if year == 2026 else (holidays_2027 if year == 2027 else {})
-    holiday_name = holidays.get((month, day))
-    return (True, holiday_name) if holiday_name else (False, None)
-
-
-def prepare_calendar_data(df, selected_month):
-    """準備行事曆數據"""
-    year = selected_month.year
-    month = selected_month.month
-
-    first_day = pd.Timestamp(year=year, month=month, day=1)
-    last_day = pd.Timestamp(year=year, month=month, day=calendar.monthrange(year, month)[1])
-
-    first_weekday = first_day.weekday()
-    calendar_start = first_day - timedelta(days=first_weekday)
-    last_weekday = last_day.weekday()
-    calendar_end = last_day + timedelta(days=(6 - last_weekday))
-
-    data_start = first_day - timedelta(days=1)
-    data_end = last_day
-    month_df = df[(df['snapshot_date'] >= data_start) & (df['snapshot_date'] <= data_end)]
-
-    cols = df.columns.tolist()
-    col_amount = find_col(cols, ['銷售金額', '業績', '金額', '總業績'])
-    col_cost = find_col(cols, ['成本', 'Cost'])
-    col_profit = find_col(cols, ['毛利', 'Profit'])
-    col_qty = find_col(cols, ['銷售數量', '銷量', 'Qty', '數量'])
-    col_name = find_col(cols, ['商品名稱', '品名'])
-
-    calendar_days = []
-    current_date = calendar_start
-
-    while current_date <= calendar_end:
-        weekday = current_date.weekday()
-        weekday_names = ['週一', '週二', '週三', '週四', '週五', '週六', '週日']
-
-        is_holiday, holiday_name = get_taiwan_holiday(current_date)
-
-        day_data = {
-            'date': current_date.strftime('%Y-%m-%d'),
-            'day': current_date.day,
-            'weekday': weekday_names[weekday],
-            'is_weekend': weekday >= 5,
-            'is_holiday': is_holiday,
-            'holiday_name': holiday_name,
-            'is_current_month': current_date.month == month,
-            'has_data': False,
-            'revenue': 0,
-            'profit': 0,
-            'margin_rate': 0,
-            'sku_count': 0,
-            'qty': 0,
-            'avg_price': 0,
-            'dod_percent': 0,
-            'dod_direction': 'neutral'
-        }
-
-        if first_day <= current_date <= last_day:
-            day_df = month_df[month_df['snapshot_date'] == current_date]
-
-            if not day_df.empty:
-                day_data['has_data'] = True
-
-                if col_amount:
-                    day_data['revenue'] = float(day_df[col_amount].sum())
-
-                if col_profit:
-                    day_data['profit'] = float(day_df[col_profit].sum())
-                elif col_cost and col_amount:
-                    total_cost = float(day_df[col_cost].sum())
-                    day_data['profit'] = day_data['revenue'] - total_cost
-
-                if day_data['revenue'] > 0:
-                    day_data['margin_rate'] = (day_data['profit'] / day_data['revenue']) * 100
-
-                if col_qty:
-                    day_data['qty'] = float(day_df[col_qty].sum())
-
-                if day_data['qty'] > 0:
-                    day_data['avg_price'] = day_data['revenue'] / day_data['qty']
-
-                if col_name:
-                    day_data['sku_count'] = int(day_df[col_name].nunique())
-
-                # DoD%
-                prev_date = current_date - timedelta(days=1)
-                prev_df = month_df[month_df['snapshot_date'] == prev_date]
-
-                if not prev_df.empty and col_amount:
-                    prev_revenue = float(prev_df[col_amount].sum())
-                    if prev_revenue > 0:
-                        dod = ((day_data['revenue'] - prev_revenue) / prev_revenue) * 100
-                        day_data['dod_percent'] = round(dod, 1)
-                        day_data['dod_direction'] = 'up' if dod >= 0 else 'down'
-
-        calendar_days.append(day_data)
-        current_date += timedelta(days=1)
-
-    weeks = []
-    for i in range(0, len(calendar_days), 7):
-        weeks.append(calendar_days[i:i + 7])
-
-    prev_month = selected_month - pd.DateOffset(months=1)
-    next_month = selected_month + pd.DateOffset(months=1)
-
-    return {
-        'year': year,
-        'month': month,
-        'month_name': selected_month.strftime('%Y年%m月'),
-        'weeks': weeks,
-        'prev_month': prev_month.strftime('%Y-%m'),
-        'next_month': next_month.strftime('%Y-%m')
-    }
-
-
 # ==========================================
 # 頁面路由
 # ==========================================
diff --git a/services/daily_sales_service.py b/services/daily_sales_service.py
new file mode 100644
index 0000000..570b63b
--- /dev/null
+++ b/services/daily_sales_service.py
@@ -0,0 +1,243 @@
+"""日報業務邏輯 — 從 routes/daily_sales_routes.py 抽出的純計算函數。
+
+這些函數不依賴 Flask request context，可獨立測試。
+"""
+import calendar
+from datetime import timedelta
+
+import pandas as pd
+
+from utils.df_helpers import find_col
+
+
+def get_taiwan_holiday(date):
+    """判斷是否為台灣國定假日"""
+    year = date.year
+    month = date.month
+    day = date.day
+
+    holidays_2026 = {
+        (1, 1): '元旦',
+        (2, 14): '春節連假', (2, 15): '小年夜', (2, 16): '除夕',
+        (2, 17): '春節 (初一)', (2, 18): '春節 (初二)', (2, 19): '春節 (初三)',
+        (2, 20): '春節連假', (2, 21): '春節連假', (2, 22): '春節連假',
+        (2, 28): '和平紀念日', (3, 2): '和平紀念日補假',
+        (4, 3): '兒童節補假', (4, 4): '清明節', (4, 5): '清明節連假', (4, 6): '清明節補假',
+        (5, 1): '勞動節',
+        (6, 19): '端午節',
+        (9, 25): '中秋節', (9, 28): '教師節',
+        (10, 9): '國慶日補假', (10, 10): '國慶日',
+        (10, 25): '臺灣光復節', (10, 26): '光復節補假',
+        (12, 25): '行憲紀念日',
+    }
+
+    holidays_2027 = {
+        (1, 1): '元旦',
+        (2, 11): '春節 (除夕)', (2, 12): '春節 (初一)', (2, 13): '春節 (初二)',
+        (2, 14): '春節 (初三)', (2, 15): '春節 (初四)', (2, 16): '春節 (初五)', (2, 17): '春節 (初六)',
+        (2, 28): '和平紀念日',
+        (4, 4): '清明節', (4, 5): '清明節連假',
+        (6, 14): '端午節',
+        (9, 21): '中秋節',
+        (10, 10): '國慶日', (10, 11): '國慶日連假',
+    }
+
+    holidays = holidays_2026 if year == 2026 else (holidays_2027 if year == 2027 else {})
+    holiday_name = holidays.get((month, day))
+    return (True, holiday_name) if holiday_name else (False, None)
+
+
+def prepare_calendar_data(df, selected_month):
+    """準備行事曆數據"""
+    year = selected_month.year
+    month = selected_month.month
+
+    first_day = pd.Timestamp(year=year, month=month, day=1)
+    last_day = pd.Timestamp(year=year, month=month, day=calendar.monthrange(year, month)[1])
+
+    first_weekday = first_day.weekday()
+    calendar_start = first_day - timedelta(days=first_weekday)
+    last_weekday = last_day.weekday()
+    calendar_end = last_day + timedelta(days=(6 - last_weekday))
+
+    data_start = first_day - timedelta(days=1)
+    data_end = last_day
+    month_df = df[(df['snapshot_date'] >= data_start) & (df['snapshot_date'] <= data_end)]
+
+    cols = df.columns.tolist()
+    col_amount = find_col(cols, ['銷售金額', '業績', '金額', '總業績'])
+    col_cost = find_col(cols, ['成本', 'Cost'])
+    col_profit = find_col(cols, ['毛利', 'Profit'])
+    col_qty = find_col(cols, ['銷售數量', '銷量', 'Qty', '數量'])
+    col_name = find_col(cols, ['商品名稱', '品名'])
+
+    calendar_days = []
+    current_date = calendar_start
+
+    while current_date <= calendar_end:
+        weekday = current_date.weekday()
+        weekday_names = ['週一', '週二', '週三', '週四', '週五', '週六', '週日']
+
+        is_holiday, holiday_name = get_taiwan_holiday(current_date)
+
+        day_data = {
+            'date': current_date.strftime('%Y-%m-%d'),
+            'day': current_date.day,
+            'weekday': weekday_names[weekday],
+            'is_weekend': weekday >= 5,
+            'is_holiday': is_holiday,
+            'holiday_name': holiday_name,
+            'is_current_month': current_date.month == month,
+            'has_data': False,
+            'revenue': 0,
+            'profit': 0,
+            'margin_rate': 0,
+            'sku_count': 0,
+            'qty': 0,
+            'avg_price': 0,
+            'dod_percent': 0,
+            'dod_direction': 'neutral'
+        }
+
+        if first_day <= current_date <= last_day:
+            day_df = month_df[month_df['snapshot_date'] == current_date]
+
+            if not day_df.empty:
+                day_data['has_data'] = True
+
+                if col_amount:
+                    day_data['revenue'] = float(day_df[col_amount].sum())
+
+                if col_profit:
+                    day_data['profit'] = float(day_df[col_profit].sum())
+                elif col_cost and col_amount:
+                    total_cost = float(day_df[col_cost].sum())
+                    day_data['profit'] = day_data['revenue'] - total_cost
+
+                if day_data['revenue'] > 0:
+                    day_data['margin_rate'] = (day_data['profit'] / day_data['revenue']) * 100
+
+                if col_qty:
+                    day_data['qty'] = float(day_df[col_qty].sum())
+
+                if day_data['qty'] > 0:
+                    day_data['avg_price'] = day_data['revenue'] / day_data['qty']
+
+                if col_name:
+                    day_data['sku_count'] = int(day_df[col_name].nunique())
+
+                # DoD%
+                prev_date = current_date - timedelta(days=1)
+                prev_df = month_df[month_df['snapshot_date'] == prev_date]
+
+                if not prev_df.empty and col_amount:
+                    prev_revenue = float(prev_df[col_amount].sum())
+                    if prev_revenue > 0:
+                        dod = ((day_data['revenue'] - prev_revenue) / prev_revenue) * 100
+                        day_data['dod_percent'] = round(dod, 1)
+                        day_data['dod_direction'] = 'up' if dod >= 0 else 'down'
+
+        calendar_days.append(day_data)
+        current_date += timedelta(days=1)
+
+    weeks = []
+    for i in range(0, len(calendar_days), 7):
+        weeks.append(calendar_days[i:i + 7])
+
+    prev_month = selected_month - pd.DateOffset(months=1)
+    next_month = selected_month + pd.DateOffset(months=1)
+
+    return {
+        'year': year,
+        'month': month,
+        'month_name': selected_month.strftime('%Y年%m月'),
+        'weeks': weeks,
+        'prev_month': prev_month.strftime('%Y-%m'),
+        'next_month': next_month.strftime('%Y-%m')
+    }
+
+
+def prepare_marketing_summary(df, selected_date=None, is_month_view=False, month_start=None, month_end=None, sort_by='revenue'):
+    """準備行銷活動業績貢獻數據"""
+    if is_month_view and month_start is not None and month_end is not None:
+        target_df = df[(df['snapshot_date'] >= month_start) & (df['snapshot_date'] <= month_end)]
+    elif selected_date is not None:
+        target_df = df[df['snapshot_date'] == selected_date]
+    else:
+        target_df = df
+
+    if target_df.empty:
+        return {'coupon': [], 'discount': [], 'bonus': [], 'click': []}
+
+    cols = target_df.columns.tolist()
+    col_amount = find_col(cols, ['銷售金額', '業績', '金額', '總業績'])
+    col_qty = find_col(cols, ['銷售數量', '銷量', '數量', 'Qty'])
+    col_profit = find_col(cols, ['毛利', 'Profit', '利潤'])
+    col_cost = find_col(cols, ['成本', 'Cost', '總成本'])
+
+    if not col_amount:
+        return {'coupon': [], 'discount': [], 'bonus': [], 'click': []}
+
+    marketing_cols = {
+        'coupon': '折價券活動名稱',
+        'discount': '折扣活動名稱',
+        'bonus': '滿額再折扣活動名稱',
+        'click': '點我再折扣'
+    }
+
+    result = {}
+    actual_sort_key = sort_by if sort_by in ['revenue', 'qty', 'profit'] else 'revenue'
+
+    for key, col_name in marketing_cols.items():
+        if col_name not in cols:
+            result[key] = []
+            continue
+
+        activity_df = target_df[
+            (target_df[col_name].notna()) &
+            (target_df[col_name] != '') &
+            (target_df[col_name] != '0') &
+            (target_df[col_name] != 0)
+        ]
+
+        if activity_df.empty:
+            result[key] = []
+            continue
+
+        agg_args = {
+            'revenue': (col_amount, 'sum'),
+            'order_count': (col_amount, 'count')
+        }
+        if col_qty:
+            agg_args['qty'] = (col_qty, 'sum')
+        if col_profit:
+            agg_args['profit'] = (col_profit, 'sum')
+
+        grouped = activity_df.groupby(col_name).agg(**agg_args).reset_index()
+
+        if 'profit' not in agg_args and col_cost:
+            cost_agg = activity_df.groupby(col_name)[col_cost].sum().reset_index()
+            grouped = grouped.merge(cost_agg, on=col_name)
+            grouped['profit'] = grouped['revenue'] - grouped[col_cost]
+
+        grouped = grouped.rename(columns={col_name: 'name'})
+
+        sort_col = actual_sort_key if actual_sort_key in grouped.columns else 'revenue'
+        grouped = grouped.sort_values(sort_col, ascending=False).head(15)
+
+        records = []
+        for _, row in grouped.iterrows():
+            record = {
+                'name': str(row['name'])[:50],
+                'revenue': float(row['revenue']),
+                'order_count': int(row['order_count'])
+            }
+            if 'qty' in row:
+                record['qty'] = float(row['qty'])
+            if 'profit' in row:
+                record['profit'] = float(row['profit'])
+            records.append(record)
+
+        result[key] = records
+
+    return result
diff --git a/utils/df_helpers.py b/utils/df_helpers.py
new file mode 100644
index 0000000..a605bf3
--- /dev/null
+++ b/utils/df_helpers.py
@@ -0,0 +1,18 @@
+"""DataFrame 共用工具 — 跨 routes/services 共享。"""
+
+
+def find_col(df_cols, keywords):
+    """從欄位列表中，根據關鍵字列表找出最匹配的欄位名稱。
+
+    Args:
+        df_cols: DataFrame 的欄位名稱 iterable
+        keywords: 關鍵字列表，依優先序
+
+    Returns:
+        匹配的欄位名稱字串，找不到則回傳 None
+    """
+    for k in keywords:
+        for col in df_cols:
+            if k in str(col):
+                return col
+    return None