From 1fdc28b6fd99fca7e2ae082a7bb2cfc736334d11 Mon Sep 17 00:00:00 2001
From: ulleo <ulleo.wang@gmail.com>
Date: Wed, 26 Aug 2026 21:08:43 +0800
Subject: [PATCH] improve: Support similarity sorting across account, name, and
 email fields

---
 backend/apps/system/api/user.py | 49 +++++++++++++++++++++++----------
 1 file changed, 34 insertions(+), 15 deletions(-)

diff --git a/backend/apps/system/api/user.py b/backend/apps/system/api/user.py
index 4461ea5e..0386f3a1 100644
--- a/backend/apps/system/api/user.py
+++ b/backend/apps/system/api/user.py
@@ -80,13 +80,14 @@ async def pager(
     if order_by and order_by != 'account':
         select_columns.append(sort_field)
 
-    # 相似度排序：精确匹配 > 前缀匹配 > 包含匹配
-    # 当有 keyword 时，将 similarity_score 加入 SELECT 列以满足 DISTINCT 约束
-    # 对 account、name、email 三个字段分别计算相似度，取最高（最小值）
-    similarity_score = None
+    # 相似度排序：综合考虑匹配字段数量和相似度分数
+    # 当有 keyword 时，将 match_count 和 total_score 加入 SELECT 列以满足 DISTINCT 约束
+    # 匹配字段越多越靠前；相同匹配字段数时，总分越低（相似度越高）越靠前
+    match_count = None
+    total_score = None
     if keyword:
         from sqlalchemy import func
-        # 每个字段的相似度分数
+        # 每个字段的相似度分数 (0=精确匹配, 1=前缀匹配, 2=包含匹配, 3=无匹配)
         account_score = case(
             (UserModel.account == keyword, 0),
             (UserModel.account.startswith(keyword), 1),
@@ -105,9 +106,16 @@ async def pager(
             (UserModel.email.contains(keyword), 2),
             else_=3
         )
-        # 取三个字段中的最小值（最高匹配度）
-        similarity_score = func.LEAST(account_score, name_score, email_score)
-        select_columns.append(similarity_score.label('similarity_score'))
+        # 计算匹配字段数量（score < 3 表示有匹配）：匹配字段越多越靠前
+        match_count = (
+            case((account_score < 3, 1), else_=0) +
+            case((name_score < 3, 1), else_=0) +
+            case((email_score < 3, 1), else_=0)
+        )
+        # 总相似度分数：三个字段分数之和，越低越好
+        total_score = account_score + name_score + email_score
+        select_columns.append(match_count.label('match_count'))
+        select_columns.append(total_score.label('total_score'))
 
     origin_stmt = (
         select(*select_columns)
@@ -117,7 +125,8 @@ async def pager(
     )
     # 根据是否有 keyword 决定排序方式
     if keyword:
-        origin_stmt = origin_stmt.order_by(similarity_score, sort_clause)
+        # 按匹配字段数降序、总分升序、再按用户选择的排序字段
+        origin_stmt = origin_stmt.order_by(match_count.desc(), total_score.asc(), sort_clause)
     else:
         origin_stmt = origin_stmt.order_by(sort_clause)
 
@@ -128,12 +137,14 @@ async def pager(
     if status is not None:
         origin_stmt = origin_stmt.where(UserModel.status == status)
     if keyword:
-        keyword_pattern = f"%{keyword}%"
+        # 转义 SQL LIKE 特殊字符（_ 匹配单个字符，% 匹配任意字符串）
+        escaped_keyword = keyword.replace('\\', '\\\\').replace('_', '\\_').replace('%', '\\%')
+        keyword_pattern = f"%{escaped_keyword}%"
         origin_stmt = origin_stmt.where(
             or_(
-                UserModel.account.ilike(keyword_pattern),
-                UserModel.name.ilike(keyword_pattern),
-                UserModel.email.ilike(keyword_pattern)
+                UserModel.account.ilike(keyword_pattern, escape='\\'),
+                UserModel.name.ilike(keyword_pattern, escape='\\'),
+                UserModel.email.ilike(keyword_pattern, escape='\\')
             )
         )
         
@@ -169,8 +180,16 @@ async def pager(
             (UserModel.email.contains(keyword), 2),
             else_=3
         )
-        similarity_score = func.LEAST(account_score, name_score, email_score)
-        stmt = stmt.order_by(similarity_score, sort_clause)
+        # 计算匹配字段数量（score < 3 表示有匹配）：匹配字段越多越靠前
+        match_count = (
+            case((account_score < 3, 1), else_=0) +
+            case((name_score < 3, 1), else_=0) +
+            case((email_score < 3, 1), else_=0)
+        )
+        # 总相似度分数：三个字段分数之和，越低越好
+        total_score = account_score + name_score + email_score
+        # 排序：匹配字段数降序、总分升序、再按用户选择的排序字段
+        stmt = stmt.order_by(match_count.desc(), total_score.asc(), sort_clause)
     else:
         stmt = stmt.order_by(sort_clause)
     user_workspaces = session.exec(stmt).all()