🐛 修改用户唯一标识符字段长度 (#549)

nonebot_plugin_tetris_stats/config/migrations/3588702dd3a4_modify_field_length.py

@@ -0,0 +1,52 @@
+"""modify field length
+
+迁移 ID: 3588702dd3a4
+父迁移: bc6abd57928f
+创建时间: 2025-07-19 17:21:17.927162
+
+"""
+
+from __future__ import annotations
+
+from typing import TYPE_CHECKING
+
+import sqlalchemy as sa
+from alembic import op
+
+if TYPE_CHECKING:
+    from collections.abc import Sequence
+
+revision: str = '3588702dd3a4'
+down_revision: str | Sequence[str] | None = 'bc6abd57928f'
+branch_labels: str | Sequence[str] | None = None
+depends_on: str | Sequence[str] | None = None
+
+
+def upgrade(name: str = '') -> None:
+    if name:
+        return
+    # ### commands auto generated by Alembic - please adjust! ###
+    with op.batch_alter_table('nb_t_tos_hist_data', schema=None) as batch_op:
+        batch_op.alter_column(
+            'user_unique_identifier',
+            existing_type=sa.VARCHAR(length=24),
+            type_=sa.String(length=256),
+            existing_nullable=False,
+        )
+
+    # ### end Alembic commands ###
+
+
+def downgrade(name: str = '') -> None:
+    if name:
+        return
+    # ### commands auto generated by Alembic - please adjust! ###
+    with op.batch_alter_table('nb_t_tos_hist_data', schema=None) as batch_op:
+        batch_op.alter_column(
+            'user_unique_identifier',
+            existing_type=sa.String(length=256),
+            type_=sa.VARCHAR(length=24),
+            existing_nullable=False,
+        )
+
+    # ### end Alembic commands ###

nonebot_plugin_tetris_stats/games/tos/api/models.py

@@ -14,7 +14,7 @@ class TOSHistoricalData(MappedAsDataclass, Model):
     __tablename__ = 'nb_t_tos_hist_data'
 
     id: Mapped[int] = mapped_column(init=False, primary_key=True)
-    user_unique_identifier: Mapped[str] = mapped_column(String(24), index=True)
+    user_unique_identifier: Mapped[str] = mapped_column(String(256), index=True)
     api_type: Mapped[Literal['User Info', 'User Profile']] = mapped_column(String(16), index=True)
     data: Mapped[UserInfoSuccess | UserProfile] = mapped_column(
         PydanticType(get_model=[], models={UserInfoSuccess, UserProfile})