ai_v/venv/Lib/site-packages/sqlalchemy/ext/indexable.py
24024 af7c11d7f9 feat(api): 实现图像生成及后台同步功能
- 新增图像生成接口,支持试用、积分和自定义API Key模式
- 实现生成图片结果异步上传至MinIO存储,带重试机制
- 优化积分预扣除和异常退还逻辑,保障用户积分准确
- 添加获取生成历史记录接口,支持时间范围和分页
- 提供本地字典配置接口,支持模型、比例、提示模板和尺寸
- 实现图片批量上传接口,支持S3兼容对象存储

feat(admin): 增加管理员角色管理与权限分配接口

- 实现角色列表查询、角色创建、更新及删除功能
- 增加权限列表查询接口
- 实现用户角色分配接口,便于统一管理用户权限
- 增加系统字典增删查改接口,支持分类过滤和排序
- 权限控制全面覆盖管理接口,保证安全访问

feat(auth): 完善用户登录注册及权限相关接口与页面

- 实现手机号验证码发送及校验功能,保障注册安全
- 支持手机号注册、登录及退出接口,集成日志记录
- 增加修改密码功能,验证原密码后更新
- 提供动态导航菜单接口,基于权限展示不同菜单
- 实现管理界面路由及日志、角色、字典管理页面访问权限控制
- 添加系统日志查询接口,支持关键词和等级筛选

feat(app): 初始化Flask应用并配置蓝图与数据库

- 创建应用程序工厂,加载配置,初始化数据库和Redis客户端
- 注册认证、API及管理员蓝图,整合路由
- 根路由渲染主页模板
- 应用上下文中自动创建数据库表,保证运行环境准备完毕

feat(database): 提供数据库创建与迁移支持脚本

- 新增数据库创建脚本,支持自动检测是否已存在
- 添加数据库表初始化脚本,支持创建和删除所有表
- 实现RBAC权限初始化,包含基础权限和角色创建
- 新增字段手动修复脚本,添加用户API Key和积分字段
- 强制迁移脚本支持清理连接和修复表结构,初始化默认数据及角色分配

feat(config): 新增系统配置参数

- 配置数据库、Redis、Session和MinIO相关参数
- 添加AI接口地址及试用Key配置
- 集成阿里云短信服务配置及开发模式相关参数

feat(extensions): 初始化数据库、Redis和MinIO客户端

- 创建全局SQLAlchemy数据库实例和Redis客户端
- 配置基于boto3的MinIO兼容S3客户端

chore(logs): 添加示例系统日志文件

- 记录用户请求、验证码发送成功与失败的日志信息
2026-01-12 00:53:31 +08:00

365 lines
12 KiB
Python

# ext/indexable.py
# Copyright (C) 2005-2025 the SQLAlchemy authors and contributors
# <see AUTHORS file>
#
# This module is part of SQLAlchemy and is released under
# the MIT License: https://www.opensource.org/licenses/mit-license.php
"""Define attributes on ORM-mapped classes that have "index" attributes for
columns with :class:`_types.Indexable` types.
"index" means the attribute is associated with an element of an
:class:`_types.Indexable` column with the predefined index to access it.
The :class:`_types.Indexable` types include types such as
:class:`_types.ARRAY`, :class:`_types.JSON` and
:class:`_postgresql.HSTORE`.
The :mod:`~sqlalchemy.ext.indexable` extension provides
:class:`_schema.Column`-like interface for any element of an
:class:`_types.Indexable` typed column. In simple cases, it can be
treated as a :class:`_schema.Column` - mapped attribute.
Synopsis
========
Given ``Person`` as a model with a primary key and JSON data field.
While this field may have any number of elements encoded within it,
we would like to refer to the element called ``name`` individually
as a dedicated attribute which behaves like a standalone column::
from sqlalchemy import Column, JSON, Integer
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.ext.indexable import index_property
Base = declarative_base()
class Person(Base):
__tablename__ = "person"
id = Column(Integer, primary_key=True)
data = Column(JSON)
name = index_property("data", "name")
Above, the ``name`` attribute now behaves like a mapped column. We
can compose a new ``Person`` and set the value of ``name``::
>>> person = Person(name="Alchemist")
The value is now accessible::
>>> person.name
'Alchemist'
Behind the scenes, the JSON field was initialized to a new blank dictionary
and the field was set::
>>> person.data
{'name': 'Alchemist'}
The field is mutable in place::
>>> person.name = "Renamed"
>>> person.name
'Renamed'
>>> person.data
{'name': 'Renamed'}
When using :class:`.index_property`, the change that we make to the indexable
structure is also automatically tracked as history; we no longer need
to use :class:`~.mutable.MutableDict` in order to track this change
for the unit of work.
Deletions work normally as well::
>>> del person.name
>>> person.data
{}
Above, deletion of ``person.name`` deletes the value from the dictionary,
but not the dictionary itself.
A missing key will produce ``AttributeError``::
>>> person = Person()
>>> person.name
AttributeError: 'name'
Unless you set a default value::
>>> class Person(Base):
... __tablename__ = "person"
...
... id = Column(Integer, primary_key=True)
... data = Column(JSON)
...
... name = index_property("data", "name", default=None) # See default
>>> person = Person()
>>> print(person.name)
None
The attributes are also accessible at the class level.
Below, we illustrate ``Person.name`` used to generate
an indexed SQL criteria::
>>> from sqlalchemy.orm import Session
>>> session = Session()
>>> query = session.query(Person).filter(Person.name == "Alchemist")
The above query is equivalent to::
>>> query = session.query(Person).filter(Person.data["name"] == "Alchemist")
Multiple :class:`.index_property` objects can be chained to produce
multiple levels of indexing::
from sqlalchemy import Column, JSON, Integer
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.ext.indexable import index_property
Base = declarative_base()
class Person(Base):
__tablename__ = "person"
id = Column(Integer, primary_key=True)
data = Column(JSON)
birthday = index_property("data", "birthday")
year = index_property("birthday", "year")
month = index_property("birthday", "month")
day = index_property("birthday", "day")
Above, a query such as::
q = session.query(Person).filter(Person.year == "1980")
On a PostgreSQL backend, the above query will render as:
.. sourcecode:: sql
SELECT person.id, person.data
FROM person
WHERE person.data -> %(data_1)s -> %(param_1)s = %(param_2)s
Default Values
==============
:class:`.index_property` includes special behaviors for when the indexed
data structure does not exist, and a set operation is called:
* For an :class:`.index_property` that is given an integer index value,
the default data structure will be a Python list of ``None`` values,
at least as long as the index value; the value is then set at its
place in the list. This means for an index value of zero, the list
will be initialized to ``[None]`` before setting the given value,
and for an index value of five, the list will be initialized to
``[None, None, None, None, None]`` before setting the fifth element
to the given value. Note that an existing list is **not** extended
in place to receive a value.
* for an :class:`.index_property` that is given any other kind of index
value (e.g. strings usually), a Python dictionary is used as the
default data structure.
* The default data structure can be set to any Python callable using the
:paramref:`.index_property.datatype` parameter, overriding the previous
rules.
Subclassing
===========
:class:`.index_property` can be subclassed, in particular for the common
use case of providing coercion of values or SQL expressions as they are
accessed. Below is a common recipe for use with a PostgreSQL JSON type,
where we want to also include automatic casting plus ``astext()``::
class pg_json_property(index_property):
def __init__(self, attr_name, index, cast_type):
super(pg_json_property, self).__init__(attr_name, index)
self.cast_type = cast_type
def expr(self, model):
expr = super(pg_json_property, self).expr(model)
return expr.astext.cast(self.cast_type)
The above subclass can be used with the PostgreSQL-specific
version of :class:`_postgresql.JSON`::
from sqlalchemy import Column, Integer
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.dialects.postgresql import JSON
Base = declarative_base()
class Person(Base):
__tablename__ = "person"
id = Column(Integer, primary_key=True)
data = Column(JSON)
age = pg_json_property("data", "age", Integer)
The ``age`` attribute at the instance level works as before; however
when rendering SQL, PostgreSQL's ``->>`` operator will be used
for indexed access, instead of the usual index operator of ``->``::
>>> query = session.query(Person).filter(Person.age < 20)
The above query will render:
.. sourcecode:: sql
SELECT person.id, person.data
FROM person
WHERE CAST(person.data ->> %(data_1)s AS INTEGER) < %(param_1)s
""" # noqa
from __future__ import annotations
from typing import Any
from typing import Callable
from typing import cast
from typing import Optional
from typing import TYPE_CHECKING
from typing import TypeVar
from typing import Union
from .. import inspect
from ..ext.hybrid import hybrid_property
from ..orm.attributes import flag_modified
if TYPE_CHECKING:
from ..sql import SQLColumnExpression
from ..sql._typing import _HasClauseElement
__all__ = ["index_property"]
_T = TypeVar("_T")
class index_property(hybrid_property[_T]):
"""A property generator. The generated property describes an object
attribute that corresponds to an :class:`_types.Indexable`
column.
.. seealso::
:mod:`sqlalchemy.ext.indexable`
"""
_NO_DEFAULT_ARGUMENT = cast(_T, object())
def __init__(
self,
attr_name: str,
index: Union[int, str],
default: _T = _NO_DEFAULT_ARGUMENT,
datatype: Optional[Callable[[], Any]] = None,
mutable: bool = True,
onebased: bool = True,
):
"""Create a new :class:`.index_property`.
:param attr_name:
An attribute name of an `Indexable` typed column, or other
attribute that returns an indexable structure.
:param index:
The index to be used for getting and setting this value. This
should be the Python-side index value for integers.
:param default:
A value which will be returned instead of `AttributeError`
when there is not a value at given index.
:param datatype: default datatype to use when the field is empty.
By default, this is derived from the type of index used; a
Python list for an integer index, or a Python dictionary for
any other style of index. For a list, the list will be
initialized to a list of None values that is at least
``index`` elements long.
:param mutable: if False, writes and deletes to the attribute will
be disallowed.
:param onebased: assume the SQL representation of this value is
one-based; that is, the first index in SQL is 1, not zero.
"""
if mutable:
super().__init__(self.fget, self.fset, self.fdel, self.expr)
else:
super().__init__(self.fget, None, None, self.expr)
self.attr_name = attr_name
self.index = index
self.default = default
is_numeric = isinstance(index, int)
onebased = is_numeric and onebased
if datatype is not None:
self.datatype = datatype
else:
if is_numeric:
self.datatype = lambda: [None for x in range(index + 1)] # type: ignore[operator] # noqa: E501
else:
self.datatype = dict
self.onebased = onebased
def _fget_default(self, err: Optional[BaseException] = None) -> _T:
if self.default == self._NO_DEFAULT_ARGUMENT:
raise AttributeError(self.attr_name) from err
else:
return self.default
def fget(self, __instance: Any) -> _T:
attr_name = self.attr_name
column_value = getattr(__instance, attr_name)
if column_value is None:
return self._fget_default()
try:
value = column_value[self.index]
except (KeyError, IndexError) as err:
return self._fget_default(err)
else:
return value # type: ignore[no-any-return]
def fset(self, instance: Any, value: _T) -> None:
attr_name = self.attr_name
column_value = getattr(instance, attr_name, None)
if column_value is None:
column_value = self.datatype()
setattr(instance, attr_name, column_value)
column_value[self.index] = value
setattr(instance, attr_name, column_value)
if attr_name in inspect(instance).mapper.attrs:
flag_modified(instance, attr_name)
def fdel(self, instance: Any) -> None:
attr_name = self.attr_name
column_value = getattr(instance, attr_name)
if column_value is None:
raise AttributeError(self.attr_name)
try:
del column_value[self.index]
except KeyError as err:
raise AttributeError(self.attr_name) from err
else:
setattr(instance, attr_name, column_value)
flag_modified(instance, attr_name)
def expr(
self, model: Any
) -> Union[_HasClauseElement[_T], SQLColumnExpression[_T]]:
column = getattr(model, self.attr_name)
index = self.index
if self.onebased:
index += 1 # type: ignore[operator]
return column[index] # type: ignore[no-any-return]