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- 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
121 lines
3.4 KiB
Python
121 lines
3.4 KiB
Python
# util/topological.py
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# Copyright (C) 2005-2025 the SQLAlchemy authors and contributors
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# <see AUTHORS file>
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#
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# This module is part of SQLAlchemy and is released under
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# the MIT License: https://www.opensource.org/licenses/mit-license.php
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"""Topological sorting algorithms."""
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from __future__ import annotations
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from typing import Any
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from typing import Collection
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from typing import DefaultDict
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from typing import Iterable
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from typing import Iterator
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from typing import Sequence
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from typing import Set
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from typing import Tuple
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from typing import TypeVar
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from .. import util
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from ..exc import CircularDependencyError
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_T = TypeVar("_T", bound=Any)
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__all__ = ["sort", "sort_as_subsets", "find_cycles"]
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def sort_as_subsets(
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tuples: Collection[Tuple[_T, _T]], allitems: Collection[_T]
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) -> Iterator[Sequence[_T]]:
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edges: DefaultDict[_T, Set[_T]] = util.defaultdict(set)
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for parent, child in tuples:
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edges[child].add(parent)
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todo = list(allitems)
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todo_set = set(allitems)
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while todo_set:
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output = []
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for node in todo:
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if todo_set.isdisjoint(edges[node]):
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output.append(node)
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if not output:
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raise CircularDependencyError(
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"Circular dependency detected.",
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find_cycles(tuples, allitems),
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_gen_edges(edges),
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)
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todo_set.difference_update(output)
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todo = [t for t in todo if t in todo_set]
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yield output
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def sort(
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tuples: Collection[Tuple[_T, _T]],
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allitems: Collection[_T],
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deterministic_order: bool = True,
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) -> Iterator[_T]:
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"""sort the given list of items by dependency.
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'tuples' is a list of tuples representing a partial ordering.
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deterministic_order is no longer used, the order is now always
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deterministic given the order of "allitems". the flag is there
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for backwards compatibility with Alembic.
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"""
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for set_ in sort_as_subsets(tuples, allitems):
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yield from set_
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def find_cycles(
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tuples: Iterable[Tuple[_T, _T]], allitems: Iterable[_T]
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) -> Set[_T]:
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# adapted from:
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# https://neopythonic.blogspot.com/2009/01/detecting-cycles-in-directed-graph.html
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edges: DefaultDict[_T, Set[_T]] = util.defaultdict(set)
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for parent, child in tuples:
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edges[parent].add(child)
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nodes_to_test = set(edges)
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output = set()
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# we'd like to find all nodes that are
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# involved in cycles, so we do the full
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# pass through the whole thing for each
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# node in the original list.
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# we can go just through parent edge nodes.
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# if a node is only a child and never a parent,
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# by definition it can't be part of a cycle. same
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# if it's not in the edges at all.
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for node in nodes_to_test:
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stack = [node]
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todo = nodes_to_test.difference(stack)
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while stack:
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top = stack[-1]
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for node in edges[top]:
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if node in stack:
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cyc = stack[stack.index(node) :]
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todo.difference_update(cyc)
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output.update(cyc)
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if node in todo:
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stack.append(node)
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todo.remove(node)
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break
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else:
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stack.pop()
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return output
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def _gen_edges(edges: DefaultDict[_T, Set[_T]]) -> Set[Tuple[_T, _T]]:
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return {(right, left) for left in edges for right in edges[left]}
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