ai_v/venv/Lib/site-packages/redis/backoff.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

184 lines
5.2 KiB
Python

import random
from abc import ABC, abstractmethod
# Maximum backoff between each retry in seconds
DEFAULT_CAP = 0.512
# Minimum backoff between each retry in seconds
DEFAULT_BASE = 0.008
class AbstractBackoff(ABC):
"""Backoff interface"""
def reset(self):
"""
Reset internal state before an operation.
`reset` is called once at the beginning of
every call to `Retry.call_with_retry`
"""
pass
@abstractmethod
def compute(self, failures: int) -> float:
"""Compute backoff in seconds upon failure"""
pass
class ConstantBackoff(AbstractBackoff):
"""Constant backoff upon failure"""
def __init__(self, backoff: float) -> None:
"""`backoff`: backoff time in seconds"""
self._backoff = backoff
def __hash__(self) -> int:
return hash((self._backoff,))
def __eq__(self, other) -> bool:
if not isinstance(other, ConstantBackoff):
return NotImplemented
return self._backoff == other._backoff
def compute(self, failures: int) -> float:
return self._backoff
class NoBackoff(ConstantBackoff):
"""No backoff upon failure"""
def __init__(self) -> None:
super().__init__(0)
class ExponentialBackoff(AbstractBackoff):
"""Exponential backoff upon failure"""
def __init__(self, cap: float = DEFAULT_CAP, base: float = DEFAULT_BASE):
"""
`cap`: maximum backoff time in seconds
`base`: base backoff time in seconds
"""
self._cap = cap
self._base = base
def __hash__(self) -> int:
return hash((self._base, self._cap))
def __eq__(self, other) -> bool:
if not isinstance(other, ExponentialBackoff):
return NotImplemented
return self._base == other._base and self._cap == other._cap
def compute(self, failures: int) -> float:
return min(self._cap, self._base * 2**failures)
class FullJitterBackoff(AbstractBackoff):
"""Full jitter backoff upon failure"""
def __init__(self, cap: float = DEFAULT_CAP, base: float = DEFAULT_BASE) -> None:
"""
`cap`: maximum backoff time in seconds
`base`: base backoff time in seconds
"""
self._cap = cap
self._base = base
def __hash__(self) -> int:
return hash((self._base, self._cap))
def __eq__(self, other) -> bool:
if not isinstance(other, FullJitterBackoff):
return NotImplemented
return self._base == other._base and self._cap == other._cap
def compute(self, failures: int) -> float:
return random.uniform(0, min(self._cap, self._base * 2**failures))
class EqualJitterBackoff(AbstractBackoff):
"""Equal jitter backoff upon failure"""
def __init__(self, cap: float = DEFAULT_CAP, base: float = DEFAULT_BASE) -> None:
"""
`cap`: maximum backoff time in seconds
`base`: base backoff time in seconds
"""
self._cap = cap
self._base = base
def __hash__(self) -> int:
return hash((self._base, self._cap))
def __eq__(self, other) -> bool:
if not isinstance(other, EqualJitterBackoff):
return NotImplemented
return self._base == other._base and self._cap == other._cap
def compute(self, failures: int) -> float:
temp = min(self._cap, self._base * 2**failures) / 2
return temp + random.uniform(0, temp)
class DecorrelatedJitterBackoff(AbstractBackoff):
"""Decorrelated jitter backoff upon failure"""
def __init__(self, cap: float = DEFAULT_CAP, base: float = DEFAULT_BASE) -> None:
"""
`cap`: maximum backoff time in seconds
`base`: base backoff time in seconds
"""
self._cap = cap
self._base = base
self._previous_backoff = 0
def __hash__(self) -> int:
return hash((self._base, self._cap))
def __eq__(self, other) -> bool:
if not isinstance(other, DecorrelatedJitterBackoff):
return NotImplemented
return self._base == other._base and self._cap == other._cap
def reset(self) -> None:
self._previous_backoff = 0
def compute(self, failures: int) -> float:
max_backoff = max(self._base, self._previous_backoff * 3)
temp = random.uniform(self._base, max_backoff)
self._previous_backoff = min(self._cap, temp)
return self._previous_backoff
class ExponentialWithJitterBackoff(AbstractBackoff):
"""Exponential backoff upon failure, with jitter"""
def __init__(self, cap: float = DEFAULT_CAP, base: float = DEFAULT_BASE) -> None:
"""
`cap`: maximum backoff time in seconds
`base`: base backoff time in seconds
"""
self._cap = cap
self._base = base
def __hash__(self) -> int:
return hash((self._base, self._cap))
def __eq__(self, other) -> bool:
if not isinstance(other, ExponentialWithJitterBackoff):
return NotImplemented
return self._base == other._base and self._cap == other._cap
def compute(self, failures: int) -> float:
return min(self._cap, random.random() * self._base * 2**failures)
def default_backoff():
return EqualJitterBackoff()