ai_v/venv/Lib/site-packages/darabonba/policy/retry.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

214 lines
7.9 KiB
Python

import random
from typing import List, Any, Dict
MAX_DELAY_TIME = 120 * 1000
MIN_DELAY_TIME = 100
class BackoffPolicy:
def __init__(self, option: Dict[str, Any]):
self.policy = option.get("policy")
def get_delay_time(self, ctx: 'RetryPolicyContext') -> int:
raise NotImplementedError('un-implemented')
@staticmethod
def new_backoff_policy(option: Dict[str, Any]) -> 'BackoffPolicy':
policy_map = {
'Fixed': FixedBackoffPolicy,
'Random': RandomBackoffPolicy,
'Exponential': ExponentialBackoffPolicy,
'EqualJitter': EqualJitterBackoffPolicy,
'ExponentialWithEqualJitter': EqualJitterBackoffPolicy,
'FullJitter': FullJitterBackoffPolicy,
'ExponentialWithFullJitter': FullJitterBackoffPolicy,
}
policy_class = policy_map.get(option.get('policy'))
if policy_class:
return policy_class(option)
raise ValueError(f"Unknown policy: {option.get('policy')}")
class FixedBackoffPolicy(BackoffPolicy):
def __init__(self, option: Dict[str, Any]):
super().__init__(option)
self.period = option.get('period')
def to_map(self):
return {
'policy': self.policy,
'period': self.period,
}
def get_delay_time(self, ctx: 'RetryPolicyContext') -> int:
return self.period
class RandomBackoffPolicy(BackoffPolicy):
def __init__(self, option: Dict[str, Any]):
super().__init__(option)
self.period = option.get('period')
self.cap = option.get('cap', 20 * 1000)
def to_map(self):
return {
'policy': self.policy,
'period': self.period,
'cap': self.cap,
}
def get_delay_time(self, ctx: 'RetryPolicyContext') -> int:
random_time = random.randint(0, ctx.retries_attempted * self.period)
return min(random_time, self.cap)
class ExponentialBackoffPolicy(BackoffPolicy):
def __init__(self, option: Dict[str, Any]):
super().__init__(option)
self.period = option.get('period')
self.cap = option.get('cap', 3 * 24 * 60 * 60 * 1000)
def to_map(self):
return {
'policy': self.policy,
'period': self.period,
'cap': self.cap,
}
def get_delay_time(self, ctx: 'RetryPolicyContext') -> int:
random_time = min(2 ** (ctx.retries_attempted * self.period), self.cap)
return random_time
class EqualJitterBackoffPolicy(BackoffPolicy):
def __init__(self, option: Dict[str, Any]):
super().__init__(option)
self.period = option.get('period')
self.cap = option.get('cap', 3 * 24 * 60 * 60 * 1000)
def to_map(self):
return {
'policy': self.policy,
'period': self.period,
'cap': self.cap,
}
def get_delay_time(self, ctx: 'RetryPolicyContext') -> int:
ceil = min(self.cap, 2 ** (ctx.retries_attempted * self.period))
return ceil // 2 + random.randint(0, ceil // 2)
class FullJitterBackoffPolicy(BackoffPolicy):
def __init__(self, option: Dict[str, Any]):
super().__init__(option)
self.period = option.get('period')
self.cap = option.get('cap', 3 * 24 * 60 * 60 * 1000)
def to_map(self):
return {
'policy': self.policy,
'period': self.period,
'cap': self.cap,
}
def get_delay_time(self, ctx: 'RetryPolicyContext') -> int:
ceil = min(self.cap, 2 ** (ctx.retries_attempted * self.period))
return random.randint(0, ceil)
class RetryCondition:
def __init__(self, condition: Dict[str, Any]):
self.max_attempts = condition.get('maxAttempts', None)
self.backoff = self._ensure_backoff_policy(condition.get('backoff', None))
self.exception = condition.get('exception', [])
self.error_code = condition.get('errorCode', [])
self.max_delay = condition.get('maxDelay', None)
def _ensure_backoff_policy(self, backoff):
if isinstance(backoff, dict):
return BackoffPolicy.new_backoff_policy(backoff)
elif isinstance(backoff, BackoffPolicy):
return backoff
def to_map(self):
result = dict()
if self.max_attempts:
result['maxAttempts'] = self.max_attempts
if self.backoff:
result['backoff'] = self.backoff.to_map()
if self.exception:
result['exception'] = self.exception
if self.error_code:
result['errorCode'] = self.error_code
if self.max_delay:
result['maxDelay'] = self.max_delay
return result
@staticmethod
def from_map(data: Dict[str, Any]) -> 'RetryCondition':
return RetryCondition({
'maxAttempts': data.get('maxAttempts'),
'backoff': data.get('backoff'),
'exception': data.get('exception', []),
'errorCode': data.get('errorCode', []),
'maxDelay': data.get('maxDelay')
})
class RetryOptions:
def __init__(self, options: Dict[str, Any]):
self.retryable = options.get('retryable', True)
self.retry_condition = [self._ensure_retry_condition(cond) for cond in options.get('retryCondition', [])]
self.no_retry_condition = [self._ensure_retry_condition(cond) for cond in options.get('noRetryCondition', [])]
def _ensure_retry_condition(self, condition):
if isinstance(condition, dict):
return RetryCondition(condition)
elif isinstance(condition, RetryCondition):
return condition
else:
raise ValueError("Condition must be either a dictionary or a RetryCondition instance")
def validate(self) -> bool:
if not isinstance(self.retryable, bool):
raise ValueError("retryable must be a boolean.")
if not isinstance(self.retry_condition, list) or not all(isinstance(cond, RetryCondition) for cond in self.retry_condition):
raise ValueError("retryCondition must be a list of RetryCondition.")
if not isinstance(self.no_retry_condition, list) or not all(isinstance(cond, RetryCondition) for cond in self.no_retry_condition):
raise ValueError("noRetryCondition must be a list of RetryCondition.")
return True
def to_map(self):
result = dict()
if self.retryable:
result['retryable'] = self.retryable
if self.retry_condition:
result['retryCondition'] = [cond.to_map() for cond in self.retry_condition]
if self.no_retry_condition:
result['noRetryCondition'] = [cond.to_map() for cond in self.no_retry_condition]
return result
@staticmethod
def from_map(data: Dict[str, Any]) -> 'RetryOptions':
options = {
'retryable': data.get('retryable', True),
'retryCondition': [cond for cond in data.get('retryCondition', [])],
'noRetryCondition': [cond for cond in data.get('noRetryCondition', [])]
}
return RetryOptions(options)
class RetryPolicyContext:
def __init__(self, retries_attempted = None, http_request = None, http_response = None, exception = None):
self.retries_attempted = retries_attempted
self.http_request = http_request
self.http_response = http_response
self.exception = exception
def get_backoff_delay(options: RetryOptions, ctx: RetryPolicyContext) -> int:
ex = ctx.exception
for condition in options.retry_condition:
if (ex and (ex.name in condition.exception or ex.code in condition.error_code)):
max_delay = condition.max_delay or MAX_DELAY_TIME
retry_after = getattr(ex, 'retryAfter', None)
if retry_after is not None:
return min(retry_after, max_delay)
if not condition.backoff:
return MIN_DELAY_TIME
return min(condition.backoff.get_delay_time(ctx), max_delay)
return MIN_DELAY_TIME