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feat: FAST-0 特殊算法

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Wang Zhiyu
2026-04-19 00:05:49 +08:00
parent 215a8648c2
commit 053c4660d0
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.python-version
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3.12

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CONTRIBUTING.md
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# 贡献指南
欢迎为此项目做出贡献!
欢迎为此项目做出贡献!\
本项目是一个开源项目, 我们鼓励社区成员参与改进.
## 开发规范
1. 分支划分:
1. 分支划分:
- `main` 分支: 稳定版本
- `dev` 分支: 开发版本
- 功能分支: 从 `dev` 分支创建, 命名格式为 `feature/描述` 或 `fix/描述` 或 `refactor/描述`
2. 代码风格:
1. 代码风格:
- 请使用 Black 格式化代码
- 遵循 PEP 8 规范
- 添加适当的文档字符串
3. 提交消息:
- 添加适当的文档字符串
1. 提交消息:
- 使用简体中文或英文撰写清晰的提交消息
- 格式: 遵循 Conventional Commits 规范
4. 合并方式:
1. 合并方式:
- 不使用 Fast-forward 合并
- 可以设置 `git config merge.ff false`
@@ -39,4 +39,4 @@ pip install -e .
## 许可证
贡献者同意其贡献将在 AGPL-3.0 许可证下发布.
贡献者同意其贡献将在 AGPL-3.0 许可证下发布.

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README.md
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# 潜进 (HeurAMS) - 启发式辅助记忆程序
## 概述
"潜进" (HeurAMS: Heuristic Auxiliary Memorizing Scheduler, 启发式记忆辅助调度器) 是为习题册, 古诗词, 及其他问答/记忆/理解型知识设计的开放源代码多用途辅助记忆软件, 提供动态规划的优化记忆方案
"潜进" (HeurAMS: Heuristic Auxiliary Memorizing Scheduler, 启发式记忆辅助调度器) 是为习题册, 古诗词, 及其他问答/记忆/理解型知识设计的开放源代码多用途辅助记忆软件, 提供动态规划的优化记忆方案
## 关于此仓库
本仓库为 "潜进" 软件组项目的核心部分, 包含核心功能模块以及基于 Textual 框架的基础用户界面(heurams.interface)实现
除了通过用户界面进行学习外, 你也可以在 Python 中导入 `heurams` 库, 使用其中实现的状态机, 算法迭代器和数据模型构建辅助记忆功能
本仓库为 "潜进" 软件组项目的核心部分, 包含核心功能模块以及基于 Textual 框架的基础用户界面(heurams.interface)实现\
除了通过用户界面进行学习外, 你也可以在 Python 中导入 `heurams` 库, 使用其中实现的状态机, 算法迭代器和数据模型构建辅助记忆功能
## 特性
### 间隔迭代算法
> 许多出版物都广泛讨论了不同重复间隔对学习效果的影响. 特别是, 间隔效应被认为是一种普遍现象. 间隔效应是指, 如果重复的间隔是分散/稀疏的, 而不是集中重复, 那么学习任务的表现会更好. 因此, 有观点提出, 学习中使用的最佳重复间隔是**最长的, 但不会导致遗忘的间隔**.
> 许多出版物都广泛讨论了不同重复间隔对学习效果的影响. 特别是, 间隔效应被认为是一种普遍现象. 间隔效应是指, 如果重复的间隔是分散/稀疏的, 而不是集中重复, 那么学习任务的表现会更好. 因此, 有观点提出, 学习中使用的最佳重复间隔是**最长的, 但不会导致遗忘的间隔**.
- 采用经实证的 SM-2 间隔迭代算法, 此算法亦用作 Anki 闪卡记忆软件的默认闪卡调度器
- 动态规划每个记忆单元的记忆间隔时间表
- 动态跟踪记忆反馈数据, 优化长期记忆保留率与稳定性
### 学习进程优化
- 元数据配置: 支持配置详细附加数据
- 自然语音: 集成文本转语音 (TTS) 功能, 支持"电台"回顾功能
- 多种谜题类型: 选择题 (MCQ), 填空题 (Cloze), 识别题 (Recognition)
@@ -23,6 +28,7 @@
- 云同步支持: 通过多种协议同步数据到远程服务器
### 实用用户界面
- 响应式 Textual 框架构建的跨平台 TUI 界面
- 支持触屏/鼠标/键盘多操作模式
- 简洁直观的复习流程设计
@@ -30,39 +36,45 @@
## 安装
### 从源码安装
1. 克隆仓库:
1. 克隆仓库:
```bash
git clone https://gitea.imwangzhiyu.xyz/ajax/HeurAMS
cd HeurAMS
```
2. 安装依赖:
1. 安装依赖:
```bash
pip install -r requirements.txt
```
3. 以开发模式安装包:
1. 以开发模式安装包:
```bash
pip install -e .
```
### 从包管理器安装
暂时还没有:(
暂时还没有:(
## 启动应用
```bash
# 在任一目录(建议是空目录或者包根目录, 将被用作存放数据)下运行
python -m heurams.interface
```
配置文件位于 `./data/config/config.toml`(相对于工作目录).
配置文件位于 `./data/config/config.toml`(相对于工作目录).\
如果不存在, 会使用内置的默认配置.
## 项目结构
### 架构图(待更新 0.5.0)
以下 Mermaid 图展示了 HeurAMS 的主要组件及其关系:
以下 Mermaid 图展示了 HeurAMS 的主要组件及其关系:
```mermaid
graph TB
@@ -123,23 +135,24 @@ graph TB
## 贡献
欢迎贡献！请参阅 [CONTRIBUTING.md](CONTRIBUTING.md) 了解贡献指南.
欢迎贡献! 请参阅 [CONTRIBUTING.md](CONTRIBUTING.md) 了解贡献指南.
## 许可证
### 项目本身
本项目基于 AGPL-3.0 许可证开源. 详见根目录下 [LICENSE](LICENSE) 文件.
本项目基于 AGPL-3.0 许可证开源. 详见根目录下 [LICENSE](LICENSE) 文件.
### 第三方代码
项目在 `src/heurams/vendor/` 目录下嵌入了以下第三方代码(可能有修改):
#### py-fsrs
- 上游版本: 6.3.1
- 位置: `src/heurams/vendor/pyfsrs/`
- 原项目: [py-fsrs](https://github.com/open-spaced-repetition/py-fsrs)
- 原许可证: Copyright (c) 2026 Open Spaced Repetition Contributors
- 原许可证: MIT License, 详见 `src/heurams/vendor/pyfsrs/LICENSE`
本项目受益于他们无私且优秀的工作
本项目受益于他们无私且优秀的工作

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data/config/config.toml
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auto_pass = false
# 对于每个项目的默认新记忆原子数量
scheduled_num = 8
scheduled_num = 20
# UTC 时间戳修正 仅用于 UNIX 日时间戳的生成修正, 单位为秒
timezone_offset = +28800 # 中国标准时间 (UTC+8)
@@ -20,10 +20,11 @@ timezone_offset = +28800 # 中国标准时间 (UTC+8)
[interface]
[interface.memorizor]
autovoice = false # 自动语音播放, 仅限于 recognition 组件
autovoice = true # 自动语音播放, 仅限于 recognition 组件
[algorithm]
default = "SM-2" # 主要算法; 可选项: SM-2, SM-15M, FSRS
# default = "SM-2" # 主要算法; 可选项: SM-2, SM-15M, FSRS, FAST-0
default = 'FAST-0'
[puzzles] # 谜题默认配置

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title = "高考必背古诗文-0"
author = "__heurams__"
desc = "高考古诗文 60 篇"

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schedule = ["quick_review", "recognition", "final_review"]
[phases]
quick_review = [["FillBlank", "1.0"], ["Recognition", "1.0"]]
recognition = [["Recognition", "1.0"]]
final_review = [["FillBlank", "1.0"], ["Recognition", "1.0"]]
[annotation]
"quick_review" = "复习旧知"
"recognition" = "新知识"
"final_review" = "总复习"

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{}

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title = "测试单元: 过秦论"
author = "__heurams__"
desc = "高考古诗文: 过秦论"

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["秦孝公据崤函之固, 拥雍州之地,"]
note = []
content = "秦孝公/据/崤函/之固/, 拥/雍州/之地,/"
translation = "秦孝公占据着崤山和函谷关的险固地势，拥有雍州的土地，"
keyword_note = {"据"="占据", "崤函"="崤山和函谷关", "雍州"="古代九州之一"}
["君臣固守以窥周室,"]
note = []
content = "君臣/固守/以窥/周室,/"
translation = "君臣牢固地守卫着，借以窥视周王室的权力，"
keyword_note = {"窥"="窥视"}

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schedule = ["quick_review", "recognition", "final_review"]
[phases]
quick_review = [["FillBlank", "1.0"], ["SelectMeaning", "0.5"], ["Recognition", "1.0"]]
recognition = [["Recognition", "1.0"]]
final_review = [["FillBlank", "1.0"], ["SelectMeaning", "1.0"], ["Recognition", "1.0"]]
[annotation]
"quick_review" = "复习旧知"
"recognition" = "新知识"
"final_review" = "总复习"

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glossary.md
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# 运行时对象
Atom: 原子, 由核子, 电子, 轨道对象一并构成, 用于处理记忆所需一系列对象
Nucleon: 核子, 负责解析文件动态内容, 并储存记忆材料内容与谜题定义, 是静态只读但可临时覆盖内容的
Electron: 电子, 负责处理记忆算法数据
Nucleon: 核子, 负责解析文件动态内容, 并储存记忆材料内容与谜题定义, 是静态只读但可临时覆盖内容的\
Electron: 电子, 负责处理记忆算法数据\
Orbital: 轨道, 储存记忆阶段信息与谜题阶段内出现配置
# 状态机对象
Transitions: 一种状态机框架库
Reactor: 状态机库
Phaser...

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pyproject.toml
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@@ -3,20 +3,19 @@ name = "heurams"
version = "0.5.0"
description = "Heuristic Auxiliary Memory Scheduler"
readme = "README.md"
authors = [
{ name = "pluvium27", email = "pluvium27@outlook.com" }
]
requires-python = ">=3.12"
authors = [{ name = "pluvium27", email = "pluvium27@outlook.com" }]
requires-python = "==3.14.*"
dependencies = [
"edge-tts==7.0.2",
"jieba==0.42.1",
"openai==1.0.0",
"edge-tts>=7.2.8",
"jieba>=0.42.1",
"openai>=2.32.0",
"playsound==1.2.2",
"psutil>=7.2.1",
"tabulate>=0.9.0",
"textual==7.0.0",
"toml==0.10.2",
"transitions==0.9.3",
"psutil>=7.2.2",
"pygobject>=3.56.2",
"tabulate>=0.10.0",
"textual>=8.2.3",
"toml>=0.10.2",
"transitions>=0.9.3",
]
[project.scripts]
@@ -25,4 +24,4 @@ tui = "heurams.interface.__main__:main"
[build-system]
requires = ["uv_build>=0.9.22,<0.10.0"]
build-backend = "uv_build"
build-backend = "uv_build"

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@@ -1,2 +1,3 @@
# Interface - 用户界面
与界面系统**强绑定**的相关代码文件, "界面系统" 在此处是基本界面实现相关的 Textual 框架

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# Kernel - HeurAMS 核心
记忆规划相关算法与数据结构, 可脱离业务层
记忆规划相关算法与数据结构, 可脱离业务层

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src/heurams/kernel/algorithms/__init__.py
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from .base import BaseAlgorithm
from .sm2 import SM2Algorithm
from .sm15m import SM15MAlgorithm
from .fast0 import FAST0Algorithm
__all__ = [
"SM2Algorithm",
"BaseAlgorithm",
"SM15MAlgorithm",
"FAST0Algorithm",
]
algorithms = {
"SM-2": SM2Algorithm,
"FAST-0": FAST0Algorithm,
"SM-15M": SM15MAlgorithm,
"Base": BaseAlgorithm,
}

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from typing import TypedDict
import heurams.services.timer as timer
from heurams.services.logger import get_logger
from .base import BaseAlgorithm
logger = get_logger(__name__)
class FAST0Algorithm(BaseAlgorithm):
algo_name = "FAST-0"
class AlgodataDict(TypedDict):
real_rept: int
rept: int
interval: int
important: int
last_date: int
next_date: int
is_activated: int
last_modify: float
defaults = {
"real_rept": 0,
'important': 0,
"rept": 0,
"interval": 0,
"last_date": 0,
"next_date": 0,
"is_activated": 0,
"last_modify": timer.get_timestamp(),
}
@classmethod
def revisor(
cls, algodata: dict, feedback: int = 5, is_new_activation: bool = False
):
"""FAST-0 算法迭代决策机制实现
根据 quality(0 ~ 5) 进行参数迭代最佳间隔
quality 由主程序评估
Args:
quality (int): 记忆保留率量化参数
"""
logger.debug(
"FAST0.revisor 开始, feedback: %d, is_new_activation: %s",
feedback,
is_new_activation,
)
if feedback == -1:
logger.debug("feedback 为 -1, 跳过更新")
return
algodata[cls.algo_name]["interval"] = (1 if feedback <= 3 else float('inf'))
algodata[cls.algo_name]["important"] = (1 if feedback <= 3 else algodata[cls.algo_name]["important"])
algodata[cls.algo_name]["last_date"] = timer.get_daystamp()
algodata[cls.algo_name]["next_date"] = (
timer.get_daystamp() + algodata[cls.algo_name]["interval"]
)
algodata[cls.algo_name]["last_modify"] = timer.get_timestamp()
logger.debug(
"更新日期: last_date=%d, next_date=%d, last_modify=%f",
algodata[cls.algo_name]["last_date"],
algodata[cls.algo_name]["next_date"],
algodata[cls.algo_name]["last_modify"],
)
@classmethod
def is_due(cls, algodata):
result = algodata[cls.algo_name]["next_date"] <= timer.get_daystamp()
logger.debug(
"FAST0.is_due: next_date=%d, current_daystamp=%d, result=%s",
algodata[cls.algo_name]["next_date"],
timer.get_daystamp(),
result,
)
return result
@classmethod
def get_rating(cls, algodata):
efactor = algodata[cls.algo_name]["efactor"]
logger.debug("FAST0.rate: efactor=%f", efactor)
return str(efactor)
@classmethod
def nextdate(cls, algodata) -> int:
next_date = algodata[cls.algo_name]["next_date"]
logger.debug("FAST0.nextdate: %d", next_date)
return next_date

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# Reactor - 记忆流程状态机模块
Reactor 是 HeurAMS 的记忆流程状态机模块, 和界面 (interface) 的实现是解耦的, 以便后期与其他框架的适配.
得益于 Pickle, 状态机模块支持快照!
Reactor 是 HeurAMS 的记忆流程状态机模块, 和界面 (interface) 的实现是解耦的, 以便后期与其他框架的适配.\
得益于 Pickle, 状态机模块支持快照!
## Phaser - 全局阶段控制器
在一次队列记忆流程中, Phaser 代表记忆流程本身.
在一次队列记忆流程中, Phaser 代表记忆流程本身.
### 属性
@@ -14,35 +14,35 @@ Reactor 是 HeurAMS 的记忆流程状态机模块, 和界面 (interface) 的实
其有状态属性:
- unsure - 用于初始化
- *quick_review - 复习逾期的单元
- *recognition - 辨识新单元
- *final_review - 复习所有逾期的和新辨认的单元
- finished - 表示完成
- \*quick_review - 复习逾期的单元
- \*recognition - 辨识新单元
- \*final_review - 复习所有逾期的和新辨认的单元
- finished - 表示完成
> 逾期的: 指 SM-2 算法间隔显示应该复习的单元
带 * 的属性表示实际的记忆阶段, 由 repo 中 schedule.toml 中 schedule 列表显式声明, 运行过程中可以选择性执行, "空的" Procession 会被直接跳过.
在初始化 Procession 时, 每个 Procession 被赋予一个不重复的状态属性 作为"阶段状态"属性, 以此标识 Procession 的阶段属性, 因为每个 Procession 管理一个阶段下的复习进程.
在初始化 Procession 时, 每个 Procession 被赋予一个不重复的状态属性 作为"阶段状态"属性, 以此标识 Procession 的阶段属性, 因为每个 Procession 管理一个阶段下的复习进程.
你可以用 state 属性获取 Phaser 的当前状态.
#### Procession 属性
储存一个顺序列表, 保存所有构造的 Procession.
储存一个顺序列表, 保存所有构造的 Procession.\
顺序与 repo 中 schedule.toml 中 schedule 列表中的顺序完全相同
### 初始化
Phaser 接受一个存储 Atom 对象的列表, 作为组织记忆流程的材料
在内部, 根据是否激活将其分为 new_atoms 与 old_atoms.
Phaser 接受一个存储 Atom 对象的列表, 作为组织记忆流程的材料\
在内部, 根据是否激活将其分为 new_atoms 与 old_atoms.\
因此, 如果你传入的列表中有算法上"无所事事"的 Atom, 流程会对其进行"加强复习"
由此创建 Procession.
由此创建 Procession.
### 直接输出呈现形式
Phaser 的 __repr__ 定义了此对象"官方的显示"用作直观的调试.
其以 ascii 表格形式输出, 格式也符合 markdown 表格规范, 你可以直接复制到 markdown.
Phaser 的 __repr__ 定义了此对象"官方的显示"用作直观的调试.\
其以 ascii 表格形式输出, 格式也符合 markdown 表格规范, 你可以直接复制到 markdown.\
示例:
```text
@@ -51,20 +51,20 @@ Phaser 的 __repr__ 定义了此对象"官方的显示"用作直观的调试.
| Phaser | unsure | ['新记忆', '总体复习'] | 新记忆 |
```
| Type | State | Processions | Current Procession |
| Type | State | Processions | Current Procession |
|:-------|:--------|:-----------------------|:---------------------|
| Phaser | unsure | ['新记忆', '总体复习'] | 新记忆 |
| Phaser | unsure | ['新记忆', '总体复习'] | 新记忆 |
### 方法
作为一个 Transition Machine 对象的继承, 其拥有 Machine 对象拥有的所有方法.
除此之外, 它也拥有一些其他方法.
作为一个 Transition Machine 对象的继承, 其拥有 Machine 对象拥有的所有方法.\
除此之外, 它也拥有一些其他方法.
#### current_procession(self)
用于查询当前的 Procession, 并且根据当前 Procession 更新自身状态.
返回一个 Procession 对象, 是当前阶段的 Procession.
内部运作是返回第一个状态不为 finished 的 Procession, 并将自身状态变更为 Procession 的"阶段状态"属性
用于查询当前的 Procession, 并且根据当前 Procession 更新自身状态.\
返回一个 Procession 对象, 是当前阶段的 Procession.\
内部运作是返回第一个状态不为 finished 的 Procession, 并将自身状态变更为 Procession 的"阶段状态"属性\
若所有 Procession 都已完成, 将返回一个"阶段状态"为 finished 的 Procession 占位符对象(它不在 procession 属性中), 并更新自身状态为 finished.
## Procession - 阶段管理器
@@ -87,7 +87,7 @@ Phaser 的 __repr__ 定义了此对象"官方的显示"用作直观的调试.
> 注意区分 "Phaser" 和 "Phase", 其中 "Phase" 表示 "Phaser State".
- name_: 阶段的命名
- name\_: 阶段的命名
- state: 当前状态属性
### 初始化
@@ -96,7 +96,7 @@ Phaser 的 __repr__ 定义了此对象"官方的显示"用作直观的调试.
### 直接输出呈现形式
同 Phaser, 但显示数据有所不同
同 Phaser, 但显示数据有所不同\
与 Phaser 不同, Procession 显示队列会对过长的 atom.ident 进行缩略(末尾 `>` 符号)
```text
@@ -105,23 +105,23 @@ Phaser 的 __repr__ 定义了此对象"官方的显示"用作直观的调试.
| Procession | 新记忆 | active | 1 / 2 | ['秦孝公>', '君臣固>'] | 秦孝公据崤函之固, 拥雍州之地, |
```
| Type | Name | State | Progress | Queue | Current Atom |
| Type | Name | State | Progress | Queue | Current Atom |
|:-----------|:-------|:--------|:-----------|:-----------------------|:------------------------------|
| Procession | 新记忆 | active | 1 / 2 | ['秦孝公>', '君臣固>'] | 秦孝公据崤函之固, 拥雍州之地, |
| Procession | 新记忆 | active | 1 / 2 | ['秦孝公>', '君臣固>'] | 秦孝公据崤函之固, 拥雍州之地, |
### 方法
作为一个 Transition Machine 对象的继承, 其拥有 Machine 对象拥有的所有方法.
除此之外, 它也拥有一些其他方法.
作为一个 Transition Machine 对象的继承, 其拥有 Machine 对象拥有的所有方法.\
除此之外, 它也拥有一些其他方法.
#### forward(self, step=1)
移动 cursor 并依情况更新 current_atom 和状态属性
无论 Procession 是否处于完成状态, forward 操作都是可逆的, 你可以传入负数, 此时已完成的 Procession 会自动"重启".
移动 cursor 并依情况更新 current_atom 和状态属性\
无论 Procession 是否处于完成状态, forward 操作都是可逆的, 你可以传入负数, 此时已完成的 Procession 会自动"重启".
#### append(self, atom=None)
追加(回忆失败的)原子(默认为当前原子, 传入 None 会自动转化为当前原子)到队列末端
追加(回忆失败的)原子(默认为当前原子, 传入 None 会自动转化为当前原子)到队列末端\
如果这个原子已经处于队列末端, 不会重复追加, 除非队列只剩下这个原子还没完成(此时最多重复两个)
#### process(self)
@@ -130,7 +130,7 @@ Phaser 的 __repr__ 定义了此对象"官方的显示"用作直观的调试.
#### __len__(self)
返回剩余原子量(而不是原子总量)
返回剩余原子量(而不是原子总量)\
可以使用 len 函数调用
获取原子总量请用 len(obj.atoms), 或者 total_length(self) 方法

3
src/heurams/providers/README.md
View File

@@ -1,2 +1,3 @@
# Provider - 提供者
底层相关与第三方 API 接口包装
底层相关与第三方 API 接口包装

3
src/heurams/services/README.md
View File

@@ -1,2 +1,3 @@
# Services - 服务
基础服务相关代码
基础服务相关代码

757
uv.lock generated
View File

@@ -1,6 +1,6 @@
version = 1
revision = 3
requires-python = ">=3.12"
requires-python = "==3.14.*"
[[package]]
name = "aiohappyeyeballs"
@@ -13,7 +13,7 @@ wheels = [
[[package]]
name = "aiohttp"
version = "3.13.3"
version = "3.13.5"
source = { registry = "https://pypi.org/simple" }
dependencies = [
{ name = "aiohappyeyeballs" },
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{ name = "propcache" },
{ name = "yarl" },
]
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