semvec/pypi-packages huggingface dataset:
SimpleTki 0.1.0
A simple wrapper for Tkinter
License: MIT
Requires Python: >=3.8
Keywords: tkinter, gui, simple

**SimpleTki**

SimpleTki is a lightweight Python library that simplifies the creation of graphical user interfaces using Tkinter. Compatible with Python 3.8+, and cross-platform support (Windows, macOS, Linux).

Installation

Install via pip (once published):
pip install SimpleTki

Or install from source:
git clone https://github.com/SummerCapybara/SimpleTki.git
cd SimpleTki
pip install .

# pip install SimpleTki  <- for PyPI
# from SimpleTki import SimpleTk  <- for Python import


Usage

from SimpleTki import SimpleTk

# Create a window
app = SimpleTk()
app.title("My App")
app.run()


Contributing & License

Contributions are welcome! Please fork the repository and submit pull requests for improvements or bug fixes. This project is licensed under the MIT License. See the LICENSE file for details.

Links

GitHub Repository: https://github.com/SummerCapybara/SimpleTki
pyrte 0.1.2
Python http client for RTE API
License: MIT
Requires Python: >=3.8
Keywords: rte, api, http, python, client, french, tso, electricity, timeseries

# pyrte

`pyrte` is a lightweight Python client library for interacting with RTE (Réseau de Transport d'Électricité) public APIs (https://data.rte-france.com). It provides a high-level interface for authentication and data retrieval from RTE endpoints, including automatic handling of per-endpoint OAuth2 tokens.

### Key features:
- High-level client for RTE APIs
- Per-endpoint OAuth2 token management
- Utilities to fetch time series data (e.g., short-term consumption)

## Installation

Install from PyPI:

```bash
pip install pyrte
```
### Testing

Simply run at the root: 
```python
pytest
```
You don't need credentials to run tests
## Credentials
**For each API you want to request :**
1. Create an account at https://data.rte-france.com/.

2. Create an application for web server and start associating the API to this application. 

3. In the application tab, one will find the client id and the related client secret code needed for requesting data.

**Quick Usage Example**

The following example demonstrates how to create an `RTEClient` and fetch short-term consumption data. Replace the credential placeholders with your real client IDs and secrets.

```python
import pandas as pd
from pyrte.rte_client import RTEClient, APIService, PrevisionType

creds = {
	APIService.short_term_consumption: {
		"client_id": "YOUR_CLIENT_ID",
		"client_secret": "YOUR_CLIENT_SECRET",
	},
	APIService.wholesale_market: {
		"client_id": "YOUR_CLIENT_ID",
		"client_secret": "YOUR_CLIENT_SECRET",
	},
}

client = RTEClient(creds)

# Use timezone-aware timestamps (example: CET / +01:00)
start = pd.Timestamp("2025-01-01T00:00:00+01:00")
end = pd.Timestamp("2025-01-02T00:00:00+01:00")

series = client.get_short_term_consumption(start, end, PrevisionType.REALISED)
print(series.head())
```

Notes:
- `APIService` and `PrevisionType` are enums so you can pass them directly as strings.
- Timestamps passed to client methods must be timezone-aware (Pandas `Timestamp` with tz info).
- The library will automatically refresh OAuth2 tokens per service when required.

## Contributing

Contributions and bug reports are welcome:

I only implemented one endpoint as an exemple and because it was the one i needed, so feel free to open issues or pull requests to add new functionality !

## License

See the `LICENSE` file for license terms.
qmoba-agent 0.1.0
A reinforcement learning framework template for MOBA game AI training
License: MIT
Requires Python: >=3.8
Keywords: reinforcement-learning, game-ai, moba, dqn, template

# QMobaAgent (autowzry-agent)

## 🎮 项目简介

[QMobaAgent](https://github.com/cndaqiang/autowzry-agent)是一个基于深度强化学习的MOBA游戏AI训练框架，以王者荣耀为示例，支持从视频学习和在线对战。本项目通过兼容层设计实现游戏逻辑与训练框架的解耦，可作为模板用于开发其他游戏的强化学习AI。

---

## 📚 文档导航

### 使用指南
- **[快速开始](docs/guides/quickstart.md)** - 完整使用教程（安装、数据收集、标记、训练、对战）
- **[架构文档](docs/design/ARCHITECTURE.md)** - 详细架构说明和模块接口

### 开发指南
- **[给开发者的开发指南](docs/guides/COLLABORATE_WITH_AGENT.md)** - 与AI代码助手协作的完整流程与技巧 ⭐
- **[给代码助手的项目指南](docs/guides/README_FOR_AGENT.md)** - 让AI代码助手快速了解本项目
- **[开发历史](docs/logs/development_log.md)** - 开发记录和版本历史


---

## 📁 项目结构

```
autowzry-agent/
├── qmoba_agent/         # 主包目录
│   ├── config/          # 配置管理
│   ├── core/            # 核心模块（DQN模型、训练器）
│   ├── environment/     # 环境交互（兼容层、动作空间、游戏状态）
│   ├── data/            # 数据处理（数据管理、训练缓冲）
│   ├── utils/           # 工具函数（图像处理、视频读取）
│   └── autowzry_lite/   # autowzry精简版
├── scripts/             # 执行脚本（收集、标记、训练、对战）
├── config/              # 配置文件（YAML）
├── docs/                # 文档
├── workspace/           # 运行时数据（episodes、checkpoints等）
└── pyproject.toml       # 项目配置
```

---

## ✨ 核心特性与架构

本项目支持完整训练流程：数据收集 → 标记 → 训练 → 在线对战。

### 设计特色

**1. 兼容层作为唯一变体**
- 🎯 **兼容层**（`environment/compatibility.py`）负责所有游戏/设备相关的特殊逻辑
- 🔧 **通用模块**（core、data、utils）与具体游戏完全解耦
- 🔄 **切换游戏**时只需重写兼容层，其他模块保持不变

**2. 依赖注入连接模块**
- 各模块通过依赖注入方式连接，而非硬编码依赖
- 模块之间通过接口通信，实现松耦合
- 便于测试、扩展和替换

**3. 模型接口标准化**
- 模型只需满足固定的输入输出接口
- 可以随意替换不同的模型实现
- 本项目提供了一个轻量级DQN实现（支持mini/full/high三种规模）

---

## 🙏 致谢

感谢 [Claude Code](https://claude.com/claude-code) 提供的强大AI编程助手。

感谢 [linux.do](https://linux.do/) 论坛各位赛博善人提供的Claude Code公益站。

本项目学习了以下优秀的强化学习王者荣耀项目：
- [myBoris/wzry_ai](https://github.com/myBoris/wzry_ai)
- [FengQuanLi/WZCQ](https://github.com/FengQuanLi/WZCQ)
- 学习笔记：[cndaqiang/learning_myBoris_wzry_ai](https://github.com/cndaqiang/learning_myBoris_wzry_ai)

---

## 🔗 相关项目

- [autowzry](https://github.com/cndaqiang/autowzry) - 王者荣耀自动化框架（图像识别和设备控制）
- **autowzry_lite** - autowzry的精简版本（包含在本项目中）
- [airtest_mobileauto](https://github.com/cndaqiang/airtest_mobileauto) - 移动端自动化工具

---

## 🤝 贡献

欢迎提交Issue和Pull Request！

---

## 📄 许可证

本项目仅供学习研究使用。
iona-ops-library 0.11.3
iona-ops library for common functions across DABs
License: MIT
Requires Python: >=3.8

# iona-ops-library

iona_ops_library for common function across dabs.

## Functions
- `send_teams_notification`
- `add_numbers(a, b)`
- `multiply_numbers(a, b)`
- `data merger class`
- `field logger class`


## Example

```python
from iona_ops_library import add_numbers, multiply_numbers

print(add_numbers(2, 3))  # 5
print(multiply_numbers(2, 3))  # 6

## Data Merger
- `decribe usage here`


## Field logger Merger
- `decribe usage here`