semvec/pypi-packages huggingface dataset:
trw-wrapper 0.1.0
Un wrapper simple para la API de TRW
Requires Python: >=3.6

# TRW API Wrapper

A simple and efficient wrapper for the TRW API (iwoozie.baby). This wrapper provides an easy-to-use interface for all API endpoints, including both free and authenticated endpoints.

## Installation

```bash
pip install trw-wrapper
```

## Quick Usage

### Free Bypass
```python
from trw_wrapper import TRWClient

# For free endpoints, no API key needed
client = TRWClient()
result = client.free_bypass(url="https://example.com")
print(result)
```

### Authenticated Bypass
```python
from trw_wrapper import TRWClient

# Initialize with your API key
client = TRWClient(api_key="your_api_key")

# Simple bypass
result = client.bypass(url="https://example.com")
print(result)

# Long-lived bypass
thread = client.bypass_v2(url="https://example.com")
thread_id = thread["ThreadID"]

# Check bypass status
status = client.check_thread(thread_id)
print(status)
```

## Available Functions

- `free_bypass(url)`: Free bypass without API key
- `bypass(url)`: General bypass (requires API key)
- `bypass_v2(url)`: Long-lived bypass (requires API key)
- `check_thread(thread_id)`: Check the status of a long-lived bypass
- `get_status()`: Check API status

## Response Examples

### Simple Bypass
```python
{
  "result": "Bypass Result",
  "success": true
}
```

### V2 Bypass (Long-lived)
```python
{
  "status": "started",
  "ThreadID": "task_id_123",
  "next": "/api/v2/threadcheck?id=task_id_123"
}
```

### Thread Status
```python
{
  "status": "Done",
  "result": "Result",
  "success": true
}
```

## Requirements
- Python 3.6+
- requests>=2.25.1

## API Documentation
For more information about the API, visit [iwoozie.baby/docs](https://iwoozie.baby/docs)

## License
MIT License

## Contributing
Contributions are welcome. Please open an issue or submit a pull request.
qianghua-xuexi-zai-ali-de-jishu-yanjin-yu-yewu-chuangxin-fix1 2025.3.25.0
强化学习在阿里的技术演进与业务创新
Requires Python: >=3.6

# 强化学习在阿里的技术演进与业务创新

## 下载

### Docker

```
docker pull apachecn0/qianghua-xuexi-zai-ali-de-jishu-yanjin-yu-yewu-chuangxin
docker run -tid -p <port>:80 apachecn0/qianghua-xuexi-zai-ali-de-jishu-yanjin-yu-yewu-chuangxin
# 访问 http://localhost:{port} 查看文档
```

### PYPI

```
pip install qianghua-xuexi-zai-ali-de-jishu-yanjin-yu-yewu-chuangxin
qianghua-xuexi-zai-ali-de-jishu-yanjin-yu-yewu-chuangxin <port>
# 访问 http://localhost:{port} 查看文档
```

### NPM

```
npm install -g qianghua-xuexi-zai-ali-de-jishu-yanjin-yu-yewu-chuangxin
qianghua-xuexi-zai-ali-de-jishu-yanjin-yu-yewu-chuangxin <port>
# 访问 http://localhost:{port} 查看文档
```
qianduan-neican-fix1 2025.3.25.0
前端内参
Requires Python: >=3.6

# 前端内参

## 下载

### Docker

```
docker pull apachecn0/qianduan-neican
docker run -tid -p <port>:80 apachecn0/qianduan-neican
# 访问 http://localhost:{port} 查看文档
```

### PYPI

```
pip install qianduan-neican
qianduan-neican <port>
# 访问 http://localhost:{port} 查看文档
```

### NPM

```
npm install -g qianduan-neican
qianduan-neican <port>
# 访问 http://localhost:{port} 查看文档
```
qianduan-daima-shi-zenyang-zhineng-shengcheng-de-fix1 2025.3.25.0
前端代码是怎样智能生成的
Requires Python: >=3.6

# 前端代码是怎样智能生成的

## 下载

### Docker

```
docker pull apachecn0/qianduan-daima-shi-zenyang-zhineng-shengcheng-de
docker run -tid -p <port>:80 apachecn0/qianduan-daima-shi-zenyang-zhineng-shengcheng-de
# 访问 http://localhost:{port} 查看文档
```

### PYPI

```
pip install qianduan-daima-shi-zenyang-zhineng-shengcheng-de
qianduan-daima-shi-zenyang-zhineng-shengcheng-de <port>
# 访问 http://localhost:{port} 查看文档
```

### NPM

```
npm install -g qianduan-daima-shi-zenyang-zhineng-shengcheng-de
qianduan-daima-shi-zenyang-zhineng-shengcheng-de <port>
# 访问 http://localhost:{port} 查看文档
```
pytorch-ziranyuyan-chuli-fix1-fix1 2025.3.25.0
PyTorch 自然语言处理（fix1）
Requires Python: >=3.6

# PyTorch 自然语言处理（fix1）

## 下载

### Docker

```
docker pull apachecn0/pytorch-ziranyuyan-chuli-fix1
docker run -tid -p <port>:80 apachecn0/pytorch-ziranyuyan-chuli-fix1
# 访问 http://localhost:{port} 查看文档
```

### PYPI

```
pip install pytorch-ziranyuyan-chuli-fix1
pytorch-ziranyuyan-chuli-fix1 <port>
# 访问 http://localhost:{port} 查看文档
```

### NPM

```
npm install -g pytorch-ziranyuyan-chuli-fix1
pytorch-ziranyuyan-chuli-fix1 <port>
# 访问 http://localhost:{port} 查看文档
```
pytorch-zhongwen-guanfang-jiaocheng-1-7-chuyi-fix1 2025.3.25.0
PyTorch 中文官方教程 1.7（初译）
Requires Python: >=3.6

# PyTorch 中文官方教程 1.7（初译）

## 下载

### Docker

```
docker pull apachecn0/pytorch-zhongwen-guanfang-jiaocheng-1-7-chuyi
docker run -tid -p <port>:80 apachecn0/pytorch-zhongwen-guanfang-jiaocheng-1-7-chuyi
# 访问 http://localhost:{port} 查看文档
```

### PYPI

```
pip install pytorch-zhongwen-guanfang-jiaocheng-1-7-chuyi
pytorch-zhongwen-guanfang-jiaocheng-1-7-chuyi <port>
# 访问 http://localhost:{port} 查看文档
```

### NPM

```
npm install -g pytorch-zhongwen-guanfang-jiaocheng-1-7-chuyi
pytorch-zhongwen-guanfang-jiaocheng-1-7-chuyi <port>
# 访问 http://localhost:{port} 查看文档
```
pytorch-shendu-xuexi-shiyong-zhinan-chuyi-fix1 2025.3.25.0
PyTorch 深度学习实用指南（初译）
Requires Python: >=3.6

# PyTorch 深度学习实用指南（初译）

## 下载

### Docker

```
docker pull apachecn0/pytorch-shendu-xuexi-shiyong-zhinan-chuyi
docker run -tid -p <port>:80 apachecn0/pytorch-shendu-xuexi-shiyong-zhinan-chuyi
# 访问 http://localhost:{port} 查看文档
```

### PYPI

```
pip install pytorch-shendu-xuexi-shiyong-zhinan-chuyi
pytorch-shendu-xuexi-shiyong-zhinan-chuyi <port>
# 访问 http://localhost:{port} 查看文档
```

### NPM

```
npm install -g pytorch-shendu-xuexi-shiyong-zhinan-chuyi
pytorch-shendu-xuexi-shiyong-zhinan-chuyi <port>
# 访问 http://localhost:{port} 查看文档
```
pytorch-rengongzhineng-yantaohui-chuyi-fix1 2025.3.25.0
PyTorch 人工智能研讨会（初译）
Requires Python: >=3.6

# PyTorch 人工智能研讨会（初译）

## 下载

### Docker

```
docker pull apachecn0/pytorch-rengongzhineng-yantaohui-chuyi
docker run -tid -p <port>:80 apachecn0/pytorch-rengongzhineng-yantaohui-chuyi
# 访问 http://localhost:{port} 查看文档
```

### PYPI

```
pip install pytorch-rengongzhineng-yantaohui-chuyi
pytorch-rengongzhineng-yantaohui-chuyi <port>
# 访问 http://localhost:{port} 查看文档
```

### NPM

```
npm install -g pytorch-rengongzhineng-yantaohui-chuyi
pytorch-rengongzhineng-yantaohui-chuyi <port>
# 访问 http://localhost:{port} 查看文档
```
pytorch-rengongzhineng-jichuzhishi-chuyi-fix1 2025.3.25.0
PyTorch 人工智能基础知识（初译）
Requires Python: >=3.6

# PyTorch 人工智能基础知识（初译）

## 下载

### Docker

```
docker pull apachecn0/pytorch-rengongzhineng-jichuzhishi-chuyi
docker run -tid -p <port>:80 apachecn0/pytorch-rengongzhineng-jichuzhishi-chuyi
# 访问 http://localhost:{port} 查看文档
```

### PYPI

```
pip install pytorch-rengongzhineng-jichuzhishi-chuyi
pytorch-rengongzhineng-jichuzhishi-chuyi <port>
# 访问 http://localhost:{port} 查看文档
```

### NPM

```
npm install -g pytorch-rengongzhineng-jichuzhishi-chuyi
pytorch-rengongzhineng-jichuzhishi-chuyi <port>
# 访问 http://localhost:{port} 查看文档
```
pytorch-1-x-ziranyuyan-chuli-shiyong-zhinan-chuyi-fix1 2025.3.25.0
PyTorch 1.x 自然语言处理实用指南（初译）
Requires Python: >=3.6

# PyTorch 1.x 自然语言处理实用指南（初译）

## 下载

### Docker

```
docker pull apachecn0/pytorch-1-x-ziranyuyan-chuli-shiyong-zhinan-chuyi
docker run -tid -p <port>:80 apachecn0/pytorch-1-x-ziranyuyan-chuli-shiyong-zhinan-chuyi
# 访问 http://localhost:{port} 查看文档
```

### PYPI

```
pip install pytorch-1-x-ziranyuyan-chuli-shiyong-zhinan-chuyi
pytorch-1-x-ziranyuyan-chuli-shiyong-zhinan-chuyi <port>
# 访问 http://localhost:{port} 查看文档
```

### NPM

```
npm install -g pytorch-1-x-ziranyuyan-chuli-shiyong-zhinan-chuyi
pytorch-1-x-ziranyuyan-chuli-shiyong-zhinan-chuyi <port>
# 访问 http://localhost:{port} 查看文档
```
python3-opencv4-jisuanji-shijue-xuexi-shouce-chuyi-fix1 2025.3.25.0
Python3 OpenCV4 计算机视觉学习手册（初译）
Requires Python: >=3.6

# Python3 OpenCV4 计算机视觉学习手册（初译）

## 下载

### Docker

```
docker pull apachecn0/python3-opencv4-jisuanji-shijue-xuexi-shouce-chuyi
docker run -tid -p <port>:80 apachecn0/python3-opencv4-jisuanji-shijue-xuexi-shouce-chuyi
# 访问 http://localhost:{port} 查看文档
```

### PYPI

```
pip install python3-opencv4-jisuanji-shijue-xuexi-shouce-chuyi
python3-opencv4-jisuanji-shijue-xuexi-shouce-chuyi <port>
# 访问 http://localhost:{port} 查看文档
```

### NPM

```
npm install -g python3-opencv4-jisuanji-shijue-xuexi-shouce-chuyi
python3-opencv4-jisuanji-shijue-xuexi-shouce-chuyi <port>
# 访问 http://localhost:{port} 查看文档
```
python-ziranyuyan-chuli-dier-ban-fix1-fix1 2025.3.25.0
Python 自然语言处理第二版（fix1）
Requires Python: >=3.6

# Python 自然语言处理第二版（fix1）

## 下载

### Docker

```
docker pull apachecn0/python-ziranyuyan-chuli-dier-ban-fix1
docker run -tid -p <port>:80 apachecn0/python-ziranyuyan-chuli-dier-ban-fix1
# 访问 http://localhost:{port} 查看文档
```

### PYPI

```
pip install python-ziranyuyan-chuli-dier-ban-fix1
python-ziranyuyan-chuli-dier-ban-fix1 <port>
# 访问 http://localhost:{port} 查看文档
```

### NPM

```
npm install -g python-ziranyuyan-chuli-dier-ban-fix1
python-ziranyuyan-chuli-dier-ban-fix1 <port>
# 访问 http://localhost:{port} 查看文档
```
python-web-shendu-xuexi-shiyong-zhinan-chuyi-fix1 2025.3.25.0
Python Web 深度学习实用指南（初译）
Requires Python: >=3.6

# Python Web 深度学习实用指南（初译）

## 下载

### Docker

```
docker pull apachecn0/python-web-shendu-xuexi-shiyong-zhinan-chuyi
docker run -tid -p <port>:80 apachecn0/python-web-shendu-xuexi-shiyong-zhinan-chuyi
# 访问 http://localhost:{port} 查看文档
```

### PYPI

```
pip install python-web-shendu-xuexi-shiyong-zhinan-chuyi
python-web-shendu-xuexi-shiyong-zhinan-chuyi <port>
# 访问 http://localhost:{port} 查看文档
```

### NPM

```
npm install -g python-web-shendu-xuexi-shiyong-zhinan-chuyi
python-web-shendu-xuexi-shiyong-zhinan-chuyi <port>
# 访问 http://localhost:{port} 查看文档
```
globalfactordata 0.1.0
JKP 글로벌 팩터 데이터를 쉽게 불러올 수 있는 도구
Requires Python: >=3.7

# 🌍 Global Factor Data

본 패키지는 JKP의 글로벌 팩터 데이터를 쉽게 불러오는 Python 도구입니다.  
총 93개국, 13개 테마, 153개 팩터에 대한 시계열 데이터가 제공됩니다.

> 📚 **참고 논문**  
> Jensen, Theis Ingerslev, Bryan Kelly, and Lasse Heje Pedersen.  
> _Is there a replication crisis in finance?_, The Journal of Finance, 2023  
> 🔗 https://github.com/bkelly-lab/ReplicationCrisis

---

## 📁 데이터 출처

모든 데이터는 아래 Dropbox 폴더에서 제공되며,  
이 패키지는 해당 링크에서 데이터를 자동으로 받아옵니다.

📂 [Dropbox 링크](https://www.dropbox.com/scl/fo/zxha6i1zcjzx8a3mb2372/AN9kkos5H5UjjXUOqW3EuDs?rlkey=i3wkvrjbadft6hld863571dol&dl=0)

---

## 🔧 주요 함수

---

### 🟦 `get_market_returns(freq="monthly")`

모든 국가의 **시장 수익률**을 불러옵니다.

**Parameters**
- `freq` (`str`, optional): `"monthly"` 또는 `"daily"`

---

### 🟨 `get_gics()`

국가별 **GICS 섹터 수익률**을 불러옵니다.

---

### 🟩 `get_cmp()`

미국 내 **시가총액 그룹별** rank-weighted 특성 기반 포트폴리오 데이터를 제공합니다.

---

### 🟪 `get_factor_all(method="lms")`

모든 국가의 **팩터 수익률 데이터**를 불러옵니다.

**Parameters**
- `method` (`str`, optional):  
  - `"lms"`: 문헌에 부합하는 부호 규칙 기반 long-short 포트폴리오  
  - `"hml"`: 특성값 상/하위 포트폴리오 차이  
  - `"pfs"`: 특성값 기준 3개 포트폴리오 원본 데이터

⚠️ `daily` 데이터는 용량이 커서 Dropbox에서 직접 받는 것을 권장합니다.

---

### 🟥 `get_cluster_all(freq="monthly")`

모든 국가의 **클러스터(테마) 수익률**을 불러옵니다.

**Parameters**
- `freq` (`str`, optional): `"monthly"` 또는 `"daily"`

---

### 🟧 `get_factor(category="country", name="USA", freq="monthly")`

국가 또는 지역별 **팩터 수익률**을 불러옵니다.

**Parameters**
- `category` (`str`, optional): `"country"` 또는 `"region"`
- `name` (`str`): 국가명 또는 지역명
- `freq` (`str`, optional): `"monthly"` 또는 `"daily"`

🔍 사용 가능한 국가 및 지역명은 `get_country_classification()` 또는 업로드된 엑셀 파일 참고

---

### 🟫 `get_cluster(name="World", freq="monthly")`

각 지역의 **테마(클러스터) 수익률**을 불러옵니다.  
국가별 테마 수익률은 `get_cluster_all()`로 확인하세요.

**Parameters**
- `name` (`str`): 지역명
- `freq` (`str`, optional): `"monthly"` 또는 `"daily"`

---

## 📂 엑셀/메타 정보 불러오기

### 📄 `get_country_classification()`

국가명과 지역 구분 정보를 불러옵니다

---

### 📄 `get_factor_details()`

각종 팩터의 상세내용을 불러옵니다.

---

### 📄 `get_factor_cluster()`

153개 팩터의 테마 클러스터링 정보를 불러옵니다.

---