semvec/pypi-packages huggingface dataset:
firefin 0.3.2
The bundled opensource toolkit for book Navigate through the Factor Zoo: The Science of Factor Investing.

# F.I.R.E. Factor Investment Research Engine

This repo is the bundled opensource toolkit for book _Navigating the Factor Zoo：The Science of Quantitative Investing_.

## Installation

```bash
# for stable version
pip install firefin

# for test and nightly version
pip install -i https://test.pypi.org/simple/ firefin

# Install from source for loacl testing!!!
## replace $ThisRepoURL with the actual repo url
git clone $ThisRepoURL 
## install from source
pip install -e .
```

## Usage

Download the data 
from [here](https://github.com/fire-institute/fire/releases/download/marketdata/AStockData.tar.gz)

run the command and download data put in correct path automatically.

```bash
# We have not released this repo yet, so you need download the data manually!!! See command below!!!
# Auto download data
firefin download
```

If you have already downloaded the data from [here](https://github.com/fire-institute/fire/releases/download/marketdata/AStockData.tar.gz), you can run the command to check the data and put the data in the correct path

```bash
# replace path_to_data.tar.gz with the actual path
firefin load path_to_data.tar.gz
```

## Start to code

```python
import firefin

# get data
data = firefin.fetch_data(["open", "close", "volume"])
open_price = data["open"]


def pv_corr(close, volume):
    # price volume correlation
    return close.rolling(20).corr(volume)


factor = pv_corr(data["close"], data["volume"])

# compute forward returns
fr = firefin.compute_forward_returns(open_price.shift(-1), [1, 5, 10])

# evaluate factor
mng = firefin.Evaluator(factor, fr)
mng.get_ic("pearson")
mng.get_quantile_returns(5)

```

## Features

1. handy functions for fast factor computation
2. various tools for factor evaluation
WeComMessage 1.0.3
发送企业微信消息的程序
Requires Python: >=3.6

# 说明
这是一个企业微信发送消息的程序

## 安装
使用pip安装：
bash
pip install SendMsg
 
### 联系我们
如果你有任何问题或建议，请联系我649898871@qq.com
nvdinterface 0.6.2
An convenience python class for interacting with NVD
Requires Python: >=3.11

# NVDInterface

NVDInterface is a python library to simplify retrieving and interacting with data from the National Vulnerability Database (NVD).

This project is currently in the early stages of development and will hopefully see changes soon, however is being made available early for others to use, test, and request changes on.

---

## Install

```shell
(.venv) $ pip install nvdinterface
```


## Example Usage

```pycon
>>> from nvdinterface import search_cves
>>> search_cves(cveId="CVE-2021-44228")
```

## Building from Source

1. Clone the repository
2. Enter repository directory
3. Install using poetry

*Example:*

```shell
(.venv) $ git clone https://github.com/LachJones/nvdinterface.git
(.venv) $ cd nvdinterface
(.venv) $ python -m poetry install
```
tsugu-uds 1.0.9
Tsugu User Data Server CLI Tool
Requires Python: >=3.8

# Tsugu User Data Server

Tsugu 用户数据库服务 CLI 实现


## 安装

```bash
pip install tsugu-uds
```

### 参数启动
```bash
tsugu-uds serve
```
### 相关参数可以在 help 中查看
```bash
tsugu-uds --help
tsugu-uds serve --help
```

### 启动服务器
使用Uvicorn ASGI服务器启动：

```bash
# 基本启动
tsugu-uds serve

# 指定日志级别
tsugu-uds serve --log-level debug

# 指定工作进程数
tsugu-uds serve --workers 4

# 调试模式启动
tsugu-uds serve --debug
```

### 配置文件启动
```bash
# 生成默认配置文件
tsugu-uds config new

# 使用配置文件启动（完全按配置文件设置）
tsugu-uds run
```

配置文件包含所有设置选项，可以手动编辑。关键配置项：
- `log_level`: 日志级别（`debug`, `info`, `warning`, `error`）
- `workers`: Uvicorn的工作进程数


### 数据库管理
```bash
tsugu-uds db --help
```


## direct-unbind 模式

使用 direct-unbind 参数启动服务器可实现解除绑定不验证, 但请保证你的服务器处于安全的非公网环境下才建议开启此功能, 否则任何人都有可能解除绑定任何账号, 此功能设计用于快速解除绑定.

此参数启用后  bind_player_request api 会在返回结果中添加一个 extra 字段, 值为 "safe_mode", 用于区分当前服务器的运行模式. 同时 bind_player_verification api 会直接解除绑定后, 返回解除成功状态.

目前支持 direct-unbind 的实现可以参考 [Tsugu-b3](https://github.com/kumoSleeping/tsugu-b3/blob/main/tsugu/__init__.py#L506).