semvec/pypi-packages huggingface dataset:
Sanatio 1.7.0
Simple and easy to validate data in Python
Requires Python: >=3.4
Keywords: sanatio, validation, python, data, data-validation, data-validation-python, data-validation-library, data-validation-python-library, data-validation-python-package, data-validation-package, data-validation-library-python

<p align="center">
  <a href="https://py-contributors.github.io/audiobook/"><img src="https://capsule-render.vercel.app/api?type=rect&color=009ACD&height=100&section=header&text=Sanatio&fontSize=80%&fontColor=ffffff" alt="website title image"></a>
  <h3 align="center">👉 Sanatio is a latin word which mean Validation 👈</h2>
  <h3 align="center"><b>Document, String, Number, Date, Email, Username, Password</b> Validator for Python. Inspired by <a href="https://github.com/validatorjs/validator.js">Validator.JS</a></h2>
</p>


## Installation

```bash
pip install sanatio
```

## Documentation

Check out the [documentation](https://sanatio.readthedocs.io/en/latest/) for more information.

## Roadmap

Check out the [roadmap](/ROADMAP.MD) for more information.

## Contributing

Check out the [contributing](/CONTRIBUTING.md) for more information.

## License

[Apache License 2.0](/LICENSE)


## Code of Conduct

[Code of Conduct](/CODE_OF_CONDUCT.md)
tea-python 1.2
Tiny Encryption Algorithm

# tea

## 介绍

tea：TEA算法由剑桥大学计算机实验室的David Wheeler和Roger Needham于1994年发明。它是一种分组密码算法，其明文密文块为64比特，密钥长度为128比特。TEA算法利用不断增加的Delta(黄金分割率)值作为变化，使得每轮的加密是不同，该加密算法的迭代次数可以改变，**本算法的迭代次数为32轮**。

本软件包已上传到 pypi, 可通过 pip 进行安装：

```
pip install tea-python
```

## 示例代码：

```python
import tea

if __name__ == '__main__':
    key = "1122334455667788".encode()
    origin = bytearray()

    for i in range(16):
        origin.append(i)

    print('原数据:  ', origin.hex())
    encrypt_data = tea.encrypt(origin, key)
    print('加密数据:', encrypt_data.hex())
    decrypt_data = tea.decrypt(encrypt_data, key)
    print('解密数据:', decrypt_data.hex())

```
mcp-server-ogp 0.1.5
OGP (Open Graph Protocol) information extraction server for Model Context Protocol (MCP)
Requires Python: >=3.10
Keywords: llm, mcp, model-context-protocol, ogp, open-graph, web-scraping

# OGP Information Server

A Model Context Protocol (MCP) server for extracting Open Graph Protocol (OGP) information from web pages. This server provides OGP metadata commonly used for social media sharing previews and rich link displays.

## Overview

Open Graph Protocol is a standard that allows web pages to control how their content appears when shared on social media platforms like Facebook, Twitter, and LinkedIn. This MCP server extracts that structured metadata and makes it available through simple tool interfaces.

## Tools

### ogp-info

Extracts comprehensive OGP information from any web page URL.

**Parameters:**

- `url` (string, required): The target web page URL

**Returns:**

Dictionary containing extracted OGP metadata such as:

- `title`: Page title
- `description`: Page description
- `image`: OGP image URL
- `site_name`: Site name
- `type`: Content type
- `url`: Canonical page URL
- Additional OGP properties as available

### ogp-image

Retrieves the OGP image from a web page and returns it as an optimized Image object.

**Parameters:**

- `url` (string, required): The target web page URL

**Returns:**

OGP Image Data

## Installation

### Using `uv` (Recommended)

No special installation is required when using `uv`. You can run `mcp-server-ogp` directly using `uvx`.

### Using PIP

Alternatively, you can install `mcp-server-ogp` using pip:

```sh
pip install mcp-server-ogp
```

After installation, you can run the script as follows:

```sh
mcp-server-ogp
```

## Configuration

### Configure for Claude.app

Add to your Claude settings:

<details>
<summary>Using uvx</summary>

```json
{
  "mcpServers": {
    "ogp": {
      "command": "uvx",
      "args": ["mcp-server-ogp"]
    }
  }
}
```

</details>

### Configure for VS Code

For quick installation, use one of the one-click install buttons below...

[![Install with UV in VS Code](https://img.shields.io/badge/VS_Code-UV-0098FF?style=flat-square&logo=visualstudiocode&logoColor=white)](https://insiders.vscode.dev/redirect/mcp/install?name=ogp&config=%7B%22command%22%3A%22uvx%22%2C%22args%22%3A%5B%22ogp%22%5D%7D)

### Command Line Options

You can specify the following options when running the server:

- `--sse`: Enable Server-Sent Events transport (on/off)
- `--host`: Server bind address (default: localhost)
- `--port`: Server port number (default: 8000)
- `--log-level`: Logging verbosity (debug, info, warning, error)

## License

MIT
seele-sdk 0.1.6
A Python SDK for interacting with Seele Agent services
Requires Python: >=3.7

# Seele SDK

Seele SDK 是一个用于与 Seele Agent 服务交互的 Python 工具包。它提供了一个简单的接口，用于与 AI 代理进行通信，包括思考、图像处理和自定义能力调用等功能。

## 安装

使用 pip 安装：

```bash
pip install seele-sdk
```

## 运行模式

SDK 有两种运行模式：

### 1. 平台模式
在 Seele 平台环境中运行时：
- Agent 信息会由平台自动注入
- 无需手动配置任何信息
- 必须在 Agent 配置面板中启用相应的能力才能调用
- 默认 base_url 为 http://127.0.0.1:8086

### 2. 本地开发模式
在本地开发和测试时：
- 需要手动提供 agent_info 字典（至少包含 id 字段）
- 确保调用的能力已在 Agent 配置面板中启用
- 可以根据需要覆盖 base_url

## 快速开始

以下是使用 SDK 的简单示例：

```python
from seele_sdk import AgentContext

# 本地开发：模拟 agent_info
agent_info = {
    "id": 53,  # 必需字段
    "name": "会议室302记录助手",  # 可选
    "description": "用于监控302会议室的助手",  # 可选
    "capabilities": {  # 可选
        "space_analysis": ["body_detection", "multimodal_vision"]
    }
}

# 使用上下文管理器（使用默认 base_url: http://127.0.0.1:8086）
with AgentContext(agent_info) as ctx:
    # 发送思考请求
    response = ctx.think("会议室现在是什么状态？")
    print(response)
    
    # 处理图片
    image_urls = ["http://example.com/image1.jpg"]
    response = ctx.look("描述一下这张图片中的内容", image_urls)
    print(response)
    
    # 清除 Agent 记忆
    # 可以清除所有记忆或指定会话的记忆
    result = ctx.clear_memory()  # 清除所有记忆
    # 或者
    result = ctx.clear_memory(session_id="session_123")  # 清除指定会话的记忆
    print(result)
```

## 最简配置

在本地开发时，如果只需要基本功能，可以只提供 id：

```python
from seele_sdk import AgentContext

# 最简配置
with AgentContext({"id": 53}) as ctx:
    response = ctx.think("你好")
    print(response)
```

## 直接使用 AgentSDK

如果你不想使用上下文管理器，可以直接使用 SDK：

```python
from seele_sdk import AgentSDK

# 初始化 SDK（使用默认 base_url）
sdk = AgentSDK(base_url="http://127.0.0.1:8086", agent_id=53)

# 发送思考请求
response = sdk.think("当前状态如何？")

# 处理图片
response = sdk.look("描述这张图片", ["http://example.com/image1.jpg"])

# 调用能力（需要在 Agent 配置中启用）
result = sdk.call_ability("namespace", "ability_name", "arg1", "arg2")

# 清除 Agent 记忆
result = sdk.clear_memory()  # 清除所有记忆
# 或者
result = sdk.clear_memory(session_id="session_123")  # 清除指定会话的记忆
```

### 关于能力的重要说明

1. **能力配置**
   - 必须在 Agent 配置面板中启用相应的能力才能调用
   - 调用未配置的能力会导致错误
   - 本地开发时可以在 agent_info 中列出能力，但这只是为了参考

2. **平台模式 vs 本地开发**
   - 平台模式：所有配置由平台自动注入，无需手动设置
   - 本地开发：只需提供必要的 agent_info（至少包含 id）

## 错误处理

SDK 内置了错误处理和日志记录功能：

```python
import logging

# 配置日志
logging.basicConfig(level=logging.INFO)

try:
    with AgentContext({"id": 53}) as ctx:
        response = ctx.think("你好")
except Exception as e:
    print(f"发生错误: {e}")
```

## 贡献

欢迎提交 Pull Request 来改进这个项目！

## 许可证

本项目采用 MIT 许可证 - 详见 LICENSE 文件。
regressalot 0.1.0
Simple AutoML tool for running and comparing ML models.
Requires Python: >=3.7

# Regressalot

**Regressalot** is a lightweight AutoML utility designed for **preliminary analysis and model comparison**.  
It helps you quickly assess the performance of multiple machine learning models using default settings and diagnostics — ideal for early exploration before fine-tuning or scaling.

## Features
- One-line run of Linear Regression, Decision Tree, Random Forest, and XGBoost
- Automatic feature encoding
- Evaluation metrics like R², RMSE, RMSPE, over/under-predictions, overfitting
- Ranking of models by performance
- Prediction plots

## Installation
```bash
pip install regressalot
mcp-server-google-news 0.1.8
Google News MCP server for fetching news articles
Requires Python: >=3.10
Keywords: google-news, llm, mcp, model-context-protocol, news, rss

# MCP Server Google News

A Model Context Protocol (MCP) server for fetching Google News articles with configurable language and region settings.

## Available Tools

### google_news_search

Search for news articles using a query.

Parameters:

- `query` (string, required): Search query
- `limit` (int, optional): Number of articles to fetch (default: 10)
- `hl` (string, optional): Language code (default: "ja")
- `gl` (string, optional): Geographic location code (optional)

### google_news_topics

Get news articles by topic.

Parameters:

- `topic_id` (string, optional): Topic ID (default: TOP)
- `limit` (int, optional): Number of articles to fetch (default: 10)
- `hl` (string, optional): Language code (default: "ja")
- `gl` (string, optional): Geographic location code (optional)

Available Topics:

- `TOP`: トップニュース (default)
- `NATION`: 国内
- `WORLD`: 国際
- `BUSINESS`: ビジネス
- `TECHNOLOGY`: テクノロジー
- `ENTERTAINMENT`: エンタメ
- `SPORTS`: スポーツ
- `SCIENCE`: 科学
- `HEALTH`: 健康

## Language and Region Codes

### Common Language Codes (hl parameter)

- `ja`: Japanese (default)
- `en`: English
- `zh-CN`: Chinese
- `fr`: French
- `de`: German
- `es`: Spanish
- `ko`: Korean

### Common Region Codes (gl parameter)

- `JP`: Japan
- `US`: United States
- `GB`: United Kingdom
- `CN`: China
- `FR`: France
- `DE`: Germany
- `KR`: South Korea

## Installation

### Using `uv` (Recommended)

No special installation is required when using `uv`. You can run `mcp-server-google-news` directly using `uvx`.

### Using PIP

Alternatively, you can install `mcp-server-google-news` using pip:

```sh
pip install mcp-server-google-news
```

After installation, you can run the script as follows:

```sh
mcp-server-google-news
```

## Configuration

### Configure for Claude.app

Add to your Claude settings:

<details>
<summary>Using uvx</summary>

```json
{
  "mcpServers": {
    "google-news": {
      "command": "uvx",
      "args": ["mcp-server-google-news"]
    }
  }
}
```

</details>

### Configure for VS Code

For quick installation, use one of the one-click install buttons below...

[![Install with UV in VS Code](https://img.shields.io/badge/VS_Code-UV-0098FF?style=flat-square&logo=visualstudiocode&logoColor=white)](https://insiders.vscode.dev/redirect/mcp/install?name=google-news&config=%7B%22command%22%3A%22uvx%22%2C%22args%22%3A%5B%22google-news%22%5D%7D)

### Command Line Options

You can specify the following options when running the server:

- `--sse`: Enable Server-Sent Events transport (on/off)
- `--host`: Server bind address (default: localhost)
- `--port`: Server port number (default: 8000)
- `--log-level`: Logging verbosity (debug, info, warning, error)

## License

MIT
easy-ask 0.1.0
Generate ECharts option dictionaries
Requires Python: >=3.12

# easy-ask

easy-ask is a minimal demonstration package intended to show how chart options can be generated programmatically. The library exposes a function called `generate_option` which accepts a chart type and data description and returns a configuration dictionary.

## Quick start

```python
from easy_ask import generate_option

# Build an option for a bar chart
option = generate_option(
    chart_type="bar",
    data=[{"value": 10}, {"value": 20}, {"value": 30}],
    title="Demo Bar Chart",
)
print(option)
```

## Python version

This project requires **Python 3.12** or newer, as specified in `pyproject.toml`.

## Running the demo

To see the package in action, run the demonstration module:

```bash
python -m easy_ask
```

Example scripts are also available in the `examples/` directory.
django-hidp-django-admin 1.0.0
A Django-admin-themed template pack for HIdP
Requires Python: >=3.11

# HIdP templates for Django-admin

## Overview

This package contains Django-admin-styled templates for HIdP.

## Installation

1. Install the package using pip:

```bash
pip install django-hidp-django-admin
```

2. Add the package to your `INSTALLED_APPS` in your Django settings.

Note: Make sure to add it above the `hidp` app so that templates are loaded correctly.

```python
INSTALLED_APPS = [
    ...
    "hidp_django_admin",
    ...
]
```

3. Add the following urls to your projects `urls.py` above the `hidp_urls`.

```python
url_patterns = [
    ...
    # Hello, ID Please
    path(
        "django-admin/login/",
        RedirectView.as_view(pattern_name="hidp_accounts:login"),
    ),
    path("django-admin/", admin.site.urls),
    ...
]
bblabs 0.1.0
A collection of reusable utility functions and modules.
Requires Python: >=3.10
Keywords: bblab, bitbytelab, python, utility, utils


<p><div align="center">
  <img src="assets/bitbytelab.png" alt="BitByteLab Logo" height="100">
 

**A Collection of reusable utilities.**

[![Release](https://img.shields.io/github/v/tag/bitbytelab/bblab)](https://github.com/bitbytelab/bblab/tag)
[![Platforms](https://img.shields.io/badge/platform-windows%20%7C%20macOS%20%7C%20linux-blue)]()
[![License](https://img.shields.io/badge/license-MIT-blue.svg)](./LICENSE)
[![Python](https://img.shields.io/badge/Python-3.9%2B-blue.svg)](https://www.python.org/)
[![PyPI](https://img.shields.io/badge/PyPI-upwork-cli-lightgrey.svg)](https://pypi.org/project/upwork-cli)

</div></p>

bblab.utils
=============================================

A collection of reusable utility functions and modules.

Usage
=====

---
## 🧪 Project Structure

<pre>
<!-- dir-tree-start -->
📁 bblab/
├── 📁 src/
│   └── 📁 bblab/
├── 📁 examples/
│   └── sample_usage.py
├── 📁 tests/
│   └── test.py
├── ⚙️ .env
├── 🚫 .gitignore
├── 📃 LICENSE
├── 📃 LICENSE.txt
├── ⚙️ pyproject.toml
├── 📝 README.md
└── ⚙️ ruff.toml
<!-- dir-tree-end -->
</pre>

---

## 📄 License

Licensed under the [MIT License](LICENSE).

---

## 🤝 Contributing

- Open an issue for ideas, bugs, or suggestions.
- Pull requests are welcome!

---

## 🔗 Links

- 📦 [PyPI](https://pypi.org/project/bblab)
- 🛠️ [Issues](https://github.com/bitbytelab/bblab/issues)
- ⭐ [Star on GitHub](https://github.com/bitbytelab/bblab)

---
qfeval_functions 0.1.0
Functions for quantitative finance
Requires Python: >=3.9

# qfeval-functions

qfevalは、Preferred Networks 金融チームが開発している、金融時系列処理のためのフレームワークです。
データ形式の仕様定義、金融時系列データを効率的に扱うためのクラス/関数群、および金融時系列モデルの評価フレームワークが含まれます。

qfeval-functionsは、qfevalの中でも、金融時系列データを効率的に扱うための関数群を提供します。

---

qfeval is a framework developed by Preferred Networks' Financial Solutions team for processing financial time series data.
It includes: data format specification definitions, a set of classes/functions for efficiently handling financial time series data, and a framework for evaluating financial time series models.

qfeval-functions specifically provides a collection of functions within qfeval that facilitate efficient processing of financial time series data.


## Installation

```bash
pip install qfeval-functions
```

## Usage
TBD

# Pitfalls

## Calling qfeval_functions.random.seed without `fast=True` may slow down `qfeval_functions.functions.rand*`

Calling `qfeval_functions.random.seed` without `fast=True` makes `QF.rand*` functions use
reproducible random number generators implemented on CPU.
Setting `fast=True` lets `qfeval_functions.functions.rand*` functions to use random number generators
provided by CUDA via PyTorch.  It is fast, but it is closed source.
It cannot be reproducible on CPUs, and it may not be reproducible with other
PyTorch/CUDA versions.
For reproducibility, calling `qfeval_functions.random.seed` forces to use a reproducible way by
default.
schedulix 0.0.2
A user friendly wrappr for scheduling tasks
Requires Python: <4,>=3.9

# schedulix

[![pypi](https://img.shields.io/pypi/v/schedulix.svg)](https://pypi.org/project/schedulix/)
[![versions](https://img.shields.io/pypi/pyversions/schedulix.svg)](https://git-ce.rwth-aachen.de/kls/schedulix)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://git-ce.rwth-aachen.de/kls/schedulix/-/blob/main/LICENSE?ref_type=heads)

*description to be added*

⚠️ Note: This package is currently in active development. It is not yet feature-complete. Users should expect changes and potential instability.

👥 Please feel free to test and contribute.

## 🚀 Quickstart Example
_to be added_

## 🔨 Installation
```bash
pip install schedulix
```

## ©️ License

This project is licensed under
the [MIT License](https://git-ce.rwth-aachen.de/kls/schedulix/-/blob/main/LICENSE?ref_type=heads).
scheudlix 0.0.2
A user friendly wrappr for scheduling tasks
Requires Python: <4,>=3.9

# schedulix

[![pypi](https://img.shields.io/pypi/v/schedulix.svg)](https://pypi.org/project/schedulix/)
[![versions](https://img.shields.io/pypi/pyversions/schedulix.svg)](https://git-ce.rwth-aachen.de/kls/schedulix)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://git-ce.rwth-aachen.de/kls/schedulix/-/blob/main/LICENSE?ref_type=heads)

*description to be added*

⚠️ Note: This package is currently in active development. It is not yet feature-complete. Users should expect changes and potential instability.

👥 Please feel free to test and contribute.

## 🚀 Quickstart Example
_to be added_

## 🔨 Installation
```bash
pip install schedulix
```

## ©️ License

This project is licensed under
the [MIT License](https://git-ce.rwth-aachen.de/kls/schedulix/-/blob/main/LICENSE?ref_type=heads).
mmb-layer0 1.0.5
MMB blockchain network
Requires Python: >=3.10

# 🧱 MMB Blockchain Network

[![Build and Release](https://github.com/devditoi/mmb_blockchain/actions/workflows/build_and_release.yaml/badge.svg)](https://github.com/devditoi/mmb_blockchain/actions/workflows/build_and_release.yaml)
[![Run Tests](https://github.com/devditoi/mmb_blockchain/actions/workflows/test.yaml/badge.svg)](https://github.com/devditoi/mmb_blockchain/actions/workflows/test.yaml)

**MMB Blockchain** is a custom-built experimental blockchain system designed from scratch with a modular, multi-layered architecture. It features a basic **Proof of Authority (PoA)** consensus, built-in smart contract handling, and support for decentralized applications (dApps) via a web interface.

---

## 🔧 System Architecture

The system is organized into **three primary layers**:

### 🧩 Layer 0 – Core Blockchain (Consensus & Networking)
- Full blockchain engine: blocks, mempool, hashing
- **PoA Consensus**: only authorized leaders are allowed to sign blocks
- Peer-to-peer node communication and block propagation
- Each node has its own private/public keypair (RSA or ECDSA)
- Signature validation and block rejection logic

### 📜 Layer 1 – Smart Contract & Token Layer
- Transaction types supported:
  - `mintburn` (native MMB token)
  - `native`, `transfer`
  - `stake`, `deploy_contract`, `call_contract` (under development)
- Smart contract data handled via `transactionData` field
- Cryptographic abstraction layer: pluggable sign/verify adapters (RSA, ECDSA)

### 🌐 Layer 2 – dApps & Web3 Interface
- User-facing frontend interfaces (in progress)
- Features: Wallets, Token Dashboard, Custom DEX
- Support for Web3 or custom RPC API

---

## ✅ Completed Features

- [x] PoA-based block creation and signature validation
- [x] Node synchronization and propagation of valid blocks
- [x] Cryptographic adapter system (RSA, ECDSA)
- [x] Minting restricted to authorized keys
- [x] Hex-encoded block outputs for readability

---

## 🚧 Roadmap

- [ ] Lightweight VM engine for smart contracts
- [ ] Stake-based validator rotation
- [ ] REST/Web3 APIs and explorer UI
- [ ] Cross-chain bridge & asset-backed token logic (e.g., USDT, BTC)
- [ ] NFT & DAO modules

---

## 📜 License

MIT License – this project is intended for educational and experimental purposes.

---

## 👤 Developer

**Lê Minh Quân** – Independent blockchain researcher and developer.
independent-validation 0.1.3
IV is a Python package designed to assess the accuracy of machine learning classifiers by generating a full probability distribution of their performance. This method goes beyond traditional cross-validation by using an iterative process and Markov Chain Monte Carlo (MCMC) to estimate uncertainty. By only using samples for training after they have been tested alpha inflation is prevented.
Requires Python: >=3.10

# IV: Independent Validation

IV is a Python package designed to assess the accuracy of machine learning classifiers by generating a full probability distribution of their performance. This method goes beyond traditional cross-validation by using an iterative process and Markov Chain Monte Carlo (MCMC) to estimate uncertainty.
By only using samples for training after they have been tested alpha inflation is prevented.

## Installation

```bash
pip install independent-validation
```


## Usage

An example of running the independent validation process with a classifier:

```python
from sklearn.datasets import load_wine
import independent_validation as iv
from sklearn.svm import SVC

wine = load_wine()
X, y = wine.data, wine.target

iv_svm = iv.IV(X, y, SVC(gamma='scale'))  # initiating
iv_svm.run_iv()  # classify samples
iv_svm.compute_posterior()  # use mcmc to compute posterior
bacc_svm_dist = iv_svm.get_bacc_dist()  # get desired output
print("Mode (MAP) value:", bacc_svm_dist.map())
```

## License

MIT License
fumes 0.1.0
A Python library for building web-based AI/data apps with custom frontends
Requires Python: >=3.8
Keywords: web, ai, data, ui, framework, streamlit, gradio

# Fumes

A Python library for building web-based AI/data apps with custom frontends. Fumes provides an intuitive Python API for creating interactive web applications, similar to Streamlit or Gradio, but with a unique design and modern features.

## Features

- 🎨 Intuitive Python API for defining UIs using decorators
- 🔄 Real-time updates via WebSocket
- 🎯 Modern, responsive UI with dark mode
- 🚀 Hot-reload for development
- 📦 Easy deployment with CLI tools
- 🎮 Rich set of UI components
- 🔌 FastAPI backend for high performance

## Installation

```bash
pip install fumes
```

## Quick Start

1. Create a new Fumes app:

```bash
fumes create my_app
cd my_app
```

2. Edit `app.py` to build your UI:

```python
from fumes import App, Textbox, Button

app = App(title="My AI Tool")

input = Textbox(label="Enter text")
btn = Button("Generate")

@app.bind(btn)
def on_click():
    return f"You typed: {input.value}"

if __name__ == "__main__":
    app.mount()
```

3. Run your app:

```bash
fumes run app.py
```

## Available Components

- `Textbox`: Text input field
- `Button`: Interactive button
- `Markdown`: Rich text display
- `Image`: Image display
- `FileUpload`: File upload component
- `Chart`: Data visualization

## CLI Commands

- `fumes create <app_name>`: Create a new Fumes app
- `fumes run <app.py>`: Run a Fumes app in development mode
- `fumes serve <app.py>`: Serve a Fumes app in production mode

## Development

```bash
# Clone the repository
git clone https://github.com/t4zn/fumes.git
cd fumes

# Install development dependencies
pip install -e ".[dev]"

# Run tests
pytest
```

## License

MIT License - see LICENSE file for details