semvec/pypi-packages huggingface dataset:
tut-langgraph 0.1.1
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Requires Python: >=3.12

# LangChain & LangGraph 学习项目

## 核心概念

### LangChain
LangChain 是一个用于构建基于语言模型应用的框架，主要功能包括：
- **组件化架构**：提供模块化组件（LLMs、记忆、索引等）
- **链式调用**：将多个组件连接成工作流（Chains）
- **记忆功能**：支持对话历史管理
- **数据增强**：可与外部数据源集成（Retrieval-Augmented Generation）
- **工具集成**：支持调用外部API和工具

### LangGraph
LangGraph 是建立在LangChain之上的框架，专注于：
- **状态机模型**：基于状态转换的流程控制
- **循环工作流**：支持多轮对话和复杂流程
- **分布式执行**：可扩展的分布式任务处理
- **可视化调试**：提供流程可视化工具

## API参考
langchain api
https://python.langchain.com/api_reference/reference.html

langgraph api
https://langchain-ai.github.io/langgraph/concepts/why-langgraph/

## 安装
```bash
uv build
```

## 技术栈

### 核心框架
- LangChain (v0.3.25+)
- LangGraph (v0.4.8+)

### 主要模块
- **语言模型集成**:
  - [x] langchain-openai (OpenAI接口)
  - [x] langchain-google-genai (Google Gemini接口)
  - [x] langchain-deepseek (DeepSeek模型)
  - [x] langchain-nvidia-ai-endpoints (NVIDIA接口)

- **数据连接器**:
  - [x] langchain-chroma (向量数据库)
  - [x] langchain-community (社区贡献连接器)
  - [x] psycopg2-binary (PostgreSQL连接)

- **工具扩展**:
  - [x] yfinance (金融数据)
  - [x] arxiv (学术论文)
  - [x] Faker (测试数据生成)

- **部署与监控**:
  - [x] Flask + Flask-SocketIO (Web服务)
  - [x] Gradio (快速UI构建)
  - [x] watchdog (文件监控)
  - [x] loguru (日志记录)
django-modern-captcha 0.1.2
A modern CAPTCHA solution for Django with behavioral analysis
Requires Python: >=3.6

Django Modern CAPTCHA 🛡️🤖
A next-generation CAPTCHA solution for Django that fights spam without frustrating users

https://img.shields.io/pypi/v/django-modern-captcha
https://img.shields.io/pypi/pyversions/django-modern-captcha
https://img.shields.io/pypi/djversions/django-modern-captcha
https://img.shields.io/badge/license-MIT-blue.svg

Features ✨
✅ Multiple verification methods - Choose from invisible, math, image, or honeypot challenges
✅ Behavioral analysis - Tracks mouse movements and typing patterns to detect bots
✅ Adaptive difficulty - Automatically adjusts based on suspicious activity
✅ Privacy-focused - No tracking or external dependencies
✅ Mobile-friendly - Works seamlessly across all devices
✅ Accessible - Designed with WCAG compliance in mind
✅ Admin analytics - Detailed reports on CAPTCHA attempts

Why Modern CAPTCHA? 🤔
Traditional CAPTCHAs are:

Annoying for users

Often inaccessible

Becoming less effective against advanced bots

Django Modern CAPTCHA solves these problems with:

Invisible verification for most users

Multiple fallback options

Machine learning-powered behavioral analysis

Simple integration with Django forms


Quick Start 🚀
bash
pip install django-modern-captcha
Add to your INSTALLED_APPS:

python
INSTALLED_APPS = [
    ...
    'modern_captcha',
]
Use in your forms:

python
from modern_captcha.forms import ModernCaptchaForm

class ContactForm(ModernCaptchaForm, forms.Form):
    name = forms.CharField()
    email = forms.EmailField()
    message = forms.CharField(widget=forms.Textarea)
Demo 🎮
Try the live demo (coming soon)

Documentation 📚
Full documentation available at modern-captcha.readthedocs.io

Contributing 🤝
We welcome contributions! Please see our Contribution Guidelines.


[![Tests](https://github.com/manish-codefyn/django-modern-captcha/actions/workflows/tests.yml/badge.svg)](https://github.com/manish-codefyn/django-modern-captcha/actions/workflows/tests.yml)
[![Code Coverage](https://codecov.io/gh/manish-codefyn/django-modern-captcha/branch/main/graph/badge.svg)](https://codecov.io/gh/manish-codefyn/django-modern-captcha)
[![Documentation Status](https://readthedocs.org/projects/django-modern-captcha/badge/?version=latest)](https://django-modern-captcha.readthedocs.io/en/latest/?badge=latest)


Author 👨💻
Manish Sharma
📧 Email: manis.shr@gmail.com
🐱 GitHub: manish-codefyn# django-modern-captcha
# django-modern-captcha
hkopenai.hk-election-mcp-server 0.1.8
Hong Kong election and legislature MCP Server providing election and legislature data tools
Requires Python: >=3.7

# Hong Kong Government Election and Legislature MCP Server

[![GitHub Repository](https://img.shields.io/badge/GitHub-Repository-blue.svg)](https://github.com/hkopenai/hk-election-mcp-server)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)

This is an MCP server that provides access to government security incident data through a FastMCP interface.

## Features

- **Registered Electors Data**: Retrieve the number of registered electors in Hong Kong's geographical constituencies for a specified range of years.

## Data Source

- Registered electors data from Registration and Electoral Office (voterregistration.gov.hk)

## Examples

* List number of registered electors in geographical constituencies in Hong Kong between 2009 and 2024

## Setup

1. Clone this repository
2. Install Python dependencies:
   ```bash
   pip install -r requirements.txt
   ```
3. Run the server:
   ```bash
   python app.py
   ```

### Running Options

- Default stdio mode: `python app.py`
- SSE mode (port 8000): `python app.py --sse`

## Cline Integration

To connect this MCP server to Cline using stdio:

1. Add this configuration to your Cline MCP settings (cline_mcp_settings.json):
```json
{
  "hk-election": {
    "disabled": false,
    "timeout": 3,
    "type": "stdio",
    "command": "uvx",
    "args": [
      "hkopenai.hk-election-mcp-server"
    ]
  }
}
```

## Testing

Tests are available in the `tests/` directory. Run with:
```bash
pytest
```
nvidia-srl-math 1.1.0
SRL Python common math functions related to robotics
Requires Python: >=3.7
Keywords: docker

# SRL Python Math Package

<h4>
    <a href="https://srl.gitlab-master-pages.nvidia.com/py/math/">Homepage</a> (
    <a href="https://srl.gitlab-master-pages.nvidia.com/py/math/getting_started.html">Getting Started</a> |
    <a href="https://srl.gitlab-master-pages.nvidia.com/py/math/cli.html">CLI</a> |
    <a href="https://srl.gitlab-master-pages.nvidia.com/py/math/examples.html">Examples</a> |
    <a href="https://srl.gitlab-master-pages.nvidia.com/py/math/contributing.html">Contributing</a> |
    <a href="https://srl.gitlab-master-pages.nvidia.com/py/math/api.html">API Reference</a> )
</h4>

This package provides basic and common math functions.

See the [documentation](https://srl.gitlab-master-pages.nvidia.com/py/math/) for detailed information.

## Quick Start

**Installation**

Use pip to install this Python distribution from the PYPI package registry (https://pypi.org/project/nvidia-srl-math/).

```
pip install nvidia-srl-math
```
istsa 1.0.5
ISTerre Time Series Analysis (ITSA) is a tool developed by Lou Marill.  This tool, developed in Python, produces a trajectory model for GNSS time series.
Requires Python: >=3.7
Keywords: gnss, gps, Time Series, Analysis, trajectory model

## ITSA = ISTerre Time Series Analysis

ITSA was developped by Lou Marill during her PhD, as a member of the ISTerre Cycle team.
This tool developped in python produces a trajectory model for GNSS time series. 

Inputs:
- the time series in PBO pos format
- the dates and types of discontinuities (antenna, earthquakes, slow-slip events, swarms)
- station coordinates (used to get earthquakes-station distance)
- optionally, a list of position outliers

ITSA calculates:
- the 3 dimensional offset for each equipment discontinuity
- post-seismic relaxation, currently without inversion (tau is an input parameter)
- linear, seasonal, and acceleration on the full time series

Outputs:
- Final time series
- Intermediate time series
- All modelled and applied corrections

ITSA is distributed under the licence CC-BY-NC: https://creativecommons.org/licenses/by-nc/4.0/

Documentation is available on the gitlab wiki: https://gricad-gitlab.univ-grenoble-alpes.fr/isterre-cycle/itsa/-/wikis/home
eplda 0.2.3
An unofficial lightweight Python client library for Premier League Data API
Requires Python: >=3.7
Keywords: premier-league football soccer api data statistics

# ⚽ English-Premier-League-Data-API

`EPL-Data` is an unofficial lightweight Python API client for [www.premierleague.com](https://www.premierleague.com/), providing quick access to data on Premier League players and clubs. It is ideal for data analysis and visualization.

**Note:** This project is for personal interest and learning only. Commercial use is strictly not permitted.


## Features
- ✅ Super user-friendly (hopefully)
- ✅ Player and club data access
- ✅ Supports both JSON and pandas DataFrame output formats
- ✅ Live Data

## What's New with the latest version
- Improved documentation and usage examples
- Self-explanatory naming
- More robust error handling and clearer API responses
- Expanded notebook example with step-by-step usage and visualization


## Installation
The easiest way to install the latest version is:
```
pip install eplda
```

## Quick Start Guide
Get the season ID for a specific season:
```python
from eplda import EPLAPI

epl = EPLAPI()
season_id = epl.get_season_id("2024/25")
```

Get the top scorer's list and convert it to a pandas DataFrame:
```python
df_goals = epl.get_player_rankings("goals", season_id, output="df")
```

Search for a player ID by name and get player information:
```python
player_id = epl.get_player_id("Erling Haaland", season_id)
player_info = epl.get_player_details(player_id, season_id)
```

## Example Notebook
A comprehensive demonstration is available in [examples.ipynb](examples.ipynb), including:

- Brief explanation of all methods
- Club and player data queries
- Data visualization

## Known Issues
- For some reason, some players cannot be found by ``search_player_by_name()`` or ``get_player_list()``.
(The temporary solution is to read the player's ID in the URL of the official website, e.g. Bukayo Saka's ID is [49481](https://www.premierleague.com/players/49481/Bukayo-Saka/overview))

## License & Terms of Use

### API Client

The `eplda` is open source with an [MIT License](LICENSE).

### T&C

``www.premierleague.com`` has a [Terms and Conditions](https://www.premierleague.com/terms-and-conditions) regarding the INTELLECTUAL PROPERTY RIGHTS. 

Please note that this project has been created for research purposes only and should not be misused in any way with this project or the data obtained from this it.

## Acknowledgement 
This project is based on Erick Ghuron's [premier-league-data](https://github.com/ghurone/premier-league-data).