semvec/pypi-packages huggingface dataset:
emailpatterns 1.2.0
Shared Email Pattern Generator
Requires Python: >=3.8

# Email Patterns

Python utility to generate email addresses based on common patterns.

## Usage
```bash
pip install emailpatterns
```

```python
from emailpatterns.utils import generate_pattern_email, generate_all_pattern_emails

email = generate_pattern_email("pattern1", "example.com", "John", "Doe")
print(email)  # john.doe@example.com

all_emails = generate_all_pattern_emails("example.com", "John", "Doe")
print(all_emails)
```
sober 0.4.0
sober optimises built environment robustly
Requires Python: >=3.12

<picture>
    <source media="(prefers-color-scheme: light)" srcset="docs/assets/logo/sober_logo_black.svg">
    <source media="(prefers-color-scheme: dark)" srcset="docs/assets/logo/sober_logo_white.svg">
    <img alt="sober logo" src="docs/assets/logo/sober_logo_black.svg" width="300">
</picture>

**sober** **o**ptimises **b**uilt **e**nvironment **r**obustly

---

[![GitHub Actions Workflow Status - Docs](https://img.shields.io/github/actions/workflow/status/airallergy/sober/publish_docs.yml?logo=github&label=docs)](https://airallergy.github.io/sober/)
[![PyPI - Version](https://img.shields.io/pypi/v/sober?logo=pypi)](https://pypi.org/project/sober/)
[![Conda - Version](https://img.shields.io/conda/vn/conda-forge/sober?logo=condaforge)](https://anaconda.org/conda-forge/sober/)
[![GitHub License](https://img.shields.io/github/license/airallergy/sober)](LICENSE)
[![GitHub Actions Workflow Status - Test](https://img.shields.io/github/actions/workflow/status/airallergy/sober/test.yml?logo=github&label=test)](https://github.com/airallergy/sober/actions/workflows/test.yml)

## Installation

**sober** can be installed via either `conda`:

```zsh
conda install -c conda-forge sober
```

or `pip`:

```zsh
pip install sober
```
langgraph-browser-agent 0.1.0
A web browser agent built with LangGraph
Requires Python: <4.0,>=3.12

# LangGraph Browser Agent

This project is a web browser agent built with LangGraph. It can navigate websites, fill out forms, and interact with web elements.

This library is built on top of LangGraph, a powerful framework for building agent applications, and leverages [deepagents](https://github.com/langchain-ai/deepagents/tree/master) and [langchain-mcp-adapters](https://github.com/langchain-ai/langchain-mcp-adapters/tree/main). It also supports two browser manipulation backends: [playwright-mcp](https://github.com/microsoft/playwright-mcp) and [BrowserMCP](https://github.com/BrowserMCP/mcp).

## Demo

![Demo](assets/demo.gif)

## Getting Started

1.  **Prerequisites:**

    This agent requires Node.js to be installed and the `npx` command to be available in your path.

    If you are using the `browsermcp` backend (the default), please read the documentation at https://docs.browsermcp.io/setup-extension to set up the browser extension.

2.  **Clone the repository:**

    ```bash
    git clone https://github.com/your-username/langgraph-browser-agent.git
    cd langgraph-browser-agent
    ```

2.  **Install dependencies:**

    ```bash
    uv pip install -e .
    ```

3.  **Set up your environment:**

    This agent uses Ollama by default. Make sure you have Ollama installed and running. You can pull the default model with:

    ```bash
    ollama pull gpt-oss:20b
    ```

    You can also use other models by specifying them when creating the agent.

## Usage

To use the browser agent in your own project, you can import the `create_browser_agent` function and use it in an async context:

```python
import asyncio
from langgraph_browser_agent import create_browser_agent

OBJECTIVE = "Go to google.com and search for 'what is langgraph?'"

async def main() -> None:
    """Run the github example."""
    async with create_browser_agent(model="openai:gpt-5") as agent:
        final_result = await agent.ainvoke({"messages": [("human", OBJECTIVE)]})
        final_result["messages"][-1].pretty_print()

if __name__ == "__main__":
    asyncio.run(main())
```

You can also specify a different model when creating the agent:

```python
async with create_browser_agent(model="ollama:qwen3:8b") as agent:
    # ...
```

## Contributing

Contributions are welcome! Please open an issue or submit a pull request if you have any suggestions or improvements.

## License

This project is licensed under the MIT License.
rigol-dg1022 0.1.1
A Python driver for Rigol arbitrary signal generators
Requires Python: >=3.8
Keywords: Rigol DG1022, Rigol DG1062, Rigol DG4102, Python driver, Ethernet, USB, Signal generator, Industrial automation

# Rigol DGx Python Driver

This package provides a Python driver for controlling Rigol DGx arbitrary waveform generators via USB or Ethernet.

Confirmed to work with **DG1022**, **DG1062**, **DG4102**.

[Rigol Programming Guide](https://www.batronix.com/pdf/Rigol/ProgrammingGuide/DG1000Z_ProgrammingGuide_EN.pdf)

## Usage

```python
from rigol_dg1022 import RigolDG

# Connect to the device
dg = RigolDG()

# Set a sine wave on Channel 1
dg.apply_waveform(channel=1, waveform="SIN", frequency=1000, amplitude=1, offset=0)

# Turn on the output for Channel 1
dg.set_output(channel=1, state=True)

# Get the current frequency of Channel 1
freq = dg.get_frequency(channel=1)
print(f"Current frequency: {freq} Hz")

# Turn off the output
dg.set_output(channel=1, state=False)
```
mcp-search-linkup 0.1.6
A MCP server to search web with Linkup - **DEPRECATED** - Use the TypeScript version instead: https://github.com/LinkupPlatform/linkup-mcp-server
Requires Python: >=3.11

# 🌟 Linkup Python MCP Server

> ⚠️ **DEPRECATED**: This package is no longer maintained.
>
> Please use the TypeScript/Node.js version instead: **https://github.com/LinkupPlatform/linkup-mcp-server**
>
> The TypeScript version is actively maintained, has better performance, and supports all the latest features.

A Model Context Protocol (MCP) server that provides web search capabilities through Linkup's advanced search API. This server enables AI assistants and development tools to perform intelligent web searches with natural language queries.

<a href="https://glama.ai/mcp/servers/69qbbv8hl9"><img width="380" height="200" src="https://glama.ai/mcp/servers/69qbbv8hl9/badge" alt="mcp-search-linkup MCP server" /></a>

## ✨ Why Linkup?

- 🔍 **Advanced Web Search**: Leverage Linkup's AI-powered search engine for high-quality, relevant results
- 💬 **Natural Language Queries**: Ask questions in plain English or your preferred language - no need for keyword optimization
- 🚀 **Real-time Information**: Access up-to-date web content and current information
- 📚 **Comprehensive Results**: Get detailed search results with source citations
- 🔧 **Easy Integration**: Works with any MCP-compatible client

## 🚀 Installation

The Linkup MCP server can be used with any MCP-compatible client.

For an integration with Claude Desktop or with Cursor, please follow instruction [here](https://docs.linkup.so/pages/integrations/mcp/mcp).

For other MCP-compatible clients, use these connection details:

- **Command**: `python -m linkup_mcp_server`
- **Required Environment Variables**: `LINKUP_API_KEY`

Consult your MCP client's documentation for specific configuration instructions.

## 💬 Example Queries

The Linkup MCP server excels at answering complex questions and finding specific information:

- "What are the latest developments in quantum computing?"
- "How does the EU AI Act affect startups?"
- "Find recent research on sustainable aviation fuel"
- "What are the current best practices for MCP server development?"

## 🤝 Contributing

Pull requests are welcome! Feel free to open an issue first to discuss what you’d like to see improved.

## 📚 Resources

- [Linkup Documentation](https://docs.linkup.so)
- [MCP Protocol Specification](https://modelcontextprotocol.io)
- [Linkup API Reference](https://docs.linkup.so/api-reference)

## 📣 Community & Support

* Email: [support@linkup.so](mailto:support@linkup.so)
* Discord: [Join our community](https://discord.com/invite/9q9mCYJa86)
* X / Twitter: [@Linkup_platform](https://x.com/Linkup_platform)

## 📄 License

This project is licensed under the MIT License - Innovate freely! 🚀