semvec/pypi-packages huggingface dataset:
ezhttpy 0.1.1
Simple HTTP server with custom commands and HTML support
Requires Python: >=3.7




# Easy HTTP Server

This is a simple HTTP server for Raspberry Pi or PC that can:

* ✅ Display custom HTML files
* ✅ Respond to custom POST requests (e.g. save form input to `output.txt`)
* ✅ Enable static file serving using the `webserverautofile` switch

---

## 📦 Usage

```python
from easy_http import EasyHTTPServer

server = EasyHTTPServer(
    ip='auto',
    port=8000,
    webserverautofile=True,
    webdir=None,
    custom_html_path=None
)
server.start()
```

---

## ⚙️ Arguments

| Argument            | Type   | Default       | Description                                                      |
| ------------------- | ------ | ------------- | ---------------------------------------------------------------- |
| `ip`                | `str`  | `'auto'`      | IP address to bind (`'auto'`, `'localhost'`, or a specific IP)   |
| `port`              | `int`  | `8080`        | Port to run the server on                                        |
| `webserverautofile` | `bool` | `False`       | If `True`, serves files from directory like a static file server |
| `webdir`            | `str`  | `os.getcwd()` | Directory to serve when `webserverautofile=True`                 |
| `custom_html_path`  | `str`  | `None`        | Path to custom HTML file (used when `webserverautofile=False`)   |

---

ℹ️ When `webserverautofile` is `False` and `custom_html_path` is not provided, the server shows a simple form and saves input to `output.txt`.

---

🔧 Simple, light, and useful for local web control panels or project dashboards!
agentec 0.1.0
Generate Markdown-based agent tasks from NLP prompts with optional OpenAI enhancement.
Requires Python: >=3.7
Keywords: ai, tasks, markdown, openai, cli, automation

# Agentec

Generate Markdown-based agent tasks from NLP prompts with optional OpenAI enhancement.

## Installation

```bash
pip install agentec
```

## Usage

### Basic Usage
```bash
agentec "Summarize product reviews"
```

### With OpenAI Enhancement
Set your OpenAI API key for enhanced task descriptions:

```bash
export OPENAI_API_KEY="your-api-key-here"
agentec "Create a data analysis pipeline"
```

Or add it to a `.env` file in your current directory:
```
OPENAI_API_KEY=your-api-key-here
```

## Features

- **Generate structured task files** from natural language prompts
- **Optional OpenAI integration** for enhanced, detailed task descriptions
- **Saves tasks in Markdown format** in your current directory under `tasks/`
- **Cross-platform compatibility** - works on Windows, macOS, and Linux
- **Simple CLI interface** - just provide your prompt and go

## Example Output

### Basic Task (without OpenAI)
```markdown
# Task: summarize_product_reviews

## Prompt
Summarize product reviews
```

### Enhanced Task (with OpenAI)
```markdown
# Task: summarize_product_reviews

## Prompt
Summarize product reviews

## Enhanced Task Description
### Overview
This task involves analyzing and summarizing product reviews to extract key insights...

### Objectives
- Extract key themes from customer feedback
- Identify common complaints and praise
- Provide actionable insights for product improvement

### Steps/Requirements
1. Collect product reviews from various sources
2. Clean and preprocess the review data
3. Apply sentiment analysis
...
```

## Requirements

- Python 3.7+
- Optional: OpenAI API key for enhanced task generation

## Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

## License

This project is licensed under the MIT License - see the LICENSE file for details.

## Author

Ahmed Hanoon - [ahmedhanoon02@gmail.com](mailto:ahmedhanoon02@gmail.com)
rss-provider 1.1.0
A new addon for Plone
Requires Python: >=3.10
Keywords: CMS, Plone, Python

# rss_provider

This is the Plone backend addon for [volto-rss-provider](https://github.com/collective/volto-rss-provider).

[![PyPI version](https://badge.fury.io/py/rss-provider.svg)](https://pypi.org/project/rss-provider/)

## Features

### Content Types

- The backend addon adds a `rss_feed` content type with `blocks` behavior enabled and two additional `max_title_length` and `max_description_length` fields in its schema.

## Installation

Install rss_provider with `pip`:

```shell
pip install rss_provider
```

## Contribute

- [Issue Tracker](https://github.com/collective/rss-provider/issues)
- [Source Code](https://github.com/collective/rss-provider/)

## License

The project is licensed under the GPLv2.
nirahmq 0.1.3a0
A Home Assistant MQTT client library
Requires Python: >=3.12
Keywords: home assistant, mqtt, mqtt client, mqtt discovery

# NirahMQ

![PyPI - Version](https://img.shields.io/pypi/v/nirahmq?label=PyPI)
![GitHub Actions Workflow Status](https://img.shields.io/github/actions/workflow/status/dionisis2014/nirahmq/ci.yaml?logo=github&label=CI)

A complete Home Assistant MQTT Python library with ease of use in mind

> [!WARNING]
> This library is currently in ALPHA! Expect things to change or break!

## ✨ Features

- Supports all Home Assistant MQTT components and all their features
- Use of device-based discovery instead of component-based for simpler organization
- Support for automatic cleanup of topics on exit
- Device wide and per component availability support
- MQTT birth and last will support for both device and Home Assistant
- Ease of use by simple static definitions, while allowing runtime modifications
- Full Python type hint support
- Validation of definitions and user inputs on load thanks to [pydantic](https://github.com/pydantic/pydantic)
- Extensible API through simple class inheritance

## 📦 Installation

NirahMQ requires Python 3.12 or later and can be installed simply with `pip install nirahmq`.

## 🚀 Simple example

Below is an example of a simple Text component that prints its contents on update:

<details>
<summary>Example code</summary>

```python
from nirahmq.components import Text
from nirahmq.device import Device, DeviceInfo, DiscoveryInfo, OriginInfo
from nirahmq.mqtt import MQTTClient


def callback(text: Text, payload: str) -> None:
    print(f"Got new text: `{payload}`")
    text.set_text(payload)


dinfo = DiscoveryInfo(
    device=DeviceInfo(
        name="NirahMQ Test Device",
        identifiers="NirahMQ-Test-Device"
    ),
    origin=OriginInfo(
        name="Python Program"
    ),
    components={
        'component1': Text(command_topic="~/cmd", state_topic="~/state", command_callback=callback)
    }
)

with (MQTTClient("homeassistant.lan", 1883, "user", r"password") as client,
      Device(client, dinfo, "node_id") as device):
    input("Press enter to continue...\n")
```
</details>

## 📝 License
Copyright © 2025 [Dionisis Toulatos](https://github.com/dionisis2014)

NirahMQ uses the [AGPL-3.0+](LICENSE) license
andyreagan 0.2.1
A command-line resume printer for Andy Reagan - Senior Data Scientist and educator with Ph.D. in Applied Mathematics
Requires Python: >=3.8
Keywords: bio, cli, cv, data-science, resume

A simple Python package that prints Andy Reagan\'s resume to the command
line when run via `uvx`.

# Installation

You can run this package directly with `uvx` without installation:

``` bash
uvx andyreagan
```

Or install it from PyPI:

``` bash
pip install andyreagan
```

Then run:

``` bash
andyreagan
```

# Usage

Simply run the command to see Andy\'s resume:

``` bash
$ uvx andyreagan
╔═══════════════════════════════════════════════════════════════════════════════╗
║                                 ANDY REAGAN                                   ║
╠═══════════════════════════════════════════════════════════════════════════════╣
║                         Senior Data Scientist & Educator                     ║
╚═══════════════════════════════════════════════════════════════════════════════╝

📍 Location: Springfield, MA
🏢 Current Role: Senior Data Scientist, MassMutual Data Science Program
🎓 Education: Ph.D. Applied Mathematics (Complex Systems), University of Vermont
...
```

# Development

To develop this package locally:

``` bash
git clone https://github.com/andyreagan/uvx-andyreagan
cd uvx-andyreagan
uvx --from . andyreagan
```

# About Andy

Andy Reagan is a Senior Data Scientist at MassMutual and educator at UC
Berkeley. He holds a Ph.D. in Applied Mathematics with a focus on
Complex Systems from the University of Vermont. His research includes
sentiment analysis, data visualization, and sociotechnical systems
analysis.

# License

This project is released under the MIT License.