semvec/pypi-packages huggingface dataset:
idotmatrix-sdk 0.1
Allow connect with I Dot Matrix screens
Requires Python: >3.9

# I Dot Matrix SDK

I Dot Matrix SDK is a Python library for controlling the I Dot Matrix display. It provides an easy-to-use interface for controlling the display based on [python3-idotmatrix-library](https://github.com/derkalle4/python3-idotmatrix-library)

## Features

- Multiple devices support
- Control the I Dot Matrix display (brightness, turn on/off, etc.)
- Time functionality
- Countdown functionality

## TODO
- Text support
- Image support

## Installation

You can install the package using pip:

```bash
pip install idotmatrix-sdk
```

## Usage

```python
import asyncio
import logging
import datetime

from idotmatrix_sdk import IDotMatrix
from idotmatrix_sdk import IDotMatrixColor

if __name__ == "__main__":
    logging.basicConfig(level=logging.DEBUG)
    logger = logging.getLogger(__name__)

    async def main():
        devices = await IDotMatrix.search_devices()
        if not devices:
            print("No devices found")
            return

        device = devices[0]
        print(f"Connecting to {device.name} ({device.address})")

        dot_matrix = IDotMatrix(device.address)
        await dot_matrix.connect()

        # Example usage of the IDotMatrix class
        await dot_matrix.set_time(datetime.datetime.now())
        await dot_matrix.turn_on()
        await dot_matrix.set_brightness(100)
        await dot_matrix.set_time_mode(3, True, True, IDotMatrixColor.random_color())

    asyncio.run(main())

```
expnumpy 0.1.0
{{package_description}}
Requires Python: >=3.7

# expnumpy

[![PyPI version](https://img.shields.io/pypi/v/expnumpy.svg)](https://pypi.org/project/expnumpy/)
[![Python Versions](https://img.shields.io/pypi/pyversions/expnumpy.svg)](https://pypi.org/project/expnumpy/)
[![License](https://img.shields.io/github/license/Sumedh1599/expnumpy.svg)](https://github.com/Sumedh1599/expnumpy/blob/main/LICENSE)
[![GitHub Issues](https://img.shields.io/github/issues/Sumedh1599/expnumpy.svg)](https://github.com/Sumedh1599/expnumpy/issues)
[![Tests](https://github.com/Sumedh1599/expnumpy/workflows/Tests/badge.svg)](https://github.com/Sumedh1599/expnumpy/actions)
[![Documentation Status](https://readthedocs.org/projects/expnumpy/badge/?version=latest)](https://expnumpy.readthedocs.io/en/latest/?badge=latest)

## Overview

{{package_description}}

This library is an enhanced version of numpy with additional features and improvements.

## Features

- All features from the original numpy
- {{feature_1}}
- {{feature_2}}
- {{feature_3}}
- Seamless integration with other exp libraries

## Installation

```bash
pip install expnumpy
```

## Quick Start

```python
import expnumpy as {{package_shortname}}

# Example code
{{example_code}}
```

## Documentation

For full documentation, visit [expnumpy.readthedocs.io](https://expnumpy.readthedocs.io/).

## Contributing

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

## License

Copyright (c) 2025 Sumedh Patil, Aipresso Limited, UK

This project is licensed under the MIT License - see the LICENSE file for details.
message-reflector 0.0.18
Streamlit component that allows you to reflect messages
Requires Python: >=3.11

# MessageReflector

## 概述
`MessageReflector` 是一个用于处理消息反射组件。它允许应用程序将服务端的消息发送给客户端，再有客户端原样返回，以避免服务端直接处理消息时卡主UI。

## 功能
- **消息处理**: 将服务端的消息发送给客户端，再有客户端原样返回

## 发布
1. 进入frontent执行npm run build
2. 进入setup.py目录执行 python setup.py sdist bdist_wheel
3. 执行运行 Upload PiPy Task

## 安装
使用 npm 或 yarn 安装组件：
```bash
npm install message_reflector
# 或者
yarn add message_reflector
```

## 使用示例
if message:= message_reflector(st.session_state["message"], delay_ms=10000):
    st.write(f"Received message: {message}")
else:
    st.write("No message")  


## 贡献
欢迎任何形式的贡献！请查看 [贡献指南](CONTRIBUTING.md) 以获取更多信息。

## 许可证
该项目遵循 MIT 许可证。有关详细信息，请参阅 [LICENSE](LICENSE) 文件。
docbuddy 0.1.5
Deprecated: Use ask-docs instead

# docbuddy (DEPRECATED)

**IMPORTANT: This package is deprecated. Please use [ask-docs](https://pypi.org/project/ask-docs/) instead.**

This package now serves as a compatibility layer that will automatically install `ask-docs` when installed.

## Migration

To migrate from docbuddy to ask-docs, simply update your imports and dependencies:

```python
# Old way
import docbuddy

# New way
import ask_docs
```

And update your requirements:

```
# Old requirement
docbuddy>=0.1.3

# New requirement
ask-docs>=0.1.0
```
persist-sql 0.2.1
Peristent SQLite Database using S3 on Cloud Workspaces
Requires Python: >=3.6

# Persist SQLite Database on Cloud Workspaces 

As a data science enthusiast, I have been using Lightning AI for my analytics and upskilling. It’s a great and cost-effective platform, but I’ve often faced one major limitation—the absence of SQL Server or any other persistent database.

This isn’t just a Lightning AI issue; it’s a common challenge with Google Colab, Codespaces, and other cloud workspaces. One common workaround is using SQLite, but there’s a catch—since cloud workspaces are ephemeral, all data is lost after every session, forcing me to recreate tables from scratch each time.

In Lightning AI, I could reuse the same database file within the same studio, but what if I wanted to access it across different studios? While there is a way around this, it’s neither easy nor straightforward.

Exploring Alternatives

I considered using AWS RDS or Azure Databases, but they are expensive and not ideal for someone using them for personal projects or learning.

The Solution: Persistent SQL Database for Cloud Workspaces

To address this, I built a python module 'persist-sql' that allows users to maintain a persistent SQL database in cloud environments using:
✅ SQLite Database for local queries
✅ AWS S3 Bucket for persistent storage

How to Use - 
1. pip install persist-sql
2. import persist-sql as ps
	ps.configure_aws(AWS_KEY, AWS_SECRET, AWS_BUCKET_NAME) 
	ps.connect_db('DEV')
	%sql select * from tablename
	ps.close_connection()

Limitations & Considerations

🔹 This works best when your database size is small.
🔹 If your data grows significantly, consider splitting tables across multiple database files to optimize performance.

GitHub Repository & Demo Notebook

I have shared sample notebook demonstrating how to use this solution. Feel free to explore, contribute, and share your feedback! 🚀
romanutils 0.1.0
A Python library for Roman numeral manipulation
Requires Python: >=3.6

A Python library for Roman numeral manipulation romanutils
# Description:

romanutils is a Python module designed to facilitate the manipulation and conversion between integers and Roman numerals. This utility provides an easy-to-use interface for developers and enthusiasts looking to work with Roman numeral representations in their applications.

>>Features
Integer to Roman Conversion: Convert integers (1-3999) to their equivalent Roman numeral representation.
Roman to Integer Conversion: Convert valid Roman numerals back to their integer form.
Validation: Check the validity of Roman numerals to ensure correct formatting.
Customizable Output: Options to format the output for different use cases.
Installation
You can install romanutils via pip:

Copy
pip install romanutils
Usage
Hereâ€™s a quick example of how to use the module:

Copy
from romanutils import roman_to_int, int_to_roman

# Convert integer to Roman numeral
roman_numeral = itor(2023)
print(roman_numeral)  # Output: MMXXIII

# Convert Roman numeral to integer
integer_value = rtoi('MMXXIII')
print(integer_value)  # Output: 2023

# Contribution
Contributions are welcome! Please open an issue or submit a pull request for any improvements or features.

Feel free to contribute as much as possible! Whether it's reporting bugs, suggesting features, or submitting pull requests, your input is valuable.

>> Open Issues: Check the issues page for current tasks and bugs.
>> Feature Requests: Have an idea? Let us know on the feature request page.
>> Pull Requests: We welcome contributions!