semvec/pypi-packages huggingface dataset:
cartinese 0.3.0
Translate normal text into Cartinese.
Requires Python: >=3.13

Translate normal text into Cartinese.

# Usage

```python
import cartinese

text = "Hello, what is your name?"

configuration = cartinese.Configuration()
translated = cartinese.translate(text, configuration)

print(translated)
```

# Configuration

```python
import cartinese

text = "Hello, what is your name?"

# you can use
configuration = cartinese.Configuration()
configuration.swap_letter_p = 0.9
# or
configuration = cartinese.Configuration(swap_letter_p = 0.9)

translated = cartinese.translate(text)
print(translated)
```
project-rigor 0.5
Project RIGOR - The Remote IGOR
Requires Python: >=3.9

# Project RIGOR - The 'Remote' IGOR
This is the next evolution of the .

**Project RIGOR** is an evolution of the original [**Project IGOR**](https://github.com/UrbanCircles/igor) by UrbanCircles, with a focus on remote control and server-client architecture. The **R** in *RIGOR* stands for **Remote**, marking a shift from the on-chip processing of the original project to a more flexible and scalable system.

---

## Evolution from Igor

- **Original Igor**: Processed everything on the chip, with WiFi capabilities never utilized for remote interaction.
- **Project RIGOR**: Introduces a **server-client architecture** to decouple logic from the device.  
  - The **server** (written in Python) handles all complex logic and decision-making.
  - The **device** receives display instructions from the server and sends user inputs back to it.
  - This separation enables **easier updates**, **scalability**, and **integration with the full Python ecosystem**.
  - The server was written with a **strong focus on modularity** which makes it easy to pick and choose what functionality you want in **your** Project RIGOR

---

## Installation

Install via pip:

```bash
pip install project-rigor
```

## Getting Started

Here is an example of how you can create and combine different screens and modules to build your very own Project RIGOR.

Note that we're using the pomodoro module which you need to install with `pip install project-rigor-pomodoro`.
If you want to create your own modules, I recommend checking it out here [Pomodoro](https://github.com/jarvick257/rigor-pomodoro).

```python
from dataclasses import dataclass

from rigor import Content, Module, App, MqttClient
from rigor.screens import MenuScreen, TimedScreen

from pomodoro import Pomodoro()

class Submenu(MenuScreen):
    def __init__(self):
        super().__init__("Submenu", ["Save", "Option2", "Option3", "Go Back"])

    def on_enter(self):
        if self.selection == "Save":
            # TimedScreen will be shown for the specified time and then pop itself automatically
            # replace will pop the current screen before pushing a new screen.
            # So this is basically 'Save and Exit' with a success message
            self.replace(TimedScreen(1, "Success", "Saved"))

        if self.selection == "Go Back":
            # pop the current screen to go back
            self.pop()



@dataclass
class MyAppState:
    # Pomodoro is a RIGOR module
    pomodoro = Pomodoro()


class MyProjectRigor(MenuScreen[AppState]):
    def __init__(self):
        super().__init__("Home", ["Submenu", "Pomodoro"])

    def on_enter(self):
        if self.selection == "Submenu":
            self.push(Submenu())
        elif self.selection == "Pomodoro":
            self.push(self.state.pomodoro)


mqtt_client = MqttClient("192.168.1.2", 1883)
app = App(mqtt_client, mqtt_client)
app.run(MyAppState(), MyProjectRigor())
```

## Docker example

TODO


## License
This project is licensed under the MIT License. See the [LICENSE](./LICENSE) file for details.
parq-tools 0.3.1
A collection of utilities for efficiently working with **large-scale** Parquet datasets.
Requires Python: <3.13,>=3.10

# parq-tools
[![Run Tests](https://github.com/Elphick/parq-tools/actions/workflows/build_and_test.yml/badge.svg?branch=main)](https://github.com/Elphick/parq-tools/actions/workflows/build_and_test.yml)
[![PyPI](https://img.shields.io/pypi/v/parq-tools.svg?logo=python&logoColor=white)](https://pypi.org/project/parq-tools/)
![Coverage](https://raw.githubusercontent.com/elphick/parq-tools/main/docs/source/_static/badges/coverage.svg)
[![Python Versions](https://img.shields.io/pypi/pyversions/parq-tools.svg)](https://pypi.org/project/parq-tools/)
[![License](https://img.shields.io/github/license/Elphick/parq-tools.svg?logo=apache&logoColor=white)](https://pypi.org/project/parq-tools/)
[![Publish Docs](https://github.com/Elphick/parq-tools/actions/workflows/docs_to_gh_pages.yml/badge.svg?branch=main)](https://github.com/Elphick/parq-tools/actions/workflows/docs_to_gh_pages.yml)
[![Open Issues](https://img.shields.io/github/issues/Elphick/parq-tools.svg)](https://github.com/Elphick/parq-tools/issues)
[![Open PRs](https://img.shields.io/github/issues-pr/Elphick/parq-tools.svg)](https://github.com/Elphick/parq-tools/pulls)


## Overview
`parq-tools` is a collection of utilities for efficiently working with **large-scale** Parquet datasets.
A typical use case is asset-based workflows with large scientific datasets.

:::note
If your datasets are not large, you might find the `pandas` library more convenient.
:::

## Features
- [x] **Filtering** → Efficiently filter large parquet files.
- [x] **Concatenation** → Combines multiple Parquet files efficiently along rows (`axis=0`) or columns (`axis=1`).
- [x] **Tokenized Filtering** → Converts **pandas-style expressions** into efficient PyArrow queries.
- [x] **Profiling Enhancements** → Improves `ydata-profiling` by profiling **specific columns incrementally**, merging results for large files.
- [ ] **DataFrame Enhancements** → Provides a `LazyParquetDataFrame` class that extends `pandas.DataFrame` with lazy loading from Parquet files.
Py-library 1.0.15
py 工具箱
Requires Python: >=3.6

# Tools

### Installation 安装

```sh
pip install Py-library
```

### 使用前, 生成 `models.py`
```shell
sqlacodegen mysql+pymysql://user:password@localhost/dbname
```

### Usage example

### 异步 `mysql`, `redis` [使用示例](example.py):

## Contributing 贡献指南

有什么问题或建议, 可以在 [issues](https://github.com/CLannadZSY/Tools/issues) 中告诉我

## License 授权协议

这个项目 MIT 协议， 请点击 [LICENSE](LICENSE) 了解更多细节。
inworld-sdk 0.7.0
A Python SDK for Inworld
Requires Python: >=3.9

# inworld-sdk

A Python SDK for interacting with [Inworld's platform](https://docs.inworld.ai/docs/introduction).

## Description

This SDK provides a Python interface for working with Inworld's services, making it easy to integrate AI characters into your applications.

Currently, this SDK only supports the TTS API.

## Installation

You can install the package using pip:

```bash
pip install inworld-sdk
```

For development installation:

```bash
# Clone the repository
git clone https://github.com/MichaelSolati/inworld-sdk-python.git
cd inworld-sdk-python

# Create and activate a virtual environment
python -m venv venv
source venv/bin/activate  # On Windows, use: .\venv\Scripts\activate

# Install the package in development mode with all dependencies
pip install -e .
```

## Basic Usage

```python
import asyncio
import base64
import io

import simpleaudio as sa

from inworld_sdk import InworldClient


async def main():
  # Initialize the client
  client = InworldClient(api_key="<YOUR_API_KEY>")
  client.tts.update_options(audioEncoding="LINEAR16")

  # Example: Get voices
  voices = await client.tts.voices()
  print(voices)

  # Example: Synthesize and play speech
  text = "Hello! This is a test of the Inworld TTS system."
  synthesizedSpeech = await client.tts.synthesizeSpeech(text)
  audio_content = synthesizedSpeech.get("audioContent")
  decoded_audio = base64.b64decode(audio_content)
  wav_file = io.BytesIO(decoded_audio)
  play_obj = sa.WaveObject.from_wave_file(wav_file)
  play_obj.play().wait_done()


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

## Contributing

Contributions are welcome! Please feel free to submit a Pull Request. For major changes, please open an issue first to discuss what you would like to change.

1. Fork the repository
2. Create your feature branch (`git checkout -b feature/amazing-feature`)
3. Commit your changes (`git commit -m 'Add some amazing feature'`)
4. Push to the branch (`git push origin feature/amazing-feature`)
5. Open a Pull Request

## License

This project is licensed under the MIT License - see the [LICENSE.md](LICENSE.md) file for details.
nyterminal 1.0.0
Play the (good) NYT games within your terminal
Requires Python: <4,>=3.3
Keywords: NYT, New, York, Times, games, Wordle, Mini, Strands, Connections

# NYTerminal
## Play the (good) NYT games within your terminal!
If you ever find yourself in a situation where you have borked your Linux system and are left with nothing but a terminal, or you are being paid by the hour to use a server interface, or you are bored and don't have a browser handy, kill some time with the New York Times games in your terminal!

This program takes advantage of the fact that the free NYT games are publicly available on their servers. For the Wordle, Connections, and the Strands, there are named files for each date (including future dates!) that contain the JSON data for each day. The Mini is similar, but it only has today's puzzle. The Spelling Bee has its data embedded in the webpage, so an HTML parser has been used to facilitate it.

### Installation
Simply install the package with `pip`: `python3 -m pip install nyterminal`

### Running
Run the package (NAMED DIFFERENTLY) with `python3 -m nyterminal` or `nyterminal` if your default Python environment is the one NYTerminal is installed to.

### Interface
Using Curses, the terminal window is turned into a highly interactive UI. Most elements can be clicked, or you can use your arrow keys to navigate menus. While the controls are intuitive, here's a handy reference:
| Key                      | Function                     |
| ------------------------ | ---------------------------- |
| Up/Down/Left/Right Arrow | Navigate Menu/Increment Date |
| Enter                    | Activate Button/Submit Guess |
| Space                    | Select (Strands, Connections)|
| Tab                      | Use Hint (Strands)           |
| Escape                   | Exit Game (Saving)           |
| Control + C              | Quit Program                 |
NOTE: If you use CTRL+C to close the program with a game open, that game's data will not be recorded to your stats!
cloudflare-stream-downloader 0.1.1
A Python tool to download Cloudflare Stream videos with automatic FFmpeg management.
Requires Python: >=3.8

Cloudflare Stream Video Downloader
A simple and easy-to-use Python script for downloading videos from Cloudflare Stream. This tool automatically checks for and attempts to install FFmpeg (on Windows and Linux), then converts Cloudflare Stream video links into downloadable .mp4 files.

✨ Features
Automatic FFmpeg Management: Automatically detects if FFmpeg is installed on the system and attempts to download and install it on Windows and major Linux distributions.

Cloudflare Stream URL Conversion: Converts Cloudflare Stream URLs in thumbnails/thumbnail.jpg format to manifest/video.m3u8 format, which is suitable for FFmpeg download.

Video Download: Uses FFmpeg to download videos and saves them in .mp4 format.

Download Progress Display: Shows real-time FFmpeg progress output during the download.

🚀 How to Use
Prerequisites
Python 3.x

FFmpeg (The tool will attempt to install it for you automatically; if it fails, you may need to install it manually)

Install Dependencies
You only need to install the requests library to handle HTTP requests:

``` python
pip install requests
```
Run the Script

``` bash 
git clone https://github.com/LovelyO0sam/cloudflare-stream-downloader.git
cd cloudflare-stream-downloader
python cloudflare-stream-downloader.py
```
Follow the prompts to enter the Cloudflare Stream video URL. Please ensure the URL contains thumbnails/thumbnail.jpg or manifest/video.m3u8.

Example URL Format:

https://customer-XXXXX.cloudflarestream.com/YYYYYYYYYYYYYYYYYYYYYYYY/thumbnails/thumbnail.jpg

https://customer-XXXXX.cloudflarestream.com/YYYYYYYYYYYYYYYYYYYYYYYY/manifest/video.m3u8

Enter the desired output filename for the video (no extension needed; the script will automatically add .mp4).

The script will automatically convert the URL and start the download.

💻 Supported Operating Systems
Windows: Supports automatic FFmpeg download and installation.

Linux (Debian/Ubuntu, CentOS/RHEL/Fedora, Arch): Supports automatic FFmpeg installation via package managers.

macOS and other systems: Requires manual FFmpeg installation (e.g., macOS users can use Homebrew: brew install ffmpeg).

🤝 Contributing
Contributions of any kind are welcome! If you have suggestions for improvement, found a bug, or want to add a new feature, feel free to submit an Issue or Pull Request.

📄 License
This project is licensed under the MIT License. For more details, please see the LICENSE file.