semvec/pypi-packages huggingface dataset:
AxisApi2 0.0.1
The second version of the axisapi. Codenamed "Ella" allows anyvody to easily connect to a hosted ai instance. Was created as part of the larger Dakota project.
Requires Python: >=3.6

# Axis API 2.0 "Ella"

Axis API 2.0 "Ella" is a Python package for connecting to a hosted llama instance.

## Installation

```bash
pip install axisapi2
```

## Usage

```python
from axisapi2 import connect

# Example usage
connect()
```

## License

This project is licensed under the MIT License. See the LICENSE file for details.
Torrscrape 1.1.5
Torrscraper is a command line tool to search and download torrents from the command line.
Keywords: python, torr, torrent, torrscrape, jackett, Torrscrape

##How to Use 

<h1>Installation</h1>
<h2>pip install Torrscrape</h2>

<h2>1)Install docker</h2> 
  mac:https://docs.docker.com/desktop/install/mac-install/<br>
  win:https://docs.docker.com/desktop/install/windows-install/<br>
  linux:https://docs.docker.com/desktop/install/linux-install/<br>
<h2>2)setup jackett:</h2>

docker run -d \
  --name=jackett \
  -e PUID=1000 \
  -e PGID=1000 \
  -e TZ=Etc/UTC \
  -e AUTO_UPDATE=true `#optional` \
  -e RUN_OPTS= `#optional` \
  -p 9117:9117 \
  -v /path/to/data:/config \
  -v /path/to/blackhole:/downloads \
  --restart unless-stopped \
  lscr.io/linuxserver/jackett:latest

<h2>3)setup qbit web(docker):</h2>

docker run -d \
  --name=qbittorrent \
  -e PUID=1000 \
  -e PGID=1000 \
  -e TZ=Etc/UTC \
  -e WEBUI_PORT=8080 \
  -p 8080:8080 \
  -p 6881:6881 \
  -p 6881:6881/udp \
  -v /path/to/appdata/config:/config \
  -v /path/to/downloads:/downloads \
  --restart unless-stopped \
  lscr.io/linuxserver/qbittorrent:latest

##Usage<br>
<h3>save api key jackett</h3>
<h3>torrscrape --api "jackett_apikey" </h3>
<h1>Search</h1>
<h3>torrscrape --search "search_term" --catagory "catagories"</h3>
<h2>catagories: TV,TV/Anime,Other,Movies,PC/Games</h2>
ytdl-1080p 0.1
ytdl is a command line tool to search and download videos in 1080p from yt using the command line.
Keywords: python, ytdl_1080p, ytdl-1080p, ytdl 1080p, 1080p, ytdl1080p, youtube, youtube downloader, ytdl, Ytdl, 1080p yt downloader, downloader, pytube

# git repo
<p>https://github.com/Tanish0907/yt-downloader-python_script-<p>

# YouTube Downloader (Python Package)

A cross-platform YouTube video/audio downloader with quality options.

## Installation

1. Install FFmpeg:

   **Linux**:
   ```bash
   sudo apt install ffmpeg
   ```

   **Windows/macOS**:  
   Download from [ffmpeg.org](https://ffmpeg.org/) and add to PATH

2. Install the package:
   ```bash
   pip install yt-downloader
   ```

## Basic Usage

```bash
yt-download --video "URL" [--quality 720|1080|best]
yt-download --audio "URL"
yt-download --playlist "URL"
```

## Features

- Multiple quality options (720p, 1080p, best available)
- Audio extraction (MP3)
- Playlist support
- Cross-platform (Windows/macOS/Linux)

## Notes

- Downloads save to `./video_downloaded/`
- Clear this folder between downloads to avoid errors
- Requires Python 3.8+

## Troubleshooting

If you get FFmpeg errors:
1. Verify installation with `ffmpeg -version`
2. Ensure it's in your system PATH

Key points:
1. Removed clone/git instructions since it's a pip package
2. Simplified FFmpeg instructions
3. Added clear pip install command
4. Basic usage shows package entry point (`yt-download`)
5. Kept essential troubleshooting info
6. Removed redundant information
openrgb-python-ng 0.3.3
A python client for the OpenRGB SDK
Requires Python: >=3.7

# OpenRGB-Python


[![Documentation Status](https://readthedocs.org/projects/openrgb-python/badge/?version=latest)](https://openrgb-python.readthedocs.io/en/latest/?badge=latest)

OpenRGB-Python is a client for the [OpenRGB SDK](https://gitlab.com/CalcProgrammer1/OpenRGB#openrgb-sdk),
a manufacturer-independent, cross-platform way to control your RGB devices.
OpenRGB-Python can be used to interface with other programs, create custom
effects, or anything else you can think of!

I started this project because I wanted to be able to control the color of my lights based on temps. I tried to implement the features in the best (easiest to use) way possible.  

SDK Feature Support:
  - [x] Setting client name
  - [x] Getting device info
  - [x] Setting color by device
  - [x] Setting color by zone
  - [x] Setting color by led
  - [x] Setting mode
  - [x] Setting custom mode
  - [x] Resizing zones

Additional Features (Not part of the OpenRGB SDK):
  - [x] Loading profiles
  - [x] Saving profiles

# Installation

requires python >= 3.7

Use this method for the newest, but possibly buggy, package:

`pip3 install git+https://github.com/jath03/openrgb-python#egg=openrgb-python`

Arch Linux:
`yay -S python-openrgb-git`

For a more stable package:

`pip3 install openrgb-python`

~~Arch Linux:
`yay -S python-openrgb`~~
This AUR package is out of date. Use `python-openrgb-git` instead.

Thanks to @GabMus for the AUR packages

# Usage

```python
from openrgb import OpenRGBClient
from openrgb.utils import RGBColor, DeviceType

client = OpenRGBClient()

client.clear() # Turns everything off

motherboard = client.get_devices_by_type(DeviceType.MOTHERBOARD)[0]

motherboard.set_color(RGBColor(0, 255, 0))
motherboard.zones[0].set_color(RGBColor(255, 0, 0))
motherboard.zones[1].leds[0].set_color(RGBColor.fromHSV(0, 100, 100))
motherboard.set_mode("breathing")
client.save_profile("profile1")
```

# Documentation

https://openrgb-python.readthedocs.io/en/latest/


For an alternative python implementation, check out [B Horn](https://github.com/bahorn)'s [OpenRGB-PyClient](https://github.com/bahorn/OpenRGB-PyClient)
skelly-viewer 2025.4.1028
View a skelly
Requires Python: <3.13,>=3.9
Keywords: basic, template, python, repository

# Installation

Create a conda environment using Python 3.11 (recommended, untested on other versions) and activate your conda environment 

Install skelly_viewer using `pip install skelly_viewer`

# Usage

After installing, in your conda terminal (with the right environment active), type `skelly_viewer'

You should see a GUI pop up with an empty graph, a slider, and two buttons

Click the `Load a session folder` button, and select a session folder that you would like to view the data from using the folder dialog 
(NOTE: As of right now, this viewer only works with pre-alpha labeled, post-processed data (it looks the `DataArrays` folder with a file 
called `mediaPipeSkel_3d_origin_aligned.npy` inside of it)

You can move the slider, and the 3D graph should show your skeleton

If you hit the `Load Videos` button on the side, select a folder of videos within your current session. When you move the slider, the videos
should load in and appear on the right hand side