semvec/pypi-packages huggingface dataset:
sharkiq 1.5.0
Python API for Shark IQ robots
Requires Python: >=3.9

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[![PyPI](https://img.shields.io/pypi/v/sharkiq)](https://pypi.org/project/sharkiq/)
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# sharkiq
Unofficial SDK for Shark IQ robot vacuums, designed primarily to support an integration for [Home Assistant](https://www.home-assistant.io/).

This library is heavily based off of [sharkiq](https://github.com/ajmarks/sharkiq) by [@ajmarks](https://github.com/ajmarks), with a few minor changes to allow it to work on newer versions of the Shark API.

## Installation

```bash
pip install sharkiq
```

## Usage
Examples can be found in the [examples directory](examples/).

## Documentation
You can view the latest documentation [here](https://sharkiqlibs.github.io/sharkiq/).

## TODOs:
 * Add support for mapping
 * Once we have mapping, it may be possible to use the RSSI property combined with an increased update frequency
 to generate a wifi strength heatmap.  Kind of orthogonal to the main purpose, but I really want to do this.
 
## License
[MIT](https://choosealicense.com/licenses/mit/)
manygo 0.2.0
Python library with helpers for packaging golang source code
Requires Python: >=3.10
Keywords: golang, packaging, platform-tags

# manygo

[![Deploy Status](https://github.com/jmelahman/manygo/actions/workflows/release.yml/badge.svg)](https://github.com/jmelahman/manygo/actions)
[![PyPI](https://img.shields.io/pypi/v/manygo.svg)](https://pypi.org/project/manygo/)

A Python library for generating platform-specific tags for Golang packages and binaries.

## Features

- Convert Golang platform identifiers (GOOS and GOARCH) to Python platform tags

## Installation

```bash
pip install manygo
```

## Usage

```python
>>> import manygo
>>> manygo.get_platform_tag('linux', 'amd64')
'manylinux_2_17_x86_64'

>>> manygo.get_platform_tag('darwin', 'arm64')
'macosx_11_0_arm64'
```
youtube-sync 1.2.86
syncs youtube for offline play
Requires Python: >=3.10
Keywords: template-python-cmd

# youtube-sync

Syncs up your youtube or other channels data to the hard drive. A library.json file will be created to track which videos have already been found. It will download any missing files.

# Docker Setup

You will need to have `config.json` embedded at the root of the container. Render.com makes this easy with a secret file.

If you do not have the ability to inject a file at the root, stash your json as a one liner into env variable "YOUTUBE_SYNC_CONFIG_JSON"

# Config.json

This configuration holds the rclone configuration as well as the channel setup and destination root. There is no type checking for the rclone section, instead
just list the key value pairs as shown below.

```json
{
    "output": "dst:Bucket/root/path",
    "rclone": {
        "dst": {
            "type": "b2",
            "account": "****",
            "key": "****"
        }
    },
    "channels": [
        {
            "name": "RonGibson",
            "source": "brighteon",
            "channel_id": "rongibsonchannel"
        },
        {
            "name": "TheDuran",
            "source": "youtube",
            "channel_id": "@theduran"
        }
    ]
}
```

In this case the files will be outputted to

  * RonGibson -> dst:path/to/RonGibson/brighteon/*
  * TheDuran -> dst:path/to/TheDuran/youtube/*

Each output directory will have one `library.json` file an multiple mp3 files.



# PO Token TODO:

  * https://github.com/LuanRT/BgUtils
  * https://github.com/iv-org/youtube-trusted-session-generator
    * docker run -p 8080:8080 quay.io/invidious/youtube-trusted-session-generator:webserver