semvec/pypi-packages huggingface dataset:
deluge-cmd 0.4.0
Command line tools to manage Synthstrom deluge SD card contents.
License: MIT
Requires Python: >=3.8,<4.0

# deluge-cmd

[![pypi](https://img.shields.io/pypi/v/deluge-cmd.svg)](https://pypi.org/project/deluge-cmd/)
[![python](https://img.shields.io/pypi/pyversions/deluge-cmd.svg)](https://pypi.org/project/deluge-cmd/)
[![Build Status](https://github.com/mupaduw/deluge-cmd/actions/workflows/dev.yml/badge.svg)](https://github.com/mupaduw/deluge-cmd/actions/workflows/dev.yml)
[![codecov](https://codecov.io/gh/mupaduw/deluge-cmd/branch/main/graphs/badge.svg)](https://codecov.io/github/mupaduw/deluge-cmd)


Some cli tools to manage Synthstrom Deluge SD card contents.

* Documentation: <https://mupaduw.github.io/deluge-cmd>
* GitHub: <https://github.com/mupaduw/deluge-cmd>
* PyPI: <https://pypi.org/project/deluge-cmd/>
* Free software: MIT

This project uses [deluge-card](https://github.com/mupaduw/deluge-card) which provides a python API for the Deluge Folder System.

## Features

- list Songs Samples, and Song Samples on a Deluge Folder System (DFS).
- check Deluge Folder Systems.
- list useful attributes tempo, key, scale.
- filter on path patterns: e.g. list all "Kick" samples).

e.g.

```
$> dls songs ~/Music/DELUGE/01 *001*
Deluge filesystem at /homie/Music/DELUGE/01 mounted: False
  DelugeSong(/homie/Music/DELUGE/01/SONGS/SONG001.XML) key C major tempo 96.0
  DelugeSong(/homie/Music/DELUGE/01/SONGS/SONG001A.XML) key C major tempo 96.0
  DelugeSong(/homie/Music/DELUGE/01/SONGS/SONG001B.XML) key C major tempo 108.0
  DelugeSong(/homie/Music/DELUGE/01/SONGS/SONG001C.XML) key C major tempo 108.0
  DelugeSong(/homie/Music/DELUGE/01/SONGS/SONG001D.XML) key C major tempo 96.0
```

## Experimental (backup first!)

> Move your samples, and update the songs that reference them
> 
> which has some [missing prime-time features](https://github.com/mupaduw/deluge-card/issues/14)

```
$> dmv ~/Music/DELUGE/TEST/02 **/CR78* SAMPLES/ANOTHER_PLACE -vs
~/Music/DELUGE/TEST/02/SONGS/SONG002A.XML update song xml
~/Music/DELUGE/TEST/02/SONGS/SONG002.XML update song xml
...
~/Music/DELUGE/TEST/02/SAMPLES/ANOTHER_PLACE/CR78 Closed hihat.wav move file
~/Music/DELUGE/TEST/02/SAMPLES/ANOTHER_PLACE/CR78 Metal.wav move file
moved 14 samples, in 9 songs
```

### Planned features
- (d)cp, and (d)rm commands.
- support for v4.0+ nested folders
- song groups (1, 1A, 1B, 1C).
- instruments, kits & synths.


## Credits

This package was created with [Cookiecutter](https://github.com/audreyr/cookiecutter) and the [waynerv/cookiecutter-pypackage](https://github.com/waynerv/cookiecutter-pypackage) project template.
scanpy-1b 0.0.0
An example project demonstrating various ways to access data files in Python package
License: MIT
Keywords: packaging,resources

## scanpy
> Scientific Anomaly detection using Python

Extreme event in computational (sci) situations are physics-driven anomalies, as opposed to
statistical outliers or measurement noise, and their detection is vital to physical nature of
scientific simulations. For example detecting combustion instabilities in 2D simulation, anomalous event in ecg-records across various patients etc.

The package provides collection of common unsupervised and supervised learning algorithms applied to scientific data settings. 

Sample turbulence dataset link: [Here](http://turbulence.pha.jhu.edu/)



## Algorithms Implemented

- KNN
- Linear Regression
- Logistic Regression
- Naive Bayes
- Perceptron
- SVM
- Decision Tree
- Random Forest
- Principal Component Analysis (PCA)
- K-Means
- AdaBoost
- Linear Discriminant Analysis (LDA)

## Where to get it
The source code is currently hosted on GitHub at: https://github.com/pandas-dev/pandas

Installers for the latest released version are available at the Python Package Index (PyPI) 

pip install 

This project has 2 dependencies.

- `numpy` for the maths implementation and writing the algorithms
- `Scikit-learn` for the data generation and testing.
- `Matplotlib` for the plotting.
- `Pandas` for loading data.
- 'Cantera'To install cantera check [Here] https://cantera.org/install/

**NOTE**: Do note that, Only `numpy` is used for the implementations. Others
help in the testing of code, and making it easy for us, instead of writing that
too from scratch.
potreepublisher 0.1.5
Small CLI to quickly publish a single LAS file or a whole folder to a Potree server.
License: MIT
Requires Python: >=3.7,<4.0

# PotreePublisher
Small CLI to quickly publish a single LAS file or a whole folder to a Potree server.


## Prerequisites
It is assumed that you have a **Potree server** installed on your machine.
<details>
<summary>Expand for instructions if you don't :wink:</summary>

1. Clone the potree repository: `git clone https://github.com/potree/potree`

2. Make sure you have the Node Package Manager (npm) installed (usually delivered with node.js).

3. Inside potree's repository, run `npm install`. It will install dependencies (specified in package.json) and create a build in ./build/potree.

4. Move the potree folder to you favorite http server.

5. Make sure you spot the location where you want to:
 + store the point clouds
 + store the viewer html files

6. You're good to go! 
</details>

It is also assumed that you have **PotreeConverter** installed. See [this page](https://github.com/potree/PotreeConverter) for instructions.

## Installation
```
pip install potreepublisher
```

## Usage
```
Usage: PotreePublisher [OPTIONS] INPUT_PATH

Arguments:
  INPUT_PATH  Path to the point cloud or a folder of point clouds to process.
              Any type supported by PotreeConverter is possible.  [required]

Options:
  --potree-server-root TEXT  Root path of the potree server.  [default:
                             /var/www/potree]
  --point-cloud-folder TEXT  Folder where the point cloud will be stored after
                             conversion to Potree Format.  [default:
                             pointclouds]
  --viewer-folder TEXT       Folder where the viewer html page will be stored.
                             [default: results]
  --help                     Show this message and exit.
```
zeustheinvestigator 0.1.7
A pure python program that checks if a site is online at the moment
License: MIT
Requires Python: >=3.7,<4.0

# Zeus the Investigator
![ZeusTheInvestigator0.1.7-preview](https://user-images.githubusercontent.com/76993204/170004945-e1ad079f-d1eb-46f5-9da2-51bd452bf635.gif)

#### **USAGE**
```powershell
$ zeus -u <first_url> -u <second_url> -c <cooldown(in secs. default=3)>
```

# Installation
## Manual Installation
**Note:** *You will need poetry for manual installation*
```bash
$ pip install poetry
```

1. Download or clone the repository.
```git
$ git clone https://github.com/777advait/Zeus-The-Investigator
```

2. Install the project by running the following command in the root of the directory.
``` bash
$ poetry install
```


## PyPi Installation
```bash
$ pip install ZeusTheInvestigator
```
pms5003-micropython 0.0.7
MicroPython library for the Plantower PMS5003 Particulate Matter Sensor.
License: MIT
Keywords: micropython,electronics

# PMS5003 MicroPython

[![PyPi Package](https://img.shields.io/pypi/v/pms5003-micropython.svg)](https://pypi.python.org/pypi/pms5003-micropython)
[![Python Versions](https://img.shields.io/pypi/pyversions/pms5003-micropython.svg)](https://pypi.python.org/pypi/pms5003-micropython)

MicroPython library for the Plantower PMS5003 Particulate Matter Sensor.

## Installing

Either download `pms5003/__init__.py` and save it to your device as "pms5003.py", or use Thonny's "Tools -> Manage Packages" to find and install "pms5003-micropython" from PyPi.