semvec/pypi-packages huggingface dataset:
cunitPy 0.0.4
A universal converter package
Requires Python: >=3.8

# CunitPy
#### This is a universal conversor. It has methods to convert measurment units and world's most popular currency.

#
## Installation
```
pip install cunitpy
```

#
## How to use
```
from cunitpy import *
```
#### Now, use the pattern bellow to asign a variable the converted value: 
##### *Quantity.your_measurement_unit2new_measurement_unit(value)*
### Examples:
```py
# 38° Celsius to Kelvin
tempKel = Temperature.celsius2kelvin(38)
```
```py
# 250 pounds to kilograms
kg = Mass.pound2kilogram(250)
```
```py
# 2000 Japanese Ienes to Dollars
dol = Currency.JPY2USD(2000)
```
alex-music 0.0.3
A terminal music player
Requires Python: >=3.7

# Alex
Alex is a cli youtube music player

## How to install
- Have pip installed
- Requirements: mpv, yt-dlp
- Install Alex: 
    `pip install alex-music`

## Usage
#### Launching:
```
python -m alex_music
```

Also,
You can add an alias for alex_music in your .bashrc file
```
echo "alias alex='python -m alex_music'" >> ~/.bashrc
```
Then, alex_music can be launched by:
```
alex
```

#### Play some music
```
play despacito
```

#### Add to playlist
```
add baby shark tu tu ru
```
and 
```
play
```

#### For more commands
```
help
```
joern2sarif 1.1.12
Utility script to convert joern/ocular json output to sarif.
Requires Python: >=3.6

# Introduction

This is a utility script to convert the json file produced by [Joern](https://joern.io)/[Ocular](https://www.shiftleft.io/ocular/) to [SARIF](https://sarifweb.azurewebsites.net/) format.

## Usage

```bash
sudo pip install joern2sarif
joern2sarif -i findings.json -o joern-findings.sarif
```

Example usage on [GitHub action](https://github.com/prabhu/explnode/blob/master/.github/workflows/ocular.yml)

## License

Apache 2.0
normflowpy 0.2.0
A Normalizing flow package using PyTorch
Requires Python: >=3.6

# NormFlowPy
This repository contains the implementation of various types of normalizing flow/ invertible neural networks. In addition, we provide a simple API run, train, and implement new types of normalizing flows.
We have implemented the following layers:
* Affine Coupling
* Invertible 1x1 
* Neural Spline Flow and Cubic Flow
and others. Note, that so implementation's based on other Github repositories and this would be stated in each file.
# Installation
```
pip install normflowpy
```
# Code Examples 
We have provide only a single example at this stage please see [moons notebook](https://github.com/haihabi/NormFlowPy/blob/main/examples/moons_glow_example.ipynb)
# Contribution & Problems

We welcomes contributions from anyone and if you find a bug or have a question, please create a GitHub issue.

# Refernces

[1] Kingma, Durk P., and Prafulla Dhariwal. "Glow: Generative flow with invertible 1x1 convolutions." Advances in neural information processing systems 31 (2018).

[2] Laurent Dinh, David Krueger, and Yoshua Bengio. NICE: nonlinear independent components estimation. In Yoshua Bengio and Yann LeCun, editors, 3rd International Conference on
Learning Representations, ICLR 2015, San Diego, CA, USA, May 7-9, 2015, Workshop Track Proceedings, 2015.

[3] Andreas Lugmayr, Martin Danelljan, Luc Van Gool, and RaduTimofte.Srflow:  Learning  the  super-resolution  space  withnormalizing flow. InEuropean Conference on Computer Vision,pages 715–732. Springer, 2020.

[4]  Laurent Dinh, Jascha Sohl-Dickstein, and Samy Bengio. Densityestimation  using  real  nvp.arXiv preprint arXiv:1605.08803,2016.

[5] Conor Durkan, Artur Bekasov, Iain Murray, and George Papa-makarios. Cubic-spline flows.arXiv preprint arXiv:1906.02145,2019
ascendpbm-package 0.0.2.16
Common methods for handling ascendpbm's IT needs.
Keywords: python,pbm,pharmacy,employer insurance,ascendpbm,business logic

This is a growing library intended to make use of other python packages streamlined and scaleable for ascendpbm. It is to include tools for interfacing with FTP, SFTP, FTPS, email, Microsoft Graph API, PostgreSQL, bash scripts, reporting infrastructure/packages, and much more. Please note that it will require several unlisted dependencies and requirements such as our business environments, Anaconda installations, and many python packages.
catbase 1.0.0
JSON-based database you were dreaming of!
Requires Python: >=3.0

# CatBase
JSON-based database you were dreaming of!

## Quickstart

```py
from catbase import CatDB

db = CatDB("example.json")

db["test"] = "apple"
print(db["test"])

db.commit() # commit to save changes
```

## Features

### Autocommiting
```py
from catbase import CatDB

db = CatDB("example.json", autocommit=True)

db["test"] = "apple" # CatDB commits here automatically!
print(db["test"])
# no commit required!
```

### KeyError safety
```py
from catbase import CatDB

db = CatDB("example.json")

# oh no! "test" doesnt exist yet!
print(db["test"])
# output: None
```

### Custom KeyError defaults
```py
from catbase import CatDB

db = CatDB("example.json", none = 3)

# oh no! "test" doesnt exist yet again!
print(db["test"] + 1)
# output: 4
```

### Broken JSON safety
```py
from catbase import CatDB

db = CatDB("example.json", safe = False)

# now, if the example.json is corrupt, db will be empty instead of crashing.
# safe is set to True by default.
```