semvec/pypi-packages huggingface dataset:
protosync 0.0.4.9
Sync code with a remote server in real time

# Protosync

Protosync syncs code seamlessly between your local development repo and a remote server. 

No more repeated git commits or long rsync commands just to test code out on the server.


### Install
```
pip install protosync
```


### Quick Start

In your **remote** directory, open a **new terminal** and enter:
```
protosync dest
```
Protosync will then print a command like this:
```
protosync source m0X1a-km0C6mCzWkl56xO0-hUQvYrhL0q5I5lK5qZgU=
```
Run this command in your **local** source directory.

And that's it! 

You local code will now be synced to the remote server.  
Just enter the same command whenever you want to sync again.

**Note:** you'll need to keep the remote terminal running for the sync to work.

### Facts

* Protosync uses your ```.gitignore``` to automatically ignore unnecessary files.
* Protosync ignores files larger than **5Mb** to prevent syncing of unwanted binaries.
* Protosync uses **end-to-end encryption** when syncing your files. The server **cannot** decrypt your data.
neuron-ml 1.0.0
A tiny image classification library.

<div align="center">
	<img width="500" height="500" src="https://raw.githubusercontent.com/arguiot/Neuron/master/assets/Neuron.png"/>
	<h1>Neuron</h1>
	A tiny and very high level transfer learning library for image classification ��
</div>

[![GitHub release](https://img.shields.io/github/release/arguiot/Neuron.svg)](https://github.com/arguiot/Neuron/releases)
[![Build Status](https://travis-ci.org/arguiot/Neuron.svg?branch=master)](https://travis-ci.org/arguiot/Neuron)
[![Github All Releases](https://img.shields.io/github/downloads/arguiot/Neuron/total.svg)](https://github.com/arguiot/Neuron/)
[![PyPI - Downloads](https://img.shields.io/pypi/dm/neuron-ml.svg)](https://pypi.org/project/neuron-ml/)
[![License](https://img.shields.io/github/license/arguiot/Neuron.svg)](LICENSE)

## What is Neuron exactly?

Neuron is a tiny library that aims to simplify image classification (If you don't know what Image classification is, it's the process to tell from an image what object / thing / feature is on it).

Using Neuron, you'll be able to build production grade model under 5 lines of code. Yes, you read it correctly: 5 lines. Where as in common Machine Learning libraries like TensorFlow, PyTorch or Keras, you would do it in hundreds of lines.

> Of course, these libraries are much more complex and versatile than Neuron. Neuron isn't replacing these libraries if you need to build your own graph, but if you're doing so, you probably already know this.

## Install
Copy - paste that in a Terminal
```
pip install neuron-ml
```
## Demo
Here is an example of what Neuron can do:
```py
import neuron_ml as n

# TensorFlow

data = n.load("./dataset/") # formats the data
model = n.train(data) # train the data
n.export(model, [
	"./Model.pb",
	"./Labels.txt"
]) # Exports everything
n.clean(model) # Clean temporary files
```

And it can also load files and classify them (before using it for production, make sure you have good hardware, as the model can take up to 5 seconds to load and run).

```py
import neuron_ml as n

model = n.model([
	"./Model.pb",
	"./Labels.txt"
]) # Load the model
graph = n.graph(model) # Generate the graph
labels = n.labels(model) # Get the labels
n.classify(graph, labels, "./dataset/Celery/celery-1.jpg") # Classify. Will return a result object
```

> See the wiki for more informations.

# Versioning

We use [SemVer](http://semver.org/) for versioning. For the versions available, see the [tags on this repository](https://github.com/arguiot/Neuron/tags).

# Authors

- **Arthur Guiot** - _Initial work_ - [@arguiot](https://github.com/arguiot)

Also look at the list of [contributors](https://github.com/arguiot/Neuron/contributors) who participated in this project. If you don't code but you have great ideas, don't hesitate to write your idea in the issue part. If your idea is accepted, I will add you to this list ��.

# License

This project is licensed under the MIT License - see the <LICENSE> file for details

Copyright © 2018 Arthur Guiot All Rights Reserved.
aviationFormula 0.0.2
A collection of formula around aviation and the globe in python.

# aviationFormula
A collection of formula around aviation and the globe in python.

A documentation of the implemented formula will follow.

## Requirements
All formula should work with every version of python. Only basic modules (like `math`) are imported. For the future I want to avoid using 3rd party packages such as `numpy`.

## Credits
None of the formula in this package where derived or invented by me. The only thing I did was an implementation in python.

The raw formula (and an implementation in VBA) are published by Ed Williams and can be found under the name [Aviation Formulary V1.46](http://www.edwilliams.org/avform.htm).

## Changelog
### version 0.0.2 - 15.12.2018
* Small fixes for wrong calculated distances

### version 0.0.1 - 12.12.2018
* First version with gcDistance and gcIntermediatePoint