semvec/pypi-packages huggingface dataset:
jupytercontrib 0.0.7
Some Jupyter contrib extensions

# jupyter contrib

Some small utilities that are related to Jupyter. 

This is not endorsed by the Jupyter team, and not part of the official Jupyter project. 

Feel free to submit any patches, or utility modules for which a full packages
might be inappropriate or too much of an hassle. 

# installation

```
pip install jupytercontrib
```

# Extensions

Any extension present here should not modify Jupyter/IPython behavior at install time. 
You can provide a tool to simplify activation, but installation should likely be without side-effects. 


# What can I find here:


## 2to3 for notebooks

An extra nbconvert exporter that convert Legacy Python 2 notebook to New Awesome and useful Python 3
It requires `nbconvert` master. 


It uses [entry points]  to directly expose a `--to=2to3` when using `jupyter nbconvert`, thus you can do thing like 

```
jupyter nbconvert --to 2to3 <mynotebook.ipynb>
```

This will create a file name `mynotebook.nbconvert.ipynb` which each cell converted to Python 3. 


## Markdown exporter w/ output

Extension of the standard notebook-to-markdown exporter that tags output cells as `output`.
Can be used, for example, when building Sphinx docs to style output differently from input code blocks. 

```
jupyter nbconvert --to mdoutput --output=<output.md> <mynotebook.ipynb>
```
dataset-downloader 1.0.0
Tool to download large dataset from a list of url

# Dataset Downloader

## Preview

Dataset_downloader allow you to download large dataset from multiple list of url, from [image-net](http://image-net.org) for example.
You can split the download into 2 folders, one for the training and one for the testing.
File are save into their class name, perfect for model training. It looks something like that:

```
root:.
|
â”œâ”€â”€â”€test
â”‚   â”œâ”€â”€â”€accerola
â”‚   â”œâ”€â”€â”€apple
â”‚   â””â”€â”€â”€lemon
â”œâ”€â”€â”€train
â”‚   â”œâ”€â”€â”€accerola
â”‚   â”œâ”€â”€â”€apple
â”‚   â””â”€â”€â”€lemon
```

## Installation

Simply install from pip:
```
pip install dataset_downloader
```

## Config

Create a `dataset.json` file with the following content:

```json
{
  "outputTrain": "...",
  "outputTest": "...",
  "ratio": ...,
  "classes": {
    "class1": [
      "http://url1",
      "http://url2"
    ],
    "class2": [
      "http://url1",
      "http://url2"
    ],
    "class3": "list_images.txt"
  }
}
```

* `outputTrain`: Output folder of the training images
* `outputTest`: Output folder of the testing images
* `ratio`: The ratio of training/testing images. 0.8 correspond of 80% of training images.
* `classes`: List of classes with their urls. Urls can be a list of url, a file containing a list of urls or an url containing a list of urls

An exemple of file on a windows computer:

```json
  "outputTrain": "D:/dataset/train",
  "outputTest": "D:/dataset/test",
  "ratio": 0.8,
  "classes": {
    "accerola": [
      "http://tiachea.files.wordpress.com/2008/10/acerolas.jpg",
      "http://www.jardimdeflores.com.br/floresefolhas/JPEGS/A56acerola5.JPG",
      "http://farm2.staticflickr.com/1353/4602150961_177e096984_z.jpg",
    ],
    "apple": [
      "http://www.naturalhealth365.com/images/apple.jpg",
      "http://urbanext.illinois.edu/fruit/images/apple1.jpg",
      "https://www.aroma-zone.com/cms//sites/default/files/plante-acerola.jpg"
    ],
    "lemon": "list_images.txt",
    "watermelon": "https://gist.githubusercontent.com/johnrazeur/645787bc08a5aedd82da9573fbfa169a/raw/49cea1ee1438cecef8ac213b20f24e5ae02d4d78/watermelon.txt"
  }
```

## Run

Simple call the dataset_downloader command:

```bash
cd yourdirectory
# You must create the dataset.json file before
dataset_downloader
```
EthIefLab 1.0.0
Library for UI used in lab experiments
Keywords: science software development

# ETH Zurich (IEF LAB): Python Lab Tools
This is a small library that uses Tkinter to provide a fast and easy method to build user interfaces for Lab Experiments.

## Introduction
In a lab environment it is often necessary to keep track of many experimental parameters in order to produce meaningful results. This library enables the user to build user interfaces really fast with some custom UI elements like plot controls, parameter tables or control panels. All controls are based on the controls of Tkinter which is a great UI library for python https://wiki.python.org/moin/TkInter.

## Usage