semvec/pypi-packages huggingface dataset:
nbfancy 0.1a3
Tools for rendering notebooks suitable for teaching

# <img alt="NBfancy" src="https://raw.githubusercontent.com/JDBetteridge/nbfancy/master/nbfancy/nbfancylogo.png" height="80">

(C) 2019 Jack Betteridge (j.d.betteridge@bath.ac.uk) and James Grant (r.j.grant@bath.ac.uk)

This repository contains NBfancy,
a tool for adding decoration and extended features to Jupyter notebooks.
The code was developed by Jack Betteridge and James Grant
for the development of programming training material:
[arc-bath](https://github.com/arc-bath) and [arc-lessons](https://github.com/arc-lessons).

### Documentation

The install contains the tools which make up the build system for enriching notebooks,
and by way of example, also contains the documentation in the form of a tutorial.
This material will assist users in creating their own courses,
as both a lesson and demonstration of NBfancy's capabilities.

Jupyter notebooks were chosen as the medium for out training material as:

*  They use markdown which is simple to use even for those not familiar.
*  Modifying individual codeblocks is intuitive compared with Sphinx/Jekyll builds.
*  We like being able to mix markdown and executable codeblocks in training material.

In order to retain these features we created NBfancy to process initial notebooks
into enriched Jupyter notebooks for interactive use by students,
html pages for lesson material
and pdfs for distribution as printouts (coming in a future release).

The documentation/tutorial is available online in
[rendered html](https://jdbetteridge.github.io/nbfancy/00_schedule.html)

The library has recently undergone a signficant refactoring so please raise an issue if you encounter any trouble using nbfancy or incosistencies in the documentation.

### Contributions to NBfancy

If you would like to contribute to NBfancy please fork the repository and create a pull request against the development branch.
t5-podcast-summariser 0.0.5
Podcast Transcript Summarisation

# T5 Podcast Summariser

The aim of this project is to demonstrate the capabilities of Google's T5 model that has been fine-tuned on Spotify's Podcasts Dataset for automatic podcast summarisation. Simply pass in a podcast's transcript as input to the summariser, and it would output a summary containing the gist of what the podcast is about.


# T5 and Spotify Podcast Dataset

 - To learn more about T5, read [this blog post](https://ai.googleblog.com/2020/02/exploring-transfer-learning-with-t5.html)
 - To learn more about the Dataset, read its [paper](https://arxiv.org/abs/2004.04270)

# Usage

This package relies on the [HuggingFace NLP Library](https://huggingface.co/) to work so you would have to install it too:

    pip install transformers
    pip install t5-podcast-summariser

You can now use the package as follows:

    from t5_podcast_summariser import Summariser
    summariser =  Summariser()
    
    transcript = """
    Full Transcript of the podcast.....
    """
   
    summary = summariser.summarise(transcript)
    print(summary)    

Below is a sample summary generated on a podcast transcript available [here](https://storycorps.org/podcast/storycorps-466-callings/):

    This week on the podcast, we talk to Ayodeji Ogunnia (@Ayodeji_Ogunnia) about his life as a bricklayer in Baltimore. We also hear from one of the most famous people in the world, and how he came to be a successful bricklayer. This is a great story for anyone who wants to learn more about what it means to be a good bricklayer. If you like what we do, please leave us a review on Apple Podcasts! Thanks for listening!
  

# Future Work

In the next update, I will make it possible for the top-n sentences to be extracted
from the transcript before a summary is generated.
pyconvertdigits 0.0.2
It is one of the useful module that can help you to convert English int to other languages

PYCONVERTDIGITS
===================


**PyConvertdigits** is a module that helps you to translate digits from English to other languages. 

----------

Features
===================

> - Conver English int to other languages and return a string

Install
===================
We recommend install pyconvertdigits through pip install using Python 3.

> $ pip install pyconvertdigits

Example
===================

To see available languages:

    import pyconvertdigits
    convertDigits = pyconvertdigits.conDigits()
    languages = convertDigits.available()
    print(languages)
    #output: ['Bangla', 'Hindi', 'Urdu', 'Malayalam', 'Thai']
To convert English to other languages:

    import pyconvertdigits
    convertDigits = pyconvertdigits.conDigits()

    convertedBangla = convertDigits.to_bangla(1234567890) #convert from English to Bangla
    print(convertedBangla)

    convertedHindi = convertDigits.to_hindi(1234567890) #convert from English to Hindi
    print(convertedHindi)

    convertedUrdu = convertDigits.to_urdu(1234567890) #convert from English to Urdu
    print(convertedUrdu)

    convertedMalayalam = numbers.to_malayalam(1234567890) #convert from English to Urdu
    print(convertedMalayalam)

    convertedThai = numbers.to_thai(1234567890) #convert from English to Urdu
    print(convertedThai)