Simple Python script to scrape youtube channles of "Parity Technologies and Web3 Foundation" and translate them to well-known braille language or any language

Overview

Simple Python script to scrape youtube channles of "Parity Technologies and Web3 Foundation" and translate them to well-known braille language or any language

The script can be used for any channel or video for scraping, in addition will provide you with the option to get any automatic captions. Automatic captions are available in Dutch, English, French, German, Indonesian, Italian, Japanese, Korean, Portuguese, Russian, Spanish, Turkish, Vietnamese and more or any, so use it as you wish.

usage:

pip install youtube_transcript_api scrapetube codext

for default channel

python tube.py 

Custom channel

python tube.py UCSs5vZi0U7qHLkUjF3QnaWg

Get all videos for a channel

import scrapetube

videos = scrapetube.get_channel("UCCezIgC97PvUuR4_gbFUs5g")

for video in videos:
    print(video['videoId'])

Filter for manually created transcripts

transcript = transcript_list.find_manually_created_transcript(['de', 'en'])

or automatically generated ones

transcript = transcript_list.find_generated_transcript(['de', 'en'])

The methods find_generated_transcript, find_manually_created_transcript, find_generated_transcript return Transcript objects. They contain metadata regarding the transcript:

print(
    transcript.video_id,
    transcript.language,
    transcript.language_code,
    # whether it has been manually created or generated by YouTube
    transcript.is_generated,
    # whether this transcript can be translated or not
    transcript.is_translatable,
    # a list of languages the transcript can be translated to
    transcript.translation_languages,
)

Codext, contraction of "codecs" and "extension", is a tiny library that gathers a few additional encodings for use with codecs. While imported, it registers new encodings to a proxy codecs registry for making the encodings available from the codecs.(decode|encode|open) calls.

Currently set on Braille codext.encode("Little Endian", "braille") accept even morse

Codecs categories

  • native: the built-in codecs from the original codecs package
  • non-native: this special category regroups all the categories mentioned hereafter
  • base: baseX codecs (e.g. base, base100)
  • binary: codecs working on strings but applying their algorithms on their binary forms (e.g. baudot, manchester)
  • common: common codecs not included in the native ones or simly added for the purpose of standardization (e.g. octal, ordinal)
  • crypto: codecs related to cryptography algorithms (e.g. barbie, rot, xor)
  • language: language-related codecs (e.g. morse, navajo)
  • other: uncategorized codecs (e.g. letters, url)
  • stegano: steganography-related codecs (e.g. sms, resistor)
  • Except the native and non-native categories, the other ones are simply the name of the subdirectories (with "s" right-stripped) of the codext package.
codext.list("binary")
['baudot', 'baudot-spaced', 'baudot-tape', 'bcd', 'bcd-extended0', 'bcd-extended1', 'excess3', 'gray', 'manchester', 'manchester-inverted']
codext.list("language")
['braille', 'leet', 'morse', 'navajo', 'radio', 'southpark', 'southpark-icase', 'tom-tom']
codext.list("native")
['ascii', 'base64_codec', 'big5', 'big5hkscs', 'bz2_codec', 'cp037', 'cp273', 'cp424', 'cp437', 'cp500', 'cp775', 'cp850', 'cp852', 'cp855', 'cp857', 'cp858', 'cp860', 'cp861', 'cp862', 'cp863', ...]

Current channels for scrapping the transcript subtitles in English language and translate them to Braille language

Up to you list, just replace the Youtube channel ID string at 🤯

videoListName = scrapetube.get_channel("UClnw_bcNg4CAzF772qEtq4g")

YouTube uses automatic speech recognition to add automatic captions to videos. The feature is available in English, Dutch, French, German, Italian, Japanese, Korean, Portuguese, Russian, and Spanish. ASR is not available for all videos.

You can eding the language at 😇

transcript = transcript_list.find_generated_transcript(['en']).fetch()

Example output:

https://www.youtube.com/watch?v=ouMK-Q9S7cc
Web3 Foundation - The Next Evolution of the Internet - Dr. Gavin Wood
⠺⠑⠃⠒⠀⠋⠕⠥⠝⠙⠁⠞⠊⠕⠝⠀⠤⠀⠞⠓⠑⠀⠝⠑⠭⠞⠀⠑⠧⠕⠇⠥⠞⠊⠕⠝⠀⠕⠋⠀⠞⠓⠑⠀⠊⠝⠞⠑⠗⠝⠑⠞⠀⠤⠀⠙⠗⠨⠀⠛⠁⠧⠊⠝⠀⠺⠕⠕⠙
⠊⠀⠞⠓⠊⠝⠅⠀⠞⠓⠑⠗⠑⠀⠺⠑⠗⠑⠀⠁⠀⠇⠕⠞⠀⠕⠋⠀⠏⠑⠕⠏⠇⠑⠀⠞⠓⠁⠞⠀⠗⠑⠁⠇⠇⠽⠀⠃⠑⠇⠊⠑⠧⠑⠙⠀⠞⠓⠑⠀⠊⠝⠞⠑⠗⠝⠑⠞⠀⠺⠁⠎⠀⠺⠁⠎⠀⠛⠕⠝⠝⠁⠀⠃⠑⠀⠁⠀⠞⠗⠁⠝⠎⠋⠕⠗⠍⠁⠞⠊⠧⠑⠀⠞⠑⠉⠓⠝⠕⠇⠕⠛⠽⠀⠋⠕⠗⠀⠎⠕⠉⠊⠑⠞⠽⠀⠁⠝⠙⠀⠊⠀⠞⠓⠊⠝⠅⠀⠺⠓⠁⠞⠀⠓⠁⠏⠏⠑⠝⠑⠙⠀⠺⠁⠎⠀⠞⠓⠑⠀⠊⠝⠞⠑⠗⠝⠑⠞⠀⠺⠁⠎⠀⠙⠑⠎⠊⠛⠝⠑⠙⠀⠊⠝⠀⠎⠥⠉⠓⠀⠁⠀⠺⠁⠽⠀⠞⠓⠁⠞⠀⠊⠞⠀⠁⠇⠇⠕⠺⠑⠙⠀⠊⠞⠀⠺⠁⠎⠀⠋⠇⠑⠭⠊⠃⠇⠑⠀⠊⠞⠀⠁⠇⠇⠕⠺⠑⠙⠀⠑⠭⠊⠎⠞⠊⠝⠛⠀⠎⠞⠗⠥⠉⠞⠥⠗⠑⠎⠀⠕⠋⠀⠎⠕⠉⠊⠑⠞⠽⠀⠑⠭⠊⠎⠞⠊⠝⠛⠀⠺⠁⠽⠎⠀⠕⠋⠀⠙⠕⠊⠝⠛⠀⠃⠥⠎⠊⠝⠑⠎⠎⠀⠞⠕⠀⠎⠊⠍⠏⠇⠽⠀⠍⠕⠧⠑⠀⠕⠧⠑⠗⠀⠕⠝⠞⠕⠀⠞⠓⠑⠀⠙⠊⠛⠊⠞⠁⠇⠀⠙⠕⠍⠁⠊⠝⠀⠎⠕⠀⠺⠓⠑⠝⠀⠺⠑⠀⠙⠕⠀⠃⠁⠝⠅⠊⠝⠛⠀⠕⠝⠀⠞⠓⠑⠀⠊⠝⠞⠑⠗⠝⠑⠞⠀⠺⠑⠀⠎⠞⠊⠇⠇⠀⠥⠎⠑⠀⠁⠀⠃⠁⠝⠅⠀⠺⠑⠀⠎⠞⠊⠇⠇⠀⠥⠎⠑⠀⠕⠥⠗⠀⠑⠭⠊⠎⠞⠊⠝⠛⠀⠃⠗⠊⠉⠅⠤⠁⠝⠙⠤⠍⠕⠗⠞⠁⠗⠀⠞⠗⠁⠙⠊⠞⠊⠕⠝⠁⠇⠀⠲⠴⠴⠀⠽⠑⠁⠗⠀⠕⠇⠙⠀⠃⠁⠝⠅⠊⠝⠛⠀⠕⠗⠛⠁⠝⠊⠵⠁⠞⠊⠕⠝⠀⠊⠞⠄⠎⠀⠚⠥⠎⠞⠀⠞⠓⠁⠞⠀⠺⠑⠀⠁⠉⠉⠑⠎⠎⠀⠞⠓⠑⠍⠀⠞⠓⠗⠕⠥⠛⠓⠀⠁⠀⠺⠑⠃⠀⠏⠁⠛⠑⠀⠊⠞⠀⠓⠁⠎⠝⠄⠞⠀⠗⠑⠁⠇⠇⠽⠀⠁⠇⠞⠑⠗⠑⠙⠀⠎⠕⠉⠊⠑⠞⠽⠀⠊⠞⠀⠗⠑⠁⠇⠇⠽⠀⠺⠁⠎⠝⠄⠞⠀⠞⠗⠁⠝⠎⠋⠕⠗⠍⠁⠞⠊⠧⠑⠀⠁⠝⠙⠀⠊⠀⠞⠓⠊⠝⠅⠀⠞⠓⠁⠞⠄⠎⠀⠞⠓⠁⠞⠄⠎⠀⠑⠧⠑⠗⠍⠕⠗⠑⠀⠉⠇⠑⠁⠗⠀⠺⠓⠑⠝⠀⠺⠑⠀⠺⠓⠑⠝⠀⠺⠑⠀⠞⠓⠊⠝⠅⠀⠁⠃⠕⠥⠞⠀⠋⠁⠉⠑⠃⠕⠕⠅⠀⠁⠝⠙⠀⠺⠑⠀⠞⠓⠊⠝⠅⠀⠁⠃⠕⠥⠞⠀⠛⠕⠕⠛⠇⠑⠀⠞⠓⠑⠎⠑⠀⠁⠗⠑⠀⠝⠕⠞⠀⠝⠑⠺⠀⠺⠁⠽⠎⠀⠕⠋⠀⠺⠕⠗⠅⠊⠝⠛⠀⠝⠑⠺⠀⠺⠁⠽⠎⠀⠕⠋⠀⠏⠑⠕⠏⠇⠑⠀⠺⠕⠗⠅⠊⠝⠛⠀⠞⠕⠛⠑⠞⠓⠑⠗⠀⠊⠝⠀⠗⠑⠁⠇⠊⠞⠽⠀⠞⠓⠑⠽⠄⠗⠑⠀⠞⠓⠑⠀⠎⠁⠍⠑⠀⠅⠊⠝⠙⠎⠀⠕⠋⠀⠎⠞⠗⠥⠉⠞⠥⠗⠑⠎⠀⠞⠓⠁⠞⠀⠞⠓⠑⠀⠎⠁⠍⠑⠀⠓⠊⠑⠗⠁⠗⠉⠓⠊⠉⠁⠇⠀⠕⠗⠛⠁⠝⠊⠵⠁⠞⠊⠕⠝⠎⠀⠞⠓⠁⠞⠀⠓⠁⠧⠑⠀⠞⠓⠑⠀⠎⠁⠍⠑⠀⠉⠑⠝⠞⠗⠁⠇⠊⠵⠑⠙⠀⠃⠁⠝⠅⠀⠁⠉⠉⠕⠥⠝⠞⠎⠀⠞⠓⠁⠞⠀⠓⠁⠧⠑⠀⠞⠓⠑⠀⠎⠁⠍⠑⠀⠎⠕⠗⠞⠀⠕⠋⠀⠍⠥⠇⠞⠊⠝⠁⠞⠊⠕⠝⠁⠇⠀⠎⠞⠗⠥⠉⠞⠥⠗⠑⠀⠁⠎⠀⠁⠇⠇⠀⠕⠋⠀⠞⠓⠑⠀⠧⠁⠗⠊⠕⠥⠎⠀⠕⠞⠓⠑⠗⠀⠋⠕⠗⠞⠥⠝⠑⠀⠢⠴⠴⠀⠉⠕⠗⠏⠕⠗⠁⠞⠑⠀⠉⠕⠍⠏⠁⠝⠊⠑⠎⠀⠊⠝⠀⠗⠑⠁⠇⠊⠞⠽⠀⠞⠕⠀⠉⠓⠁⠝⠛⠑⠀⠎⠕⠉⠊⠑⠞⠽⠀⠺⠑⠀⠗⠑⠁⠇⠇⠽⠀⠝⠑⠑⠙⠀⠞⠕⠀⠙⠕⠀⠎⠕⠍⠑⠞⠓⠊⠝⠛⠀⠃⠑⠞⠞⠑⠗⠀⠞⠓⠁⠝⠀⠉⠗⠑⠁⠞⠊⠝⠛⠀⠞⠑⠉⠓⠝⠕⠇⠕⠛⠊⠑⠎⠀⠞⠓⠁⠞⠀⠚⠥⠎⠞⠀⠁⠇⠇⠕⠺⠀⠥⠎⠀⠞⠕⠀⠍⠊⠗⠗⠕⠗⠀⠓⠕⠺⠀⠎⠕⠉⠊⠑⠞⠽⠀⠺⠕⠗⠅⠎⠀⠁⠝⠽⠺⠁⠽⠀⠺⠑⠀⠝⠑⠑⠙⠀⠞⠕⠀⠉⠗⠑⠁⠞⠑⠀⠞⠑⠉⠓⠝⠕⠇⠕⠛⠊⠑⠎⠀⠞⠓⠁⠞⠀⠋⠕⠗⠛⠑⠀⠝⠑⠺⠀⠺⠁⠽⠎⠀⠕⠋⠀⠃⠑⠊⠝⠛⠀⠁⠃⠇⠑⠀⠞⠕⠀⠺⠕⠗⠅⠀⠺⠊⠞⠓⠀⠑⠁⠉⠓⠀⠕⠞⠓⠑⠗⠀⠁⠝⠙⠀⠞⠓⠁⠞⠄⠎⠀⠙⠊⠋⠋⠑⠗⠑⠝⠞⠀⠞⠕⠀⠝⠑⠺⠀⠺⠁⠽⠎⠀⠕⠋⠀⠃⠑⠊⠝⠛⠀⠁⠃⠇⠑⠀⠞⠕⠀⠉⠕⠍⠍⠥⠝⠊⠉⠁⠞⠑⠀⠺⠊⠞⠓⠀⠑⠁⠉⠓⠀⠕⠞⠓⠑⠗⠀⠊⠞⠄⠎⠀⠁⠇⠎⠕⠀⠛⠕⠞⠀⠞⠕⠀⠃⠑⠀⠝⠑⠺⠀⠺⠁⠽⠎⠀⠕⠋⠀⠃⠑⠊⠝⠛⠀⠁⠃⠇⠑⠀⠞⠕⠀⠕⠗⠛⠁⠝⠊⠵⠑⠀⠁⠝⠙⠀⠞⠗⠥⠎⠞⠀⠞⠓⠁⠞⠀⠑⠁⠉⠓⠀⠕⠞⠓⠑⠗⠀⠊⠎⠀⠛⠕⠊⠝⠛⠀⠞⠕⠀⠙⠕⠀⠺⠓⠁⠞⠀⠺⠓⠁⠞⠀⠞⠓⠑⠽⠀⠝⠑⠑⠙⠀⠞⠕⠀⠙⠕⠀⠊⠝⠀⠕⠗⠙⠑⠗⠀⠞⠕⠀⠓⠁⠧⠑⠀⠎⠕⠍⠑⠀⠎⠕⠗⠞⠀⠕⠋⠀⠎⠓⠁⠗⠑⠙⠀⠉⠕⠝⠉⠇⠥⠎⠊⠕⠝⠀⠕⠗⠀⠗⠁⠍⠊⠋⠊⠉⠁⠞⠊⠕⠝⠀⠞⠕⠀⠞⠓⠑⠀⠉⠕⠕⠏⠑⠗⠁⠞⠊⠕⠝⠀⠁⠝⠙⠀⠞⠓⠁⠞⠄⠎⠀⠗⠑⠁⠇⠇⠽⠀⠁⠀⠃⠊⠛⠀⠉⠕⠍⠏⠕⠝⠑⠝⠞⠀⠕⠋⠀⠺⠑⠃⠀⠒⠀⠺⠑⠃⠀⠒⠀⠊⠎⠀⠗⠑⠁⠇⠇⠽⠀⠁⠃⠕⠥⠞⠀⠁⠇⠇⠕⠺⠊⠝⠛⠀⠏⠑⠕⠏⠇⠑⠀⠞⠕⠀⠉⠕⠍⠑⠀⠞⠕⠛⠑⠞⠓⠑⠗⠀⠁⠝⠙⠀⠉⠕⠕⠗⠙⠊⠝⠁⠞⠑⠀⠞⠓⠑⠊⠗⠀⠑⠋⠋⠕⠗⠞⠎⠀⠋⠕⠗⠀⠎⠕⠍⠑⠞⠓⠊⠝⠛⠀⠛⠗⠑⠁⠞⠑⠗⠀⠞⠓⠑⠀⠞⠓⠁⠝⠀⠞⠓⠑⠀⠎⠥⠍⠀⠕⠋⠀⠊⠞⠎⠀⠏⠁⠗⠞⠎⠀⠪⠍⠥⠎⠊⠉⠻

With Git Actions Workflow file for this run as example in real-time

available OS's: [ windows-latest, macos-latest, ubuntu-latest ]

name: Cross-platform matrix run
on: [push]
jobs:
  build:
    runs-on: ${{ matrix.os }}
    strategy:
      matrix:
        os: [ubuntu-latest]
        python-version: ['3.6', '3.9']
        exclude:
          - os: ubuntu-latest
            python-version: '3.6'
    steps:
      - uses: actions/[email protected]
      - name: Set up Python
        uses: actions/[email protected]
        with:
          python-version: ${{ matrix.python-version }}
      - name: Install dependencies 
        run: pip install youtube_transcript_api scrapetube codext
      - name: Web3 Foundation videos to braille language 
        run: python tube.py

For Support && Nominations

  • Display name. KSMNETWORK

  • Email [email protected]

  • Riot @gtoocool:matrix.org

  • KUSAMA (KSM) Address

  • H1bSKJxoxzxYRCdGQutVqFGeW7xU3AcN6vyEdZBU7Qb1rsZ

  • PolkaDOT (DOT) Address:

  • 15FxvBFDd3X7H9qcMGqsiuvFYEg4D3mBoTA2LQufreysTHKA

  • https://ksm.network

Owner
Little Endian
Riot @gtoocool:matrix.org                  KUSAMA Address:  H1bSKJxoxzxYRCdGQutVqFGeW7xU3AcN6vyEdZBU7Qb1rsZ
Little Endian
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Source code for the paper "TearingNet: Point Cloud Autoencoder to Learn Topology-Friendly Representations"

TearingNet: Point Cloud Autoencoder to Learn Topology-Friendly Representations Created by Jiahao Pang, Duanshun Li, and Dong Tian from InterDigital In

InterDigital 21 Dec 29, 2022
An implementation of WaveNet with fast generation

pytorch-wavenet This is an implementation of the WaveNet architecture, as described in the original paper. Features Automatic creation of a dataset (t

Vincent Herrmann 858 Dec 27, 2022
The NewSHead dataset is a multi-doc headline dataset used in NHNet for training a headline summarization model.

This repository contains the raw dataset used in NHNet [1] for the task of News Story Headline Generation. The code of data processing and training is available under Tensorflow Models - NHNet.

Google Research Datasets 31 Jul 15, 2022
Spooky Skelly For Python

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Kur0R1uka 1 Dec 23, 2021
Python library for Serbian Natural language processing (NLP)

SrbAI - Python biblioteka za procesiranje srpskog jezika SrbAI je projekat prikupljanja algoritama i modela za procesiranje srpskog jezika u jedinstve

Serbian AI Society 3 Nov 22, 2022