Our code is available on GitHub Here. You can use it by installing over PIP !
This Package performs GET requests to our Flask Back-end server API for summarizing the transcripts.
More details about our backend can be read at our back-end repository here.
YouTube Video Transcript Summarization using PIP: Yes. You heard it right! This package is available on PyPi. Just read below to know how can you integrate it in your own project.
When ever you invoke the function of our package, it sends API calls to our Flask server, and then the server responds back with the summarized text response. Then you can further display the received result to the user.
As we make API calls to our back-end, this package needs an internet connection to received summarized transcript using requests library.
Python>=3.5(Users below 3.5 might still run it, but you may face some errors since the package was not tested below 3.5)requests(Used to make API calls to our server)
Pre-requisite Knowledge: YouTube is an American free to use online video sharing and social media platform launched in February 2005. It is currently one of the biggest video platforms where its users watch more than 1 billion hours of videos every day.
Closed captions are the text derived from the video which are intended for adding more details (such as dialogues, speech translation, non-speech elements) for the viewer. They are widely used to understand video without understanding its audio.
Use case Scenario: YouTube has very large number of videos which has transcripts. Summarization would be especially helpful in the cases where videos are longer and different parts might have varying importance. In this sense, Summarization of the video might be useful in saving the viewer’s time. It will help in improving user productivity since they will focus only on the important text spoken in video.
This repository is part of our project, in which there is a back-end server using Flask Framework. The backend has also a browser based summarizer, but the package available in this repository depict how server-client server makes efficient use of our code!
When you install the package, and then invoke the function, it makes request only, and the back-end summarizes the transcript, and sends the response back in JSON Format.
This package returns a tuple which has a summary and a dictionary storing some insights about your request. Read below for more details.
You can go to your terminal, and before you start, make sure that pip is installed. Then, simply type:
pip install yt_trans_sumOnce the installation is complete, you can import and use the package like this:
from yt_trans_sum import YouTubeTranscriptSummarizer
if __name__ == "__main__":
# Simplest Call Example
my_summary, my_summary_insights = YouTubeTranscriptSummarizer().get_by_url('https://www.youtube.com/watch?v=zhUgaKb0s5A')
print("My Summary:", my_summary) # String
print("My Summary Insights: ", my_summary_insights) # DictionaryHere, 'my_summary_insights` is a dictionary with key-value pairs with insight of your request. Below snippet can help you understand the values inside this dictionary.
# There are 4 values inside this dictionary for now. The snippet is self explanatory.
print("Characters in Transcript:", my_summary_insights['length_original'])
print("Sentences in Transcript:", my_summary_insights['sentence_original'])
print("Characters in Summary:", my_summary_insights['length_summary'])
print("Sentences in Summary:", my_summary_insights['sentence_summary'])Since the backend requires video id, algorithm and a percentage to summarize the transcript, this package also takes these inputs.
id: Video ID of the YouTube Video. Each video has its own unique ID in its URL. For example, 9No-FiEInLA is the Video ID in https://www.youtube.com/watch?v=9No-FiEInLA..
You can give video id directly usingget_by_id()or give your complete URL byget_by_url()method as shown in the sample snippets.
choice: Algorithm Choice for the summarizing the Transcript. There are only six accepted values in this variable.
These choices are written along with algorithm names as follows:gensim-sum: Text Rank Algorithm Based using Gensimspacy-sum: Frequency Based Approach using Spacy.nltk-sum: Frequency Based Summarization using NLTK.sumy-lsa-sum: Latent Semantic Analysis Based using Sumy.sumy-luhn-sum: Luhn Algorithm Based using Sumy.sumy-text-rank-sum: Text Rank Algorithm Based using Sumy.
percent: The percentage is used to present the summary in approx.X% linesof the available transcript. Values between 20 and 30 give better results.
NOTE: By default, Algorithm selected is gensim-sum and percentage is 20. You can change these values like below.
- Print logs while we request the summary. While
debug_logsis True, the package prints the current status of the request as well.
from yt_trans_sum import YouTubeTranscriptSummarizer
if __name__ == "__main__":
# Debug Logs turned on.
my_summary, my_summary_insights = YouTubeTranscriptSummarizer(debug_logs=True).get_by_url('https://www.youtube.com/watch?v=zhUgaKb0s5A')
print("My Summary:", my_summary)
print("My Summary Insights: ", my_summary_insights)- Change percentage and algorithm for the summary request:
from yt_trans_sum import YouTubeTranscriptSummarizer
if __name__ == "__main__":
# Full control of arguments
my_summary, my_summary_insights = YouTubeTranscriptSummarizer().get_by_url(video_url='https://www.youtube.com/watch?v=zhUgaKb0s5A', percent=10, choice='sumy-lsa-sum')
print("My Summary:", my_summary)
print("My Summary Insights: ", my_summary_insights)- Summarization request by using video ID instead of video URL
from yt_trans_sum import YouTubeTranscriptSummarizer
if __name__ == "__main__":
# get_by_id() is called instead of get_by_url()
my_summary, my_summary_insights = YouTubeTranscriptSummarizer().get_by_id(video_id='zhUgaKb0s5A', percent=10, choice='sumy-lsa-sum')
print("My Summary:", my_summary)
print("My Summary Insights: ", my_summary_insights)You can click here to know more about how backend receives and sends data.