Datasets:
File size: 2,822 Bytes
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"""
fetches the captions from each video uploaded on a particular youtube channel
by channel_id and then writes it in a json file as with title, index and transcript data
"""
from dotenv import load_dotenv
import logging
logging.basicConfig(filename='youtube_fetch.log', level=logging.ERROR)
load_dotenv()
import timeit
start_time = timeit.default_timer()
import os
os.chdir('d:/Machine Learning/SLM-Project/Data Collection/')
api_key = os.getenv('yt_secret_key')
from googleapiclient.discovery import build
from youtube_transcript_api import TranscriptsDisabled, YouTubeTranscriptApi
youtube = build('youtube', 'v3', developerKey=api_key)
import json
file_path = 'channel_ids.json'
with open(file_path, 'r') as file:
channelData = json.load(file)
videoNo = 0
for links in channelData:
next_page_token = None
vid_json = []
while True:
channelRes = youtube.channels().list(
part='contentDetails', id=links
).execute()
if 'items' in channelRes and channelRes['items']:
playlistId = channelRes['items'][0]['contentDetails']['relatedPlaylists']['uploads']
playlistResult = youtube.playlistItems().list(
part='contentDetails', playlistId=playlistId,
maxResults = 50, pageToken = next_page_token
).execute()
for item in playlistResult.get('items', []):
video_response = youtube.videos().list(
part='snippet',
id=[item['contentDetails']['videoId']]
).execute()
title = video_response['items'][0]['snippet']['title']
id = item['contentDetails']['videoId']
videoUrl = f"https://www.youtube.com/watch?v={id}"
try:
captions = YouTubeTranscriptApi.get_transcript(
id, languages=['en'], preserve_formatting=True
)
if captions:
formatted_captions = [{caption['text']} for caption in captions]
raw_transcripts = ' '.join(caption.pop() for caption in formatted_captions)
else:
continue
except TranscriptsDisabled as e:
print(F"There was an error while getting the captions: {e}")
except Exception as e:
logging.error(f"There was some error while fetching the video: {str(e)}")
video_data = {'title': title, 'video_id': id, 'captions': str(raw_transcripts)}
videoNo += 1
vid_json.append(video_data)
print(f"no of video with valid captions: {videoNo}")
next_page_token = playlistResult.get('nextPageToken')
if not next_page_token:
break
with open('finetune_data.json', 'w') as file:
json.dump(vid_json, file, indent=2)
end_time = timeit.default_timer()
print(f"file written, no of videos fetched were {videoNo}")
print(f"time taken to fetch the data {(end_time - start_time) /60} mins") |