Datasets:
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import os
import json
from dotenv import load_dotenv
from googleapiclient.discovery import build
from youtube_transcript_api import TranscriptsDisabled, YouTubeTranscriptApi
import logging
import timeit
from tqdm import tqdm # Import tqdm
start_time = timeit.default_timer()
logging.basicConfig(filename='youtube_fetch.log', level=logging.ERROR)
load_dotenv()
api_key = os.getenv('yt_secret_key')
os.chdir("d:/Machine Learning/SLM-Project/")
youtube = build('youtube', 'v3', developerKey=api_key)
file_path = 'Data Collection/Transcript Collection/channel_ids_snippet.json'
with open(file_path, 'r') as file:
channelData = json.load(file)
videoNo = 0
for links in channelData:
next_page_token = None
videoIds = []
while True:
channelRes = youtube.channels().list(
part='contentDetails,snippet', id=links
).execute()
if 'items' in channelRes and channelRes['items']:
channel_name = channelRes["items"][0]["snippet"]["title"]
playlistId = channelRes['items'][0]['contentDetails']['relatedPlaylists']['uploads']
playlistResult = youtube.playlistItems().list(
part='contentDetails', playlistId=playlistId,
maxResults=100, pageToken=next_page_token
).execute()
videoIds.extend([item['contentDetails']['videoId'] for item in playlistResult.get('items', [])])
next_page_token = playlistResult.get('nextPageToken')
if not next_page_token:
break
with tqdm(total=len(videoIds), desc=f"Fetching '{channel_name}' videos") as pbar:
for ids in videoIds:
videoUrl = f"https://www.youtube.com/watch?v={ids}"
try:
raw_transcripts = []
try:
captions = YouTubeTranscriptApi.get_transcript(
ids, languages=['en'], preserve_formatting=True
)
if captions:
formatted_captions = [{'text': caption['text']} for caption in captions]
raw_transcripts.append(formatted_captions)
videoNo += 1
pbar.update(1)
else:
continue
except TranscriptsDisabled as e:
continue
except Exception as e:
logging.error(f"There was some error while fetching the video: {str(e)}")
except Exception as e:
logging.error(f"There was some error while getting the captions: {str(e)}")
with open('Data/caption files/new_data.txt', 'a', encoding='utf-8') as file:
for videoCaptions in raw_transcripts:
for line in videoCaptions:
file.write(line['text'] + ' ')
print(f"total {videoNo} videos were fetched")
print(f"time taken to execute the code is {(timeit.default_timer() - start_time) / 3600} hrs")
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