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yt_analytics_v2.py
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yt_analytics_v2.py
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import argparse
import os
from google.oauth2.credentials import Credentials
from google_auth_oauthlib.flow import InstalledAppFlow
from googleapiclient.discovery import build
import gspread
from pymongo import MongoClient
from datetime import datetime
SCOPES = ['https://www.googleapis.com/auth/yt-analytics.readonly', 'https://www.googleapis.com/auth/spreadsheets']
API_SERVICE_NAME = 'youtubeAnalytics'
API_VERSION = 'v2'
CLIENT_SECRETS_FILE = 'CLIENT_SECRET.json'
SPREADSHEET_ID = '1TLN8sg-lky6ujeCGWudbiVrM010C8mDYdASHBz7mxGs'
MONGO_CONNECTION_STRING = "mongodb+srv://jayanthkumar597:ekO7numbM1hpO23K@cluster0.0wjrnqw.mongodb.net/"
def transform_data(data, column_headers):
transformed_data = []
for row in data:
row_dict = dict(zip(column_headers, row))
transformed_data.append(row_dict)
return transformed_data
# Function to insert data into MongoDB
def insert_data_into_mongodb(db_name, collection_name, data, column_headers):
transformed_data = transform_data(data, column_headers)
client = MongoClient(MONGO_CONNECTION_STRING)
db_name = db_name.replace('/', '_')
db = client[db_name]
collection = db[collection_name]
collection.insert_many(transformed_data)
def get_service():
flow = InstalledAppFlow.from_client_secrets_file(CLIENT_SECRETS_FILE, SCOPES)
credentials = flow.run_local_server(port=0)
return build(API_SERVICE_NAME, API_VERSION, credentials=credentials)
def execute_api_request(client_library_function, **kwargs):
response = client_library_function(**kwargs).execute()
return response
def write_data_to_spreadsheet(data, sheet_name, column_headers):
gc = gspread.service_account(filename='SERVICE_ACCOUNT.json')
sh = gc.open_by_key(SPREADSHEET_ID)
try:
# Try to open the sheet. If it doesn't exist, create a new one.
worksheet = sh.worksheet(sheet_name)
except gspread.exceptions.WorksheetNotFound:
worksheet = sh.add_worksheet(title=sheet_name, rows="100", cols="100")
# Clear the existing data in the worksheet.
worksheet.clear()
# Write the column headers to the first row
if column_headers:
worksheet.insert_rows([column_headers], 2)
# Write the data starting from the second row
if data:
# Create a list of lists from the data
data_list = [list(map(str, row)) for row in data]
# Insert the data into the worksheet
worksheet.insert_rows(data_list, 3)
db_name = f"youtube_analytics_2023_for_MF"
insert_data_into_mongodb(db_name, sheet_name, data, column_headers)
def get_video_titles(youtube, video_ids):
video_info = youtube.videos().list(
part='snippet',
id=','.join(video_ids)
).execute()
titles = {}
for video in video_info.get('items', []):
video_id = video['id']
title = video['snippet']['title']
titles[video_id] = title
return titles
def fetch_and_write_basic_stats(youtubeAnalytics,start_date,end_date):
response = execute_api_request(
youtubeAnalytics.reports().query,
ids='channel==MINE',
startDate=start_date,
endDate=end_date,
metrics='estimatedMinutesWatched,views,likes,subscribersGained',
dimensions='day',
sort='day',
maxResults=100
)
column_headers = ['day', 'estimatedMinutesWatched', 'views', 'likes', 'subscribersGained']
write_data_to_spreadsheet(response.get('rows', []), 'Basic Stats', column_headers)
def fetch_and_write_top_videos(youtubeAnalytics, start_date, end_date):
response = execute_api_request(
youtubeAnalytics.reports().query,
ids='channel==MINE',
startDate=start_date,
endDate=end_date,
metrics='views,likes,comments,shares,estimatedMinutesWatched,averageViewDuration,averageViewPercentage',
dimensions='video',
sort='-views',
maxResults=10
)
video_ids = [row[0] for row in response.get('rows', [])]
column_headers = ['video', 'video_id', 'views', 'likes', 'comments', 'shares', 'estimatedMinutesWatched', 'averageViewDuration', 'averageViewPercentage']
# Fetch video titles using YouTube Data API
youtube = build('youtube', 'v3', developerKey='AIzaSyD0gbH6qSaSGJNhU4TsQH-Xs8genUcuGEc')
video_titles = get_video_titles(youtube, video_ids)
data = []
for row in response.get('rows', []):
video_id = row[0]
views = row[1]
likes = row[2]
comments = row[3]
shares = row[4]
estimated_minutes_watched = row[5]
average_view_duration = row[6]
average_view_percentage = row[7]
title = video_titles.get(video_id, 'Title Not Found')
data.append([title, video_id, views, likes, comments, shares, estimated_minutes_watched, average_view_duration, average_view_percentage])
write_data_to_spreadsheet(data, 'Top Videos', column_headers)
def fetch_and_write_audience_retention(youtubeAnalytics,start_date,end_date):
response = execute_api_request(
youtubeAnalytics.reports().query,
ids='channel==MINE',
startDate=start_date,
endDate=end_date,
metrics='averageViewPercentage,averageViewDuration',
dimensions='day',
maxResults=100
)
column_headers = ['day', 'averageViewPercentage', 'averageViewDuration']
write_data_to_spreadsheet(response.get('rows', []), 'Audience Retention',column_headers)
def fetch_and_write_time_based_data(youtubeAnalytics,start_date,end_date):
response = execute_api_request(
youtubeAnalytics.reports().query,
ids='channel==MINE',
startDate=start_date,
endDate=end_date,
metrics='views,averageViewDuration,estimatedMinutesWatched,averageViewPercentage,subscribersGained',
dimensions='day',
sort='day',
maxResults=1000
)
column_headers = ['day', 'views', 'averageViewDuration', 'estimatedMinutesWatched', 'averageViewPercentage', 'subscribersGained']
write_data_to_spreadsheet(response.get('rows', []), 'Time-based Data',column_headers)
def fetch_and_write_user_geography(youtubeAnalytics,start_date,end_date):
response = execute_api_request(
youtubeAnalytics.reports().query,
ids='channel==MINE',
startDate=start_date,
endDate=end_date,
metrics='views,estimatedMinutesWatched,averageViewDuration,averageViewPercentage,subscribersGained',
dimensions='country',
sort='-views',
maxResults=10
)
column_headers = ['country', 'views','estimatedMinutesWatched','averageViewDuration','averageViewPercentage','subscribersGained']
write_data_to_spreadsheet(response.get('rows', []), 'User Geography',column_headers)
def fetch_and_write_traffic_source(youtubeAnalytics,start_date,end_date):
response = execute_api_request(
youtubeAnalytics.reports().query,
ids='channel==MINE',
startDate=start_date,
endDate=end_date,
metrics='views',
dimensions='insightTrafficSourceType',
sort='-views',
maxResults=20
)
column_headers = ['trafficSource', 'views']
write_data_to_spreadsheet(response.get('rows', []), 'Traffic Source',column_headers)
def fetch_and_write_device_and_os(youtubeAnalytics,start_date,end_date):
response = execute_api_request(
youtubeAnalytics.reports().query,
ids='channel==MINE',
startDate=start_date,
endDate=end_date,
metrics='views',
dimensions='deviceType,operatingSystem',
sort='-views',
maxResults=10
)
column_headers = ['deviceType', 'operatingSystem', 'views']
write_data_to_spreadsheet(response.get('rows', []), 'Device and OS',column_headers)
def fetch_and_write_viewer_demographics(youtubeAnalytics,start_date,end_date):
response = execute_api_request(
youtubeAnalytics.reports().query,
ids='channel==MINE',
startDate=start_date,
endDate=end_date,
metrics='viewerPercentage',
dimensions='ageGroup,gender',
sort='gender,ageGroup',
maxResults=10
)
column_headers = ['viewerAge','viewerGender', 'viewerPercentage']
write_data_to_spreadsheet(response.get('rows', []), 'Viewer Demographics',column_headers)
def playbacklocation(youtubeAnalytics,start_date,end_date):
response = execute_api_request(
youtubeAnalytics.reports().query,
ids='channel==MINE',
startDate=start_date,
endDate=end_date,
metrics='estimatedMinutesWatched,views',
dimensions='insightPlaybackLocationType',
sort='-views',
maxResults=50
)
column_headers = ['insightPlaybackLocationType','estimatedMinutesWatched', 'views']
write_data_to_spreadsheet(response.get('rows', []), 'Playback Location',column_headers)
def socialshares(youtubeAnalytics,start_date,end_date):
response = execute_api_request(
youtubeAnalytics.reports().query,
ids='channel==MINE',
startDate=start_date,
endDate=end_date,
metrics='shares',
dimensions='sharingService',
sort='-shares',
maxResults=50
)
column_headers = ['sharingService','shares']
write_data_to_spreadsheet(response.get('rows', []), 'Social',column_headers)
if __name__ == '__main__':
parser = argparse.ArgumentParser(description='YouTube Analytics Data Fetcher')
parser.add_argument('--start_date', type=str, help='Start date for analytics data (YYYY-MM-DD)')
parser.add_argument('--end_date', type=str, help='End date for analytics data (YYYY-MM-DD)')
args = parser.parse_args()
if not args.start_date or not args.end_date:
parser.error('Please provide both start_date and end_date parameters.')
# Disable OAuthlib's HTTPs verification when running locally.
# *DO NOT* leave this option enabled when running in production.
os.environ['OAUTHLIB_INSECURE_TRANSPORT'] = '1'
youtubeAnalytics = get_service()
fetch_and_write_basic_stats(youtubeAnalytics, args.start_date, args.end_date)
fetch_and_write_top_videos(youtubeAnalytics, args.start_date, args.end_date)
fetch_and_write_audience_retention(youtubeAnalytics, args.start_date, args.end_date)
fetch_and_write_time_based_data(youtubeAnalytics, args.start_date, args.end_date)
fetch_and_write_user_geography(youtubeAnalytics, args.start_date, args.end_date)
fetch_and_write_traffic_source(youtubeAnalytics, args.start_date, args.end_date)
fetch_and_write_device_and_os(youtubeAnalytics, args.start_date, args.end_date)
#fetch_and_write_viewer_demographics(youtubeAnalytics, args.start_date, args.end_date)
playbacklocation(youtubeAnalytics, args.start_date, args.end_date)
socialshares(youtubeAnalytics, args.start_date, args.end_date)