download google fit data through GCP project enabling fitness API

download_google_fit_data.py

from google.oauth2.credentials import Credentials
from googleapiclient.discovery import build
from datetime import datetime, timedelta
import pandas as pd
from google_auth_oauthlib.flow import InstalledAppFlow

# Replace with the path to your credentials.json file
credentials_path = 'fitternew.json'

# Define the scopes that your app needs
SCOPES = ['https://www.googleapis.com/auth/fitness.activity.read']

# Create a flow object to handle the OAuth 2.0 authorization process
flow = InstalledAppFlow.from_client_secrets_file(
    credentials_path, 
    scopes=SCOPES,
    redirect_uri='urn:ietf:wg:oauth:2.0:oob'
)

# Start the authorization flow and get the authorization URL
auth_url, _ = flow.authorization_url(access_type='offline')

# Print the authorization URL and prompt the user to visit it
print(f"Visit this URL to authorize the application: {auth_url}")
auth_code = input("Enter the authorization code: ")

# Exchange the authorization code for a set of access and refresh tokens
flow.fetch_token(code=auth_code)

# Get the credentials object from the flow object
creds = flow.credentials

# Use the credentials object to make authorized requests to the API


# set up Google Fit API client
fit_client = build('fitness', 'v1', credentials=creds)

# define date range for step data to download
end_date = datetime.utcnow()
start_date = end_date - timedelta(days=500) # last 365 days

# make requests for each 90-day chunk of data
step_data = []
while end_date > start_date:
    request_end_date = end_date
    request_start_date = request_end_date - timedelta(days=90) # 90-day chunk
    if request_start_date < start_date:
        request_start_date = start_date
    
    # set up request to retrieve step data from Google Fit API
    request = fit_client.users().dataset().aggregate(userId='me', body={
      "aggregateBy": [{
        "dataTypeName": "com.google.step_count.delta",
        "dataSourceId": "derived:com.google.step_count.delta:com.google.android.gms:estimated_steps"
      }],
      "bucketByTime": { "durationMillis": 86400000*7 },
      "startTimeMillis": int(request_start_date.timestamp()) * 1000,
      "endTimeMillis": int(request_end_date.timestamp()) * 1000,
    })
    
    # execute request and retrieve step data
    response = request.execute()
    
    # extract step data from response
    if 'bucket' in response:
        for bucket in response['bucket']:
            if 'dataset' in bucket:
                for dataset in bucket['dataset']:
                    if 'point' in dataset:
                        for point in dataset['point']:
                            if 'value' in point:
                                step_count = point['value'][0]['intVal']
                                timestamp = int(point['endTimeNanos']) / 1000000
                                date = datetime.utcfromtimestamp(timestamp / 1000).strftime('%Y-%m-%d')
                                step_data.append({'date': date, 'timestamp': timestamp, 'step_count': step_count})
    
    # update end_date for next iteration
    end_date = request_start_date
    
# print step data
print(step_data)