Nempickaxe · April 19, 2023 09:34
diff --git a/download_google_fit_data.py b/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)
	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)