How to load data from Toggl to Google Sheets

Learn how to use Airbyte to synchronize your Toggl data into Google Sheets within minutes.

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Set up a Toggl connector in Airbyte

Connect to Toggl or one of 400+ pre-built or 10,000+ custom connectors through simple account authentication.

Set up Google Sheets for your extracted Toggl data

Select Google Sheets where you want to import data from your Toggl source to. You can also choose other cloud data warehouses, databases, data lakes, vector databases, or any other supported Airbyte destinations.

Configure the Toggl to Google Sheets in Airbyte

This includes selecting the data you want to extract - streams and columns -, the sync frequency, where in the destination you want that data to be loaded.

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How to Sync Toggl to Google Sheets Manually

  1. Go to the Toggl API documentation to understand how to interact with the Toggl API.
  2. Register for a Toggl account if you haven’t already, and get your API token from the bottom of the Toggl Profile Settings page.
  1. Go to the Google Developers Console.
  2. Create a new project or select an existing one.
  3. Navigate to the “Library” section and enable the Google Sheets API for your project.
  4. Go to “Credentials” and create credentials for your application. You’ll need an OAuth 2.0 client ID for a web application.
  5. Download the JSON file that contains your client ID and client secret.
  1. Go to Google Sheets and create a new spreadsheet.
  2. Name the spreadsheet and take note of the spreadsheet ID found in the URL (between /d/ and /edit).
  1. Choose a programming language that you’re comfortable with. For this example, we’ll use Python.
  2. Install the necessary libraries for HTTP requests and OAuth2 (e.g., requests for Python).
  3. Write a script that uses your Toggl API token to authenticate and fetch data from Toggl. You’ll likely be making a GET request to an endpoint like https://api.track.toggl.com/reports/api/v2/details to get detailed report data.
  4. Parse the response data into a format suitable for insertion into Google Sheets (e.g., a list of lists, where each inner list represents a row).
  1. Using the Google Sheets API or Apps Script, authenticate with the OAuth 2.0 credentials you downloaded.
  2. Write a function that takes the parsed data from Step 4 and inserts it into the Google Sheet you created. You may use the spreadsheets.values.append method to append data to the sheet.
  1. Combine the Toggl data fetching and Google Sheets data insertion scripts into a single script or process.
  2. Ensure that you handle pagination if the Toggl data exceeds one page.
  3. Run the script and check your Google Sheet to see if the data has been inserted correctly.
  1. If you want to automate the process, you can schedule the script to run at regular intervals.
  2. This could be done using a cron job on a Linux server, Windows Task Scheduler, or any other scheduling tool that works with your setup.

Sample Python Code

Here’s a very basic example of how you might start writing a Python script to fetch data from Toggl and insert it into Google Sheets:

import requests
from google.oauth2.credentials import Credentials
from googleapiclient.discovery import build

# Toggl API request
toggl_api_token = 'YOUR_TOGGL_API_TOKEN'
auth_header = {'Authorization': 'Basic ' + toggl_api_token}
toggl_url = 'https://api.track.toggl.com/reports/api/v2/details'
toggl_params = {
   'workspace_id': 'YOUR_WORKSPACE_ID',
   'since': 'START_DATE',
   'until': 'END_DATE'
}
toggl_response = requests.get(toggl_url, headers=auth_header, params=toggl_params)
toggl_data = toggl_response.json()

# Parse Toggl data
toggl_rows = []
for entry in toggl_data['data']:
   toggl_rows.append([
       entry['description'],
       entry['start'],
       entry['end'],
       entry['duration']
   ])

# Google Sheets API request
spreadsheet_id = 'YOUR_SPREADSHEET_ID'
range_name = 'A1'
creds = Credentials.from_authorized_user_file('path_to_your_credentials.json')
service = build('sheets', 'v4', credentials=creds)
sheet = service.spreadsheets()

# Insert data into Google Sheets
request = sheet.values().append(spreadsheetId=spreadsheet_id, range=range_name,
                               valueInputOption='USER_ENTERED', body={'values': toggl_rows})
response = request.execute()

Please ensure you replace placeholders like 'YOUR_TOGGL_API_TOKEN', 'YOUR_WORKSPACE_ID', 'START_DATE', 'END_DATE', 'YOUR_SPREADSHEET_ID', and 'path_to_your_credentials.json' with your actual data.

How to Sync Toggl to Google Sheets Manually - Method 2:

FAQs

ETL, an acronym for Extract, Transform, Load, is a vital data integration process. It involves extracting data from diverse sources, transforming it into a usable format, and loading it into a database, data warehouse or data lake. This process enables meaningful data analysis, enhancing business intelligence.

Toggl is a favorite app which lets you track how much time you spend on activities. Toggl generally builds work tools to uphold your productivity and eliminate stress. Toggl Track is entirely designed for effortless time tracking. It is a simple but mighty time tracker that exhibits you how much your time is valuable. Time tracking that is easy, powerful, and frictionless. The app that helps you make the most of your time. Start and stop tracking your time with a single tap.

Toggl's API provides access to a wide range of data related to time tracking and project management. The following are the categories of data that can be accessed through Toggl's API:  

1. Time entries: This includes data related to the time spent on tasks, projects, and clients.  
2. Projects: This includes data related to the projects being worked on, such as project name, description, and status.  
3. Clients: This includes data related to the clients associated with the projects, such as client name, contact information, and billing details.  
4. Users: This includes data related to the users who are using Toggl, such as user name, email address, and role.  
5. Tags: This includes data related to the tags associated with time entries, projects, and clients.  
6. Workspaces: This includes data related to the workspaces in which the projects and time entries are being managed.  
7. Reports: This includes data related to the reports generated by Toggl, such as time summary reports, detailed reports, and project reports.  

Overall, Toggl's API provides a comprehensive set of data that can be used to track time, manage projects, and generate reports.

This can be done by building a data pipeline manually, usually a Python script (you can leverage a tool as Apache Airflow for this). This process can take more than a full week of development. Or it can be done in minutes on Airbyte in three easy steps: 
1. Set up Toggl to Google Sheets as a source connector (using Auth, or usually an API key)
2. Choose a destination (more than 50 available destination databases, data warehouses or lakes) to sync data too and set it up as a destination connector
3. Define which data you want to transfer from Toggl to Google Sheets and how frequently
You can choose to self-host the pipeline using Airbyte Open Source or have it managed for you with Airbyte Cloud. 

ELT, standing for Extract, Load, Transform, is a modern take on the traditional ETL data integration process. In ELT, data is first extracted from various sources, loaded directly into a data warehouse, and then transformed. This approach enhances data processing speed, analytical flexibility and autonomy.

ETL and ELT are critical data integration strategies with key differences. ETL (Extract, Transform, Load) transforms data before loading, ideal for structured data. In contrast, ELT (Extract, Load, Transform) loads data before transformation, perfect for processing large, diverse data sets in modern data warehouses. ELT is becoming the new standard as it offers a lot more flexibility and autonomy to data analysts.

What should you do next?

Hope you enjoyed the reading. Here are the 3 ways we can help you in your data journey:

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