Transfer time entries from Clockify to Toggl Track

clockify_to_toggl.py

import pandas as pd
from sys import argv

input_csv_path = argv[1]

df = pd.read_csv(input_csv_path)

## Create column mapping dictionary
column_mapping = {'Category': 'Client',         ## <- if you have not changed settings in Clockify, remove this entry
                  'Duration (h)': 'Duration',
                  'Start Date': 'Start date',
                  'Start Time': 'Start time',
                  'End Date': 'End date',
                  'End Time': 'End time',
                  'Billable Amount (USD)': 'Amount (USD)'
                 }

## Rename columns
df.rename(columns=column_mapping, inplace=True)

## Remove columns based on their names
columns_to_remove = ['Group', 'Billable Rate (USD)', 'Duration (decimal)']
df.drop(columns=columns_to_remove, inplace=True, errors='ignore')

## Write to a new CSV file
output_csv_path = argv[2]
df.to_csv(output_csv_path, index=False)

Transfer time entries from Clockify to Toggl Track using Export/Import

Using this code, You can transfer your time entries from Clockify to Toggl Track using Export and Import functionality of these tools

Usage

python3 converter.py path/to/clockify_export.csv path/to/output.csv

Notes

1. I've changed settings in Clockify to show "Categories" instead of "Clients", so if you did NOT do the same, remove 'Category': 'Client', from column_mapping

2. My display format in Clockify set to "YYYY-MM-DD", change yours to this or you will encounter an error while importing to Toggl Track (Toggl Track format in my setting, set to "DD/MM/YYYY" which is not important as I tested)

3. If you on Toggl Track FREE plan, open output.csv (using Numbers on Mac or Excel on Windows or any similar app on Linux 😉) and DELETE Tasks column entirely because task is not available for free accounts on Toggl Track! (funny though)

Good luck