Converts data from Loop Habit Tracker (Android, CSV) to Awesome Habits (iOS, JSON)

habits-transition.py

import pandas as pd
import json
from datetime import datetime, timezone

# Function to convert date to Apple epoch time
def to_apple_epoch(date_str):
    dt = datetime.strptime(date_str, "%Y-%m-%d")
    apple_epoch = datetime(2001, 1, 1, tzinfo=timezone.utc)
    delta = dt.replace(tzinfo=timezone.utc) - apple_epoch
    return int(delta.total_seconds())

# Habit mapping from names to IDs
habit_mapping = {
    "Do something": "ABDB7B76-B8CF-4AAD-8B83-E212695B1D2D",
    "No something": "DFB3AE83-D3B5-4CE6-82E2-36B9FDD72D08"
}

# Load the CSV file
file_path = 'checkmarks.csv'
df = pd.read_csv(file_path)

# Generate the JSON records
records = []
for index, row in df.iterrows():
    date_apple_epoch = to_apple_epoch(row['Date'])
    for column in df.columns[1:]:
        habit_id = habit_mapping.get(column, "")
        if not habit_id:
            continue  # Skip columns not in habit mapping
        
        if column.lower().startswith("no"):
            quit_habit = True
            count_goal = 0
            count_done = 0 if row[column] == 2 else 1
            skip = row[column] == -1
        else:
            quit_habit = False
            count_goal = 1
            count_done = 1 if row[column] == 2 else 0
            skip = row[column] == -1

        record = {
            "countDone": count_done,
            "countDoneLocked": 0,
            "countGoal": count_goal,
            "countGoalLocked": 0,
            "date": date_apple_epoch,
            "frequency": 0,
            "habitId": habit_id,
            "note": "",
            "quitHabit": quit_habit,
            "skip": skip,
            "timeZone": "Europe/Prague",
            "unit": "",
            "weekdays": "MoTuWeThFrSaSu"
        }
        records.append(record)

# Create the final JSON structure
json_data = json.dumps({
    "customLists": [],
    "habitListRelations": [],
    "habits": [],
    "records": records,
    "reminders": []
}, indent =  2)

# Save JSON to a file
output_path = "habits.json"
with open(output_path, "w") as json_file:
    json_file.write(json_data)