import gradio as gr
import datetime
import json
import os
import calendar
from pathlib import Path
import plotly.graph_objects as go
import plotly.express as px
import numpy as np
# Create data directory if it doesn't exist
DATA_DIR = Path("daily_data")
try:
DATA_DIR.mkdir(parents=True, exist_ok=True)
except Exception as e:
print(f"Error creating data directory: {e}")
JOURNAL_QUESTIONS = [
"What made you happiest today, and why?",
"What was the biggest challenge you faced today, and how did you approach it?",
"What's one thing you learned or realized today?",
"What are you grateful for today?",
"What emotion did you feel the most today? What triggered it?",
"What's one moment or interaction that stood out to you?",
"What progress did you make toward your goals today?",
"Did you notice any recurring habits or patterns in your day?",
"How did you support or connect with someone today?",
"What could you have done differently to improve your day?",
"What's one thing you want to prioritize or focus on tomorrow?",
"If today were a chapter in your life story, what would its title be?"
]
def get_date_key():
"""Get current date in YYYY-MM-DD format"""
return datetime.datetime.now().strftime("%Y-%m-%d")
def save_daily_data(data, date_key=None):
"""Save daily data to JSON file"""
if date_key is None:
date_key = get_date_key()
# Ensure data is a dictionary
if not isinstance(data, dict):
data = create_empty_daily_data()
# Convert DataFrame to list for JSON serialization
if "focus" in data:
if "priorities" in data["focus"]:
priorities = data["focus"]["priorities"]
if hasattr(priorities, '__array__') or hasattr(priorities, 'values'):
data["focus"]["priorities"] = priorities.values.tolist() if hasattr(priorities, 'values') else priorities.tolist()
if "later" in data["focus"]:
later = data["focus"]["later"]
if hasattr(later, '__array__') or hasattr(later, 'values'):
data["focus"]["later"] = later.values.tolist() if hasattr(later, 'values') else later.tolist()
# Deep merge required fields with existing data
required_fields = {
"tracking_metrics": {
"productivity": 0,
"energy": 0,
"mood": 0,
"sleep_quality": 0,
"exercise_intensity": 0
},
"habits": {},
"focus": {
"priorities": [],
"later": [],
"priority_reward": "",
"later_reward": ""
},
"meals": {
"breakfast": "",
"lunch": "",
"dinner": "",
"snacks": ""
},
"last_updated": datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
}
for key, default_value in required_fields.items():
if key not in data:
data[key] = default_value
elif isinstance(default_value, dict):
for subkey, subvalue in default_value.items():
if subkey not in data[key]:
data[key][subkey] = subvalue
file_path = DATA_DIR / f"{date_key}.json"
try:
# Ensure the directory exists again (in case it was deleted)
DATA_DIR.mkdir(parents=True, exist_ok=True)
# Write directly to the file first
with open(file_path, 'w') as f:
json.dump(data, f, indent=2, sort_keys=True)
except Exception as e:
print(f"Error saving data: {e}")
try:
# Fallback: try to save in the current directory
with open(f"{date_key}.json", 'w') as f:
json.dump(data, f, indent=2, sort_keys=True)
print(f"Saved data to current directory as fallback")
except Exception as e2:
print(f"Final save attempt failed: {e2}")
def clean_daily_data_file(date_key):
"""Clean up corrupted JSON file and restore it with valid data"""
file_path = DATA_DIR / f"{date_key}.json"
try:
if file_path.exists():
with open(file_path, 'r') as f:
content = f.read().strip()
try:
# Try to parse the content directly first
data = json.loads(content)
return validate_data_structure(data)
except json.JSONDecodeError:
# If that fails, try to clean the content
content = content.rstrip(', \t\n\r')
last_brace = content.rfind('}')
if last_brace != -1:
content = content[:last_brace + 1]
try:
data = json.loads(content)
data = validate_data_structure(data)
# Save the cleaned data
save_daily_data(data, date_key)
return data
except:
pass
# If all cleaning attempts fail, create new data
print(f"Creating new data for {date_key}")
data = create_empty_daily_data()
save_daily_data(data, date_key)
return data
except Exception as e:
print(f"Error cleaning data file {date_key}: {e}")
return create_empty_daily_data()
def load_daily_data(date_key=None):
"""Load daily data from JSON file"""
if date_key is None:
date_key = get_date_key()
file_path = DATA_DIR / f"{date_key}.json"
try:
if file_path.exists():
try:
# Try to load and clean the file
data = clean_json_file(file_path)
# Validate and update the data structure
data = validate_data_structure(data)
save_daily_data(data, date_key)
return data
except Exception as e:
print(f"Error loading data: {e}")
return create_empty_daily_data()
else:
# Only create new file if it's today's date
if date_key == get_date_key():
data = create_empty_daily_data()
save_daily_data(data, date_key)
return data
else:
return create_empty_daily_data()
except Exception as e:
print(f"Error loading data: {e}")
return create_empty_daily_data()
def validate_data_structure(data):
"""Validate and update data structure if needed"""
if not isinstance(data, dict):
return create_empty_daily_data()
# Create a new data structure with all required fields
valid_data = create_empty_daily_data()
# Copy existing data while ensuring all required fields exist
for key, default_value in valid_data.items():
if key in data:
if isinstance(default_value, dict):
valid_data[key] = {**default_value, **data[key]}
else:
valid_data[key] = data[key]
return valid_data
def create_empty_daily_data():
"""Create empty data structure for a new day"""
# Load current habits list
current_habits = load_habits()
data = {
"habits": {habit: [False] * 7 for habit in current_habits},
"focus": {
"priorities": [
["", ""], # Empty task and status
["", ""],
["", ""],
["", ""],
["", ""]
],
"later": [
["", ""], # Empty task and status
["", ""],
["", ""],
["", ""],
["", ""]
],
"priority_reward": "",
"later_reward": ""
},
"meals": {
"breakfast": "",
"lunch": "",
"dinner": "",
"snacks": ""
},
"last_updated": datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
"tracking_metrics": {
"productivity": 0,
"energy": 0,
"mood": 0,
"sleep_quality": 0,
"exercise_intensity": 0
}
}
# Add journal section with empty entries
data["journal"] = {
question: "" for question in JOURNAL_QUESTIONS
}
return data
def get_week_dates():
"""Get dates for current week"""
today = datetime.date.today()
monday = today - datetime.timedelta(days=today.weekday())
return [(monday + datetime.timedelta(days=i)).strftime("%Y-%m-%d") for i in range(7)]
def get_month_dates():
"""Get dates for current month"""
today = datetime.date.today()
_, num_days = calendar.monthrange(today.year, today.month)
return [(datetime.date(today.year, today.month, day)).strftime("%Y-%m-%d")
for day in range(1, num_days + 1)]
def load_week_data():
"""Load data for the current week"""
week_data = {}
week_dates = get_week_dates()
for date in week_dates:
file_path = DATA_DIR / f"{date}.json"
if file_path.exists():
try:
data = load_daily_data(date)
week_data[date] = data
except Exception as e:
print(f"Error loading week data for {date}: {e}")
week_data[date] = create_empty_daily_data()
else:
# Don't create a file, just return empty data structure
week_data[date] = {
"tracking_metrics": {
"productivity": 0,
"energy": 0,
"mood": 0,
"sleep_quality": 0,
"exercise_intensity": 0
}
}
return week_data
def load_month_data():
"""Load data for the current month"""
month_data = {}
month_dates = get_month_dates()
for date in month_dates:
file_path = DATA_DIR / f"{date}.json"
if file_path.exists():
try:
data = load_daily_data(date)
month_data[date] = data
except Exception as e:
print(f"Error loading month data for {date}: {e}")
month_data[date] = create_empty_daily_data()
else:
# Don't create a file, just return empty data structure
month_data[date] = {
"tracking_metrics": {
"productivity": 0,
"energy": 0,
"mood": 0,
"sleep_quality": 0,
"exercise_intensity": 0
}
}
return month_data
def calculate_success_rate(data_dict, metric):
"""Calculate success rate for a given metric"""
if not data_dict:
return 0
total = 0
count = 0
for date, data in data_dict.items():
# Ensure tracking_metrics exists for each data point
if "tracking_metrics" not in data:
data["tracking_metrics"] = {
"productivity": 0,
"energy": 0,
"mood": 0,
"sleep_quality": 0,
"exercise_intensity": 0
}
if metric in data.get("tracking_metrics", {}):
total += data["tracking_metrics"][metric]
count += 1
return round((total / count) if count > 0 else 0, 2)
# Replace the hardcoded HABITS list with a function to load habits
def get_default_habits():
"""Get the default habits list if no custom list exists"""
return [
# Morning Routine (Essential)
"Morning Exercise/Yoga",
"Meditation (20min)",
# After Work Activities
"Evening Stretch (20min)",
"Active Learning (20min)",
"Journal",
# Flexible Throughout Day
"Reading (20min)",
"Take a photo",
"Future Planning"
]
def load_habits():
"""Load the current habits list from the configuration"""
config_path = Path("habits_config.json")
if config_path.exists():
try:
with open(config_path, 'r') as f:
data = json.load(f)
if "habits" in data and isinstance(data["habits"], list):
return data["habits"]
else:
# If the file exists but is invalid, create a new one with defaults
default_habits = get_default_habits()
save_habits(default_habits)
return default_habits
except Exception as e:
print(f"Error loading habits: {e}")
# If there's an error reading the file, create a new one with defaults
default_habits = get_default_habits()
save_habits(default_habits)
return default_habits
else:
# If the file doesn't exist, create it with defaults
default_habits = get_default_habits()
save_habits(default_habits)
return default_habits
def save_habits(habits_list):
"""Save the current habits list to configuration"""
config_path = Path("habits_config.json")
try:
# Ensure the list is unique and sorted
habits_list = sorted(list(set(habits_list)))
# Save to config file
with open(config_path, 'w') as f:
json.dump({"habits": habits_list}, f, indent=2)
# Also update the current day's data to match
current_data = load_daily_data()
new_habits = {habit: [False] * 7 for habit in habits_list}
# Preserve existing habit states
for habit, states in current_data["habits"].items():
if habit in new_habits:
new_habits[habit] = states
current_data["habits"] = new_habits
save_daily_data(current_data)
except Exception as e:
print(f"Error saving habits: {e}")
# Remove redundant constants
DEFAULT_SELF_CARE_ITEMS = [
"Yoga (AM)", "Vitamins", "Outside",
"Stretch (PM)", "Reading", "Learning", "Journal",
"Tapping", "Meditate", "Brain Train"
]
def parse_time(time_str):
"""Parse time string in either 12-hour or 24-hour format"""
try:
# Try 24-hour format first
return datetime.datetime.strptime(time_str, "%H:%M").strftime("%H:%M")
except ValueError:
try:
# Try 12-hour format with AM/PM
return datetime.datetime.strptime(time_str.strip().upper(), "%I:%M %p").strftime("%H:%M")
except ValueError:
try:
# Try 12-hour format without space before AM/PM
return datetime.datetime.strptime(time_str.strip().upper(), "%I:%M%p").strftime("%H:%M")
except ValueError:
return "00:00" # Default if parsing fails
def calculate_age_stats(birth_date_str, birth_time_str="00:00"):
"""Calculate age-related statistics with precise birth date and time"""
try:
# Parse birth date and time
try:
birth_time = parse_time(birth_time_str)
except ValueError:
return {"Error": "Invalid time format. Please use either HH:MM (24-hour) or HH:MM AM/PM (12-hour)"}
birth_datetime = datetime.datetime.strptime(f"{birth_date_str} {birth_time}", "%Y-%m-%d %H:%M")
now = datetime.datetime.now()
# Calculate time differences
time_lived = now - birth_datetime
age_days = time_lived.days
age_hours = time_lived.total_seconds() / 3600
age_minutes = time_lived.total_seconds() / 60
age_weeks = age_days / 7
age_months = age_days / 30.44
age_years = age_days / 365.25
# Calculate time until milestones
days_until_90 = (datetime.datetime(birth_datetime.year + 90, birth_datetime.month, birth_datetime.day) - now).days
weeks_until_90 = days_until_90 / 7
months_until_90 = days_until_90 / 30.44
years_until_90 = days_until_90 / 365.25
# Calculate percentages and milestones
percent_lived = (age_years / 90) * 100
percent_of_year = (now.timetuple().tm_yday / 365.25) * 100
percent_of_month = (now.day / calendar.monthrange(now.year, now.month)[1]) * 100
percent_of_week = ((now.weekday() + 1) / 7) * 100
percent_of_day = ((now.hour * 3600 + now.minute * 60 + now.second) / 86400) * 100
# Calculate next birthday
next_birthday = datetime.datetime(now.year, birth_datetime.month, birth_datetime.day)
if next_birthday < now:
next_birthday = datetime.datetime(now.year + 1, birth_datetime.month, birth_datetime.day)
days_to_birthday = (next_birthday - now).days
return {
"Current Age": {
"Years": f"{age_years:.2f}",
"Months": f"{age_months:.1f}",
"Weeks": f"{age_weeks:.1f}",
"Days": str(age_days),
"Hours": f"{age_hours:,.0f}",
"Minutes": f"{age_minutes:,.0f}"
},
"Time Until 90": {
"Years": f"{years_until_90:.1f}",
"Months": f"{months_until_90:.1f}",
"Weeks": f"{weeks_until_90:.1f}",
"Days": str(days_until_90)
},
"Life Progress": {
"Life Percentage": f"{percent_lived:.1f}%",
"Current Year": f"{percent_of_year:.1f}%",
"Current Month": f"{percent_of_month:.1f}%",
"Current Week": f"{percent_of_week:.1f}%",
"Current Day": f"{percent_of_day:.1f}%"
},
"Milestones": {
"Days to Next Birthday": str(days_to_birthday),
"Weeks Lived": f"{age_weeks:,.0f}",
"Days Lived": f"{age_days:,d}",
"Hours Lived": f"{age_hours:,.0f}",
"10,000 Days": f"{10000 - (age_days % 10000)} days until next 10k milestone",
"Life Seasons": f"You are in season {int(age_years/20) + 1} of your life"
}
}
except ValueError as e:
return {"Error": f"Invalid date or time format. Please use YYYY-MM-DD for date and HH:MM (24-hour) or HH:MM AM/PM (12-hour) for time."}
def update_progress(checkboxes):
"""Calculate progress percentage"""
completed = sum(1 for x in checkboxes if x)
total = len(checkboxes)
return f"{(completed/total)*100:.1f}%" if total > 0 else "0%"
def check_and_refresh_day(current_data):
"""Check if we need to start a new day"""
# Ensure tracking_metrics exists
if "tracking_metrics" not in current_data:
current_data["tracking_metrics"] = {
"productivity": 0,
"energy": 0,
"mood": 0,
"sleep_quality": 0,
"exercise_intensity": 0
}
last_updated = datetime.datetime.strptime(current_data["last_updated"], "%Y-%m-%d %H:%M:%S")
current_time = datetime.datetime.now()
# If it's a new day (past midnight)
if last_updated.date() < current_time.date():
# Save current data with previous date
previous_date = last_updated.strftime("%Y-%m-%d")
save_daily_data(current_data, previous_date)
# Create new empty data for today
current_data = create_empty_daily_data()
save_daily_data(current_data)
# Always return the current data
return current_data
def update_data(data_key, value):
"""Update specific data in the daily record"""
current_data = load_daily_data()
current_data = check_and_refresh_day(current_data)
# Convert value to list only if it's a DataFrame or numpy array and not a dict
if not isinstance(value, dict) and (hasattr(value, '__array__') or hasattr(value, 'values')):
value = value.values.tolist() if hasattr(value, 'values') else value.tolist()
# Update the specified data
keys = data_key.split('.')
target = current_data
# Special handling for habits which are stored as lists
if keys[0] == "habits" and len(keys) == 3:
habit_name = keys[1]
day_index = int(keys[2]) # Convert string index to integer
if habit_name in target["habits"]:
target["habits"][habit_name][day_index] = value
else:
# Normal dictionary path traversal
for key in keys[:-1]:
target = target[key]
target[keys[-1]] = value
current_data["last_updated"] = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
save_daily_data(current_data)
return current_data
def update_activity(new_name, old_name):
"""Update a self-care activity name and maintain its status"""
if not new_name.strip() or new_name == old_name:
return gr.update()
try:
current_data = load_daily_data()
# Ensure proper data structure
if "self_care" not in current_data or not isinstance(current_data["self_care"], dict):
current_data["self_care"] = {
"items": DEFAULT_SELF_CARE_ITEMS.copy(),
"status": {item: "Not Done" for item in DEFAULT_SELF_CARE_ITEMS}
}
if "items" not in current_data["self_care"]:
current_data["self_care"]["items"] = list(current_data["self_care"].keys())
current_data["self_care"]["status"] = current_data["self_care"].copy()
# Update activity in items list
if old_name in current_data["self_care"]["items"]:
idx = current_data["self_care"]["items"].index(old_name)
current_data["self_care"]["items"][idx] = new_name.strip()
# Update status
if "status" in current_data["self_care"]:
if old_name in current_data["self_care"]["status"]:
current_data["self_care"]["status"][new_name.strip()] = current_data["self_care"]["status"].pop(old_name)
save_daily_data(current_data)
return gr.update()
except Exception as e:
print(f"Error updating activity: {e}")
return gr.update()
def create_life_visualizations(stats):
figures = {}
# 1. Life Progress Donut Chart
progress_data = {k: float(v.strip('%')) for k, v in stats["Life Progress"].items()}
fig_progress = go.Figure(data=[go.Pie(
labels=list(progress_data.keys()),
values=list(progress_data.values()),
hole=.3,
marker_colors=px.colors.qualitative.Set3
)])
fig_progress.update_layout(title="Life Progress Metrics")
figures["progress"] = fig_progress
# 2. Time Remaining Bar Chart
time_until = {k: float(v) for k, v in stats["Time Until 90"].items()}
fig_remaining = go.Figure(data=[go.Bar(
x=list(time_until.keys()),
y=list(time_until.values()),
marker_color='lightblue'
)])
fig_remaining.update_layout(title="Time Until 90")
figures["remaining"] = fig_remaining
# 3. Life Timeline
current_year = float(stats["Current Age"]["Years"])
fig_timeline = go.Figure()
# Add seasons
seasons = [
{"name": "Learning & Discovery", "start": 0, "end": 20, "color": "lightgreen"},
{"name": "Creation & Building", "start": 20, "end": 40, "color": "lightblue"},
{"name": "Mastery & Leadership", "start": 40, "end": 60, "color": "lightyellow"},
{"name": "Wisdom & Guidance", "start": 60, "end": 80, "color": "lightpink"},
{"name": "Legacy & Reflection", "start": 80, "end": 90, "color": "lavender"}
]
for season in seasons:
fig_timeline.add_shape(
type="rect",
x0=season["start"],
x1=season["end"],
y0=0,
y1=1,
fillcolor=season["color"],
opacity=0.3,
layer="below",
line_width=0,
)
# Add current age marker
fig_timeline.add_trace(go.Scatter(
x=[current_year, current_year],
y=[0, 1],
mode="lines",
line=dict(color="red", width=2),
name="Current Age"
))
fig_timeline.update_layout(
title="Life Seasons Timeline",
xaxis_title="Age",
yaxis_showticklabels=False,
showlegend=True
)
figures["timeline"] = fig_timeline
return figures
def update_metrics(prod, en, m, slp, ex, selected_date=None):
"""Update tracking metrics and return updated weekly grid"""
if selected_date is None:
selected_date = get_date_key()
# Load data for the selected date
current_data = load_daily_data(selected_date)
# Update the metrics
current_data["tracking_metrics"] = {
"productivity": prod,
"energy": en,
"mood": m,
"sleep_quality": slp,
"exercise_intensity": ex
}
# Save the updated data
save_daily_data(current_data, selected_date)
# Reload week data to get updated grid
week_data = load_week_data()
# Create updated weekly grid values
week_dates = get_week_dates()
grid_values = [
["Productivity"] + [week_data[date]["tracking_metrics"]["productivity"] for date in week_dates],
["Energy"] + [week_data[date]["tracking_metrics"]["energy"] for date in week_dates],
["Mood"] + [week_data[date]["tracking_metrics"]["mood"] for date in week_dates],
["Sleep"] + [week_data[date]["tracking_metrics"]["sleep_quality"] for date in week_dates],
["Exercise"] + [week_data[date]["tracking_metrics"]["exercise_intensity"] for date in week_dates]
]
# Calculate monthly averages
month_data = load_month_data()
avg_prod = calculate_success_rate(month_data, "productivity")
avg_energy = calculate_success_rate(month_data, "energy")
avg_mood = calculate_success_rate(month_data, "mood")
avg_sleep = calculate_success_rate(month_data, "sleep_quality")
avg_exercise = calculate_success_rate(month_data, "exercise_intensity")
return [
grid_values, # Weekly grid values
f"Average Productivity: {avg_prod}/5",
f"Average Energy: {avg_energy}/5",
f"Average Mood: {avg_mood}/5",
f"Average Sleep: {avg_sleep}/5",
f"Average Exercise: {avg_exercise}/5"
]
def update_journal_entry(question, answer):
"""Update a specific journal entry"""
current_data = load_daily_data()
# Ensure journal section exists
if "journal" not in current_data:
current_data["journal"] = {q: "" for q in JOURNAL_QUESTIONS}
# Update the specific question's answer
current_data["journal"][question] = answer
# Save the updated data
save_daily_data(current_data)
return current_data
# Add this function to format the stats display
def create_stats_display(stats):
# Current Age Section
current_age = f"""
### 🎂 Current Age
- **Years:** {stats["Current Age"]["Years"]} years
- **Months:** {stats["Current Age"]["Months"]} months
- **Weeks:** {stats["Current Age"]["Weeks"]} weeks
- **Days:** {stats["Current Age"]["Days"]} days
⏰ You've been alive for:
- **{stats["Current Age"]["Hours"]}** hours
- **{stats["Current Age"]["Minutes"]}** minutes
"""
# Time Until 90 Section
time_remaining = f"""
### ⏳ Time Until 90
- **Years:** {stats["Time Until 90"]["Years"]} years
- **Months:** {stats["Time Until 90"]["Months"]} months
- **Weeks:** {stats["Time Until 90"]["Weeks"]} weeks
- **Days:** {stats["Time Until 90"]["Days"]} days
"""
# Progress Section
progress = f"""
### 📊 Life Progress
- **Life Journey:** {stats["Life Progress"]["Life Percentage"]} complete
- **This Year:** {stats["Life Progress"]["Current Year"]} complete
- **This Month:** {stats["Life Progress"]["Current Month"]} complete
- **This Week:** {stats["Life Progress"]["Current Week"]} complete
- **Today:** {stats["Life Progress"]["Current Day"]} complete
"""
# Milestones Section
milestones = f"""
### 🏆 Key Milestones
- **Next Birthday:** {stats["Milestones"]["Days to Next Birthday"]} days away
- **Weeks Journey:** {stats["Milestones"]["Weeks Lived"]} weeks lived
- **Days Journey:** {stats["Milestones"]["Days Lived"]} days experienced
- **Hours Journey:** {stats["Milestones"]["Hours Lived"]} hours lived
- **10k Milestone:** {stats["Milestones"]["10,000 Days"]}
- **Life Season:** {stats["Milestones"]["Life Seasons"]}
"""
return current_age, time_remaining, progress, milestones
# Add this function to format daily data for display
def format_daily_summary(date, data):
"""Format daily data into a summary row for the history table"""
try:
metrics = data.get("tracking_metrics", {})
habits_completed = sum(1 for habit in data.get("habits", {}).values()
for done in habit if done)
total_habits = len(data.get("habits", {})) * 7
habits_percent = f"{(habits_completed/total_habits)*100:.1f}%" if total_habits > 0 else "0%"
journal_entries = sum(1 for entry in data.get("journal", {}).values() if entry.strip())
# Format date for display
display_date = datetime.datetime.strptime(date, "%Y-%m-%d").strftime("%Y-%m-%d (%a)")
return [
display_date,
metrics.get("productivity", 0),
metrics.get("energy", 0),
metrics.get("mood", 0),
metrics.get("sleep_quality", 0),
metrics.get("exercise_intensity", 0),
habits_percent,
journal_entries
]
except Exception as e:
print(f"Error formatting data for {date}: {e}")
return [date, 0, 0, 0, 0, 0, "0%", 0]
# Add this function to load history data
def load_history_data():
"""Load all available daily data files"""
history_data = []
# Get all JSON files in the data directory
json_files = sorted(DATA_DIR.glob("*.json"), reverse=True) # Sort newest first
for file_path in json_files:
date = file_path.stem # Get date from filename
try:
with open(file_path, 'r') as f:
data = json.load(f)
# Format the data for display
history_data.append(format_daily_summary(date, data))
except Exception as e:
print(f"Error loading {file_path}: {e}")
return history_data
def save_user_config(birth_date, birth_time):
"""Save user configuration data"""
try:
# Validate date format
datetime.datetime.strptime(birth_date, "%Y-%m-%d")
# Convert time to 24-hour format
formatted_time = parse_time(birth_time)
config = {
"birth_date": birth_date,
"birth_time": formatted_time
}
config_path = Path("user_config.json")
with open(config_path, "w") as f:
json.dump(config, f, indent=2)
return True
except Exception as e:
print(f"Error saving config: {e}")
return False
def load_user_config():
"""Load user configuration data"""
config_path = Path("user_config.json")
default_config = {
"birth_date": "", # Your birth date
"birth_time": "" # Your birth time in 24-hour format
}
if config_path.exists():
try:
with open(config_path, "r") as f:
config = json.load(f)
# Validate loaded data
datetime.datetime.strptime(config["birth_date"], "%Y-%m-%d")
parse_time(config["birth_time"])
return config
except Exception as e:
print(f"Error loading config: {e}")
return default_config
def add_new_habit(habit_name, duration, category):
"""Add a new habit to the tracking system"""
try:
if not habit_name.strip():
return "⚠️ Please enter a habit name", None, None, None
# Format the habit name with duration if provided
formatted_habit = habit_name.strip()
if duration:
formatted_habit = f"{formatted_habit} ({duration})"
# Add category prefix for sorting
if category == "Morning":
formatted_habit = f"Morning {formatted_habit}"
elif category == "Evening":
formatted_habit = f"Evening {formatted_habit}"
# Load current habits
current_habits = load_habits()
# Check if habit already exists
if formatted_habit in current_habits:
return "⚠️ This habit already exists", None, None, None
# Add new habit to list
current_habits.append(formatted_habit)
# Save updated habits list
save_habits(current_habits)
# Return success message and clear inputs
return "✅ Habit added successfully!", "", "", ""
except Exception as e:
print(f"Error adding habit: {e}")
return f"❌ Error adding habit: {str(e)}", None, None, None
def create_habit_section():
"""Create the habit tracking section with better layout"""
# Load current habits
current_habits = load_habits()
# Group habits by time of day
morning_habits = [h for h in current_habits if any(x in h.lower() for x in ["wake", "morning", "meditation", "brain", "walk"])]
evening_habits = [h for h in current_habits if any(x in h.lower() for x in ["evening", "massage", "learning", "journal", "guitar"])]
flexible_habits = [h for h in current_habits if h not in morning_habits + evening_habits]
with gr.Column(scale=1):
gr.Markdown("### 📅 Daily Habits & Tasks")
# Create summary text component first
with gr.Row():
gr.Markdown("### 📊 Weekly Summary")
summary_text = gr.Markdown()
refresh_btn = gr.Button("🔄 Refresh")
# Add status message component
status_message = gr.Markdown(visible=False)
# Connect refresh button to update summary
refresh_btn.click(
fn=update_summary,
outputs=summary_text
)
# Add column headers once at the top
with gr.Row(equal_height=True, variant="compact"):
with gr.Column(scale=6):
gr.Markdown("Task")
with gr.Column(scale=7):
with gr.Row(equal_height=True, variant="compact"):
days = ["M", "T", "W", "Th", "F", "S", "Su"]
for day in days:
with gr.Column(scale=1, min_width=35):
gr.Markdown(day)
with gr.Column(scale=3):
gr.Markdown("Progress")
# Morning Section
with gr.Group():
gr.Markdown("#### 🌅 Morning Routine")
create_habit_group(morning_habits, summary_text)
gr.Markdown("---")
# Evening Section
with gr.Group():
gr.Markdown("#### 🌙 Evening Activities")
create_habit_group(evening_habits, summary_text)
gr.Markdown("---")
# Flexible Section
with gr.Group():
gr.Markdown("#### ⭐ Flexible Activities")
create_habit_group(flexible_habits, summary_text)
gr.Markdown("---")
# Add new habit section
with gr.Row(equal_height=True):
new_habit = gr.Textbox(
label="New Habit/Task",
placeholder="Enter a new habit or task to track",
scale=3,
min_width=200
)
category = gr.Dropdown(
choices=["Morning", "Evening", "Flexible"],
label="Category",
value="Flexible",
scale=2,
min_width=100
)
duration = gr.Dropdown(
choices=["", "15min", "20min", "30min", "45min", "60min"],
label="Duration",
scale=2,
min_width=100
)
add_btn = gr.Button("Add Habit", scale=1, min_width=100)
# Add status message component
status_message = gr.Markdown(visible=False)
def add_and_refresh(habit_name, category, duration):
message, _, _, _ = add_new_habit(habit_name, duration, category)
# Reload habits and recreate sections
current_habits = load_habits()
morning_habits = [h for h in current_habits if any(x in h.lower() for x in ["wake", "morning", "meditation", "brain", "walk"])]
evening_habits = [h for h in current_habits if any(x in h.lower() for x in ["evening", "massage", "learning", "journal", "guitar"])]
flexible_habits = [h for h in current_habits if h not in morning_habits + evening_habits]
# Update summary
summary = update_summary()
# Create updated habit groups
create_habit_group(morning_habits, summary_text)
create_habit_group(evening_habits, summary_text)
create_habit_group(flexible_habits, summary_text)
return [
message, # Status message
"", # Clear habit input
category, # Keep category selection
"", # Clear duration input
gr.update(visible=True), # Show status message
gr.update(value=summary) # Update summary text
]
# Connect the add button event
add_btn.click(
fn=add_and_refresh,
inputs=[new_habit, category, duration],
outputs=[
status_message,
new_habit,
category,
duration,
status_message,
summary_text
]
)
# Create a refresh button that will be clicked programmatically
refresh_habits_btn = gr.Button("Refresh", visible=False)
def add_and_refresh(habit_name, duration):
message, _, _ = add_new_habit(habit_name, duration)
return [
message, # Status message
"", # Clear habit input
"", # Clear duration input
gr.update(visible=True), # Show status message
True # Trigger refresh button
]
# Connect the add button event
add_btn.click(
fn=add_and_refresh,
inputs=[new_habit, duration],
outputs=[
status_message,
new_habit,
duration,
status_message,
refresh_habits_btn
]
)
# Connect refresh button to reload habits
def reload_habits():
current_habits = load_habits()
morning_habits = [h for h in current_habits if any(x in h.lower() for x in ["wake", "morning", "meditation", "brain", "walk"])]
evening_habits = [h for h in current_habits if any(x in h.lower() for x in ["evening", "massage", "learning", "journal", "guitar"])]
flexible_habits = [h for h in current_habits if h not in morning_habits + evening_habits]
return [
gr.update(value=update_summary()), # Update summary
gr.update(visible=False) # Hide status message
]
refresh_habits_btn.click(
fn=reload_habits,
outputs=[
summary_text,
status_message
]
)
def create_habit_group(habits, summary_text):
"""Create a group of habit tracking rows with better scaling"""
for habit in habits:
with gr.Row(equal_height=True, variant="compact") as row:
# Task name and duration (left side)
with gr.Column(scale=6, min_width=300):
name_edit = gr.Textbox(
value=habit,
label="Task Name",
interactive=True,
container=False,
)
# Duration slider (optional, shown inline)
duration_edit = None
if any(x in habit.lower() for x in ["min", "hour"]):
duration_edit = gr.Slider(
minimum=5,
maximum=60,
value=int(''.join(filter(str.isdigit, habit))) if any(c.isdigit() for c in habit) else 20,
step=5,
label="Duration",
container=False,
scale=1
)
# Checkboxes container (middle)
with gr.Column(scale=7, min_width=350):
with gr.Row(equal_height=True, variant="compact"):
days = ["M", "T", "W", "Th", "F", "S", "Su"]
checkboxes = []
for day in days:
with gr.Column(scale=1, min_width=30):
checkbox = gr.Checkbox(
label=day,
container=False,
scale=1,
min_width=25,
show_label=False
)
gr.Markdown(day, container=False)
checkboxes.append(checkbox)
# Progress and actions (right side)
with gr.Column(scale=3, min_width=150):
with gr.Row(equal_height=True, variant="compact"):
progress = gr.Textbox(
value="0%",
label="Progress",
interactive=False,
container=False,
scale=2
)
edit_btn = gr.Button("✏️", scale=1, min_width=30)
delete_btn = gr.Button("🗑️", scale=1, min_width=30)
# Connect edit button handler
def edit_habit(name, duration=None):
if duration is not None:
result = update_habit_name(habit, name, duration)
gr.Info(f"Updated: {name}")
return result
result = update_habit_name(habit, name)
gr.Info(f"Updated: {name}")
return result
edit_btn.click(
fn=edit_habit,
inputs=[name_edit] + ([duration_edit] if duration_edit else []),
outputs=[name_edit]
)
# Connect delete button handler
def delete_habit_fn(habit_name=habit):
"""Delete a habit and update the UI"""
try:
# 1. Delete from habits_config.json first
config_path = Path("habits_config.json")
if config_path.exists():
with open(config_path, 'r') as f:
config_data = json.load(f)
if "habits" in config_data:
if habit_name in config_data["habits"]:
config_data["habits"].remove(habit_name)
with open(config_path, 'w') as f:
json.dump(config_data, f, indent=2)
print(f"Removed {habit_name} from habits_config.json")
# 2. Update current daily data
current_data = load_daily_data()
if "habits" in current_data and habit_name in current_data["habits"]:
del current_data["habits"][habit_name]
save_daily_data(current_data)
print(f"Removed {habit_name} from current daily data")
# 3. Clean up historical data
json_files = list(DATA_DIR.glob("*.json"))
for file_path in json_files:
try:
with open(file_path, 'r') as f:
day_data = json.load(f)
if "habits" in day_data and habit_name in day_data["habits"]:
del day_data["habits"][habit_name]
with open(file_path, 'w') as f:
json.dump(day_data, f, indent=2)
print(f"Removed {habit_name} from {file_path}")
except Exception as e:
print(f"Error updating file {file_path}: {e}")
# Show success notification
gr.Info(f"Deleted: {habit_name}")
# Force reload habits from config
load_habits() # Reload habits to ensure sync
# Hide the row in UI
return gr.update(visible=False)
except Exception as e:
print(f"Error deleting habit: {e}")
gr.Warning(f"Failed to delete {habit_name}")
return gr.update()
# Connect delete button with proper output
delete_btn.click(
fn=delete_habit_fn,
outputs=row
)
# Update progress when checkboxes change
def make_progress_handler(current_habit):
"""Create a closure for the progress handler to capture the habit name"""
def update_progress_display(*checkbox_values):
"""Update progress display for a habit"""
completed = sum(1 for x in checkbox_values if x)
total = len(checkbox_values)
percentage = f"{(completed/total)*100:.1f}%" if total > 0 else "0%"
# Update the data
current_data = load_daily_data()
if current_habit in current_data["habits"]:
current_data["habits"][current_habit] = list(checkbox_values)
save_daily_data(current_data)
return percentage
return update_progress_display
# Connect checkbox handlers using closure
progress_handler = make_progress_handler(habit)
for checkbox in checkboxes:
checkbox.change(
fn=progress_handler,
inputs=checkboxes,
outputs=progress
)
def update_habit_name(old_name, new_name, duration=None):
"""Update habit name and optionally duration"""
if not new_name.strip():
return gr.update()
try:
# Format new name
new_full_name = new_name.strip()
if duration is not None:
new_full_name = f"{new_full_name} ({int(duration)}min)"
# Update habits configuration
current_habits = load_habits()
if old_name in current_habits:
current_habits.remove(old_name)
current_habits.append(new_full_name)
save_habits(current_habits)
# Update all daily files
update_all_daily_files(habit_to_rename=old_name, new_name=new_full_name)
# Return update for the textbox
return gr.update(value=new_full_name)
except Exception as e:
print(f"Error updating habit name: {e}")
gr.Warning(f"Failed to update {old_name}")
return gr.update()
def update_summary():
"""Update the weekly summary text"""
current_data = load_daily_data()
total_habits = len(current_data["habits"])
total_completed = sum(
sum(1 for x in habit_data if x)
for habit_data in current_data["habits"].values()
)
total_possible = total_habits * 7
completion_rate = (total_completed / total_possible * 100) if total_possible > 0 else 0
return f"""
- Total Habits: {total_habits}
- Completed Tasks: {total_completed}/{total_possible}
- Overall Completion Rate: {completion_rate:.1f}%
"""
def auto_refresh():
"""Auto refresh function to check and refresh day data"""
try:
current_data = load_daily_data()
current_data = check_and_refresh_day(current_data)
save_daily_data(current_data)
# Don't return anything
except Exception as e:
print(f"Error in auto refresh: {e}")
def update_all_daily_files(habit_to_remove=None, habit_to_rename=None, new_name=None):
"""Update all daily data files when habits are modified"""
try:
# Get all JSON files in the data directory
json_files = list(DATA_DIR.glob("*.json"))
for file_path in json_files:
try:
# Load the file
with open(file_path, 'r') as f:
data = json.load(f)
modified = False
# Handle habit removal
if habit_to_remove and habit_to_remove in data.get("habits", {}):
del data["habits"][habit_to_remove]
modified = True
# Handle habit renaming
if habit_to_rename and new_name and habit_to_rename in data.get("habits", {}):
data["habits"][new_name] = data["habits"].pop(habit_to_rename)
modified = True
# Save if modified
if modified:
with open(file_path, 'w') as f:
json.dump(data, f, indent=2, sort_keys=True)
except Exception as e:
print(f"Error updating file {file_path}: {e}")
continue
except Exception as e:
print(f"Error updating daily files: {e}")
def get_available_dates():
"""Get list of dates with existing data files"""
try:
json_files = sorted(DATA_DIR.glob("*.json"), reverse=True) # Most recent first
dates = [file.stem for file in json_files] # Get dates from filenames
return dates
except Exception as e:
print(f"Error getting available dates: {e}")
return [get_date_key()] # Return today's date as fallback
def refresh_dates():
"""Refresh the available dates in the dropdown"""
dates = get_available_dates()
return gr.update(choices=dates)
def load_selected_date_metrics(date):
"""Load metrics for the selected date"""
data = load_daily_data(date)
metrics = data.get("tracking_metrics", {
"productivity": 0,
"energy": 0,
"mood": 0,
"sleep_quality": 0,
"exercise_intensity": 0
})
return [
metrics["productivity"],
metrics["energy"],
metrics["mood"],
metrics["sleep_quality"],
metrics["exercise_intensity"]
]
def load_day_details(evt: gr.SelectData):
"""Load detailed view of a specific day"""
try:
# Get clicked date (remove the day of week if present)
date = evt.value[0].split(" (")[0] if isinstance(evt.value, list) else evt.value
data = load_daily_data(date)
# Ensure required data structures exist with defaults
if "focus" not in data:
data["focus"] = {
"priorities": [],
"later": [],
"priority_reward": "",
"later_reward": ""
}
if "meals" not in data:
data["meals"] = {
"breakfast": "",
"lunch": "",
"dinner": "",
"snacks": ""
}
# Ensure focus lists exist and are properly formatted
if not isinstance(data["focus"].get("priorities", []), list):
data["focus"]["priorities"] = []
if not isinstance(data["focus"].get("later", []), list):
data["focus"]["later"] = []
# Format metrics data
metrics_data = [
["Productivity", data.get("tracking_metrics", {}).get("productivity", 0)],
["Energy", data.get("tracking_metrics", {}).get("energy", 0)],
["Mood", data.get("tracking_metrics", {}).get("mood", 0)],
["Sleep Quality", data.get("tracking_metrics", {}).get("sleep_quality", 0)],
["Exercise Intensity", data.get("tracking_metrics", {}).get("exercise_intensity", 0)]
]
# Format habits data with proper validation
habits_data = []
habits_dict = data.get("habits", {})
# Load current habits configuration to ensure we show all configured habits
current_habits = load_habits()
# Create a row for each habit, using stored data if available or default values if not
for habit in current_habits:
status = habits_dict.get(habit, [False] * 7)
# Ensure status is a list of 7 boolean values
if not isinstance(status, list) or len(status) != 7:
status = [False] * 7
row = [habit]
row.extend(["✓" if done else "×" for done in status])
habits_data.append(row)
# Sort habits by category (morning, evening, flexible)
def get_habit_category(habit):
if any(x in habit.lower() for x in ["wake", "morning", "meditation", "brain", "walk"]):
return 0 # Morning
elif any(x in habit.lower() for x in ["evening", "massage", "learning", "journal", "guitar"]):
return 1 # Evening
return 2 # Flexible
habits_data.sort(key=lambda x: get_habit_category(x[0]))
# Format journal data with validation
journal_data = []
for q, a in data.get("journal", {}).items():
if isinstance(a, str):
if a.strip():
journal_data.append([q, a])
# Format focus and meals data with proper validation
priorities_text = "\n".join([
f"- {task[0]}: {task[1]}" if isinstance(task, list) and len(task) >= 2 else "- No task"
for task in data["focus"]["priorities"]
if isinstance(task, list) and len(task) >= 2 and task[0]
]) or "No priorities set"
later_text = "\n".join([
f"- {task[0]}: {task[1]}" if isinstance(task, list) and len(task) >= 2 else "- No task"
for task in data["focus"]["later"]
if isinstance(task, list) and len(task) >= 2 and task[0]
]) or "No tasks set"
focus_meals = f"""### 🎯 Focus Tasks
**Must Do Today:**
{priorities_text}
**For Later:**
{later_text}
### 🍽️ Meals
- **Breakfast:** {data["meals"].get("breakfast", "") or "Not recorded"}
- **Lunch:** {data["meals"].get("lunch", "") or "Not recorded"}
- **Dinner:** {data["meals"].get("dinner", "") or "Not recorded"}
- **Snacks:** {data["meals"].get("snacks", "") or "Not recorded"}
"""
return [
date, # Selected date
metrics_data, # Metrics view
habits_data, # Habits view
journal_data, # Journal view
focus_meals # Focus and meals view
]
except Exception as e:
print(f"Error loading details for date {date if 'date' in locals() else 'unknown'}: {str(e)}")
# Return a graceful fallback with empty/default values
return [
evt.value,
[["No metrics data available", 0]],
[["No habits data available", "×", "×", "×", "×", "×", "×", "×"]],
[["No journal entries available", ""]],
"""### 🎯 Focus Tasks\n\n**Must Do Today:**\nNo data available\n\n**For Later:**\nNo data available\n\n### 🍽️ Meals\nNo meal data available"""
]
def manual_save():
"""Manually save all current data"""
try:
current_data = load_daily_data()
save_daily_data(current_data)
return "✅ Data saved successfully!"
except Exception as e:
print(f"Error saving data: {e}")
return "❌ Error saving data"
def clean_json_file(file_path):
"""Clean up potentially corrupted JSON file"""
try:
with open(file_path, 'r') as f:
content = f.read().strip()
# Try to find the last valid JSON structure
try:
# First try to parse as-is
data = json.loads(content)
return data
except json.JSONDecodeError:
# If that fails, try to clean up the content
# Find the last closing brace
last_brace = content.rfind('}')
if last_brace != -1:
content = content[:last_brace + 1]
try:
data = json.loads(content)
# Save the cleaned data back to file
with open(file_path, 'w') as f:
json.dump(data, f, indent=2)
return data
except json.JSONDecodeError:
pass
# If all cleanup attempts fail, create new data
data = create_empty_daily_data()
with open(file_path, 'w') as f:
json.dump(data, f, indent=2)
return data
except Exception as e:
print(f"Error cleaning JSON file {file_path}: {e}")
return create_empty_daily_data()
with gr.Blocks() as demo:
# Load initial data
current_data = load_daily_data()
current_data = check_and_refresh_day(current_data)
# Centered, smaller logo
with gr.Row():
with gr.Column(scale=2):
pass # Empty column for spacing
with gr.Column(scale=1):
gr.Image("./logo.png", show_label=False, container=False, width=250, show_download_button=False, )
with gr.Column(scale=2):
pass # Empty column for spacing
with gr.Row():
date_text = gr.Textbox(
value=datetime.datetime.now().strftime("%A, %B %d"),
label="Date",
interactive=False
)
date_picker = gr.Dropdown(
choices=get_available_dates(),
value=get_date_key(),
label="Select Date",
interactive=True
)
today_btn = gr.Button("Return to Today")
refresh_dates_btn = gr.Button("🔄 Refresh Dates")
save_btn = gr.Button("💾 Save Data", variant="primary")
save_status = gr.Markdown(visible=True)
# Connect save button event
save_btn.click(
fn=manual_save,
outputs=save_status
).then(
lambda: gr.update(visible=True),
None,
save_status
)
# Create state for all components that need updating
with gr.Tabs():
# Must Do Daily Tab
with gr.TabItem("Must Do Daily"):
create_habit_section()
# Today's Focus Tab
with gr.TabItem("Today's Focus"):
with gr.Column():
gr.Markdown("### Today's Focus")
with gr.Row():
# Left column for priorities
with gr.Column(scale=2):
gr.Markdown("#### Must Do Today")
priorities = gr.Dataframe(
headers=["Task", "Status"],
datatype=["str", "str"],
value=current_data["focus"]["priorities"],
row_count=5, # Fixed number of rows
col_count=(2, "fixed"), # Fixed number of columns
interactive=True
)
priority_reward = gr.Textbox(
label="Reward for Completion",
value=current_data["focus"]["priority_reward"],
placeholder="Enter reward for completing priorities",
lines=2
)
# Right column for later tasks
with gr.Column(scale=2):
gr.Markdown("#### For Later")
later = gr.Dataframe(
headers=["Task", "Status"],
datatype=["str", "str"],
value=current_data["focus"]["later"],
row_count=5, # Fixed number of rows
col_count=(2, "fixed"), # Fixed number of columns
interactive=True
)
later_reward = gr.Textbox(
label="Reward for Completion",
value=current_data["focus"]["later_reward"],
placeholder="Enter reward for completing later tasks",
lines=2
)
# Event handlers
priorities.change(
lambda x: update_data("focus.priorities", x),
inputs=[priorities]
)
priority_reward.change(
lambda x: update_data("focus.priority_reward", x),
inputs=[priority_reward]
)
later.change(
lambda x: update_data("focus.later", x),
inputs=[later]
)
later_reward.change(
lambda x: update_data("focus.later_reward", x),
inputs=[later_reward]
)
# Meals Tab
with gr.TabItem("Meals"):
with gr.Column():
meal_inputs = {}
for meal in ["breakfast", "lunch", "dinner", "snacks"]:
meal_inputs[meal] = gr.Textbox(
label=meal.capitalize(),
value=current_data["meals"][meal],
placeholder=f"What did you have for {meal}?"
)
meal_inputs[meal].change(
lambda x, m=meal: update_data(f"meals.{m}", x),
inputs=[meal_inputs[meal]]
)
# Life Overview Tab
with gr.TabItem("Life Overview"):
with gr.Column():
gr.Markdown("""
### 🌟 Your Life Journey Calculator
Time is our most precious resource - not because it's limited, but because it's an opportunity for endless possibilities.
Let's explore your unique journey through time and discover the incredible potential that lies ahead.
""")
# Load saved config
user_config = load_user_config()
with gr.Row():
birth_date = gr.Textbox(
label="Your Birth Date (YYYY-MM-DD)",
value=user_config["birth_date"],
placeholder="YYYY-MM-DD"
)
birth_time = gr.Textbox(
label="Your Birth Time",
value=user_config["birth_time"],
placeholder="HH:MM (24-hour) or HH:MM AM/PM"
)
calculate_btn = gr.Button("✨ Calculate Your Life Journey", variant="primary")
# Add status message
status_msg = gr.Markdown()
with gr.Tabs():
with gr.TabItem("Life Stats"):
with gr.Row():
current_age_md = gr.Markdown()
time_remaining_md = gr.Markdown()
with gr.Row():
progress_md = gr.Markdown()
milestones_md = gr.Markdown()
with gr.TabItem("Visualizations"):
with gr.Row():
progress_plot = gr.Plot(label="Life Progress")
remaining_plot = gr.Plot(label="Time Until 90")
timeline_plot = gr.Plot(label="Life Seasons Timeline")
# Update the calculate button click handler
def update_stats_and_plots(birth_date_str, birth_time_str):
try:
# Save the values
if save_user_config(birth_date_str, birth_time_str):
stats = calculate_age_stats(birth_date_str, birth_time_str)
if "Error" in stats:
return [
f"⚠️ {stats['Error']}", "", "", "", None, None, None
]
figures = create_life_visualizations(stats)
current_age, time_remaining, progress, milestones = create_stats_display(stats)
return [
current_age,
time_remaining,
progress,
milestones,
figures["progress"],
figures["remaining"],
figures["timeline"]
]
else:
return ["⚠️ Failed to save configuration", "", "", "", None, None, None]
except Exception as e:
return [f"⚠️ Error: {str(e)}", "", "", "", None, None, None]
calculate_btn.click(
fn=update_stats_and_plots,
inputs=[birth_date, birth_time],
outputs=[
current_age_md,
time_remaining_md,
progress_md,
milestones_md,
progress_plot,
remaining_plot,
timeline_plot
]
)
# Progress Tracking Tab
with gr.TabItem("Progress Tracking"):
with gr.Column():
gr.Markdown("### Daily Metrics")
with gr.Row():
# Load data for the selected date
selected_data = load_daily_data(date_picker.value)
if "tracking_metrics" not in selected_data:
selected_data["tracking_metrics"] = {
"productivity": 0,
"energy": 0,
"mood": 0,
"sleep_quality": 0,
"exercise_intensity": 0
}
productivity = gr.Slider(minimum=0, maximum=5, value=selected_data["tracking_metrics"]["productivity"], label="Productivity", step=1)
energy = gr.Slider(minimum=0, maximum=5, value=selected_data["tracking_metrics"]["energy"], label="Energy Level", step=1)
mood = gr.Slider(minimum=0, maximum=5, value=selected_data["tracking_metrics"]["mood"], label="Mood", step=1)
sleep = gr.Slider(minimum=0, maximum=5, value=selected_data["tracking_metrics"]["sleep_quality"], label="Sleep Quality", step=1)
exercise = gr.Slider(minimum=0, maximum=5, value=selected_data["tracking_metrics"]["exercise_intensity"], label="Exercise Intensity", step=1)
gr.Markdown("### Weekly Overview")
week_data = load_week_data()
week_dates = get_week_dates()
weekly_grid = gr.DataFrame(
headers=["Metric"] + [datetime.datetime.strptime(date, "%Y-%m-%d").strftime("%a %d") for date in week_dates],
value=[
["Productivity"] + [week_data[date]["tracking_metrics"]["productivity"] for date in week_dates],
["Energy"] + [week_data[date]["tracking_metrics"]["energy"] for date in week_dates],
["Mood"] + [week_data[date]["tracking_metrics"]["mood"] for date in week_dates],
["Sleep"] + [week_data[date]["tracking_metrics"]["sleep_quality"] for date in week_dates],
["Exercise"] + [week_data[date]["tracking_metrics"]["exercise_intensity"] for date in week_dates]
],
interactive=False
)
gr.Markdown("### Monthly Stats")
month_data = load_month_data()
with gr.Row():
prod_label = gr.Label(f"Average Productivity: {calculate_success_rate(month_data, 'productivity')}/10")
energy_label = gr.Label(f"Average Energy: {calculate_success_rate(month_data, 'energy')}/10")
mood_label = gr.Label(f"Average Mood: {calculate_success_rate(month_data, 'mood')}/10")
sleep_label = gr.Label(f"Average Sleep: {calculate_success_rate(month_data, 'sleep_quality')}/10")
exercise_label = gr.Label(f"Average Exercise: {calculate_success_rate(month_data, 'exercise_intensity')}/10")
# Update tracking metrics and connect to UI elements
for slider in [productivity, energy, mood, sleep, exercise]:
slider.change(
fn=update_metrics,
inputs=[productivity, energy, mood, sleep, exercise, date_picker],
outputs=[
weekly_grid,
prod_label,
energy_label,
mood_label,
sleep_label,
exercise_label
]
)
# Journaling Tab
with gr.TabItem("Daily Journal"):
with gr.Column():
gr.Markdown("""
### 📝 Daily Reflection Journal
Take a moment to reflect on your day. These questions will help you process your experiences,
learn from them, and plan for tomorrow. Your responses are saved automatically.
""")
# Create journal entries
journal_inputs = {}
current_journal = current_data.get("journal", {})
for question in JOURNAL_QUESTIONS:
with gr.Group():
gr.Markdown(f"#### {question}")
journal_inputs[question] = gr.TextArea(
value=current_journal.get(question, ""),
placeholder="Write your thoughts here...",
lines=3,
label=""
)
# Add change handler for each text area
journal_inputs[question].change(
fn=update_journal_entry,
inputs=[
gr.State(question),
journal_inputs[question]
]
)
# Add export button
def export_journal():
current_data = load_daily_data()
if "journal" in current_data:
date = get_date_key()
export_text = f"Journal Entry for {date}\n\n"
for question in JOURNAL_QUESTIONS:
answer = current_data["journal"].get(question, "")
if answer: # Only include questions with answers
export_text += f"Q: {question}\n"
export_text += f"A: {answer}\n\n"
return export_text
return "No journal entries found for today."
with gr.Row():
export_btn = gr.Button("Export Journal Entry")
export_text = gr.TextArea(
label="Exported Journal",
interactive=False,
visible=False
)
export_btn.click(
fn=export_journal,
outputs=export_text,
show_progress=True
).then(
lambda: gr.update(visible=True),
None,
[export_text]
)
# History Tab
with gr.TabItem("History"):
with gr.Column():
gr.Markdown("### 📚 History Viewer")
# Create the history table
history_headers = [
"Date",
"Productivity",
"Energy",
"Mood",
"Sleep",
"Exercise",
"Habits",
"Journal"
]
with gr.Row():
history_table = gr.DataFrame(
headers=history_headers,
datatype=["str", "number", "number", "number", "number", "number", "str", "number"],
value=load_history_data(),
interactive=False
)
# Create detail view sections
with gr.Row():
selected_date = gr.Textbox(label="Selected Date", interactive=False)
refresh_btn = gr.Button("🔄 Refresh History")
with gr.Tabs() as detail_tabs:
with gr.TabItem("Metrics"):
metrics_view = gr.DataFrame(
headers=["Metric", "Value"],
datatype=["str", "number"],
interactive=False
)
with gr.TabItem("Habits"):
gr.Markdown("### Daily Habits Tracking")
habits_view = gr.DataFrame(
headers=["Habit", "M", "T", "W", "Th", "F", "S", "Su"],
datatype=["str", "str", "str", "str", "str", "str", "str", "str"],
interactive=False,
value=[[habit] + ["×"] * 7 for habit in load_habits()] # Initialize with default values
)
with gr.TabItem("Journal"):
journal_view = gr.DataFrame(
headers=["Question", "Response"],
datatype=["str", "str"],
interactive=False
)
with gr.TabItem("Focus & Meals"):
focus_meals_md = gr.Markdown()
# Connect event handlers
history_table.select(
fn=load_day_details,
outputs=[
selected_date,
metrics_view,
habits_view,
journal_view,
focus_meals_md
]
)
refresh_btn.click(
fn=load_history_data,
outputs=[history_table]
)
# Documentation Tab
with gr.TabItem("Documentation"):
with gr.Column():
gr.Markdown("""
# Potential Made Simple System Documentation
## Overview
Welcome to your Life Tracking System, inspired by Rob Dyrdek's "Rhythm of Existence" philosophy. This comprehensive app helps you monitor and optimize various aspects of your life, creating a harmonious balance between work, health, personal life, and sleep.
## Philosophy
The "Rhythm of Existence" philosophy, pioneered by entrepreneur Rob Dyrdek, emphasizes the importance of creating intentional, balanced routines that maximize both productivity and life satisfaction. Key principles include:
- **Intentional Living**: Every day is an opportunity to make progress towards your goals
- **Balance**: Maintaining equilibrium between work, health, relationships, and personal growth
- **Consistency**: Building sustainable habits that compound over time
- **Measurement**: What gets measured gets improved
- **Reflection**: Regular review and adjustment of life patterns
## Features
### 1. Must Do Daily
- Track daily habits and routines
- Organize tasks into morning, evening, and flexible time slots
- Monitor weekly progress and completion rates
- Set custom durations for time-based activities
### 2. Today's Focus
- Prioritize tasks with "Must Do Today" and "For Later" lists
- Set rewards for completing priority tasks
- Track task status and progress
- Maintain clarity on daily objectives
### 3. Meals
- Log daily meals and snacks
- Monitor eating patterns
- Track nutritional consistency
### 4. Life Overview
- Calculate and visualize your life journey
- Track progress through different life seasons
- Set and monitor life milestones
- Understand time allocation and remaining potential
### 5. Progress Tracking
- Monitor daily metrics:
- Productivity (0-5)
- Energy Level (0-5)
- Mood (0-5)
- Sleep Quality (0-5)
- Exercise Intensity (0-5)
- View weekly and monthly trends
- Track success rates and improvements
### 6. Daily Journal
- Reflect on daily experiences
- Answer guided questions for deeper insight
- Export journal entries for review
- Build self-awareness through consistent reflection
### 7. History
- Review past data and trends
- Analyze patterns in habits and metrics
- Track long-term progress
- Learn from historical patterns
## Best Practices
1. **Morning Routine**
- Start with mindfulness and exercise
- Review daily priorities
- Set intentions for the day
2. **Throughout the Day**
- Update task status regularly
- Log meals as they happen
- Track metrics while they're fresh
3. **Evening Routine**
- Complete journal entries
- Review task completion
- Plan for tomorrow
4. **Weekly Review**
- Analyze progress trends
- Adjust habits as needed
- Set new goals and rewards
## Tips for Success
1. **Start Small**
- Begin with a few key habits
- Gradually add more as you build consistency
- Focus on progress, not perfection
2. **Be Consistent**
- Log data daily
- Complete journal entries regularly
- Track metrics consistently
3. **Review and Adjust**
- Use the History tab to spot patterns
- Adjust goals based on progress
- Celebrate improvements
4. **Stay Motivated**
- Set meaningful rewards
- Track progress visually
- Share achievements with others
## Technical Notes
- Data is saved automatically
- Manual save option available
- Export functionality for journal entries
- Daily refresh at midnight
- Ability to view and edit past dates
## Support and Feedback
This is a free tool designed to help you optimize your life and create your own perfect rhythm of existence. As you use the app, remember that the goal is progress, not perfection. Every small improvement compounds over time to create significant life changes.
For support or to share feedback, please visit the project's repository or contact the development team.
Happy tracking! 🌟
""")
# Date selection handlers
def load_selected_date(date):
try:
# Validate date format
datetime.datetime.strptime(date, "%Y-%m-%d")
data = load_daily_data(date)
# Update display date
display_date = datetime.datetime.strptime(date, "%Y-%m-%d").strftime("%A, %B %d")
# Update journal entries if they exist
journal_updates = []
for question in JOURNAL_QUESTIONS:
journal_updates.append(data.get("journal", {}).get(question, ""))
return [display_date] + journal_updates
except ValueError:
return [date_text.value] + ["" for _ in JOURNAL_QUESTIONS]
def return_to_today():
today = get_date_key()
date_picker.value = today
return [today, datetime.datetime.now().strftime("%A, %B %d")]
# Connect date selection events
date_picker.change(
fn=load_selected_date,
inputs=[date_picker],
outputs=[date_text] + list(journal_inputs.values())
)
today_btn.click(
fn=return_to_today,
outputs=[date_picker, date_text]
)
# Auto-refresh every minute
def auto_refresh():
"""Auto refresh function to check and refresh day data"""
try:
current_data = load_daily_data()
current_data = check_and_refresh_day(current_data)
save_daily_data(current_data)
except Exception as e:
print(f"Error in auto refresh: {e}")
demo.load(fn=auto_refresh) # No outputs needed
demo.queue()
# Connect the date selection events
date_picker.change(
fn=load_selected_date_metrics,
inputs=[date_picker],
outputs=[productivity, energy, mood, sleep, exercise]
)
refresh_dates_btn.click(
fn=refresh_dates,
outputs=[date_picker]
)
demo.launch()