import os
from notion_client import Client
from dotenv import load_dotenv
from datetime import datetime
import matplotlib.pyplot as plt
import pandas as pd
from datetime import timedelta
import mplcyberpunk

load_dotenv()

notion = Client(auth=os.getenv("NOTION_TOKEN"))

# Replace this URL with the URL of your database
database_id = os.getenv("DATABASE_ID")

# Use the databases.query endpoint
response = notion.databases.query(database_id)

#print(response["results"])

data = [(page["properties"]["Date"]["date"]["start"], page["properties"]["Progress"]["formula"]["number"]) for page in response["results"]]

# Sort data by date
data.sort(key=lambda x: datetime.strptime(x[0], "%Y-%m-%d"))

# Separate dates and progress into two lists
dates, progress = zip(*data)

# Create a DataFrame
df = pd.DataFrame({"date": dates, "progress": progress})

# Convert the dates to a datetime format
df["date"] = pd.to_datetime(df["date"])

# Filter to include only the last 7 days
start_date = df["date"].max() - timedelta(days=6)
df_last_7_days = df[df["date"] >= start_date].copy() 
# Aggregate by day and take the mean
df_last_7_days = df_last_7_days.groupby(df_last_7_days["date"].dt.date).mean().reset_index()

# Convert the date column to the names of the day of the week
df_last_7_days["day_of_week"] = pd.to_datetime(df_last_7_days["date"]).dt.day_name()

# Set figure size
fig = plt.figure(figsize=(12, 6)) 
plt.style.use("cyberpunk")
# Plot progress data for last 7 days using matplotlib
colors = ["#7c3aed"]
bars = plt.bar(df_last_7_days["day_of_week"], df_last_7_days["progress"],color=colors, zorder=2)

mplcyberpunk.add_bar_gradient(bars=bars)

plt.ylabel('Habits')
plt.tight_layout()  # Adjust layout for better visibility
plt.show()