import telegram_send
from sqlalchemy import create_engine, text
import pandas as pd
import datetime as dt
import matplotlib.pyplot as plt

# Get the relevant data
engine = create_engine('sqlite:///history/data.sqlite')
query = 'SELECT * FROM messages'
data = pd.read_sql_query(sql=text(query), con=engine.connect())

data = data[data['content']=='Coffee']
grand_total = len(data)

data['datetime'] = pd.to_datetime(data['date'])

# Calculate weekdays and hours
data['weekday'] = data['datetime'].dt.dayofweek
data['hour'] = data['datetime'].dt.hour
data['day'] = data['datetime'].dt.day
lastmonth = (dt.datetime.now().month - 1) % 12
monthly = data[data['datetime'].dt.month == lastmonth].copy()

# Make plots
monthly['weekday'].plot.hist(bins=7)
plt.savefig('files/monthly_weekdays.png')
plt.close()

monthly['hour'].plot.hist(bins=24)
plt.savefig('files/monthly_hour.png')
plt.close()

data['weekday'].plot.hist(bins=7)
plt.savefig('files/all_weekdays.png')
plt.close()

data['hour'].plot.hist(bins=24)
plt.savefig('files/all_hour.png')
plt.close()

# Calculate on which day the most coffee was made
monthly['count'] = 1
aggregated = monthly.groupby(['day']).count()['count']
message1 = 'Last month, coffee was made {amount} times.'.format(amount=len(monthly)) + ' Most coffee was made on day {day} of the month, with a total amount of {amount} times.'.format(day=aggregated.idxmax(),amount=aggregated.max()) + ' From the start of this chat, a grand total amount of {amount} times coffee was made.'.format(amount=grand_total)

telegram_send.send(messages=[message1])