jdt / task_operations.py
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# components/task_operations.py
import pandas as pd
import os
from datetime import datetime
import streamlit as st
class TaskManager:
TASKS_FILE = "tasks.csv"
CATEGORIES = ['Learning', 'Gym', 'Personal', 'Family', 'Work', 'Prayer']
def __init__(self):
if 'tasks' not in st.session_state:
st.session_state.tasks = self.load_tasks()
def load_tasks(self):
if os.path.exists(self.TASKS_FILE):
if os.path.getsize(self.TASKS_FILE) > 0:
return pd.read_csv(self.TASKS_FILE, parse_dates=['Task Time']).to_dict(orient='records')
else:
return []
else:
df = pd.DataFrame(columns=["Task Name", "Task Time", "Task Duration (hours)", "Task Duration (minutes)", "Category"])
df.to_csv(self.TASKS_FILE, index=False)
return []
def save_tasks(self, tasks):
df = pd.DataFrame(tasks)
df.to_csv(self.TASKS_FILE, index=False)
def add_task(self, task_name, task_time, task_duration_hours, task_duration_minutes, task_category):
task_time_full = datetime.combine(datetime.today(), task_time)
task_entry = {
"Task Name": task_name,
"Task Time": task_time_full,
"Task Duration (hours)": int(task_duration_hours),
"Task Duration (minutes)": int(task_duration_minutes),
"Category": task_category
}
st.session_state.tasks.append(task_entry)
self.save_tasks(st.session_state.tasks)
def delete_task_by_name(self, task_name):
for index, task in enumerate(st.session_state.tasks):
if task['Task Name'] == task_name:
st.session_state.tasks.pop(index)
self.save_tasks(st.session_state.tasks)
return True
return False
def generate_report(self, timeframe):
df = pd.DataFrame(st.session_state.tasks)
if df.empty:
return pd.DataFrame() # Return empty DataFrame if no tasks are present
# Ensure the 'Task Time' is in datetime format
df['Task Time'] = pd.to_datetime(df['Task Time'])
if timeframe == 'daily':
report = df[df['Task Time'].dt.date == pd.Timestamp.today().date()]
elif timeframe == 'weekly':
week_start = pd.Timestamp.today() - pd.DateOffset(days=pd.Timestamp.today().dayofweek)
report = df[(df['Task Time'] >= week_start) & (df['Task Time'] < pd.Timestamp.today() + pd.DateOffset(days=1))]
elif timeframe == 'monthly':
report = df[df['Task Time'].dt.month == pd.Timestamp.today().month]
elif timeframe == 'yearly':
report = df[df['Task Time'].dt.year == pd.Timestamp.today().year]
else:
report = pd.DataFrame() # Empty DataFrame for unsupported timeframes
report['Total Duration'] = report['Task Duration (hours)'] + report['Task Duration (minutes)'] / 60.0
return report