Update task_operations.py

task_operations.py

@@ -1,84 +1,28 @@
-# components/task_operations.py
-
-import pandas as pd
-import os
-from datetime import datetime, time
-import streamlit as st
-import pytz
-
 class TaskManager:
-    TASKS_FILE = "tasks.csv"
-    CATEGORIES = ['Learning', 'Gym', 'Personal', 'Family', 'Work', 'Prayer']
-
     def __init__(self):
-        # Initialize the timezones properly
-        self.local_timezone = pytz.timezone('Etc/GMT-6')  # Adjusted for GMT+6 time zone
-        self.utc_timezone = pytz.utc  # UTC timezone
-
-        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:
-                tasks = pd.read_csv(self.TASKS_FILE, parse_dates=['Task Time']).to_dict(orient='records')
-                # Convert stored UTC times to local time
-                for task in tasks:
-                    task['Task Time'] = pd.Timestamp(task['Task Time']).tz_localize(self.utc_timezone).tz_convert(self.local_timezone)
-                return tasks
-            else:
-                return []
+        # Initialization code (e.g., setting up local time zones and loading tasks)
+
+    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 'Task Time' is already timezone-aware and convert it to local time for the report
+        df['Task Time'] = pd.to_datetime(df['Task Time']).apply(lambda x: x.tz_convert(self.local_timezone))
+
+        today = pd.Timestamp.now(tz=self.local_timezone).date()
+
+        if timeframe == 'daily':
+            report = df[df['Task Time'].dt.date == today]
+        elif timeframe == 'weekly':
+            week_start = pd.Timestamp.now(tz=self.local_timezone) - pd.DateOffset(days=pd.Timestamp.now(tz=self.local_timezone).dayofweek)
+            report = df[(df['Task Time'] >= week_start) & (df['Task Time'] < pd.Timestamp.now(tz=self.local_timezone) + pd.DateOffset(days=1))]
+        elif timeframe == 'monthly':
+            report = df[df['Task Time'].dt.month == pd.Timestamp.now(tz=self.local_timezone).month]
+        elif timeframe == 'yearly':
+            report = df[df['Task Time'].dt.year == pd.Timestamp.now(tz=self.local_timezone).year]
         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):
-        # Convert local time back to UTC for saving
-        tasks_copy = []
-        for task in tasks:
-            task_copy = task.copy()
-            task_copy['Task Time'] = task_copy['Task Time'].astimezone(self.utc_timezone)
-            tasks_copy.append(task_copy)
-
-        df = pd.DataFrame(tasks_copy)
-        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)
-        # Localize to your local timezone and then convert to UTC for consistency
-        task_time_full = self.local_timezone.localize(task_time_full).astimezone(self.utc_timezone)
-        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 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 'Task Time' is already timezone-aware and convert it to local time for the report
-    df['Task Time'] = pd.to_datetime(df['Task Time']).apply(lambda x: x.tz_convert(self.local_timezone))
-
-    today = pd.Timestamp.now(tz=self.local_timezone).date()
-
-    if timeframe == 'daily':
-        report = df[df['Task Time'].dt.date == today]
-    elif timeframe == 'weekly':
-        week_start = pd.Timestamp.now(tz=self.local_timezone) - pd.DateOffset(days=pd.Timestamp.now(tz=self.local_timezone).dayofweek)
-        report = df[(df['Task Time'] >= week_start) & (df['Task Time'] < pd.Timestamp.now(tz=self.local_timezone) + pd.DateOffset(days=1))]
-    elif timeframe == 'monthly':
-        report = df[df['Task Time'].dt.month == pd.Timestamp.now(tz=self.local_timezone).month]
-    elif timeframe == 'yearly':
-        report = df[df['Task Time'].dt.year == pd.Timestamp.now(tz=self.local_timezone).year]
-    else:
-        report = pd.DataFrame()  # Empty DataFrame for unsupported timeframes
+            report = pd.DataFrame()  # Empty DataFrame for unsupported timeframes
 
-    report['Total Duration'] = report['Task Duration (hours)'] + report['Task Duration (minutes)'] / 60.0
-    return report
+        report['Total Duration'] = report['Task Duration (hours)'] + report['Task Duration (minutes)'] / 60.0
+        return report