Update task_operations.py

task_operations.py

@@ -1,63 +1,72 @@
-import streamlit as st
+# components/task_operations.py
+
 import pandas as pd
-from datetime import datetime, time, timedelta
-import pytz
+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):
-        self.utc_timezone = pytz.utc
-        self.local_timezone = pytz.timezone('Asia/Dhaka')  # GMT+6 for your timezone
         if 'tasks' not in st.session_state:
             st.session_state.tasks = self.load_tasks()
 
     def load_tasks(self):
-        # Assuming tasks are stored as a list of dictionaries
-        tasks = st.session_state.get('tasks', [])
-        if not tasks:
-            return pd.DataFrame()
-        
-        df = pd.DataFrame(tasks)
-        df['Task Time'] = pd.to_datetime(df['Task Time'])
+        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 []
 
-        # Convert timezone if the timestamps are already timezone-aware
-        df['Task Time'] = df['Task Time'].dt.tz_convert(self.local_timezone)
-        
-        return df
+    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).replace(tzinfo=self.local_timezone)
-        task_duration = timedelta(hours=task_duration_hours, minutes=task_duration_minutes)
-        task = {
-            'Task Name': task_name,
-            'Task Time': task_time_full,
-            'Task Duration (hours)': task_duration_hours,
-            'Task Duration (minutes)': task_duration_minutes,
-            'Task Category': 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)
+        st.session_state.tasks.append(task_entry)
         self.save_tasks(st.session_state.tasks)
 
-    def save_tasks(self, tasks):
-        st.session_state.tasks = 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()
-        
-        df['Task Time'] = pd.to_datetime(df['Task Time']).dt.tz_convert(self.local_timezone)
-        df['Total Duration'] = df['Task Duration (hours)'] + df['Task Duration (minutes)'] / 60.0
+            return pd.DataFrame()  # Return empty DataFrame if no tasks are present
         
-        # Filter based on the timeframe
-        today = datetime.now(self.local_timezone).date()
+        # Ensure the 'Task Time' is in datetime format
+        df['Task Time'] = pd.to_datetime(df['Task Time'])
+
         if timeframe == 'daily':
-            df = df[df['Task Time'].dt.date == today]
+            report = df[df['Task Time'].dt.date == pd.Timestamp.today().date()]
         elif timeframe == 'weekly':
-            start_of_week = today - timedelta(days=today.weekday())
-            df = df[(df['Task Time'].dt.date >= start_of_week) & (df['Task Time'].dt.date <= today)]
+            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':
-            df = df[df['Task Time'].dt.month == today.month]
+            report = df[df['Task Time'].dt.month == pd.Timestamp.today().month]
         elif timeframe == 'yearly':
-            df = df[df['Task Time'].dt.year == today.year]
-        
-        return df
+            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