Update app.py

app.py

@@ -1,38 +1,89 @@
 import streamlit as st
 import pandas as pd
-from datetime import datetime
-import random
+from collections import defaultdict
+import plotly.express as px
 
-# Upload spreadsheet
-st.title("Duty Roster Generator")
-uploaded_file = st.file_uploader("Upload your spreadsheet", type=["csv", "xlsx"])
+# Title and file upload
+st.title("Enhanced Duty Roster Generator with Role-Specific Assignments")
+uploaded_file = st.file_uploader("Upload your availability spreadsheet with roles", type=["csv", "xlsx"])
+
+# Multi-shift configuration
+shifts = st.multiselect("Select shifts for each day", ["Morning", "Afternoon", "Night"], ["Morning", "Afternoon"])
+shift_requirements = {shift: st.number_input(f"Personnel required for {shift} shift", min_value=1, value=1) for shift in shifts}
 
 if uploaded_file:
-    # Load the data
+    # Load the file
     if uploaded_file.name.endswith('.csv'):
         df = pd.read_csv(uploaded_file)
     else:
         df = pd.read_excel(uploaded_file)
 
-    # Display uploaded data
-    st.write("Personnel Availability Data:")
+    # Display data and allow user to confirm roles
+    st.write("Personnel Availability and Roles Data:")
     st.dataframe(df)
 
-    # Input for user-specific conditions or preferences
-    user_prompt = st.text_input("Enter specific roster requirements (e.g., preferred shifts, coverage needs)")
-
-    # Generate duty roster (basic example)
-    def generate_roster(data, prompt):
-        # Dummy logic to assign random available days based on constraints
-        roster = {}
-        for _, row in data.iterrows():
-            name = row['Name']
-            unavailable_days = row['Unavailable Days'].split(',')
-            available_days = [day for day in range(1, 31) if str(day) not in unavailable_days]
-            roster[name] = random.choice(available_days) if available_days else "No Available Days"
+    # Generate duty roster with roles
+    def generate_duty_roster_with_roles(data, shifts, shift_reqs):
+        roster = defaultdict(lambda: defaultdict(list))
+
+        for day in range(1, 31):  # Example with 30 days
+            for shift in shifts:
+                role_counts = defaultdict(int)
+                assigned_today = 0
+
+                for _, row in data.iterrows():
+                    name = row['Name']
+                    role = row['Role']
+                    unavailable_days = set(map(int, row['Unavailable Days'].split(',')))
+
+                    if day not in unavailable_days and role_counts[role] < shift_reqs[shift]:
+                        roster[day][shift].append((name, role))
+                        role_counts[role] += 1
+                        assigned_today += 1
+
+                    if assigned_today == shift_reqs[shift]:
+                        break
+
+                # If unable to meet required personnel, mark as unassigned
+                if assigned_today < shift_reqs[shift]:
+                    roster[day][shift].append(("Unassigned", "N/A"))
+
         return roster
 
-    # Display roster
-    roster = generate_roster(df, user_prompt)
-    st.write("Generated Duty Roster:")
-    st.write(roster)
+    # Generate and display the duty roster
+    duty_roster = generate_duty_roster_with_roles(df, shifts, shift_requirements)
+
+    # Display the roster with roles and shifts
+    st.write("Generated Duty Roster with Roles:")
+    for day, shifts in duty_roster.items():
+        st.write(f"Day {day}:")
+        for shift, personnel in shifts.items():
+            st.write(f"{shift} Shift: {', '.join([f'{p[0]} ({p[1]})' for p in personnel])}")
+
+    # Interactive Calendar Visualization
+    flattened_data = []
+    for day, shifts in duty_roster.items():
+        for shift, personnel in shifts.items():
+            for name, role in personnel:
+                flattened_data.append({"Day": day, "Shift": shift, "Personnel": name, "Role": role})
+
+    df_roster = pd.DataFrame(flattened_data)
+    fig = px.timeline(df_roster, x_start="Day", x_end="Day", y="Personnel", color="Shift", title="Duty Roster Calendar View")
+    st.plotly_chart(fig)
+
+    # Downloadable individual schedules
+    st.write("Download Individual Schedules:")
+    for person in df['Name'].unique():
+        person_schedule = df_roster[df_roster['Personnel'] == person]
+        person_csv = person_schedule.to_csv(index=False).encode('utf-8')
+        st.download_button(f"Download Schedule for {person}", data=person_csv, file_name=f"{person}_schedule.csv", mime="text/csv")
+
+    # Scheduling Insights and Analytics
+    st.write("Scheduling Insights:")
+    personnel_counts = df_roster.groupby("Personnel").size()
+    st.bar_chart(personnel_counts)
+    st.write(f"Total shifts assigned per person: {personnel_counts.to_dict()}")
+
+    st.write("Days with unassigned shifts:")
+    unassigned_days = df_roster[df_roster['Personnel'] == "Unassigned"]
+    st.write(unassigned_days[['Day', 'Shift']].drop_duplicates())