Update timetable.py

timetable.py

@@ -1,56 +1,81 @@
 import pandas as pd
-from datetime import time
+import random
 
 DAYS = ["Monday", "Tuesday", "Wednesday", "Thursday", "Friday"]
+TIME_SLOTS = ["9:00-10:00", "10:00-11:00", "11:00-12:30", "12:30-1:30", "1:30-3:00"]
 
-def generate_time_slots():
-    slots = []
-    start_hour = 9.0
-    end_hour = 15.0
-
-    while start_hour < end_hour:
-        slots.append(start_hour)
-        start_hour += 1.5 if start_hour + 1.5 <= end_hour else 1.0
-
-    return slots
+def split_course_hours(courses_df):
+    """
+    Split total weekly hours into chunks of max 1.5 hours per day.
+    Returns a list of dicts with course, teacher, duration.
+    """
+    course_blocks = []
+    for _, row in courses_df.iterrows():
+        remaining = row['Hours']
+        while remaining > 0:
+            dur = 1.5 if remaining >= 1.5 else 1.0
+            course_blocks.append({
+                "Course": row['Course'],
+                "Teacher": row['Teacher'],
+                "Duration": dur
+            })
+            remaining -= dur
+    return course_blocks
 
 
 def generate_timetable(courses_path, rooms_path):
     courses = pd.read_csv(courses_path)
     rooms = pd.read_csv(rooms_path)["Room"].tolist()
 
-    slots = generate_time_slots()
-    timetable = []
+    course_blocks = split_course_hours(courses)
+
+    # Initialize timetable dictionary: one list per day
+    timetable = {day: [] for day in DAYS}
+    teacher_last_slot = {t: None for t in courses['Teacher'].unique()}
+
+    for day in DAYS:
+        available_slots = TIME_SLOTS.copy()
+        random.shuffle(course_blocks)  # Randomize to reduce conflicts
+        day_schedule = []
 
-    day_idx = 0
-    slot_idx = 0
-    room_idx = 0
+        i = 0
+        while i < len(course_blocks) and available_slots:
+            block = course_blocks[i]
+            teacher = block['Teacher']
 
-    for _, row in courses.iterrows():
-        remaining_hours = row["Hours"]
+            # Check teacher consecutive slot
+            if teacher_last_slot[teacher] == day and available_slots:
+                i += 1
+                continue
 
-        while remaining_hours > 0:
-            duration = 1.5 if remaining_hours >= 1.5 else 1.0
-            start = slots[slot_idx]
-            end = start + duration
+            slot = available_slots.pop(0)
+            room = rooms[i % len(rooms)]
 
-            timetable.append({
-                "Day": DAYS[day_idx],
-                "Time": f"{start:0.1f} - {end:0.1f}",
-                "Course": row["Course"],
-                "Teacher": row["Teacher"],
-                "Room": rooms[room_idx % len(rooms)]
+            day_schedule.append({
+                "Time": slot,
+                "Course": block['Course'],
+                "Teacher": teacher,
+                "Room": room
             })
 
-            remaining_hours -= duration
-            slot_idx += 1
-            room_idx += 1
+            teacher_last_slot[teacher] = day
+            # Remove block from list if allocated
+            course_blocks.pop(i)
+        timetable[day] = day_schedule
 
-            if slot_idx >= len(slots):
-                slot_idx = 0
-                day_idx += 1
+    # Convert timetable dict to printable DataFrame
+    max_columns = max(len(v) for v in timetable.values())
+    table_data = []
 
-            if day_idx >= len(DAYS):
-                return pd.DataFrame(timetable)
+    for day in DAYS:
+        row = [day]
+        for cls in timetable[day]:
+            row.append(f"{cls['Course']} ({cls['Teacher']})\n{cls['Time']}")
+        # Fill remaining columns with empty
+        while len(row) <= max_columns:
+            row.append("")
+        table_data.append(row)
 
-    return pd.DataFrame(timetable)
+    columns = ["Day"] + [f"Slot {i+1}" for i in range(max_columns)]
+    df = pd.DataFrame(table_data, columns=columns)
+    return df