initial project

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Talhadeveloperr
2026-09-09 17:00:54 +05:00
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"""
Verifies that no instructor is booked into two sessions at the same
day+slot (whether both are lectures, both labs, or a mix of either).
Like student_conflict_checker, this re-derives occupancy directly from the
session list rather than trusting the scheduler's internal busy-maps.
"""
from collections import defaultdict
def check_teacher_conflicts(sessions):
"""
Returns a list of conflict dicts, one per (instructor_code, day, slot)
where two or more sessions overlap for that instructor:
{
"instructor_code": str,
"day": str,
"slot_index": int,
"sessions": [session, session, ...],
}
"""
# (instructor_code, day, slot_index) -> list of sessions occupying that cell
occupied = defaultdict(list)
for session in sessions:
day = session["day"]
instructor_code = session["instructor_code"]
for slot_index in session["slot_indices"]:
occupied[(instructor_code, day, slot_index)].append(session)
conflicts = []
for (instructor_code, day, slot_index), cell_sessions in occupied.items():
if len(cell_sessions) > 1:
conflicts.append({
"instructor_code": instructor_code,
"day": day,
"slot_index": slot_index,
"sessions": cell_sessions,
})
conflicts.sort(key=lambda c: (c["instructor_code"], c["day"], c["slot_index"]))
return conflicts
def format_teacher_conflicts(conflicts):
"""Human-readable lines describing each teacher conflict."""
lines = []
for c in conflicts:
course_list = ", ".join(
f'{s["course_id"]} ({s["course_type"]}) for batch(es) {"+".join(s["batch_codes"])} in {s["room_id"]}'
for s in c["sessions"]
)
instructor_name = c["sessions"][0]["instructor_name"]
lines.append(
f'Instructor {instructor_name} ({c["instructor_code"]}) is double-booked on '
f'{c["day"]} slot {c["slot_index"]}: {course_list}'
)
return lines