"""
Generates small illustrative dummy CSV datasets under data/dummy/ so the
timetable template generator has something to schedule and render.

Run once:
    python data/dummy/generate_dummy_data.py
"""

import csv
import os

BASE_DIR = os.path.dirname(os.path.abspath(__file__))


def write_csv(relative_path, header, rows):
    path = os.path.join(BASE_DIR, relative_path)
    os.makedirs(os.path.dirname(path), exist_ok=True)
    with open(path, "w", newline="", encoding="utf-8") as f:
        writer = csv.writer(f)
        writer.writerow(header)
        writer.writerows(rows)
    print(f"wrote {len(rows)} rows -> {path}")


def main():
    # ---- blocks & rooms (Building/Block A only) ----
    write_csv(
        "blocks/blocks.csv",
        ["block_id", "block_name"],
        [["A", "Block A"]],
    )

    write_csv(
        "blocks/rooms.csv",
        ["room_id", "room_name", "block_id", "room_type", "capacity"],
        [
            ["A-101", "Room 101", "A", "classroom", 60],
            ["A-102", "Room 102", "A", "classroom", 60],
            ["A-103", "Room 103", "A", "classroom", 50],
            ["A-201", "Room 201", "A", "classroom", 60],
            ["A-L01", "Computer Lab 1", "A", "lab", 35],
            ["A-L02", "Computer Lab 2", "A", "lab", 35],
        ],
    )

    # ---- departments / programs / batches ----
    # batch_code = session(2) + program_id(6)  e.g. 25021519
    batches_25 = [
        ["25021519", "CS", "BSCS", "25"],
        ["25021520", "CS", "BSSE", "25"],
        ["25031519", "EE", "BSEE", "25"],
    ]
    batches_26 = [
        ["26021519", "CS", "BSCS", "26"],
        ["26021520", "CS", "BSSE", "26"],
        ["26031519", "EE", "BSEE", "26"],
    ]

    write_csv(
        "batch_codes/25/batches.csv",
        ["batch_code", "department", "program", "session"],
        batches_25,
    )
    write_csv(
        "batch_codes/26/batches.csv",
        ["batch_code", "department", "program", "session"],
        batches_26,
    )

    all_batches = batches_25 + batches_26

    # ---- courses ----
    # One row per subject: lectures/labs per week are counted separately so
    # a single course can carry both, and each course names its preferred
    # lecture/lab room (the scheduler falls back to another same-type room
    # only if the preferred one is busy).
    # is_general courses are shared across every batch of the same session
    # (so they can be scheduled together on Tuesday first, with no clash).
    courses = [
        # course_id, course_name, credit_hours, lectures_per_week, labs_per_week, is_general, lecture_room_id, lab_room_id
        ["CS101", "Programming Fundamentals", 4, 2, 1, "no", "A-101", "A-L01"],
        ["CS201", "Data Structures", 4, 2, 1, "no", "A-102", "A-L01"],
        ["EE101", "Basic Electronics", 4, 2, 1, "no", "A-201", "A-L02"],
        ["GEN101", "Functional English", 3, 2, 0, "yes", "A-103", ""],
        ["GEN102", "Islamic Studies", 2, 1, 0, "yes", "A-103", ""],
    ]
    write_csv(
        "courses/courses.csv",
        [
            "course_id", "course_name", "credit_hours", "lectures_per_week",
            "labs_per_week", "is_general", "lecture_room_id", "lab_room_id",
        ],
        courses,
    )

    # ---- course offerings: course + section (a section groups the batches
    # taking that section together) + who teaches it ----
    # A course can have many sections; here each CS/EE batch of a session is
    # its own section (Section A/B/...), while general courses have a single
    # section "ALL" grouping every batch of that session.
    offerings = []

    dept_course = {"CS": ["CS101", "CS201"], "EE": ["EE101"]}
    dept_instructors = {
        "CS": ["1001", "1002", "1003", "1006"],
        "EE": ["1004", "1005"],
    }

    section_letters = ["A", "B", "C", "D"]
    dept_section_counter = {"CS": 0, "EE": 0}

    for batch_code, department, program, session in all_batches:
        section_id = section_letters[dept_section_counter[department] % len(section_letters)]
        dept_section_counter[department] += 1

        for i, course_id in enumerate(dept_course[department]):
            instr_pool = dept_instructors[department]
            instr = instr_pool[i % len(instr_pool)]
            offerings.append([course_id, section_id, batch_code, instr])

    # general courses: one offering per (course, session), section "ALL"
    # grouping every batch code sharing that session, separated by "|"
    for session, batch_group in (
        ("25", [b[0] for b in batches_25]),
        ("26", [b[0] for b in batches_26]),
    ):
        offerings.append(["GEN101", "ALL", "|".join(batch_group), "1002"])
        offerings.append(["GEN102", "ALL", "|".join(batch_group), "1006"])

    write_csv(
        "courses/course_offering.csv",
        ["course_id", "section_id", "batch_codes", "instructor_code"],
        offerings,
    )

    # ---- instructors (4-digit employee codes) ----
    # Derived from the offerings above so it can never drift: one row per
    # unique (instructor, course, section) teaching assignment.
    instructor_names = {
        "1001": "Dr. Ahsan Raza",
        "1002": "Ms. Sana Tariq",
        "1003": "Mr. Bilal Khan",
        "1004": "Dr. Farah Iqbal",
        "1005": "Mr. Usman Ali",
        "1006": "Ms. Hira Shah",
    }
    instructors = []
    for course_id, section_id, batch_codes, instr_code in offerings:
        instructors.append([instr_code, instructor_names[instr_code], course_id, section_id])

    write_csv(
        "instructor/instructors.csv",
        ["instructor_code", "instructor_name", "course_id", "section_id"],
        instructors,
    )

    # ---- students (roll_no = batch_code-seq) ----
    students = []
    for batch_code, department, program, session in all_batches:
        for seq in range(1, 6):  # 5 sample students per batch
            roll_no = f"{batch_code}-{seq:03d}"
            students.append([roll_no, batch_code, f"Student {roll_no}"])

    write_csv(
        "roll_no/students.csv",
        ["roll_no", "batch_code", "student_name"],
        students,
    )

    print("\nDummy data generation complete.")


if __name__ == "__main__":
    main()