import random
from collections import Counter

from coldcall_lti import selection


STUDENTS = ["a", "b", "c", "d"]


def test_weights_halve_per_answered_call():
    weights = selection.compute_weights(STUDENTS, {"a": 0, "b": 1, "c": 3}, 2.0)
    assert weights == {"a": 1.0, "b": 0.5, "c": 0.125, "d": 1.0}


def test_weight_factor_one_is_uniform():
    weights = selection.compute_weights(STUDENTS, {"a": 5, "b": 2}, 1.0)
    assert set(weights.values()) == {1.0}


def test_heavily_called_student_selected_less():
    rng = random.Random(42)
    counts = Counter(
        selection.select_student(STUDENTS, {"a": 4}, 2.0, rng)
        for _ in range(4000)
    )
    # "a" has weight 1/16 against 1 for the others, so it should get
    # roughly 1/49th of the picks; the others roughly a third each.
    assert counts["a"] < 250
    for s in ("b", "c", "d"):
        assert 1000 < counts[s] < 1700


def test_generate_call_list_downweights_within_list():
    rng = random.Random(7)
    picks = selection.generate_call_list(STUDENTS, {}, 200, 2.0, rng)
    assert len(picks) == 200
    counts = Counter(picks)
    # Sequential downweighting keeps the distribution close to even.
    assert all(35 < counts[s] < 65 for s in STUDENTS)


def test_generate_cycle_batch_covers_everyone_once():
    rng = random.Random(1)
    picks = selection.generate_cycle_batch(STUDENTS, {}, None, rng)
    assert sorted(picks) == sorted(STUDENTS)


def test_generate_cycle_batches_walk_the_pass():
    rng = random.Random(1)
    counts = {}
    first = selection.generate_cycle_batch(STUDENTS, counts, 3, rng)
    assert len(first) == 3
    for s in first:
        counts[s] = counts.get(s, 0) + 1

    # The remainder batch is short, not wrapped into the next pass.
    second = selection.generate_cycle_batch(STUDENTS, counts, 3, rng)
    assert len(second) == 1
    assert sorted(first + second) == sorted(STUDENTS)
    for s in second:
        counts[s] = counts.get(s, 0) + 1

    # Everyone called once: a new pass opens with the full roster.
    third = selection.generate_cycle_batch(STUDENTS, counts, 3, rng)
    assert len(third) == 3
    assert set(third) <= set(STUDENTS)