import importlib

import pandas as pd


def test_streamlit_app_imports():
    importlib.import_module("multi_swarm.dashboard.data")


def test_dashboard_data_helpers_signatures():
    from multi_swarm.dashboard import data

    assert hasattr(data, "list_runs_df")
    assert hasattr(data, "generations_df")
    assert hasattr(data, "evaluations_df")
    assert hasattr(data, "genomes_df")


def test_aquarium_helper_builds_html():
    from multi_swarm.dashboard.aquarium import build_aquarium_html

    fish = [
        {
            "id": "abc123",
            "fitness": 0.8,
            "cognitive_style": "physicist",
            "n_trades": 30,
            "dsr": 0.7,
        },
        {
            "id": "def456",
            "fitness": 0.0,
            "cognitive_style": "biologist",
            "n_trades": 0,
            "dsr": 0.0,
        },
    ]
    html = build_aquarium_html(fish, canvas_w=800, canvas_h=400, show_labels=True)
    assert "canvas" in html
    assert "abc123" in html
    assert "physicist" in html or "4cc9f0" in html
    assert "requestAnimationFrame" in html


def test_aquarium_build_fish_dataset_sorts_and_caps():
    from multi_swarm.dashboard.aquarium import build_fish_dataset

    df = pd.DataFrame(
        [
            {"genome_id": "low", "fitness": 0.1, "cognitive_style": "physicist",
             "n_trades": 1, "dsr": 0.0},
            {"genome_id": "high", "fitness": 0.9, "cognitive_style": "biologist",
             "n_trades": 10, "dsr": 0.5},
            {"genome_id": "mid", "fitness": 0.5, "cognitive_style": "engineer",
             "n_trades": 5, "dsr": 0.2},
        ]
    )
    out = build_fish_dataset(df, max_fish=2)
    assert len(out) == 2
    assert out[0]["id"] == "high"
    assert out[1]["id"] == "mid"
    assert out[0]["cognitive_style"] == "biologist"


def test_aquarium_build_fish_dataset_drops_nan_fitness():
    from multi_swarm.dashboard.aquarium import build_fish_dataset

    df = pd.DataFrame(
        [
            {"genome_id": "ok", "fitness": 0.4, "cognitive_style": "historian",
             "n_trades": 2, "dsr": 0.1},
            {"genome_id": "bad", "fitness": float("nan"), "cognitive_style": "ecologist",
             "n_trades": 0, "dsr": 0.0},
        ]
    )
    out = build_fish_dataset(df)
    assert len(out) == 1
    assert out[0]["id"] == "ok"


def test_aquarium_empty_input_returns_empty():
    from multi_swarm.dashboard.aquarium import build_aquarium_html, build_fish_dataset

    assert build_fish_dataset(pd.DataFrame()) == []
    html = build_aquarium_html([], canvas_w=400, canvas_h=200)
    assert "canvas" in html
    assert "Acquario vuoto" in html