"""SwanLab 可视化封装：可用时记录，不可用时必须静默降级、不影响训练。"""

import builtins

import pytest

from engine.visualizer import SwanLabLogger


def test_disabled_logger_is_noop(tmp_path):
    logger = SwanLabLogger(enabled=False, work_dir=tmp_path)
    assert logger.enabled is False
    logger.log({"loss": 1.0}, step=1)
    logger.finish()


def test_mode_disabled_is_treated_as_off(tmp_path):
    assert SwanLabLogger(work_dir=tmp_path, mode="disabled").enabled is False


def test_invalid_mode_raises(tmp_path):
    with pytest.raises(ValueError, match="swanlab mode"):
        SwanLabLogger(work_dir=tmp_path, mode="cloud")


def test_missing_swanlab_degrades_gracefully(tmp_path, monkeypatch):
    real_import = builtins.__import__

    def fake_import(name, *args, **kwargs):
        if name == "swanlab":
            raise ImportError("no swanlab")
        return real_import(name, *args, **kwargs)

    monkeypatch.setattr(builtins, "__import__", fake_import)
    logger = SwanLabLogger(work_dir=tmp_path)
    assert logger.enabled is False
    logger.log({"loss": 1.0})  # 不应抛异常


def test_offline_run_records_metrics(tmp_path):
    pytest.importorskip("swanlab")
    logger = SwanLabLogger(
        work_dir=tmp_path, project="mte-tests", mode="offline", config={"lr": 0.1}
    )
    if not logger.enabled:  # 环境不允许起 run 时跳过，不让测试变脆
        pytest.skip("swanlab 无法在当前环境初始化")
    logger.log({"total": 1.0, "lr": 0.1}, step=1, prefix="train/")
    logger.finish()
    assert (tmp_path / "swanlog").exists()


def test_log_failure_disables_instead_of_raising(tmp_path):
    logger = SwanLabLogger(enabled=False, work_dir=tmp_path)
    logger.enabled = True  # 伪造已启用但底层不可用的状态

    class Broken:
        @staticmethod
        def log(*args, **kwargs):
            raise RuntimeError("network down")

    logger._swanlab = Broken()
    logger.log({"loss": 1.0}, step=1)
    assert logger.enabled is False