# coding=utf-8
from datetime import datetime
from spark_executor.models import Connection, Job, JobStatus, PendingSubmission, SubmitResult


def test_job_roundtrip():
    job = Job(
        job_id="abc123",
        application_id="application_17400000001",
        script_path="/tmp/jobs/job_001.py",
        queue="default",
        submit_time=datetime(2026, 6, 24, 10, 0, 0),
        connection="prod-yarn",
        yarn_rm_url="http://rm:8088",
    )
    dumped = job.model_dump()
    assert dumped["job_id"] == "abc123"
    assert dumped["application_id"] == "application_17400000001"
    assert dumped["connection"] == "prod-yarn"
    assert dumped["yarn_rm_url"] == "http://rm:8088"


def test_job_yarn_rm_url_optional():
    job = Job(
        job_id="j1",
        application_id="application_1",
        script_path="/tmp/x.py",
        queue="default",
        submit_time=datetime(2026, 6, 24),
        connection="dev",
    )
    assert job.yarn_rm_url is None


def test_job_status_default_raw():
    s = JobStatus(application_id="application_1", state="RUNNING")
    assert s.raw == ""


def test_submit_result_tracking_url_optional():
    r = SubmitResult(job_id="j1", application_id="application_1", tracking_url=None)
    assert r.tracking_url is None


def test_connection_defaults():
    c = Connection(name="prod", master="yarn")
    assert c.deploy_mode == "cluster"
    assert c.yarn_rm_url is None
    assert c.spark_conf == {}


def test_connection_with_spark_conf():
    c = Connection(
        name="dev",
        master="spark://master:7077",
        deploy_mode="client",
        spark_conf={"spark.sql.shuffle.partitions": "200"},
    )
    assert c.spark_conf["spark.sql.shuffle.partitions"] == "200"


def test_pending_submission_defaults_to_pending_status():
    p = PendingSubmission(
        pending_id="p_1",
        connection="prod",
        master="yarn",
        deploy_mode="cluster",
        script_path="/tmp/j.py",
        queue="default",
        executor_memory="4G",
        executor_cores=2,
        num_executors=2,
        spark_conf={},
        created_at=datetime(2026, 6, 24),
    )
    assert p.status == "PENDING"
    assert p.error is None
    assert p.job_id is None
    assert p.application_id is None
    assert p.yarn_rm_url is None  # default for connections without one set


def test_pending_submission_carries_yarn_rm_url_snapshot():
    """snapshotting yarn_rm_url lets prepare/confirm survive connection edits."""
    p = PendingSubmission(
        pending_id="p_x",
        connection="prod",
        master="yarn",
        deploy_mode="cluster",
        yarn_rm_url="http://rm-prod:8088",
        script_path="/tmp/j.py",
        queue="default",
        executor_memory="4G",
        executor_cores=2,
        num_executors=2,
        spark_conf={},
        created_at=datetime(2026, 6, 24),
    )
    assert p.yarn_rm_url == "http://rm-prod:8088"


def test_pending_submission_can_record_outcome():
    p = PendingSubmission(
        pending_id="p_2",
        connection="prod",
        master="yarn",
        deploy_mode="cluster",
        script_path="/tmp/j.py",
        queue="default",
        executor_memory="4G",
        executor_cores=2,
        num_executors=2,
        spark_conf={},
        created_at=datetime(2026, 6, 24),
        status="SUBMITTED",
        job_id="j_abc",
        application_id="application_17400000001",
    )
    assert p.status == "SUBMITTED"
    assert p.job_id == "j_abc"
    assert p.application_id == "application_17400000001"