chore: add pytest dev-deps and pydantic models (Job, Connection, PendingSubmission)

tests/__init__.py

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+# coding=utf-8
+"""
+@Time   :2026/6/24
+@Author :tao.chen
+"""

tests/conftest.py

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+# coding=utf-8
+# Ensures the project root is on sys.path when running pytest from any cwd.
+import sys
+from pathlib import Path
+
+ROOT = Path(__file__).resolve().parents[1]
+if str(ROOT) not in sys.path:
+    sys.path.insert(0, str(ROOT))

tests/unit/__init__.py

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+# coding=utf-8
+"""
+@Time   :2026/6/24
+@Author :tao.chen
+"""

tests/unit/test_models.py

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+# 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",
+    )
+    dumped = job.model_dump()
+    assert dumped["job_id"] == "abc123"
+    assert dumped["application_id"] == "application_17400000001"
+    assert dumped["connection"] == "prod-yarn"
+
+
+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
+
+
+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"