feat: support batch repetition and selective case import

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chenmingxuan committed 2026-10-09 16:29:16 +08:00
1 parent df66897ff4
commit 4d6560dbd4
16 files changed
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@@ -185,6 +185,107 @@ def test_preferences_and_required_device(client):
assert client.post("/api/automation/batches", json=payload(device_serial="")).status_code == 422
def test_batch_repetitions_are_ordered_independent_and_idempotent(client, isolated):
request = payload(repeat_count=3, request_id="repeat-test")
created = client.post("/api/automation/batches", json=request)
assert created.status_code == 200
batch = created.json()
assert (batch["case_count"], batch["repeat_count"], batch["total_executions"]) == (2, 3, 6)
jobs = isolated.jobs(batch["id"])
assert len({j["session_id"] for j in jobs}) == 6
assert [j["position"] for j in jobs] == list(range(1, 7))
assert [(j["iteration"], j["case_position"]) for j in jobs] == [
(1, 1),
(1, 2),
(2, 1),
(2, 2),
(3, 1),
(3, 2),
]
assert [j["case"]["goal"] for j in jobs] == ["观察设置", "观察首页"] * 3
assert all(j["status"] == "pending" for j in jobs)
assert client.post("/api/automation/batches", json=request).json()["id"] == batch["id"]
assert len(isolated.jobs(batch["id"])) == 6
assert (
client.post("/api/automation/batches", json={**request, "repeat_count": 2}).status_code
== 409
)
# Each selected failure is copied once, including failures from different rounds.
for job in (jobs[0], jobs[4]):
isolated.save_job({**job, "status": "failed"})
retry = service.batch_action(batch["id"], "retry_failed")
assert retry["repeat_count"] == 1
assert len(isolated.jobs(retry["id"])) == 2
report = reports.session_report(jobs[4]["session_id"])
assert "第 3 / 3 轮" in report["name"]
archive = reports.export_batch(batch["id"])
with zipfile.ZipFile(archive) as z:
assert len([n for n in z.namelist() if n.endswith(".xlsx")]) == 7
assert len(set(z.namelist())) == len(z.namelist())
@pytest.mark.parametrize("count", [0, -1, 1.5, True, "3", None])
def test_batch_rejects_invalid_repetitions(client, isolated, count):
assert (
client.post("/api/automation/batches", json=payload(repeat_count=count)).status_code == 422
)
assert isolated.records("batch") == []
def test_batch_limit_is_checked_before_creating_records(client, isolated, monkeypatch):
monkeypatch.setattr(service.settings, "ARTEMIS_BATCH_MAX_EXECUTIONS", 5)
assert client.get("/api/automation/preferences").json()["batch_max_executions"] == 5
response = client.post("/api/automation/batches", json=payload(repeat_count=3))
assert response.status_code == 409
assert "5" in response.json()["detail"]
assert not isolated.records("batch")
assert not isolated.jobs()
@pytest.mark.asyncio
async def test_loop_dispatch_continues_after_failure_and_resume_without_repeating(
isolated, monkeypatch
):
from apps.admin_console import server
from artemis.runtime.device_pool import DeviceStatus
batch = service.create_batch(payload(repeat_count=2))
service.batch_action(batch["id"], "resume")
monkeypatch.setattr(service, "state", type("State", (), {"is_paused": False})())
enqueue = AsyncMock(return_value={"tasks": [{"device_serial": "test-device"}]})
monkeypatch.setattr(server.task_queue_service, "enqueue_tasks", enqueue)
monkeypatch.setattr(
"artemis.runtime.device_pool.try_list_devices_async",
AsyncMock(return_value=[DeviceStatus(serial="test-device", state="device")]),
)
for index in range(4):
await service.tick_batches()
await service.tick_batches() # Polling must not enqueue the same execution twice.
assert enqueue.await_count == index + 1
job = isolated.jobs(batch["id"])[index]
assert enqueue.call_args.kwargs["session_id"] == job["session_id"]
assert f"第 {job['iteration']} / 2 轮" in enqueue.call_args.kwargs["display_name"]
isolated.save_job({**job, "status": "failed" if index == 0 else "completed"})
if index == 1:
service.batch_action(batch["id"], "pause")
await service.tick_batches()
assert enqueue.await_count == 2
service.batch_action(batch["id"], "resume")
await service.tick_batches()
assert isolated.get("batch", batch["id"])["status"] == "completed"
assert enqueue.await_count == 4
@pytest.mark.asyncio
async def test_repeat_fail_fast_skips_future_rounds(isolated):
batch = service.create_batch(payload(repeat_count=3, stop_on_failure=True))
first = isolated.jobs(batch["id"])[0]
isolated.save_job({**first, "status": "failed"})
service.batch_action(batch["id"], "resume")
await service.tick_batches()
assert [j["status"] for j in isolated.jobs(batch["id"])] == ["failed"] + ["skipped"] * 5
def test_batch_delete_removes_tasks_and_files_and_prevents_request_replay(client, isolated):
created = client.post(
"/api/automation/batches", json=payload(request_id="delete-example")