ray/doc/source/cluster/running-applications/job-submission/rest.rst
Chen Shen ddca52d2ca
[cluster doc] Promote new doc and deprecate the old (#27759)
Co-authored-by: Richard Liaw <rliaw@berkeley.edu>
2022-08-10 17:41:56 -07:00

65 lines
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.. warning::
This page is under construction!
.. _ray-job-rest-api-under-construction:
REST API
^^^^^^^^
Under the hood, both the Python SDK and the CLI make HTTP calls to the job server running on the Ray head node. You can also directly send requests to the corresponding endpoints via HTTP if needed:
**Submit Job**
.. code-block:: python
import requests
import json
import time
resp = requests.post(
"http://127.0.0.1:8265/api/jobs/",
json={
"entrypoint": "echo hello",
"runtime_env": {},
"job_id": None,
"metadata": {"job_submission_id": "123"}
}
)
rst = json.loads(resp.text)
job_id = rst["job_id"]
**Query and poll for Job status**
.. code-block:: python
start = time.time()
while time.time() - start <= 10:
resp = requests.get(
"http://127.0.0.1:8265/api/jobs/<job_id>"
)
rst = json.loads(resp.text)
status = rst["status"]
print(f"status: {status}")
if status in {JobStatus.SUCCEEDED, JobStatus.STOPPED, JobStatus.FAILED}:
break
time.sleep(1)
**Query for logs**
.. code-block:: python
resp = requests.get(
"http://127.0.0.1:8265/api/jobs/<job_id>/logs"
)
rst = json.loads(resp.text)
logs = rst["logs"]
**List all jobs**
.. code-block:: python
resp = requests.get(
"http://127.0.0.1:8265/api/jobs/"
)
print(resp.json())
# {"job_id": {"metadata": ..., "status": ..., "message": ...}, ...}