mirror of
https://github.com/vale981/ray
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03d835e4e2
This adds the structure described here, namely adding a new section under Ray Clusters which is focused on running applications on Ray clusters. Signed-off-by: Cade Daniel <cade@anyscale.com> Co-authored-by: Stephanie Wang <swang@cs.berkeley.edu>
65 lines
1.5 KiB
ReStructuredText
65 lines
1.5 KiB
ReStructuredText
.. warning::
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This page is under construction!
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.. _ray-job-rest-api-under-construction:
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REST API
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^^^^^^^^
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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:
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**Submit Job**
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.. code-block:: python
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import requests
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import json
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import time
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resp = requests.post(
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"http://127.0.0.1:8265/api/jobs/",
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json={
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"entrypoint": "echo hello",
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"runtime_env": {},
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"job_id": None,
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"metadata": {"job_submission_id": "123"}
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}
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)
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rst = json.loads(resp.text)
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job_id = rst["job_id"]
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**Query and poll for Job status**
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.. code-block:: python
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start = time.time()
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while time.time() - start <= 10:
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resp = requests.get(
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"http://127.0.0.1:8265/api/jobs/<job_id>"
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)
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rst = json.loads(resp.text)
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status = rst["status"]
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print(f"status: {status}")
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if status in {JobStatus.SUCCEEDED, JobStatus.STOPPED, JobStatus.FAILED}:
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break
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time.sleep(1)
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**Query for logs**
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.. code-block:: python
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resp = requests.get(
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"http://127.0.0.1:8265/api/jobs/<job_id>/logs"
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)
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rst = json.loads(resp.text)
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logs = rst["logs"]
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**List all jobs**
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.. code-block:: python
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resp = requests.get(
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"http://127.0.0.1:8265/api/jobs/"
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)
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print(resp.json())
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# {"job_id": {"metadata": ..., "status": ..., "message": ...}, ...}
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