using ray sdk vs cli for byot

guidebooks/ml/codeflare/training/byot/index.md

@@ -19,10 +19,15 @@ Submit the job.
 export JOB_NAME=BYOT
 ```
 
-```shell
+```python
 ---
-exec: ray job submit  --job-id ${JOB_ID} --no-wait --runtime-env  ${CUSTOM_WORKING_DIR}/runtime-env.yaml --working-dir ${CUSTOM_WORKING_DIR} --address ${RAY_ADDRESS}  -- python main.py 
+#exec: ray job submit  --job-id ${JOB_ID} --no-wait --runtime-env  ${CUSTOM_WORKING_DIR}/runtime-env.yaml --working-dir ${CUSTOM_WORKING_DIR} --address ${RAY_ADDRESS}  -- python main.py 
+#the below command is equivalent of this command
+exec: 
+    #assumes that all these variables are set already, and are cross checked via asserts in python
+    #JOB_ID=${JOB_ID} CUSTOM_WORKING_DIR=${CUSTOM_WORKING_DIR} RAY_ADDRESS=${RAY_ADDRESS}
 ---
+--8<-- "./job_submission.py"
 ```
 
 --8<-- "ml/ray/run/logs"

guidebooks/ml/codeflare/training/byot/job_submission.py

@@ -0,0 +1,43 @@
+import os
+from re import template
+import yaml
+from ray.job_submission import JobSubmissionClient
+
+"""
+    uses the job SDK to submit the command
+"""
+def execute_job():
+    assigned_job_id = os.getenv("JOB_ID")
+    cluster_address = os.getenv("RAY_ADDRESS")
+    template_location = os.getenv("CUSTOM_WORKING_DIR")
+    config_file_location = f"{template_location}/config.yaml"
+
+    assert assigned_job_id is not None, "JOB_ID cannot be none"
+    assert cluster_address is not None, "RAY_ADDDRESS cannot be none"
+    assert template_location is not None, "RAY_ADDDRESS cannot be none"
+    assert os.path.isfile(config_file_location), f"config file config.yaml should be present at {template_location}"
+
+    with open(config_file_location, "r") as config_file:
+        print(f"reading configuration from {config_file_location}")
+        config = yaml.safe_load(config_file)
+        validate_config(config)
+        #set the working directory to be what is provided by the user
+        config["runtime_env"] = config.get("runtime_env", {})
+        config["runtime_env"]["working_dir"] = template_location
+
+    print(f"executing command ray job submit wiith job-id: {assigned_job_id} working_dir: ${template_location} address: {cluster_address}")
+    client = JobSubmissionClient(address=cluster_address)
+    job_id = client.submit_job(
+        job_id=assigned_job_id,
+        entrypoint=config['entrypoint'],
+        runtime_env=config['runtime_env'],
+        metadata=config['metadata']
+    )
+
+
+def validate_config(config):
+    #print(f"config {config}")
+    assert config['entrypoint'], "entry point cannot be empty"
+
+if __name__ == "__main__":
+    execute_job()

guidebooks/ml/ray/install/cli.md

@@ -4,7 +4,7 @@
 ---
 validate: which ray
 ---
-pip install -U "ray[default]"
+pip install -U "ray[default]" pyyaml 
 ```
 
 ```shell