Merge pull request #1 from criteo-forks/fix/ml-bump

fix(ml): adapt experimental ml commands to 8.x ES API

detection_rules/ml.py

@@ -395,16 +395,17 @@ def upload_job(ctx: click.Context, job_file, overwrite):
     with open(job_file, 'r') as f:
         job = json.load(f)
 
-    def safe_upload(func):
+    def safe_upload(func, job_type, **kwargs):
         try:
-            func(name, body)
+            func(**kwargs)
         except (elasticsearch.ConflictError, elasticsearch.RequestError) as err:
             if isinstance(err, elasticsearch.RequestError) and err.error != 'resource_already_exists_exception':
                 client_error(str(err), err, ctx=ctx)
 
             if overwrite:
-                ctx.invoke(delete_job, job_name=name, job_type=job_type)
-                func(name, body)
+                click.echo(f'WARN: Overwriting job {name} if it exists.')
+                ctx.invoke(delete_job, job_name=kwargs.get('job_id'), job_type=job_type)
+                func(**kwargs)
             else:
                 client_error(str(err), err, ctx=ctx)
 
@@ -414,11 +415,11 @@ def safe_upload(func):
         body = job['body']
 
         if job_type == 'anomaly_detection':
-            safe_upload(ml_client.put_job)
+            safe_upload(ml_client.put_job, job_type=job_type, job_id=name, body=body)
         elif job_type == 'data_frame_analytic':
-            safe_upload(ml_client.put_data_frame_analytics)
+            safe_upload(ml_client.put_data_frame_analytics, job_type=job_type, id=name, body=body)
         elif job_type == 'datafeed':
-            safe_upload(ml_client.put_datafeed)
+            safe_upload(ml_client.put_datafeed, job_type=job_type, datafeed_id=name, body=body)
         else:
             client_error(f'Unknown ML job type: {job_type}')
 
@@ -438,11 +439,11 @@ def delete_job(ctx: click.Context, job_name, job_type, verbose=True):
 
     try:
         if job_type == 'anomaly_detection':
-            ml_client.delete_job(job_name)
+            ml_client.delete_job(job_id=job_name)
         elif job_type == 'data_frame_analytic':
-            ml_client.delete_data_frame_analytics(job_name)
+            ml_client.delete_data_frame_analytics(job_id=job_name)
         elif job_type == 'datafeed':
-            ml_client.delete_datafeed(job_name)
+            ml_client.delete_datafeed(job_id=job_name)
         else:
             client_error(f'Unknown ML job type: {job_type}')
     except (elasticsearch.NotFoundError, elasticsearch.ConflictError) as e: