Run a Python Function on Chunks of Rows
post
/api/py-scripts/v1/row-apply/{scriptName}
Run a user-owned Python function on data chunked in sets of rows.
Request
Supported Media Types
- application/json
Path Parameters
-
scriptName: string
The name of the Python script
A JSON str of (name - value) pairs specifying arguments of the request and additional arguments to the script
Root Schema : EmbedScriptComputeRow
Type:
Show Source
object
-
asyncFlag(optional):
boolean
Whether to execute the job asynchronously.
-
envName(optional):
string
Name of the conda environment.
-
graphicsFlag(optional):
boolean
Whether to capture images rendered in the script to the result.
-
input:
string
Query statement specifying input data.
-
parallel(optional):
integer(int32)
Degree of parallelism.
-
parallelFlag(optional):
boolean
Whether to execute job in parallel.
-
parameters(optional):
string
A JSON str of (name - value) pairs specifying keyword arguments to be passed into the script.
-
rows:
integer(int32)
Number of rows to chunk by.
-
service(optional):
string
Allowed Values:
[ "LOW", "MEDIUM", "HIGH" ]
LEVEL of the service. Default is LOW. -
timeout(optional):
integer(int32)
Minimum Value:
1800
Maximum Value:43200
The timeout limit (in seconds, default 1800s) of asynchronous job. Must be used together with `asyncFlag`=true.
Example Request (application/json)
{"input":"select name, finalgrade from GRADE where score > 90", "rows":5, "parameters":"{\"oml_input_type\":\"pandas.DataFrame\"}", "parallelFlag":true}
Response
Supported Media Types
- application/json
200 Response
By default, returns the job result.
201 Response
If asyncFlag=True, returns the location header where the status of the job can be fetched.
Headers
400 Response
Invalid parameters specified, output exceeding size limit or other script execution error.
500 Response
Problem connecting to Broker, executing job or other unexpected error.
Examples
Example 1
The following example runs the script named my_predict
.
curl -i -X POST --header "Authorization: Bearer ${token}" \
--header 'Content-Type: application/json' --header 'Accept: application/json' \
-d '{"input":"select * from IRIS", "parameters":"{\"oml_input_type\":\"pandas.DataFrame\"}", "rows":4, "parallelFlag":true, "service":"LOW"}' \
"<oml-cloud-service-location-url>/oml/api/py-scripts/v1/row-apply/my_predict"
Response Headers
The response headers are the following:
HTTP/1.1 200 OK
Date: Thu, 27 Aug 2020 14:41:33 GMT
Content-Type: application/json
Transfer-Encoding: chunked
Connection: keep-alive
Cache-Control: no-cache, no-store, private
X-Frame-Options: SAMEORIGIN
X-XSS-Protection: 1;mode=block
Strict-Transport-Security: max-age=31536000; includeSubDomains
X-Content-Type-Options: nosniff
Set-Cookie: JSESSIONID=node0iyk3jfk7ub82onaoj7c2gdxv698.node0; Path=/oml; Secure; HttpOnly
Expires: Thu, 01 Jan 1970 00:00:00 GMT
Response Body
The a portion of the response body in JSON format is the following:
{"result":[{"Pred_Petal_Width":6.8462408185,"Species":"setosa","Petal_Width":0.2},
{"Pred_Petal_Width":5.2786489228,"Species":"versicolor","Petal_Width":1.1},
{"Pred_Petal_Width":5.0951801182,"Species":"versicolor","Petal_Width":1},...]}
Example 2
The following example runs the script named test_seaborn_inp
.
curl -i -k -X POST --header "Authorization: Bearer ${token}" --header
'Content-Type: application/json' --header 'Accept: application/json' -d
'{"input": "select * from IRIS", "rows": 50, "envName": "seaborn", "graphicsFlag": true}'
"<oml-cloud-service-location-url>/oml/api/py-scripts/v1/row-apply/test_seaborn_inp"
Response Body
The result of the REST endpoint is a JSON representation of the value returned from the Python script, which includes the image and the data. Image bytes are returned in PNG format.
{
"result": {
"0": {
"IMAGE": "iVBORw0KGgoAAAAN......AAABJRU5ErkJggg==",
"DATA": "\"hello world\"",
"TITLE": "Iris plot",
"ID": 1,
"CHUNK": 1
},
"1": {
"IMAGE": "iVBORw0KGgoAAAAN......AAAAASUVORK5CYII=",
"DATA": "\"hello world\"",
"TITLE": "Iris plot",
"ID": 1,
"CHUNK": 2
},
"2": {
"IMAGE": "iVBORw0KGgoAAAAN......3AAAAAElFTkSuQmCC",
"DATA": "\"hello world\"",
"TITLE": "Iris plot",
"ID": 1,
"CHUNK": 3
}
}
}