i have a adaptive card choice set like below, as you can see am trying to get the value under title from a variable which is an array, is there a way i can iterate the choice set automatically because i don't know how many values the array has i want to show all the values inside the array in the choice set title
{
"type" : "Input.ChoiceSet",
"isMultiSelect": true,
"id": "myColor",
"style": "compact",
"value": "1",
"choices": [
{
"title": vars.responsedata.items[0].topic,
"value": "1"
},
{
"title": vars.responsedata.items[1].topic,
"value": "2"
},
{
"title": "Recording 3 sample",
"value": "3"
}
]
}
You can use the map() function.
Example in DataWeave:
{
choices: vars.responsedata.items map {
title: $.topic,
value: $$
}
}
Related
I would like to get the value from the response based on a condition and store it to a variable.
In the below JSON, I would like to store the value when the name matches to something I prefer. Is there a way to achieve this using Karate API?
{
"results": [
{
"name": "Sample1",
"email": "sample1#text.com",
"id": "U-123"
},
{
"name": "Sample2",
"email": "sample2#text.com",
"id": "U-456"
},
{
"name": "Sample3",
"email": "sample3#text.com",
"id": "U-789"
}
]
}
So after reading the comment, my interpretation is to "find" the id where name is Sample2. Easy, just use a filter() operation, refer the docs: https://github.com/karatelabs/karate#jsonpath-filters
Instead of using a filter, I'm using the JS Array find() method as a very concise example below:
* def response =
"""
{ "results": [
{ "name": "Sample1", "email": "sample1#text.com", "id": "U-123" },
{ "name": "Sample2", "email": "sample2#text.com", "id": "U-456" },
{ "name": "Sample3", "email": "sample3#text.com", "id": "U-789" }
]
}
"""
* def id = response.results.find(x => x.name == 'Sample2').id
* match id == 'U-456'
Take some time to understand how it works. Talk to someone who knows JS if needed.
[
{
"key": "test1",
"category": "test",
"name": "test1",
"translations":
{
"english": "eng"
}
},
{
"key": "test2",
"category": "test",
"name": "test1",
"translations":
{
"english": "eng2",
"german": "German"
}
},
{
"key": "test3",
"category": "power",
"name": "test1",
"translations":
{
"EN_lang": "jik"
}
}
]
Here, we have multiple field's are with different values and we have to match value in translations (field position will change on every call)
You have to be clear about what you want to assert. Hint, the new contains deep (available in 0.9.6.RC4) can help:
* match response contains deep { key: 'test2', translations: { english: 'eng2' } }
Else you should look at transforming the JSON into a shape where it is easier to do the assertions you want: https://github.com/intuit/karate#json-transforms
I have Cosmos DB collection (called sample) containing the following documents:
[
{
"id": "id1",
"messages": [
{
"messageId": "message1",
"Text": "Value1"
},
{
"messageId": "message2",
"Text": "Value2"
}
]
},
{
"id": "id2",
"messages": [
{
"messageId": "message3",
"Text": "Value3"
},
{
"messageId": "message4",
"Text": "Value1"
}
]
},
{
"id": "id3",
"messages": [
{
"messageId": "message5",
"Text": "Value1"
},
{
"messageId": "message6",
"Text": "Value2"
}
]
},
{
"id": "id4",
"messages": [
{
"messageId": "message7",
"Text": "Value5"
},
{
"messageId": "message8",
"Text": "Value2"
}
]
},
]
I am trying to retrieve all the Documents, having messages and the first message has the field "Text"= 'Value1'.
In this sample the documents with the ids '1' and '3' would be retrieved. Please notice that the document with id='id2' wouldn't be retrieved,
since the value of the text of the first message is 'Value3'.
The collection as mentioned is called sample and I am running the following Query:
"select sample.id, sample.messages, ARRAY_SLICE(sample.messages, 0, 1)[0].Text as valueOfText from sample"
As you can see in the first two images, I retrieve all Documents and every one of them have the field "valueOfText" set to value of the first message, as expected.
Now when I filter the collection (the third image), I retrieve no results at all.
Is this an expected behavior?
Following your sql, got same results:
But why you have to use ARRAY_SLICE,it is used to return truncated array.Since your requirement is specific:
trying to retrieve all the Documents, having messages and the first
message has the field "Text"= 'Value1'
Just use sql:
SELECT c.id,c.messages,c.messages[0].Text as valueOfText FROM c
where c.messages[0].Text = 'Value1'
Output:
I'm trying to use UpdateRecord 1.9.0 processor to modify a JSON but it does not replace the values as I want.
this is the source message
{
"type": "A",
"ids": [{
"id": "1",
"value": "abc"
}, {
"id": "2",
"value": "def"
}, {
"id": "3",
"value": "ghi"
}
]
}
and the wanted output
{
"ids": [{
"userId": "1",
}, {
"userId": "2",
}, {
"userId": "3",
}
]
}
I have configured the processor as follows
processor config
Reader:
reader
Schema registry:
schema
writer:
writer
And it works, the output is a JSON without the field 'type' and the ids have the field 'userId' instead 'id' and 'value'.
To fill the value of userId, I defined the replace strategy and the property to replace:
strategy
But the output is wrong. The userId is always filled with the id of the last element in the array:
{
"ids": [{
"userId": "3"
}, {
"userId": "3"
}, {
"userId": "3"
}
]
}
I think the value of the expression is ok because if I try to replace only one record it works fine (/ids[0]/userId, ..id)
Nifi docs has a really similar example (example 3):
https://nifi.apache.org/docs/nifi-docs/components/org.apache.nifi/nifi-standard-nar/1.7.1/org.apache.nifi.processors.standard.UpdateRecord/additionalDetails.html
But it does not work for me.
What am I doing wrong?
thanks
Finally I have used JoltJSONTransform processor instead UpdateRecord
JoltJSONTransform
template:
[
{
"operation": "shift",
"spec": {
"ids":{
"*":{
"id": "ids[&1].userId"
}
}
}
}
]
Easier than UpdateRecord
"totalRows": 1,
"colDefs": [
{
"entityAttributeId": "acctNm",
"headerName": "Account Name",
"field": "2",
"entityPath": "",
"entityId": "account"
},
{
"entityAttributeId": "acctId",
"headerName": "Account ID",
"field": "1",
"entityPath": "",
"entityId": "account"
}
],
"rowData": [
{
"1": "1939",
"2": "Bay Pond Partners",
"rowMeta": {
"account": {
"acctInstrumentId": "0025-1939",
"acctId": "1939"
}
}
}
]
}
I have following response from a filter query. As the filter should return only one value, that I am validating with this :
And match GetDataSet_Response contains {"totalRows": 1}
The filter is based on Acctid. Now, I need to validate acctID value and entire json schema. How can I do it in KARATE?
In Schema you can define a
The data type of values which you are expecting but don't know the exact values.
Write an expected condition for your data.
Define the variable of data or hardcode data which you already know.
Ignore few data which don't bother.
break down your JSON and create multiple logical schemas(From your JSON you can have a separate schema for "colDefs" and "rowData")
and many more options for complex validations.
I am not sure about your exact requirement, I have tried to create a schema that might suit your requirement.
{
"colDefs": [
{
"entityAttributeId": "acctNm",
"entityId": "account",
"entityPath": "",
"field": "2",
"headerName": "Account Name"
},
{
"entityAttributeId": "acctId",
"entityId": "account",
"entityPath": "",
"field": "1",
"headerName": "Account ID"
}
],
"rowData": [
{
"1": "#string",
"2": "#string",
"rowMeta": {
"account": {
"acctId": "#(acctID)",
"acctInstrumentId": "#string"
}
}
}
],
"totalRows": 1
}
You can store schema in a JSON file / define it directly in your script and match it with your response
assume we stored this schema in a file filterResponseSchema.json
YourFilter.feature
* def acctID = "1939"
# call your filter request
* def myFilterSchema = read('filterResponseSchema.json')
* match response == myFilterSchema
Note:
i) make sure there is a variable name "acctID" before calling this schema so that karate will embed that value to you JSON schema.
ii) my assumption for your "colDefs" values will be always the same, so I hardcoded it.
Karate documentation covers a good amount of example for Schema validation
I suggest you read this for more insights.