I have a list of values that I can use for the title field in my json request. I would like to store a function in the common.feature file which randomizes the title value when a scenario is executed.
I have attempted using the random number function provided on the commonly needed utilities tab on the readme. I have generated a random number successfully, the next step would be using that randomly gernerated number within the jsonpath line in order to retrieve a value from my data list which is in json.
* def myJson =
"""
{
"title" : {
"type" : "string",
"enum" : [
"MR",
"MRS",
"MS",
"MISS"
[...]
]
}
}
"""
* def randomNumber = random(3)
* def title = get[0] myJson.title.enum
* print title```
The code above works but I would like to randomize the number within the get[0]. How is this possible in Karate?
I'm not sure of what you want, but can't you just replace 0 by randomNumber in get[randomNumber] myJson.title.enum ?
Related
this is my test json file.
{
"item" : {
"fracData" : [ ],
"fractimeData" : [ {
"number" : "1232323232",
"timePeriods" : [ {
"validFrom" : "2021-08-03"
} ]
} ],
"Module" : [ ]
}
}
This is how I read the json file.
starhist_test_df = spark.read.json("/mapr/xxx/yyy/ttt/dev/rawdata/Test.json", multiLine=True)
starhist_test_df.createOrReplaceTempView("v_test_df")
This query works.
df_test_01 = spark.sql("""
select item.fractimeData.number from v_test_df""")
df_test_01.collect();
Result
[Row(number=['1232323232'])]
But this query doesn't work.
df_test_01 = spark.sql("""
select item.fractimeData.timePeriods.validFrom from v_test_df""")
df_test_01.collect();
Error
cannot resolve 'v_test_df.`item`.`fractimeData`.`timePeriods`['validFrom']' due to data type mismatch: argument 2 requires integral type, however, ''validFrom'' is of string type.; line 3 pos 0;
What do I have to change, to read the validFrom field?
dot notation to access values works with struct or array<struct> types.
The schema for field number in item.fractimeData is string and accessing it via dot notation returns an array<string> since fractimeData is an array.
Similarly, the schema for field timePeriods in item.fractimeData is <array<struct<validFrom>>, and accessing it via dot notation wraps it into another array, resulting in final schema of array<array<struct<validFrom>>>.
The error you get is because the dot notation can work on array<struct> but not on array<array>.
Hence, flatten the result from item.fractimeData.timePeriods to get back an array<struct<validFrom>> and then apply the dot notation.
df_test_01 = spark.sql("""
select flatten(item.fractimeData.timePeriods).validFrom as validFrom from v_test_df""")
df_test_01.collect()
"""
[Row(validFrom=['2021-08-03', '2021-08-03'])]
"""
I'm creating an AWS Step Function definition in Dhall. However, I don't know how to create a common structure they use for Choice states such as the example below:
{
"Not": {
"Variable": "$.type",
"StringEquals": "Private"
},
"Next": "Public"
}
The Not is pretty straightforward using mapKey and mapValue. If I define a basic Comparison:
{ Type =
{ Variable : Text
, StringEquals : Optional Text
}
, default =
{ Variable = "foo"
, StringEquals = None Text
}
}
And the types:
let ComparisonType = < And | Or | Not >
And adding a helper function to render the type as Text for the mapKey:
let renderComparisonType = \(comparisonType : ComparisonType )
-> merge
{ And = "And"
, Or = "Or"
, Not = "Not"
}
comparisonType
Then I can use them in a function to generate the record halfway:
let renderRuleComparisons =
\( comparisonType : ComparisonType ) ->
\( comparisons : List ComparisonOperator.Type ) ->
let keyName = renderComparisonType comparisonType
let compare = [ { mapKey = keyName, mapValue = comparisons } ]
in compare
If I run that using:
let rando = ComparisonOperator::{ Variable = "$.name", StringEquals = Some "Cow" }
let comparisons = renderRuleComparisons ComparisonType.Not [ rando ]
in comparisons
Using dhall-to-json, she'll output the first part:
{
"Not": {
"Variable": "$.name",
"StringEquals": "Cow"
}
}
... but I've been struggling to merge that with "Next": "Sup". I've used all the record merges like /\, //, etc. and it keeps giving me various type errors I don't truly understand yet.
First, I'll include an approach that does not type-check as a starting point to motivate the solution:
let rando = ComparisonOperator::{ Variable = "$.name", StringEquals = Some "Cow" }
let comparisons = renderRuleComparisons ComparisonType.Not [ rando ]
in comparisons # toMap { Next = "Public" }
toMap is a keyword that converts records to key-value lists, and # is the list concatenation operator. The Dhall CheatSheet has a few examples of how to use both of them.
The above solution doesn't work because # cannot merge lists with different element types. The left-hand side of the # operator has this type:
comparisons : List { mapKey : Text, mapValue : Comparison.Type }
... whereas the right-hand side of the # operator has this type:
toMap { Next = "Public" } : List { mapKey : Text, mapValue : Text }
... so the two Lists cannot be merged as-is due to the different types for the mapValue field.
There are two ways to resolve this:
Approach 1: Use a union whenever there is a type conflict
Approach 2: Use a weakly-typed JSON representation that can hold arbitrary values
Approach 1 is the simpler solution for this particular example and Approach 2 is the more general solution that can handle really weird JSON schemas.
For Approach 1, dhall-to-json will automatically strip non-empty union constructors (leaving behind the value they were wrapping) when translating to JSON. This means that you can transform both arguments of the # operator to agree on this common type:
List { mapKey : Text, mapValue : < State : Text | Comparison : Comparison.Type > }
... and then you should be able to concatenate the two lists of key-value pairs and dhall-to-json will render them correctly.
There is a second solution for dealing with weakly-typed JSON schemas that you can learn more about here:
Dhall Manual - How to convert an existing YAML configuration file to Dhall
The basic idea is that all of the JSON/YAML integrations recognize and support a weakly-typed JSON representation that can hold arbitrary JSON data, including dictionaries with keys of different shapes (like in your example). You don't even need to convert the entire the expression to this weakly-typed representation; you only need to use this representation for the subset of your configuration where you run into schema issues.
What this means for your example, is that you would change both arguments to the # operator to have this type:
let Prelude = https://prelude.dhall-lang.org/v12.0.0/package.dhall
in List { mapKey : Text, mapValue : Prelude.JSON.Type }
The documentation for Prelude.JSON.Type also has more details on how to use this type.
slurperresponse = new JsonSlurper().parseText(responseContent)
log.info (slurperresponse.WorkItems[0].WorkItemExternalId)
The above code helps me get the node value "WorkItems[0].WorkItemExternalId" using Groovy. Below is the response.
{
"TotalRecordCount": 1,
"TotalPageCount": 1,
"CurrentPage": 1,
"BatchSize": 10,
"WorkItems": [ {
"WorkItemUId": "4336c111-7cd6-4938-835c-3ddc89961232",
"WorkItemId": "20740900",
"StackRank": "0",
"WorkItemTypeUId": "00020040-0200-0010-0040-000000000000",
"WorkItemExternalId": "79853"
}
I need to append the string "WorkItems[0].WorkItemExternalId" (being read from a excel file) and multiple other such nodes dynamically to "slurperresponse" to get the value of nodes rather than directly hard coding as slurperresponse.WorkItems[0].WorkItemExternalId..
Tried append and "+" operator but i get a compilation error. What other way can I do this?
slurperrsesponse is an object its not a string that's why the concatenation does not work
Json Slurper creates an object out of the input string. This object is dynamic by nature, you can access it, you can add fields to it or alter the existing fields. Contatenation won't work here.
Here is an example:
import groovy.json.*
def text = '{"total" : 2, "students" : [{"name": "John", "age" : 20}, {"name": "Alice", "age" : 21}] }'
def json = new JsonSlurper().parseText(text)
json.total = 3 // alter the value of the existing field
json.city = 'LA' // add a totally new field
json.students[0].age++ // change the field in a list
println json
This yields the output:
[total:3, students:[[name:John, age:21], [name:Alice, age:21]], city:LA]
Now if I've got you right you want to add a new student dynamically and the input is a text that you've read from Excel. So here is the example:
json.students << new JsonSlurper().parseText('{"name" : "Tom", "age" : 25}')
// now there are 3 students in the list
Update
Its also possible to get the values without 'hardcoding' the property name:
// option 1
println json.city // prints 'LA'
// option 2
println json.get('city') // prints 'LA' but here 'city' can be a variable
// option 3
println json['city'] // the same as option 2
I am trying to use JSX to convert a list of tuples to a JSON object.
The list items are based on a record definition:
-record(player, {index, name, description}).
and looks like this:
[
{player,1,"John Doe","Hey there"},
{player,2,"Max Payne","I am here"}
]
The query function looks like this:
select_all() ->
SelectAllFunction =
fun() ->
qlc:eval(qlc:q(
[Player ||
Player <- mnesia:table(player)
]
))
end,
mnesia:transaction(SelectAllFunction).
What's the proper way to make it convertable to a JSON knowing that I have a schema of the record used and knowing the structure of tuples?
You'll have to convert the record into a term that jsx can encode to JSON correctly. Assuming you want an array of objects in the JSON for the list of player records, you'll have to either convert each player to a map or list of tuples. You'll also have to convert the strings to binaries or else jsx will encode it to a list of integers. Here's some sample code:
-record(player, {index, name, description}).
player_to_json_encodable(#player{index = Index, name = Name, description = Description}) ->
[{index, Index}, {name, list_to_binary(Name)}, {description, list_to_binary(Description)}].
go() ->
Players = [
{player, 1, "John Doe", "Hey there"},
% the following is just some sugar for a tuple like above
#player{index = 2, name = "Max Payne", description = "I am here"}
],
JSON = jsx:encode(lists:map(fun player_to_json_encodable/1, Players)),
io:format("~s~n", [JSON]).
Test:
1> r:go().
[{"index":1,"name":"John Doe","description":"Hey there"},{"index":2,"name":"Max Payne","description":"I am here"}]
Rails 5 now support native JSON data type in MySQL, so if I have a column data that contains an array: ["a", "b", "c"], and I want to search if this column contains values, so basically I would like to have something like: data_json_cont: ["b"]. So can this query be built using ransack ?
Well I found quite some way to do this with Arrays(not sure about json contains for hash in mysq). First include this code in your active record model:
self.columns.select{|column| column.type == :json}.each do |column|
ransacker "#{column.name}_json_contains".to_sym,
args: [:parent, :ransacker_args] do |parent, args|
query_parts = args.map do |val|
"JSON_CONTAINS(#{column.name}, '#{val.to_json}')"
end
query = query_parts.join(" * ")
Arel.sql(query)
end
end
Then assuming you have class Shirt with column size, then you can do the following:
search = Shirt.ransack(
c: [{
a: {
'0' => {
name: 'size_json_contains',
ransacker_args: ["L", "XL"]
}
},
p: 'eq',
v: [1]
}]
)
search.result
It works as follows: It checks that the array stored in the json column contains all elements of the asked array, by getting the result of each json contains alone, then multiplying them all, and comparing them to arel predicate eq with 1 :) You can do the same with OR, by using bitwise OR instead of multiplication.