I have the following code:
def customers = Customer.findAll()
def json = new JsonBuilder()
json {
customers.each { customer ->
id customer.id
name customer.name
address customer.address
}
}
I'm expecting that the result is an json array of customers, but instead it only contains 1 customer. Note the customers list contains 2 elements.
I saw some other post mentioning to use something like:
customers.collect {
Customer c -> [id: c.id, name: c.name, address: c.address]
}
But this style does not really fit nicely in the builder. E.g. I have to use colons : to assign values.
Is there another approach without creating groovy objects?
What you need is just this.
def json = new JsonBuilder( customers )
if there are no additional item in customer that is not required in the json.
No, json is a map, and you need a list of maps. What you are doing with each is re-assigning the id, name and address fields, so you just get the last value.
So you need to collect a list of maps together as you have in the question.
Related
I am trying to turn a data frame into some nested json and have been struggling a bit. Here is an example I created. The use case is to split a document for each guest at a hotel chain, with the guest at the top, the hotel details under the visit data, and the daily charges under the 'measurements' info.
The dataframe:
Here is an example of how I am trying to get the JSON to look
I have tried creating a multilevel index and using to_json:
Is there a way to do this using to_json() or will I need to build some nested loops to create nested dictionaries? This is the best I have been able to get:
I would recommend a programming approach. pandas.DataFrame.groupby can be useful.
def hotel_data_to_json(df):
return [
person_data_to_json(person_df)
for person_id, person_df
in df.groupby('person_id')
]
def person_data_to_json(df):
row = df.iloc[0]
return {
'person_id': row['person_id'],
'personal_name': row['personal_name'],
'family_name': row['family_name'],
'visits': [
visit_data_to_json(visit_df)
for visit_id, visit_df
in df.groupby('visit_id')
]
}
def visit_data_to_json(df):
row = df.iloc[0]
# and so on
I have in my bucket a document containing a list of ID (childList).
I would like to query over this list and keep the result ordered like in my JSON. My query is like (using java SDK) :
String query = new StringBuilder().append("SELECT B.name, META(B).id as id ")
.append("FROM" + bucket.name() + "A ")
.append("USE KEYS $id ")
.append("JOIN" + bucket.name() + "B ON KEYS ARRAY i FOR i IN A.childList end;").toString();
This query will return rows that I will transform into my domain object and create a list like this :
n1qlQueryResult.allRows().forEach(n1qlQueryRow -> (add to return list ) ...);
The problem is the output order is important.
Any ideas?
Thank you.
here is a rough idea of a solution without N1QL, provided you always start from a single A document:
List<JsonDocument> listOfBs = bucket
.async()
.get(idOfA)
.flatMap(doc -> Observable.from(doc.content().getArray("childList")))
.concatMapEager(id -> bucket.async().get(id))
.toList()
.toBlocking().first();
You might want another map before the toList to extract the name and id, or to perform your domain object transformation even maybe...
The steps are:
use the async API
get the A document
extract the list of children and stream these ids
asynchronously fetch each child document and stream them but keeping them in original order
collect all into a List<JsonDocument>
block until the list is ready and return that List.
I am using Dell Boomi to map data from one system to another. I can use groovy in the maps but have no experience with it. I tried to do this with the other Boomi tools, but have been told that I'll need to use groovy in a script. My inbound data is:
132265,Brown
132265,Gold
132265,Gray
132265,Green
I would like to output:
132265,"Brown,Gold,Gray,Green"
Hopefully this makes sense! Any ideas on the groovy code to make this work?
It can be elegantly solved with groupBy and the spread operator:
#Grapes(
#Grab(group='org.apache.commons', module='commons-csv', version='1.2')
)
import org.apache.commons.csv.*
def csv = '''
132265,Brown
132265,Gold
132265,Gray
132265,Green
'''
def parsed = CSVParser.parse(csv, CSVFormat.DEFAULT.withHeader('code', 'color')
parsed.records.groupBy({ it.code }).each { k,v -> println "$k,\"${v*.color.join(',')}\"" }
The above prints:
132265,"Brown,Gold,Gray,Green"
Well, I don't know how are you getting your data, but here is a general way to achieve your goal. You can use a library, such as the one bellow to parse the csv.
https://github.com/xlson/groovycsv
The example for your data would be:
#Grab('com.xlson.groovycsv:groovycsv:1.1')
import static com.xlson.groovycsv.CsvParser.parseCsv
def csv = '''
132265,Brown
132265,Gold
132265,Gray
132265,Green
'''
def data = parseCsv(csv)
I believe you want to associate the number with various values of colors. So for each line you can create a map of the number and the colors associated with that number, splitting the line by ",":
map = [:]
for(line in data) {
number = line.split(',')[0]
colour = line.split(',')[1]
if(!map[number])
map[number] = []
map[number].add(colour)
}
println map
So map should contain:
[132265:["Brown","Gold","Gray","Green"]]
Well, if it is not what you want, you can extract the general idea.
Assuming your data is coming in as a comma separated string of data like this:
"132265,Brown 132265,Gold 132265,Gray 132265,Green 122222,Red 122222,White"
The following Groovy script code should do the trick.
def csvString = "132265,Brown 132265,Gold 132265,Gray 132265,Green 122222,Red 122222,White"
LinkedHashMap.metaClass.multiPut << { key, value ->
delegate[key] = delegate[key] ?: []; delegate[key] += value
}
def map = [:]
def csv = csvString.split().collect{ entry -> entry.split(",") }
csv.each{ entry -> map.multiPut(entry[0], entry[1]) }
def result = map.collect{ k, v -> k + ',"' + v.join(",") + '"'}.join("\n")
println result
Would print:
132265,"Brown,Gold,Gray,Green"
122222,"Red,White"
Do you HAVE to use scripting for some reason? This can be easily accomplished with out-of-the-box Boomi functionality.
Create a map function that prepends the ID field to a string of your choice (i.e. 222_concat_fields). Then use that value to set a dynamic process prop with that value.
The value of the process prop will contain the result of concatenating the name fields. Simply adding this function to your map should take care of it. Then use the final value to populate your result.
Well it depends upon the data how is it coming.
If the data which you have posted in the question is coming in a single document, then you can easily handle this in a map with groovy scripting.
If the data which you have posted in the question is coming into multiple documents i.e.
doc1: 132265,Brown
doc2: 132265,Gold
doc3: 132265,Gray
doc4: 132265,Green
In that case it cannot be handled into map. You will need to use Data Process Step with Custom Scripting.
For the code which you are asking to create in groovy depends upon the input profile in which you are getting the data. Please provide more information i.e. input profile, fields etc.
I am building a CSV file parser through node and Angular . so basically a user upload a csv file , on my server side which is node the csv file is traversed and parsed using node-csv
. This works fine and it returns me an array of object based on csv file given as input , Now on angular end I need to display two table one is csv file data itself and another is cross tabulation analysis. I am facing problem while rendering data, so for a table like
I am getting parse responce as
For cross tabulation we need data in a tabular form as
I have a object array which I need to manipulate in best possible way so as to make easily render on html page . I am not getting a way how to do calculation on data I get so as to store cross tabulation result .Any idea on how should I approach .
data json is :
[{"Sample #":"1","Gender":"Female","Handedness;":"Right-handed;"},{"Sample #":"2","Gender":"Male","Handedness;":"Left-handed;"},{"Sample #":"3","Gender":"Female","Handedness;":"Right-handed;"},{"Sample #":"4","Gender":"Male","Handedness;":"Right-handed;"},{"Sample #":"5","Gender":"Male","Handedness;":"Left-handed;"},{"Sample #":"6","Gender":"Male","Handedness;":"Right-handed;"},{"Sample #":"7","Gender":"Female","Handedness;":"Right-handed;"},{"Sample #":"8","Gender":"Female","Handedness;":"Left-handed;"},{"Sample #":"9","Gender":"Male","Handedness;":"Right-handed;"},{"Sample #":";"}
There are many ways you can do this and since you have not been very specific on the usage, I will go with the simplest one.
Assuming you have an object structure such as this:
[
{gender: 'female', handdness: 'lefthanded', id: 1},
{gender: 'male', handdness: 'lefthanded', id: 2},
{gender: 'female', handdness: 'righthanded', id: 3},
{gender: 'female', handdness: 'lefthanded', id: 4},
{gender: 'female', handdness: 'righthanded', id: 5}
]
and in your controller you have exposed this with something like:
$scope.members = [the above array of objects];
and you want to display the total of female members of this object, you could filter this in your html
{{(members | filter:{gender:'female'}).length}}
Now, if you are going to make this a table it will obviously make some ugly and unreadable html so especially if you are going to repeat using this, it would be a good case for making a directive and repeat it anywhere, with the prerequisite of providing a scope object named tabData (or whatever you wish) in your parent scope
.directive('tabbed', function () {
return {
restrict: 'E',
template: '<table><tr><td>{{(tabData | filter:{gender:"female"}).length}}</td></tr><td>{{(tabData | filter:{handedness:"lefthanded"}).length}}</td></table>'
}
});
You would use this in your html like so:
<tabbed></tabbed>
And there are ofcourse many ways to improve this as you wish.
This is more of a general data structure/JS question than Angular related.
Functional helpers from Lo-dash come in very handy here:
_(data) // Create a chainable object from the data to execute functions with
.groupBy('Gender') // Group the data by its `Gender` attribute
// map these groups, using `mapValues` so the named `Gender` keys persist
.mapValues(function(gender) {
// Create named count objects for all handednesses
var counts = _.countBy(gender, 'Handedness');
// Calculate the total of all handednesses by summing
// all the values of this named object
counts.Total = _(counts)
.values()
.reduce(function(sum, num) { return sum + num });
// Return this named count object -- this is what each gender will map to
return counts;
}).value(); // get the value of the chain
No need to worry about for-loops or anything of the sort, and this code also works without any changes for more than two genders (even for more than two handednesses - think of the aliens and the ambidextrous). If you aren't sure exactly what's happening, it should be easy enough to pick apart the single steps and their result values of this code example.
Calculating the total row for all genders will work in a similar manner.
This should be a fairly simple one.
myobject has various properties, _id, name, createdBy, date etc
In my find query I want to only return specific fields from within myObject. So for example, what would I need to do to modify the find query below so that only name was returned?
myCollection.find({createdBy: someId}, {fields: {myObject: 1}}).fetch();
Currently this will return everything in myObject which it should do, I just want one field within myObject returned.
Here is a way to do it within the query:
myCollection.find({createdBy: someId}, {fields: {'myObject.name':
1}}).fetch();
Note the quotes around
'myObject.name'
Lets assume we are talking about posts, and a post document looks like this:
{
_id: 'abc123',
title: 'All about meteor',
author: {
firstName: 'David',
lastName: 'Weldon'
}
}
You can then extract all of the last names from all of the authors with this:
var lastNames = Posts.find().map(function(post) {
return post.author.lastName;
});
Modify the selector and options as needed for your collection. Using fields in this case may be a small optimization if you are running this on the server and fetching the data directly from the DB.