I have nested url parameters being passed to an endpoint, and I need these represented in as a JsValue. My initial assumption was that Play would parse them in a way similar to Rails, however parameters seem to only be split by & and =. Example:
Query params: ?test[testkey]=testvalue&test[newkey]=newvalue
Actual:
Map(
"test[testkey]" -> "testvalue" ,
"test[newkey]" -> "newvalue
)
Expected:
Map(
"test" -> Map(
"testkey" -> "testvalue" ,
"newkey" -> "newvalue"
)
)
Note that the end goal here is to be able to convert this into a JsObject.
I've started writing this myself, however simply porting the function from Rack is very un-scala-y and I feel like there has to be a quick way to get this that I am simply missing.
UPDATE
I am trying to find a generic solution which mimics the parsing that Rails uses (ie, with nested objects, lists, etc), and not just one level deep objects.
Just for fun, one option is to do something like:
import scala.util.matching.Regex
val pattern = new Regex("""(\w+)\[(\w+)\]""")
val qs : Map[String, Map[String, List[Seq[String]]]] = request.queryString.toList.map {
case (k, v) =>
pattern findFirstIn k match {
case Some(pattern(key, value)) => (key, value, v)
}
}.groupBy(_._1).mapValues(value => value.groupBy(_._2).mapValues {
value => value.map(x => x._3)
})
To convert this is to a JsValue, we can simply invoke:
import play.api.libs.json.Json
Json.toJson(qs)
This assumes that all your url params look like map[key]=value. You would have to modify the code a little to accommodate the standard key=value pattern.
Related
I have a situation here
I have two strins
val keyMap = "anrodiApp,key1;iosApp,key2;xyz,key3"
val tentMap = "androidApp,tenant1; iosApp,tenant1; xyz,tenant2"
So what I want to add is to create a nested immutable nested map like this
tenant1 -> (andoidiApp -> key1, iosApp -> key2),
tenant2 -> (xyz -> key3)
So basically want to group by tenant and create a map of keyMap
Here is what I tried but is done using mutable map which I do want, is there a way to create this using immmutable map
case class TenantSetting() {
val requesterKeyMapping = new mutable.HashMap[String, String]()
}
val requesterKeyMapping = keyMap.split(";")
.map { keyValueList => keyValueList.split(',')
.filter(_.size==2)
.map(keyValuePair => (keyValuePair[0],keyValuePair[1]))
.toMap
}.flatten.toMap
val config = new mutable.HashMap[String, TenantSetting]
tentMap.split(";")
.map { keyValueList => keyValueList.split(',')
.filter(_.size==2)
.map { keyValuePair =>
val requester = keyValuePair[0]
val tenant = keyValuePair[1]
if (!config.contains(tenant)) config.put(tenant, new TenantSetting)
config.get(tenant).get.requesterKeyMapping.put(requester, requesterKeyMapping.get(requester).get)
}
}
The logic to break the strings into a map can be the same for both as it's the same syntax.
What you had for the first string was not quite right as the filter you were applying to each string from the split result and not on the array result itself. Which also showed in that you were using [] on keyValuePair which was of type String and not Array[String] as I think you were expecting. Also you needed a trim in there to cope with the spaces in the second string. You might want to also trim the key and value to avoid other whitespace issues.
Additionally in this case the combination of map and filter can be more succinctly done with collect as shown here:
How to convert an Array to a Tuple?
The use of the pattern with 2 elements ensures you filter out anything with length other than 2 as you wanted.
The iterator is to make the combination of map and collect more efficient by only requiring one iteration of the collection returned from the first split (see comments below).
With both strings turned into a map it just needs the right use of groupByto group the first map by the value of the second based on the same key to get what you wanted. Obviously this only works if the same key is always in the second map.
def toMap(str: String): Map[String, String] =
str
.split(";")
.iterator
.map(_.trim.split(','))
.collect { case Array(key, value) => (key.trim, value.trim) }
.toMap
val keyMap = toMap("androidApp,key1;iosApp,key2;xyz,key3")
val tentMap = toMap("androidApp,tenant1; iosApp,tenant1; xyz,tenant2")
val finalMap = keyMap.groupBy { case (k, _) => tentMap(k) }
Printing out finalMap gives:
Map(tenant2 -> Map(xyz -> key3), tenant1 -> Map(androidApp -> key1, iosApp -> key2))
Which is what you wanted.
In a PUT request from a client device, I would like the application/json body to look like {"content": []} in order to clear a list I'm maintaining for the client. However, in a Play Form such key-value pair where the value is an empty array disappears after form parsing.
You can see that in regular (non-Form) Play JSON parsing, the empty array is maintained as expected.
[info] Starting scala interpreter...
Welcome to Scala 2.11.12 (OpenJDK 64-Bit Server VM, Java 1.8.0_212).
Type in expressions for evaluation. Or try :help.
scala> import play.api.libs.json._
import play.api.libs.json._
scala> val json = Json.parse("""{"content": []}""")
json: play.api.libs.json.JsValue = {"content":[]}
However, in Play's form parsing, the behavior is different.
private[data] object FormUtils {
def fromJson(prefix: String = "", js: JsValue): Map[String, String] = js match {
case JsObject(fields) =>
val prefix2 = Option(prefix).filterNot(_.isEmpty).map(_ + ".").getOrElse("")
fields.iterator
.map { case (key, value) => fromJson(prefix2 + key, value) }
.foldLeft(Map.empty[String, String])(_ ++ _)
case JsArray(values) =>
values.zipWithIndex.iterator
.map { case (value, i) => fromJson(s"$prefix[$i]", value) }
.foldLeft(Map.empty[String, String])(_ ++ _)
case JsNull => Map.empty
case JsUndefined() => Map.empty
case JsBoolean(value) => Map(prefix -> value.toString)
case JsNumber(value) => Map(prefix -> value.toString)
case JsString(value) => Map(prefix -> value.toString)
}
}
https://github.com/playframework/playframework/blob/826c76ee967d8ec35b76b9a8b594bfaa676a9510/core/play/src/main/scala/play/api/data/Form.scala#L397
The general idea of the function is a recursive traversal of the incoming JSValue objects and arrays where null, undefined, booleans, numbers, strings, and empty objects and arrays serve as base cases.
In the JsArray case, if values is empty then it returns Map.empty[String, String]. As a result, both [] and {"content": []} will be parsed to Map.empty[String, String]. For a form, the [] case seems reasonable, but {"content": []} is a legitimate key-value pair that should be kept in the form. Note that the same issue occurs with an empty JsObject.
Does this seem like a reasonable issue? If so, any workarounds that you can think of? I understand that it could be difficult for Play to change this since users of the framework might already be depending on this behavior.
I think that is correct behavior, since as far as forms are concerned there is no concept of an Array.
A form simply consists of a set of key-value-pairs and an array is just flattened to fit into this scheme, a la path.to.array[0] = value.
The form, however, can then be mapped to a model which actually has a sequence of values.
Say we have an array of one dimensional javascript objects contained in a file Array.json for which the key schema isn't known, that is the keys aren't known until the file is read.
Then we wish to output a CSV file with a header or first entry which is a comma delimited set of keys from all of the objects.
Each next line of the file should contain the comma separated values which correspond to each key from the file.
Array.json
[
abc:123,
xy:"yz",
s12:13,
],
...
[
abc:1
s:133,
]
A valid output:
abc,xy,s12,s
123,yz,13,
1,,,133
I'm teaching myself 'functional style' programming but I'm thinking that this problem doesn't lend itself well to a functional solution.
I believe that this problem requires some state to be kept for the output header and that subsequently each line depends on that header.
I'm looking to solve the problem in a single pass. My goals are efficiency for a large data set, minimal traversals, and if possible, parallelizability. If this isn't possible then can you give a proof or reasoning to explain why?
EDIT: Is there a way to solve the problem like this functionally?:
Say you pass through the array once, in some particular order. Then
from the start the header set looks like abc,xy,s12 for the first
object. With CSV entry 123,yz,13 . Then on the next object we add an
additional key to the header set so abc,xy,s12,s would be the header
and the CSV entry would be 1,,,133 . In the end we wouldn't need to
pass through the data set a second time. We could just append extra
commas to the result set. This is one way we could approach a single
pass....
Are there functional tools ( functions ) designed to solve problems like this, and what should I be considering? [ By functional tools I mean Monads,FlatMap, Filters, etc. ] . Alternatively, should I be considering things like Futures ?
Currently I've been trying to approach this using Java8, but am open to solutions from Scala, etc. Ideally I would be able to determine if Java8s' functional approach can solve the problem since that's the language I'm currently working in.
Since the csv output will change with every new line of input, you must hold that in memory before writing it out. If you consider creating an output text format from an internal representation of a csv file another "pass" over the data (the internal representation of the csv is practically a Map[String,List[String]] which you must traverse to convert it to text) then it's not possible to do this in a single pass.
If, however, this is acceptable, then you can use a Stream to read a single item from your json file, merge that into the csv file, and do this until the stream is empty.
Assuming, that the internal representation of the csv file is
trait CsvFile {
def merge(line: Map[String, String]): CsvFile
}
And you can represent a single item as
trait Item {
def asMap: Map[String, String]
}
You can implement it using foldLeft:
def toCsv(items: Stream[Item]): CsvFile =
items.foldLeft(CsvFile(Map()))((csv, item) => csv.merge(item.asMap))
or use recursion to get the same result
#tailrec def toCsv(items: Stream[Item], prevCsv: CsvFile): CsvFile =
items match {
case Stream.Empty => prevCsv
case item #:: rest =>
val newCsv = prevCsv.merge(item.asMap)
toCsv(rest, newCsv)
}
Note: Of course you don't have to create types for CsvFile or Item, you can use Map[String,List[String]] and Map[String,String] respectively
UPDATE:
As more detail was requested for the CsvFile trait/class, here's an example implementation:
case class CsvFile(lines: Map[String, List[String]], rowCount: Int = 0) {
def merge(line: Map[String, String]): CsvFile = {
val orig = lines.withDefaultValue(List.fill(rowCount)(""))
val current = line.withDefaultValue("")
val newLines = (lines.keySet ++ line.keySet) map {
k => (k, orig(k) :+ current(k))
}
CsvFile(newLines.toMap, rowCount + 1)
}
}
This could be one approach:
val arr = Array(Map("abc" -> 123, "xy" -> "yz", "s12" -> 13), Map("abc" -> 1, "s" -> 133))
val keys = arr.flatMap(_.keys).distinct // get the distinct keys for header
arr.map(x => keys.map(y => x.getOrElse(y,""))) // get an array of rows
Its completely OK to have state in functional programming. But having mutable state or mutating state is not allowed in functional programming.
Functional programming advocates creating new changed state instead of mutating the state in place.
So, its Ok to read and access state created in the program until and unless you are mutating or side effecting.
Coming to the point.
val list = List(List("abc" -> "123", "xy" -> "yz"), List("abc" -> "1"))
list.map { inner => inner.map { case (k, v) => k}}.flatten
list.map { inner => inner.map { case (k, v) => v}}.flatten
REPL
scala> val list = List(List("abc" -> "123", "xy" -> "yz"), List("abc" -> "1"))
list: List[List[(String, String)]] = List(List((abc,123), (xy,yz)), List((abc,1)))
scala> list.map { inner => inner.map { case (k, v) => k}}.flatten
res1: List[String] = List(abc, xy, abc)
scala> list.map { inner => inner.map { case (k, v) => v}}.flatten
res2: List[String] = List(123, yz, 1)
or use flatMap instead of map and flatten
val list = List(List("abc" -> "123", "xy" -> "yz"), List("abc" -> "1"))
list.flatMap { inner => inner.map { case (k, v) => k}}
list.flatMap { inner => inner.map { case (k, v) => v}}
In functional programming, mutable state is not allowed. But immutable states/values are fine.
Assuming that you have read your json file in to a value input:List[Map[String,String]], the codes below will solve your problem:
val input = List(Map("abc"->"123", "xy"->"yz" , "s12"->"13"), Map("abc"->"1", "s"->"33"))
val keys = input.map(_.keys).flatten.toSet
val keyvalues = input.map(kvs => keys.map(k => (k->kvs.getOrElse(k,""))).toMap)
val values = keyvalues.map(_.values)
val result = keys.mkString(",") + "\n" + values.map(_.mkString(",")).mkString("\n")
If I have a a Map which maps values from String to (String,String,String)
How can I remove the second Stringfrom the List that the Map would be like Map( String ->(String,String))
Example:
var mp = Map(
"K1" -> List("K1_C1","K1_C2","K1_C3"),
"K2" -> List("K2_C1","K2_C2","K2_C3"),
"K2" -> List("K3_C1","K3_C2","K3_C3")
)
How can I reach this:
Map(
"K1" -> List("K1_C1","K1_C3"),
"K2" -> List("K2_C1","K2_C3"),
"K2" -> List("K3_C1","K3_C3")
)
What I've tried this but didn't work
mp.mapValues( _.map(_.drop(2)))
Also I've tried to convert the (String,String,String) to Listbut It didn't work
mp.mapValues(_.map(_.toList.remove(2)))
This is like my first time writing in scala because I have to, and I'm tottaly use it like I write Java
You were pretty close with the drop function, but I suggest you take a look at its documentation. It drops the given number of elements from the beginning of the list.
What you actually want is take the first one and takeRight the last one:
mp.mapValues(list => list.take(1) ++ list.takeRight(1))
This is pretty ugly, however. If you are certain that your values are always a 3-element list, I suggest pattern matching just as I showed with tuples:
mp.mapValues {
case List(first, _, third) => List(first, third)
}
It looks like your map has lists of tuples, not lists of strings. Something like this should work:
m.mapValues { case List((a,b,c)) => (a,c) }
or
m.mapValues { case List((a,b,c)) => List((a,c)) }
or
m.mapValues { case List((a,b,c)) => List(a,c) }
... depending on what type of output you want to end up with.
Consider the following from the Scala interpreter:
scala> JSON.parseFull("""{"name":"jack","greeting":"hello world"}""")
res6: Option[Any] = Some(Map(name -> jack, greeting -> hello world))
Why is the Map returned in Some() thing? And how do I work with it?
I want to put the values in an xml template:
<test>
<name>name goes here</name>
<greeting>greeting goes here</greeting>
</test>
What is the Scala way of getting my map out of Some(thing) and getting those values in the xml?
You should probably use something like this:
res6 collect { case x: Map[String, String] => renderXml(x) }
Where:
def renderXml(m: Map[String, String]) =
<test><name>{m.get("name") getOrElse ""}</name></test>
The collect method on Option[A] takes a PartialFunction[A, B] and is a combination of filter (by a predicate) and map (by a function). That is:
opt collect pf
opt filter (a => pf isDefinedAt a) map (a => pf(a))
Are both equivalent. When you have an optional value, you should use map, flatMap, filter, collect etc to transform the option in your program, avoiding extracting the option's contents either via a pattern-match or via the get method. You should never, ever use Option.get - it is the canonical sign that you are doing it wrong. Pattern-matching should be avoided because it represents a fork in your program and hence adds to cyclomatic complexity - the only time you might wish to do this might be for performance
Actually you have the issue that the result of the parseJSON method is an Option[Any] (the reason is that it is an Option, presumably, is that the parsing may not succeed and Option is a more graceful way of handling null than, well, null).
But the issue with my code above is that the case x: Map[String, String] cannot be checked at runtime due to type erasure (i.e. scala can check that the option contains a Map but not that the Map's type parameters are both String. The code will get you an unchecked warning.
An Option is returned because parseFull has different possible return values depending on the input, or it may fail to parse the input at all (giving None). So, aside from an optional Map which associates keys with values, an optional List can be returned as well if the JSON string denoted an array.
Example:
scala> import scala.util.parsing.json.JSON._
import scala.util.parsing.json.JSON._
scala> parseFull("""{"name":"jack"}""")
res4: Option[Any] = Some(Map(name -> jack))
scala> parseFull("""[ 100, 200, 300 ]""")
res6: Option[Any] = Some(List(100.0, 200.0, 300.0))
You might need pattern matching in order to achieve what you want, like so:
scala> parseFull("""{"name":"jack","greeting":"hello world"}""") match {
| case Some(m) => Console println ("Got a map: " + m)
| case _ =>
| }
Got a map: Map(name -> jack, greeting -> hello world)
Now, if you want to generate XML output, you can use the above to iterate over the key/value pairs:
import scala.xml.XML
parseFull("""{"name":"jack","greeting":"hello world"}""") match {
case Some(m: Map[_,_]) =>
<test>
{
m map { case (k,v) =>
XML.loadString("<%s>%s</%s>".format(k,v,k))
}
}
</test>
case _ =>
}
parseFull returns an Option because the string may not be valid JSON (in which case it will return None instead of Some).
The usual way to get the value out of a Some is to pattern match against it like this:
result match {
case Some(map) =>
doSomethingWith(map)
case None =>
handleTheError()
}
If you're certain the input will always be valid and so you don't need to handle the case of invalid input, you can use the get method on the Option, which will throw an exception when called on None.
You have two separate problems.
It's typed as Any.
Your data is inside an Option and a Map.
Let's suppose we have the data:
val x: Option[Any] = Some(Map("name" -> "jack", "greeting" -> "hi"))
and suppose that we want to return the appropriate XML if there is something to return, but not otherwise. Then we can use collect to gather those parts that we know how to deal with:
val y = x collect {
case m: Map[_,_] => m collect {
case (key: String, value: String) => key -> value
}
}
(note how we've taken each entry in the map apart to make sure it maps a string to a string--we wouldn't know how to proceed otherwise. We get:
y: Option[scala.collection.immutable.Map[String,String]] =
Some(Map(name -> jack, greeting -> hi))
Okay, that's better! Now if you know which fields you want in your XML, you can ask for them:
val z = for (m <- y; name <- m.get("name"); greet <- m.get("greeting")) yield {
<test><name>{name}</name><greeting>{greet}</greeting></test>
}
which in this (successful) case produces
z: Option[scala.xml.Elem] =
Some(<test><name>jack</name><greeting>hi</greeting></test>)
and in an unsuccessful case would produce None.
If you instead want to wrap whatever you happen to find in your map in the form <key>value</key>, it's a bit more work because Scala doesn't have a good abstraction for tags:
val z = for (m <- y) yield <test>{ m.map { case (tag, text) => xml.Elem(null, tag, xml.Null, xml.TopScope, xml.Text(text)) }}</test>
which again produces
z: Option[scala.xml.Elem] =
Some(<test><name>jack</name><greeting>hi</greeting></test>)
(You can use get to get the contents of an Option, but it will throw an exception if the Option is empty (i.e. None).)