I would like to write a unittest to the function
import com.github.nscala_time.time.Imports.{DateTime, richReadableInstant}
def myFunction(ts: Long):Long = {
(new DateTime(ts) to DateTime.now()).toDurationMillis
}
Is it possible to somehow mock Datetime.now(), so that the test result does not depend on when the test is running?
From what I can see this library is a wrapper around joda-time (which, as the official documentation recommends, should be dropped in favor of java.time, but I assume you have some constraint that forces you to work on a pre-Java 8 release).
joda-time comes with a collection of static helpers that, among other things, allow you to manage what the response is when a method asks for the "current time" (see their JavaDoc here).
The easiest possible way (but possibly prone to mistakes due to the shared mutable state it relies on) would look like the following:
import com.github.nscala_time.time.Imports.{DateTime, richReadableInstant}
import org.joda.time.DateTimeUtils
DateTimeUtils.setCurrentMillisFixed(42)
def myFunction(ts: Long):Long = {
(new DateTime(ts) to DateTime.now()).toDurationMillis
}
assert(myFunction(42) == 0)
You can play around with this code here on Scastie.
As mentioned, this approach is a bit clunky and relies on shared mutable state, which makes it prone to confusing errors. You can build a nice small helper to make sure you can use a custom clock on a specific test and reset to the system clock once done. The required synchronization means a performance hit, but it's probably acceptable for your tests.
import com.github.nscala_time.time.Imports.{DateTime, richReadableInstant}
import org.joda.time.DateTimeUtils
import org.joda.time.DateTimeUtils.MillisProvider
def myFunction(ts: Long):Long = {
(new DateTime(ts) to DateTime.now()).toDurationMillis
}
final class FixedClock(at: Long) extends MillisProvider {
override def getMillis(): Long = at
}
def withCustomClock[A](clock: MillisProvider)(f: => A): A = {
synchronized {
try {
DateTimeUtils.setCurrentMillisProvider(clock)
f
} finally {
DateTimeUtils.setCurrentMillisSystem() // _always_ reset to the system clock once done
}
}
}
assert(myFunction(42) > 1000000)
withCustomClock(new FixedClock(at = 42)) {
assert(myFunction(42) == 0)
Thread.sleep(1000)
assert(myFunction(42) == 0)
}
assert(myFunction(42) > 1000000)
You can play around with this other example here on this other worksheet on Scastie.
After migrating from scala.js 0.6.x to 1.0, I've got some code related to #JSGlobalScope broken.
My use case is like this:
there's a 3rd-party library that expects some global var to be set to a function
when loaded and ready, it calls this function (by name)
I set this function in global scope from scala.js
The code looks like this:
#js.native
#JSGlobalScope
object Globals extends js.Object {
var callbackFunctionFor3rdPartyLib: js.Function0[Unit] = js.native
}
then I set this var like this:
Globals.callbackFunctionFor3rdPartyLib = () => {
// do things
}
and then I add the script into the DOM.
This was working with scala.js 0.6.x, but with 1.0 I'm getting an exception like the following:
scala.scalajs.js.JavaScriptException: ReferenceError: callbackFunctionFor3rdPartyLib is not defined
In the changelog for 1.0.0 there's a "Breaking changes" section that mentions this:
Accessing a member that is not declared causes a ReferenceError to be thrown
...
js.Dynamic.global.globalVarThatDoesNotExist = 42
would previously create said global variable. In Scala.js 1.x, it also throws a ReferenceError.
My question is:
what is the right way to do something like this (create a new global var) in scala.js 1.0?
If you know you'll always be in a browser context, you can use #JSGlobal("window") instead of #JSGlobalScope on your Globals, which will then be equivalent to doing window.myGlobalVarFor3rdPartyLib in JS. So that will work.
#js.native
#JSGlobal("window")
object Globals extends js.Object {
var callbackFunctionFor3rdPartyLib: js.Function0[Unit] = js.native
}
If not, but you are using a script (so not a CommonJS nor an ES module), the best thing is actually to use
object Globals {
#JSExportTopLevel("myGlobalVarFor3rdPartyLib")
var foo: js.Function[Unit] = ...
}
Note that Globals is a normal Scala object now, not a JS one.
The #JSExportTopLevel creates a top-level var myGlobalVarFor3rdPartyLib at the top of the script, and then assigning Globals.foo will also assign that top-level var.
If you're not using a script nor know that you're going to always be in a browser, then you need to figure out the global object yourself. Scala.js 0.6.x tried to do that for you, but could fail, so we don't do that anymore. You can at least follow the "instructions" on the documentation of js.special.fileLevelThis to reproduce what Scala.js 0.6.x was doing. I repeat the instructions here:
Using this value should be rare, and mostly limited to writing code
detecting what the global object is. For example, a typical detection
code--in case we do not need to worry of ES modules--looks like:
val globalObject = {
import js.Dynamic.{global => g}
if (js.typeOf(g.global) != "undefined" && (g.global.Object eq g.Object)) {
// Node.js environment detected
g.global
} else {
// In all other well-known environment, we can use the global `this`
js.special.fileLevelThis
}
}
Note that the above code is not comprehensive, as there can be JavaScript
environments where the global object cannot be fetched neither through
global nor this. If your code needs to run in such an environment, it
is up to you to use an appropriate detection procedure.
Is it possible to take a string/AST of source code and evaluate it (like eval()) at runtime in Fantom? I found some suggesting features in the documentation but not obvious evidence.
It's not as easy as calling an eval() function, but it is possible. You need to first compile your Fantom code into a class before you can execute it.
Plastic, a library from Alien-Factory, does just that. Example:
using afPlastic
class Example {
Void main() {
eval("2 + 2") // --> 4
}
Obj? eval(Str code) {
model := PlasticClassModel("MyClass", true)
model.addMethod(Obj?#, "eval", "", code)
myType := PlasticCompiler().compileModel(model.toFantomCode)
return myType.make->eval()
}
}
The PlasticCompiler class does the job of compiling Fantom code into a usable Type.
It uses the Fantom compiler library and is based on code found in Fansh - a Fantom shell, part of the Fantom distribution.
Solved. IntelliJ didn't highlight the fact that my imports were incomplete.
Hi,
I have a simple Scala program that I'm trying to develop using jMock. Setting basic expectations works nicely but for some reason Scala does not understand my attempt to return a value from a mock object. My maven build spews out the following error
TestLocalCollector.scala:45: error: not found: value returnValue
one (nodeCtx).getParameter("FilenameRegex"); will( returnValue(regex))
^
And the respective code snippets are
#Before def setUp() : Unit = { nodeCtx = context.mock(classOf[NodeContext]) }
...
// the value to be returned
val regex = ".*\\.data"
...
// setting the expectations
one (nodeCtx).getParameter("FilenameRegex"); will( returnValue(regex))
To me it sounds that Scala is expecting that the static jMock method returnValue would be a val? What am I missing here?
Are you sure about the ';'?
one (nodeCtx).getParameter("FilenameRegex") will( returnValue(regex))
might work better.
In this example you see a line like:
expect {
one(blogger).todayPosts will returnValue(List(Post("...")))
}
with the following comment:
Specify what the return value should be in the same expression by defining "will" as Scala infix operator.
In the Java equivalent we would have to make a separate method call (which our favorite IDE may insist on putting on the next line!)
one(blogger).todayPosts; will(returnValue(List(Post("..."))))
^
|
-- semicolon only in the *Java* version
The OP explains it himself:
the returnValue static method was not visible, thus the errors.
And the will method just records an action on the latest mock operation, that's why it can be on the next line or after the semicolon :)
import org.jmock.Expectations
import org.jmock.Expectations._
...
context.checking(
new Expectations {
{ oneOf (nodeCtx).getParameter("FilenameRegex") will( returnValue(".*\\.data") ) }
}
)
Recommendations for languages with native (so no FSM generation tools) support for state machine development and execution and passing of messages/signals. This is for telecoms, e.g implementation of FSMs of this level of complexity.
I have considered Erlang, but would love some feedback, suggestions, pointer to tutorials, alternatives, particularly Java based frameworks. Maybe Scala?
Open source only. I'm not looking for UML or regular expression related solutions.
As this is for the implementation of telecoms protocols the FSMs may be non-trivial. Many states, many transitions, signal based, input constraints/guards. Dynamic instantiation would be a plus. Switch statements are out of the question, it quickly nests to unusable. It's barely better that if/else.
I would prefer to not depend on graphical design; the format FSM description should be human readable/editable/manageable.
--
I have decided to focus on an Actor based solution for C++
For example, the Theron framework provides a starting point http://theron.ashtonmason.net/ and to avoid switch statements in the FSM based event handler this C++ FSM Template Framework looks useful http://satsky.spb.ru/articles/fsm/fsmEng.php
This particular application, telco protocol implementation, is what Erlang was built for. The initial applications of Erlang at Ericsson were telephone switches and the earliest commercial products were ATM switches supporting all manner of telco protocols.
OTP has a standard behaviour for implementing FSMs called gen_fsm. There's an example of its use in a non-trivial FSM in some of the OTP Documentation.
OSERL is an open souce SMPP implementation in Erlang and demonstrates how you can implement a telco protocol using gen_fsms. A good example to look at would be gen_esme_session.
While I can't point you to the code, I know there are quite a few Erlang companies selling telco oriented products: Corelatus, Synapse, Motivity among others.
I agree that switch statements should be out of the question... they eventually lead to maintenance nightmares. Can't you use the State Pattern to implement your FSM? Depending on your actual implementation, you could use actors (if you have multiple FSM collaborating - hm... is that possible?). The nice thing about actors is that the framework for passing messages is already there.
An example of using State would be:
trait State {
def changeState(message: Any): State
}
trait FSM extends Actor {
var state: State
def processMessage(message: Any) {
state = state.changeState(message)
}
override def act() {
loop {
react {
case m: Any => processMessage(m)
}
}
}
}
This is very basic code, but as I don't know more of the requirements, that's the most I can think of. The advantage of State is that every state is self-contained in one class.
I disagree that FSM are trivial to implement. This is very short-sighted, and shows either a lack of familiarity with the alternatives, or the lack of experience with complex state machines.
The fundamental problem is that a state machine graph is obvious, but FSM code is not. Once you get beyond a dozen states and a score of transitions, FSM code becomes ugly and difficult to follow.
There are tools whereby you draw the state machine, and generate Java code for it. I don't know of any open source tools for that, however.
Now, getting back to Erlang/Scala, Scala has Actors and message passing as well, and is based on the JVM, so it might be a better alternative than Erlang given your constraints.
There's a DFA/NFA library on Scala as well, though it is not particularly a good one. It supports conversion from arbitrary regular expressions (ie, the literals need not be characters) into DFA/NFA.
I'll post some code below using it. In this code, the idea is creating a FSM which will accept any sequential combination of arbitrary prefixes for a list of words, the idea being looking up menu options without predefined keybinds.
import scala.util.regexp._
import scala.util.automata._
// The goal of this object below is to create a class, MyChar, which will
// be the domain of the tokens used for transitions in the DFA. They could
// be integers, enumerations or even a set of case classes and objects. For
// this particular code, it's just Char.
object MyLang extends WordExp {
type _regexpT = RegExp
type _labelT = MyChar
case class MyChar(c:Char) extends Label
}
// We now need to import the types we defined, as well as any classes we
// created extending Label.
import MyLang._
// We also need an instance (singleton, in this case) of WordBerrySethi,
// which will convert the regular expression into an automatum. Notice the
// language being used is MyLang.
object MyBerrySethi extends WordBerrySethi {
override val lang = MyLang
}
// Last, a function which takes an input in the language we defined,
// and traverses the DFA, returning whether we are at a sink state or
// not. For other uses it will probably make more sense to test against
// both sink states and final states.
def matchDet(pat: DetWordAutom[MyChar], seq: Seq[Char]): Boolean =
!pat.isSink((0 /: seq) ((state, c) => pat.next(state, MyChar(c))))
// This converts a regular expression to a DFA, with using an intermediary NFA
def compile(pat: MyLang._regexpT) =
new SubsetConstruction(MyBerrySethi.automatonFrom(pat, 100000)).determinize
// Defines a "?" function, since it isn't provided by the library
def Quest(rs: _regexpT*) = Alt(Eps, Sequ(rs: _*)) // Quest(pat) = Eps|pat = (pat)?
// And now, the algorithm proper. It splits the string into words
// converts each character into Letter[MyChar[Char]],
// produce the regular expression desired for each word using Quest and Sequ,
// then the final regular expression by using Sequ with each subexpression.
def words(s : String) = s.split("\\W+")
def wordToRegex(w : String) : Seq[MyLang._regexpT] = w.map(c => Letter(MyChar(c)))
def wordRegex(w : String) = Quest(wordToRegex(w) reduceRight ((a,b) => Sequ(a, Quest(b))))
def phraseRegex(s : String) = Sequ(words(s).map(w => wordRegex(w)) : _*)
// This takes a list of strings, produce a DFA for each, and returns a list of
// of tuples formed by DFA and string.
def regexList(l : List[String]) = l.map(s => compile(phraseRegex(s)) -> s)
// The main function takes a list of strings, and returns a function that will
// traverse each DFA, and return all strings associated with DFAs that did not
// end up in a sink state.
def regexSearcher(l : List[String]) = {
val r = regexList(l)
(s : String) => r.filter(t => matchDet(t._1, s)).map(_._2)
}
I can hardly think of any language where implementing an FSM is non-trivial. Maybe this one.
...
if (currentState == STATE0 && event == EVENT0) return STATE1;
if (currentState == STATE1 && event == EVENT0) return STATE2;
...
The State pattern (using Java enums) is what we use in our telecom application, however we use small FSM's:
public class Controller{
private State itsState = State.IDLE;
public void setState(State aState){
itsState = aState;
}
public void action1(){
itsState.action1(this);
}
public void action2(){
itsState.action2(this);
}
public void doAction1(){
// code
}
public void doAction2(){
// code
}
}
public enum State{
IDLE{
#Override
public void action1(Controller aCtx){
aCtx.doAction1();
aCtx.setState(State.STATE1);
}
},
STATE1{
#Override
public void action2(Controller aCtx){
aCtx.doAction2();
aCtx.setState(State.IDLE);
}
},
public void action1(Controller aCtx){
throw new IllegalStateException();
}
public void action2(Controller aCtx){
throw new IllegalStateException();
}
}
FSM should be trivial to implement in any language that has a case statement.Your choice of language should be based on what that finite state machine needs to do.
For example, you state that you need to do this for telecom development and mention messages. I would look at systems/languages that support distributed message passing. Erlang does this, and I"m sure just about every other common language supports this through an API/library for the language.