Wednesday, December 28, 2011

Convert java.util.Properties to a Clojure Map

As I previously mentioned, a lot of the work I do involves Clojure & Java interop. This work includes the occasional case of working with a java.util.Properties object from within Clojure. Working with a Properties object isn't a huge deal, but while in Clojure I prefer to use destructuring and the various functions (e.g. update-in, assoc, dissoc, etc) that are designed to work with Clojure maps.

The following example shows how easy it is to convert a Properties object to a Clojure map.
user=> (def prop-obj (doto (java.util.Properties.) (.putAll {"a" 1 "b" 2})))
user=> prop-obj
#<Properties {b=2, a=1}>

user=> (reduce (fn [x [y z]] (assoc x y z)) {} prop-obj)
{"a" 1, "b" 2}
That's fairly easy, but you'll quickly want your keys to be keywords if you plan on destructuring. You can drop in a quick call to keyword to convert the keys; however, you'll probably also want to dasherize the keys to allow for easy destructuring using keys and idiomatic names.
user=> (defn dash-match [[ _ g1 g2]]      
          (str g1 "-" g2))

user=> (defn dasherize [k]
          (-> k
            (clojure.string/replace #"([A-Z]+)([A-Z][a-z])" dash-match)
            (clojure.string/replace #"([a-z\d])([A-Z])" dash-match)
            (clojure.string/lower-case)))#'user/dash-match

user=> (def prop-obj (doto (java.util.Properties.) (.putAll {"FirstName" "Mike" "LastName" "Green"})))
user=> (reduce (fn [x [y z]] (assoc x y z)) {} prop-obj)                                              
{"LastName" "Green", "FirstName" "Mike"}
user=> (reduce (fn [x [y z]] (assoc x (-> y dasherize keyword) z)) {} prop-obj)
{:last-name "Green", :first-name "Mike"}
That looks good, but you might also find yourself working with a properties file that uses dots or dashes to group similar data. For example, you might find the following entry in your properties file (and the resulting Properties object).
person.name=Mike Green
person.age=26
person.sex=male
Loading this into a map works fine; however, it would be nice if the resulting map was nested (to keep common data together, and for easier access using get-in, update-in, etc).

The following code splits on dots and nests the values appropriately.
user=> (def prop-obj (doto (java.util.Properties.) (.putAll {"person.name" "Mike Green" "person.age" "26" "person.sex" "male"})))        
user=> prop-obj                                                                                                                  
#<Properties {person.name=Mike Green, person.age=26, person.sex=male}>
user=> (reduce (fn [x [y z]] (assoc-in x (-> y dasherize (clojure.string/split #"\.")) z)) {} prop-obj)
{"person" {"sex" "male", "age" "26", "name" "Mike Green"}}

user=> (-> (reduce (fn [x [y z]] (assoc-in x (-> y dasherize (clojure.string/split #"\.")) z)) {} prop-obj) clojure.walk/keywordize-keys)
{:person {:sex "male", :age "26", :name "Mike Green"}}
So, not too complicated, but much more complicated than what we started with. It turns out you'll likely want to do other things like parse integers, parse booleans, require keys, and add defaults when a key=value pair isn't specified.

We could go through the effort here of providing all that functionality, but instead I've created a small library that provides all of the above mentioned features: propertea

If you'd like to see the implementation of the above features, you'll just need to look in propertea.core. If you want examples of all of the features of propertea, checkout the tests in github.

Clojure & Java Interop

About a year ago I got a phone call asking if I wanted to join another team at DRW. The team supports a (primarily) Java application, but the performance requirements would also allow it to be written in a higher level language. I'd been writing Clojure (basically) full-time at that point - so my response was simple: I'd love to join, but I'm going to want to do future development using Clojure.

A year later we still have plenty of Java, but the vast majority of the new code I add is Clojure. One of the big reasons I'm able to use Clojure so freely is the seamless interop with Java.

Execute Clojure from Java
Calling Clojure from Java is as simple as loading the .clj file and invoking a method from that file. I used the same example years ago, but I'll inline it here for simplicity.
; interop/core.clj
(ns interop.core)

(defn print-string [arg]
  (println arg))

// Java calling code
RT.loadResourceScript("interop/core.clj");
RT.var("interop.core", "print-string").invoke("hello world");
note: examples from this blog entry are available in this git repo. The commit with the code from the previous example is available here and I'm running the example from the command line with:
lein jar && java -cp "interop-1.0.0.jar:lib/*" interop.Example
Execute Java from Clojure
At this point we have Java executing some Clojure code, and we also have Clojure using an object that was created in Java. Even though we're in Clojure we can easily call methods on any Java object.
(ns interop.core)

(defn print-string [arg]
  (println arg "is" (.length arg) "characters long"))
commit

The above code (using the length method of a String instance) produces the following output.
hello world is 11 characters long
Calling a Java method and passing in additional arguments is also easy in Clojure.
(ns interop.core)

(defn print-string [arg]
  (println (.replace arg "hello" "goodbye")))
commit

The above code produces the following output.
goodbye world
There are a few other things to know about calling Java from Clojure. The following examples show how to call static methods, use enums, and use inner classes.
(ns interop.core)

(defn print-string [arg]
  ;;; calling a static method
  (println (String/valueOf true))

  ;;; using an enum
  (println (java.util.concurrent.TimeUnit/SECONDS))

  ;;; using a Java nested (inner) class. Note, in Clojure you
  ;;; use a $ instead of a .
  (println (java.util.AbstractMap$SimpleEntry. "key" "val")))
commit

And, the output:
true
#< SECONDS>
#<SimpleEntry key=val>
Create Java objects in Clojure
When working with Clojure you'll likely want to interact with existing Java objects, but you'll probably also want to create new instances of Java objects. You might have noticed the dot at the end of Abstract$SimpleEntry. in the previous example - that's how you instruct Clojure to create an instance of a Java object. The following example shows the dot notation for calling a constructor of the String class.
(ns interop.core)

(defn print-string [arg]
  (println (String. arg)))
commit

At this point our output is back to the original output.
hello world
When creating Java objects it's often beneficial to know which Java interfaces the Clojure data structures implement. The following examples demonstrate how you can create Java objects while passing Clojure datastructures (and functions) as constructor arguments.
(ns interop.core)

(defn print-string [arg]
  ;;; pass a Clojure vector where Java expects a java.util.Collection
  (println (java.util.HashSet. ["1" "2"]))

  ;;; pass a Clojure map where Java expects a java.util.Map
  (println (java.util.LinkedHashMap. {1 "1" 2 "2"}))

  ;;; pass a Clojure function where Java expects a Runnable
  (println (Thread. (fn [] (println "clojure fns are runnables (and callables)")))))
commit

The output shows the constructed Java objects.
#<HashSet [2, 1]>
#<LinkedHashMap {1=1, 2=2}>
#<Thread Thread[Thread-1,5,main]>
Calling constructors in Clojure is very easy, but that's not always an option when creating a Java object. At times you will likely need to create an instance of a Java interface. Clojure provides both proxy and reify for creating instances of Java interfaces. The following example demonstrates the syntax for using either proxy or reify.
(ns interop.core)

(defn proxy-coll []
  (proxy [java.util.Collection] []
    (add [o]
         (println o)
         true)))

(defn reify-coll []
  (reify java.util.Collection
    (add [this o]
         (println o)
         (println this)
         true)))

(defn main []
  (.add (proxy-coll) "this string is printed on proxied.add")
  (.add (reify-coll) "this string is printed on reified.add"))
commit

note, I also changed Example.java (the details are available in the above linked commit). The syntax for proxy and reify are fairly similar, and both offer additional options that are worth looking into. The primary differences between these two simple examples are:
  • The proxy implementation requires an empty vector where we could specify constructor arguments (if this were an abstract class instead of an interface).
  • The arg list for all methods of reify will specify the reified instance as the first argument. In our example the Collection.add method only takes one argument, but in our reify we also get the instance of the collection.
You might have also noticed that both implementations of add have "true" at the end - in our example we're hard-coding the return value of add to always return true. The following output is the result of running the current example code.
this string is printed on proxied.add
this string is printed on reified.add
#<core$reify_coll$reify__11 interop.core$reify_coll$reify__11@556917ee>
It's worth reading the docs to determine whether you want proxy or reify; however, if you don't see a clear choice I would opt for reify.

Returning objects from Clojure to Java
Our current Example.java returns something from the call to invoke on the clojure.lang.Var that is returned from RT.var("interop.core", "main"), but we're ignoring it so we have no idea what's returned.* Let's change the code and return something on purpose.
// interop/Example.java
package interop;

import clojure.lang.RT;

public class Example {
    public static void main(String[] args) throws Exception {
        RT.loadResourceScript("interop/core.clj");
        System.out.println(RT.var("interop.core", "main").invoke());
    }
}

; interop/core.clj
(ns interop.core)

(defn main []
  {:a "1" :b "2"})
Running our changes produces the following output.
{:a "1", :b "2"}
commit

At this point we are back in Java land after making a quick trip to Clojure to get a value. Returning most objects will be pretty straightforward; however, at some point you may want to return a Clojure function. This turns out to be fairly easy as well, since Clojure functions are instances of the IFn interface. The following code demonstrates how to return a Clojure function and call it from within Java.
// interop/Example.java
package interop;

import clojure.lang.RT;

public class Example {
    public static void main(String[] args) throws Exception {
        RT.loadResourceScript("interop/core.clj");
        clojure.lang.IFn f = (clojure.lang.IFn) RT.var("interop.core", "main").invoke();
        f.invoke("hello world");
    }
}

// interop/core.clj
(ns interop.core)

(defn main [] println)
commit

The above example returns the println function from interop.core/main and then invokes the println function from within Java. I only chose to pass one argument to invoke; however, the IFn.invoke method has various overrides to allow you to pass several arguments. The above code works, but it can be simplified to the following example.
package interop;

import clojure.lang.RT;

public class Example {
    public static void main(String[] args) throws Exception {
        clojure.lang.IFn f = (clojure.lang.IFn) RT.var("clojure.core", "println");
        f.invoke("hello world");
    }
}
commit

It seems like a fitting end that our final output is the same as our original output.
hello world
*actually, it's the last thing that's returned, or "true" for this specific case.

Saturday, November 19, 2011

Clojure: expectations - scenarios

expectations.scenarios are now deprecated: http://blog.jayfields.com/2012/11/clojure-deprecating-expectationsscenari.html


When I set out to write expectations I wanted to create a simple unit testing framework. I'm happy with what expectations provides for unit testing; however, I also need to write the occasional test that changes values or causes a side effect. There's no way I could go back to clojure.test after enjoying better failure messages, trimmed stack traces, automatic testing running, etc. Thus, expectations.scenarios was born.

Using expectations.scenarios should be fairly natural if you already use expectations. The following example is a simple scenario (which could be a unit test, but we'll start here for simplicity).
(ns example.scenarios
  (:use expectations.scenarios))

(scenario
 (expect nil? nil))
A quick trip to the command line shows us that everything is working as expected.
Ran 1 tests containing 1 assertions in 4 msecs
0 failures, 0 errors.
As I said above, you could write this test as a unit test. However, expectations.scenarios was created for the cases in which you want to verify a value, make a change, and verify a value again. The following example shows multiple expectations verifying changing values in the same scenario.
(scenario
  (let [a (atom 0)]
    (swap! a inc)
    (expect 1 @a)
    (swap! a inc)
    (expect 2 @a)))
In expectations (unit tests) you can only have one expect (or given) so failures are captured, but they do not stop execution. However, due to the procedural nature of scenarios, the first failing expect stops execution.
(scenario
  (let [a (atom 0)]
    (swap! a inc)
    (expect 2 @a)
    (println "you'll never see this")))

failure in (scenarios.clj:4) : example.scenarios
           (expect 2 (clojure.core/deref a))
           expected: 2 
                was: 1
           on (scenarios.clj:7)
Ran 1 tests containing 1 assertions in 81 msecs
1 failures, 0 errors.
expectations.scenarios also allows you to easily verify calls to any function. I generally use interaction expects when I need to verify some type of side effect (e.g. logging or message publishing).
(scenario
 (println "1")
 (expect (interaction (println "1"))))
It's important to note the ordering of this scenario. You don't 'setup' an expectation and then call the function. Exactly the opposite is true - you call the function the same way you would in production, then you expect the interaction to have occurred. You may find this jarring if you're used to setting up your mocks ahead of time; However, I think this syntax is the least intrusive - and I think you'll prefer it in the long term.

The above example calls println directly, but your tests are much more likely to look something like this.
(defn foo [x] (println x))

(scenario
 (foo "1")
 (expect (interaction (println "1"))))
Similar to all other mocking frameworks (that I know of) the expect is using an implicit "once" argument. You can also specify :twice and :never if you find yourself needing those interaction tests.
(defn foo [x] (println x))

(scenario
 (foo "1")
 (foo "1")
 (expect (interaction (println "1")) :twice)
 (expect (interaction (identity 1)) :never))
On occasion you may find yourself interested in verifying 2 out of 3 arguments - expectations.scenarios provides the 'anything' var that can be used for arguments you don't care about.
(defn foo [x y z] (println x y z))

(scenario
 (foo "1" 2 :a)
 (expect (interaction (println "1" anything :a))))
That's about all there is to expectations.scenarios, hopefully it fills the gap for tests you want to write that simply can't be done as unit tests.

Tuesday, November 01, 2011

Clojure: expectations unit testing wrap-up

Clojure Unit Testing with Expectations Part One
Clojure Unit Testing with Expectations Part Two
Clojure Unit Testing with Expectations Part Three
Clojure Unit Testing with Expectations Part Four
Clojure Unit Testing with Expectations Part Five
Clojure Unit Testing with Expectations Part Six (this entry)

The previous blog posts on expectations unit testing syntax cover all of the various ways that expectations can be used to write tests and what you can expect when your tests fail. However, there are a few other things worth knowing about expectations.

Stacktraces
expectations aggressively removes lines from the stacktraces. Just like many other aspects of expectations, the focus is on more signal and less noise. Any line in the stacktrace from clojure.core, clojure.lang, clojure.main, and java.lang will be removed. As a result any line appearing in your stacktrace should be relevant to your application or a third-party lib you're using. expectations also removes any duplicates that can occasionally appear when anonymous functions are part of the stacktrace. Again, it's all about improving signal by removing noise. Speaking of noise...

Test Names
You might have noticed that expectations does not require you to create a test name. This is a reflection of my personal opinion that test names are nothing more than comments and shouldn't be required. If you desire test names, feel free to drop a comment above each test. Truthfully, this is probably a better solution anyway, since you can use spaces (instead of dashes) to separate words in a comment. Comments are good when used properly, but they can become noise when they are required. The decision to simply use comments for test names is another example of improving signal by removing noise.

Running Focused Expectations
Sometimes you'll have a file full of expectations, but you only want to run a specific expectation - expectations solves this problem by giving you 'expect-focused'. If you use expect-focused only expectations that are defined using expect-focused will be run.

For example, if you have the following expectations in a file you should see the following results from 'lein expectations'.
(ns sample.test.core
(:use [expectations]))

(expect zero? 0)
(expect zero? 1)
(expect-focused nil? nil)

jfields$ lein expectations
Ran 1 tests containing 1 assertions in 2 msecs
IGNORED 2 EXPECTATIONS
0 failures, 0 errors.
As you can see, expectations only ran one test - the expect-focused on line 6. If the other tests had been run the test on line 5 would have created a failure. It can be easy to accidentally leave a few expect-focused calls in, so expectations prints the number of ignored expectations in capital letters as a reminder. Focused expectation running is yet another way to remove noise while working through a problem.

Tests Running
If you always use 'lein expectations' to run your tests you'll never even care; however, if you ever want to run individual test files it's important to know that your tests run by default on JVM shutdown. When I'm working with Clojure and Java I usually end up using IntelliJ, and therefore have the ability to easily run individual files. When I switched from clojure.test to expectations I wanted to make test running as simple as possible - so I removed the need to specify (run-all-tests). Of course, if you don't want expectations to run for some reason you can disable this feature by calling (expectations/disable-run-on-shutdown).

JUnit Integration
Lack of JUnit integration was a deal breaker for my team in the early days, so expectations comes with an easy way to run all tests as part of JUnit. If you want all of your tests to run in JUnit all you need to do is implement ExpectationsTestRunner.TestSource. The following example is what I use to run all the tests in expectations with JUnit.
import expectations.junit.ExpectationsTestRunner;
import org.junit.runner.RunWith;

@RunWith(expectations.junit.ExpectationsTestRunner.class)
public class SuccessTest implements ExpectationsTestRunner.TestSource{

public String testPath() {
return "test/clojure/success";
}
}
As you can see from the example above, all you need to do is tell the test runner where to find your Clojure files.

That should be everything you need to know about expectations for unit testing use. If anything is unclear, please drop me a line in the comments.

Clojure: expectations - removing duplication with given

Clojure Unit Testing with Expectations Part One
Clojure Unit Testing with Expectations Part Two
Clojure Unit Testing with Expectations Part Three
Clojure Unit Testing with Expectations Part Four
Clojure Unit Testing with Expectations Part Five (this entry)
Clojure Unit Testing with Expectations Part Six

expectations obviously has a bias towards one assertion per test; however, there are times that verifying several things at the same time does make sense. For example, if you want to verify a few different properties of the same Java object it probably makes sense to make multiple assertions on the same instance.

One of the biggest problems with multiple assertions per test is when your test follows this pattern:
  1. create some state
  2. verify a bit about the state
  3. alter the state
  4. verify more about the state
Part of the problem is that the assertions that occurred before the altering of the state may or may not be relevant after the alteration. Additionally, if any of the assertions fail you have to stop running the entire test - thus some of your assertions will not be run (and you'll be lacking some information).

expectations takes an alternate route - embracing the idea of multiple assertions by providing a specific syntax that allows multiple verifications and the least amount of duplication.

The following example shows how you can test multiple properties of a Java object using the 'given' syntax.
(given (java.util.ArrayList.)
(expect
.size 0
.isEmpty true))

jfields$ lein expectations
Ran 2 tests containing 2 assertions in 4 msecs
0 failures, 0 errors.
The syntax is simple enough: (given an-object (expect method return-value [method return-value]))
note: [method return-value] may be repeated any number of times.

This syntax allows us to expect return-values from as many methods as we care to verify, but encourages us not to change any state between our various assertions. This syntax also allows us to to run each assertion regardless of the outcome of any previous assertion.

Obviously you could call methods that change the internal state of the object and at that point you're on your own. I definitely wouldn't recommend testing that way. However, as long as you call methods that don't change any state 'given' can help you write succinct tests that verify as many aspects of an object as you need to test.

As usual, I'll show the output for tests that fail using this syntax.
(given (java.util.ArrayList.)
(expect
.size 1
.isEmpty false))

jfields$ lein expectations
failure in (core.clj:4) : sample.test.core
(expect 1 (.size (java.util.ArrayList.)))
expected: 1
was: 0
failure in (core.clj:4) : sample.test.core
(expect false (.isEmpty (java.util.ArrayList.)))
expected: false
was: true
This specific syntax was created for testing Java objects, but an interesting side effect is that it actually works on any value and you can substitute method calls with any function. For example, you can test a vector or a map using the examples below as a template.
(given [1 2 3]
(expect
first 1
last 3))

(given {:a 2 :b 4}
(expect
:a 2
:b 4))

jfields$ lein expectations
Ran 4 tests containing 4 assertions in 8 msecs
0 failures, 0 errors.
And, of course, the failures.
(given [1 2 3]
(expect
first 2
last 1))

(given {:a 2 :b 4}
(expect
:a 1
:b 1))

jfields$ lein expectations
failure in (core.clj:4) : sample.test.core
(expect 2 (first [1 2 3]))
expected: 2
was: 1
failure in (core.clj:4) : sample.test.core
(expect 1 (last [1 2 3]))
expected: 1
was: 3
failure in (core.clj:9) : sample.test.core
(expect 1 (:a {:a 2, :b 4}))
expected: 1
was: 2
failure in (core.clj:9) : sample.test.core
(expect 1 (:b {:a 2, :b 4}))
expected: 1
was: 4
Ran 4 tests containing 4 assertions in 14 msecs
4 failures, 0 errors.
When you want to call methods on a Java object or call functions with the same instance over and over the previous given syntax is really the simplest solution. However, there are times where you want something more flexible.

expectations also has a 'given' syntax that allows you to specify a template - thus reducing code duplication. The following example shows a test that verifies + with various arguments.
(given [x y] (expect 10 (+ x y))
4 6
6 4
12 -2)

jfields$ lein expectations
Ran 3 tests containing 3 assertions in 5 msecs
0 failures, 0 errors.
The syntax for this flavor of given is: (given bindings template-form values-to-be-bound). The template form can be anything you need - just remember to put the expect in there.

Here's another example where we combine given with in to test a few different things. This example shows both the successful and failing versions.
;; successful
(given [x y] (expect x (in y))
:a #{:a :b}
{:a :b} {:a :b :c :d})

;; failure
(given [x y] (expect x (in y))
:c #{:a :b}
{:a :d} {:a :b :c :d})

lein expectations
failure in (core.clj:8) : sample.test.core
(expect :c (in #{:a :b}))
key :c not found in #{:a :b}
failure in (core.clj:8) : sample.test.core
(expect {:a :d} (in {:a :b, :c :d}))
expected: {:a :d}
in: {:a :b, :c :d}
:a expected: :d
was: :b
Ran 4 tests containing 4 assertions in 13 msecs
2 failures, 0 errors.
That's basically it for 'given' syntax within expectations. There are times that I use all of the various versions of given; however, there seems to be a connection with using given and interacting with Java objects. If you don't find yourself using Java objects very often then you probably wont have a strong need for given.