When we are working with sets in Clojure we can use some useful functions from the clojure.set namespace. In a previous post we learned how we can get the difference of several sets. To get the union of several input sets we use the union function of the clojure.set namespace. The function returns a new set that is the union of unique elements from the input sets. A nil value is ignored by the union function.

In the following example code we use union:

If we want to get the values from a set that are not part of one or more other sets we must use the difference function in the clojure.set namespace. The function returns a set with all values from the first set that are different from values in other sets.

In the following example we use the difference with several sets:

In Clojure functions are everywhere. In a previous post we learned that sets can be functions, but Clojure also makes keywords functions. A keyword is a symbol starting with a colon (:) and is mostly used in map entries as key symbol. The keyword as function accepts a map as single argument and returns the value for the key that equals the keyword in the map or nil if the keyword cannot be found.

In the following code we use keywords as function in several examples:

One of the nice things in Clojure is that some data structures are also functions. For me this felt rather strange when learning Clojure (coming from Java), but it can be very powerful. A set in Clojure is also a function. The set as function accept a single argument and it return nil when the argument is not part of the set, otherwise the argument value is returned. This behaviour also makes a set as function a nice predicate to be used for example in collection functions.

In the following example code we use different sets as function:

The Clojure function complement can be used to created a new function that returns the opposite truth value of the old function. The new function accepts the same number of arguments as the old function. Also when we invoke the new function created by the complement the old function is actually invoked and the result is used as argument for the not function to return the opposite truth value. So if the original function returns false or nil the result for the new function is true.

In the following example code we create a new function bad-weather that is the complement of good-weather:

In Java we can use the iterate method of the Stream class to create an unbounded stream based on function invocations. We pass to the iterate method an initial value and a function that can be applied to the value. The first element in the unbounded stream is the initial value, the next element is the result of the function invocation with as argument the value from the previous element and this continues for each new element. Suppose we have a function expressed as lambda expression i → i + 2. When we use this lambda expression with the iterate method and a initial value of 1 we get a stream of 1, 1 → 1 + 2, 3 → 3 + 2, …​.

As we get an unbounded stream we must for example use limit to get the values we want from the stream. But we can also use an extra argument for the iterate method that is a Predicate definition. The iterate method will provide elements as long as the result of the Predicate is true. This way we the result of the iterate method is a bounded stream.

In Java we can use the generate method of the Stream class to create an infinite stream of values. The values are coming from a Supplier instance we pass as argument to the generate method. The Supplier instance usually will be a lambda expression. To give back a fixed value we simply implement a Supplier that returns the value. We can also have different values when we use a method that returns a different value on each invocation, for example the randomUUID method of the UUID class. When we use such a method we can create the Supplier as method reference: UUID::randomUUID.

The generate method returns an unbounded stream. We must use methods like limit and takeWhile to get a bounded stream again. We must use findFirst or findAny to terminate the unbounded stream and get a value.

If we want to transform items in a collection we can use the map function. If we also want to use the index of the element in the collection in the transformation we must use the map-indexed function. We must provide a function with 2 arguments, where the first argument is the index of the element in the collection and the second argument is the element in the collection.

In the following examples we use the map-indexed function:

In Clojure we can use the repeat function to get an infinite sequence of a given value. We can pass a length argument to get a fixed size sequence of the value. Clojure also provides the repeatedly function that takes as argument a function without arguments. A infinite sequence of invocations of the function is returned. Just like with the repeat function we can pass a length argument so the returned sequence has a fixed size.

We use the repeat and repeatedly function in the following example:

The Clojure function cycle take a collections as argument and creates a lazy sequence by repeating the items in the collection. So if we pass a collection with the characters \a, \b and \c we get a lazy sequence of (\a \b \c \a \b \c …​).

Written with Clojure 1.10.1.

The Clojure function zipmap create a map by interleaving a collection of keys with a collection of values. The first element of the keys collection is the map entry keyword and the first element of the values collection is than the map entry value, and so on for the other elements in the keys and values collections.

In the following example code we use zipmap using different examples of keys and values collections:

How do you know when having a tech lead may be taking your organisation in the wrong direction? Let’s take a look at some of the archetypical tech leads, their pitfalls and ways to go about and deal with them.