From ed4cb23472805c8ffa711755dee2d04fd798faa5 Mon Sep 17 00:00:00 2001 From: Andrey Antukh Date: Thu, 2 Mar 2017 13:20:28 +0100 Subject: [PATCH] Generate book --- _clojurescript-unraveled.epub | Bin 182927 -> 0 bytes assets/pygment-light.css | 205 - assets/pygments.css | 205 - clojurescript-unraveled.epub | Bin 322609 -> 0 bytes clojurescript-unraveled.mobi | Bin 428869 -> 0 bytes clojurescript-unraveled.pdf | Bin 869404 -> 0 bytes clojurescript-unraveled.xml | 7138 ---------------------------- fonts/monoid-regular-webfont.eot | Bin 21742 -> 0 bytes fonts/monoid-regular-webfont.svg | 236 - fonts/monoid-regular-webfont.ttf | Bin 51808 -> 0 bytes fonts/monoid-regular-webfont.woff | Bin 25184 -> 0 bytes fonts/monoid-regular-webfont.woff2 | Bin 19552 -> 0 bytes index.html | 245 +- 13 files changed, 151 insertions(+), 7878 deletions(-) delete mode 100644 _clojurescript-unraveled.epub delete mode 100644 assets/pygment-light.css delete mode 100644 assets/pygments.css delete mode 100644 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    - -Rich Hickey - -Why are we doing this? Because Clojure rocks, and JavaScript reaches. -
    -ClojureScript is an implementation of the Clojure programming language that -targets JavaScript. Because of this, it can run in many different execution -environments including web browsers, Node.js, io.js and Nashorn. -Unlike other languages that intend to compile to JavaScript (like TypeScript, -FunScript, or CoffeeScript), ClojureScript is designed to use JavaScript like -bytecode. It embraces functional programming and has very safe and consistent -defaults. Its semantics differ significantly from those of JavaScript. -Another big difference (and in our opinion an advantage) over other languages is -that Clojure is designed to be a guest. It is a language without its own virtual -machine that can be easily adapted to the nuances of its execution environment. This -has the benefit that Clojure (and hence ClojureScript) has access to all the -existing libraries written for the host language. -Before we jump in, let us summarize some of the core ideas that ClojureScript brings -to the table. Don’t worry if you don’t understand all of them right now, they’ll -become clear throughout the book. - - -ClojureScript enforces the functional programming paradigm with its design -decisions and idioms. Although being strongly opinionated about functional -programming it’s a pragmatic language rather than pursuing theoretical purity. - - -Encourages programming with immutable data, offering highly performant and -state of the art immutable collection implementations. - - -It makes a clear distinction of identity and its state, with explicit constructs -for managing change as a series of immutable values over time. - - -It has type-based and value-based polymorphism, elegantly solving the expression -problem. - - -It is a Lisp dialect so programs are written in the programming language’s own -data structures, a property known as homoiconicity that makes metaprogramming -(programs that write programs) as simple as it can be. - - -These ideas together have a great influence in the way you design and implement -software, even if you are not using ClojureScript. Functional programming, decoupling -of data (which is immutable) from the operations to transform it, explicit idioms for -managing change over time and polymorphic constructs for programming to abstractions -greatly simplify the systems we write. -
    - -Rich Hickey - -We can make the same exact software we are making today with dramatically simpler -stuff — dramatically simpler languages, tools, techniques, approaches. -
    -We hope you enjoy the book and ClojureScript brings the same joy and inspiration that -has brought to us. - - -Language (the basics) -This chapter will be a little introduction to ClojureScript without assumptions about -previous knowledge of the Clojure language, providing a quick tour over all the -things you will need to know about ClojureScript and understand the rest of this -book. -You can run the code snippets in the online interactive repl: -http://www.clojurescript.io/ -
    -First steps with Lisp syntax -Invented by John McCarthy in 1958, Lisp is one of the oldest programming languages -that is still around. It has evolved into many derivatives called dialects, -ClojureScript being one of them. It is a programming language written in its own -data structures — originally lists enclosed in parentheses — but Clojure(Script) has -evolved the Lisp syntax with more data structures, making it more pleasant to write -and read. -A list with a function in the first position is used for calling a function in -ClojureScript. In the example below, we apply the addition function to three -arguments. Note that unlike in other languages, + is not an operator but a -function. Lisp has no operators; it only has functions. -(+ 1 2 3) -;; => 6 -In the example above, we’re applying the addition function + to the arguments 1, -2 and 3. ClojureScript allows many unusual characters like ? or - in symbol -names, which makes it easier to read: -(zero? 0) -;; => true -To distinguish function calls from lists of data items, we can quote lists to keep -them from being evaluated. The quoted lists will be treated as data instead of as a -function call: -'(+ 1 2 3) -;; => (+ 1 2 3) -ClojureScript uses more than lists for its syntax. The full details will be covered -later, but here is an example of the usage of a vector (enclosed in brackets) for -defining local bindings: -(let [x 1 - y 2 - z 3] - (+ x y z)) -;; => 6 -This is practically all the syntax we need to know for using not only ClojureScript, -but any Lisp. Being written in its own data structures (often referred to as -homoiconicity) is a great property since the syntax is uniform and simple; also, -code generation via macros is easier than in any other -language, giving us plenty of power to extend the language to suit our needs. -
    -
    -The base data types -The ClojureScript language has a rich set of data types like most programming -languages. It provides scalar data types that will be very familiar to you, such as -numbers, strings, and floats. Beyond these, it also provides a great number of -others that might be less familiar, such as symbols, keywords, regexes (regular -expressions), vars, atoms, and volatiles. -ClojureScript embraces the host language, and where possible, uses the host’s -provided types. For example: numbers and strings are used as is and behave in the -same way as in JavaScript. -
    -Numbers -In ClojureScript, numbers include both integers and floating points. Keeping in -mind that ClojureScript is a guest language that compiles to JavaScript, integers -are actually JavaScript’s native floating points under the hood. -As in any other language, numbers in ClojureScript are represented in the -following ways: -23 -+23 --100 -1.7 --2 -33e8 -12e-14 -3.2e-4 -
    -
    -Keywords -Keywords in ClojureScript are objects that always evaluate to themselves. They are -usually used in map data structures to efficiently represent the -keys. -:foobar -:2 -:? -:foo/bar -As you can see, the keywords are all prefixed with :, but this character is only -part of the literal syntax and is not part of the name of the object. -You can also create a keyword by calling the keyword function. Don’t worry if you -don’t understand or are unclear about anything in the following example; -functions are discussed in a later section. -(keyword "foo") -;; => :foo -
    -
    -Symbols -Symbols in ClojureScript are very, very similar to keywords (which you now know -about). But instead of evaluating to themselves, symbols are evaluated to something -that they refer to, which can be functions, variables, etc. -Symbols start with a non numeric character and can contain alphanumeric characters -as well as *, +, !, -, _, ', and ? such as : -sample-symbol -othersymbol -f1 -my-special-swap! -Don’t worry if you don’t understand right away; symbols are used in almost all of -our examples, which will give you the opportunity to learn more as we go on. -
    -
    -Strings -There is almost nothing new we can explain about strings that you don’t already -know. In ClojureScript, they work the same as in any other language. One point of -interest, however, is that they are immutable. -In this case they are the same as in JavaScript: -"An example of a string" -One peculiar aspect of strings in ClojureScript is due to the language’s Lisp -syntax: single and multiline strings have the same syntax: -"This is a multiline - string in ClojureScript." -
    -
    -Characters -ClojureScript also lets you write single characters using Clojure’s character -literal syntax. -\a ; The lowercase a character -\newline ; The newline character -Since the host language doesn’t contain character literals, ClojureScript -characters are transformed behind the scenes into single character JavaScript -strings. -
    -
    -Collections -Another big step in explaining a language is to explain its collections and -collection abstractions. ClojureScript is not an exception to this rule. -ClojureScript comes with many types of collections. The main difference between -ClojureScript collections and collections in other languages is that they are -persistent and immutable. -Before moving on to these (possibly) unknown concepts, we’ll present a high-level -overview of existing collection types in ClojureScript. -
    -Lists -This is a classic collection type in languages based on Lisp. Lists are the simplest -type of collection in ClojureScript. Lists can contain items of any type, -including other collections. -Lists in ClojureScript are represented by items enclosed between parentheses: -'(1 2 3 4 5) -'(:foo :bar 2) -As you can see, all list examples are prefixed with the ' char. This is because -lists in Lisp-like languages are often used to express things like function or macro -calls. In that case, the first item should be a symbol that will evaluate to -something callable, and the rest of the list elements will be function -arguments. However, in the preceding examples, we don’t want the first item as a -symbol; we just want a list of items. -The following example shows the difference between a list without and with the -preceding single quote mark: -(inc 1) -;; => 2 - -'(inc 1) -;; => (inc 1) -As you can see, if you evaluate (inc 1) without prefixing it with ', it will -resolve the inc symbol to the inc function and will execute it with 1 as the -first argument, returning the value 2. -You can also explicitly create a list with the list function: -(list 1 2 3 4 5) -;; => (1 2 3 4 5) - -(list :foo :bar 2) -;; => (:foo :bar 2) -Lists have the peculiarity that they are very efficient if you access them -sequentially or access their first elements, but a list is not a very good option if -you need random (index) access to its elements. -
    -
    -Vectors -Like lists, vectors store a series of values, but in this case, with very -efficient index access to their elements, as opposed to lists, which are evaluated -in order. Don’t worry; in the following sections we’ll go in depth with details, but -at this moment, this simple explanation is more than enough. -Vectors use square brackets for the literal syntax; let’s see some examples: -[:foo :bar] -[3 4 5 nil] -Like lists, vectors can contain objects of any type, as you can observe in the -preceding example. -You can also explicitly create a vector with the vector function, but this is not -commonly used in ClojureScript programs: -(vector 1 2 3) -;; => [1 2 3] - -(vector "blah" 3.5 nil) -;; => ["blah" 3.5 nil] -
    -
    -Maps -Maps are a collection abstraction that allow you to store key/value pairs. In other -languages, this type of structure is commonly known as a hash-map or dict -(dictionary). Map literals in ClojureScript are written with the pairs between -curly braces. -{:foo "bar", :baz 2} -{:alphabet [:a :b :c]} - -Commas are frequently used to separate a key-value pair, but they are -completely optional. In ClojureScript syntax, commas are treated like spaces. - -Like vectors, every item in a map literal is evaluated before the result is stored -in a map, but the order of evaluation is not guaranteed. -
    -
    -Sets -And finally, sets. -Sets store zero or more unique items of any type and are unordered. Like maps, they -use curly braces for their literal syntax, with the difference being that they use a -# as the leading character. You can also use the set function to convert a -collection to a set: -#{1 2 3 :foo :bar} -;; => #{1 :bar 3 :foo 2} -(set [1 2 1 3 1 4 1 5]) -;; => #{1 2 3 4 5} -In subsequent sections, we’ll go in depth about sets and the other collection types -you’ve seen in this section. -
    -
    -
    -
    -Vars -ClojureScript is a mostly functional language that focuses on -immutability. Because of that, it does not have the concept of variables as you know -them in most other programming languages. The closest analogy to variables are the -variables you define in algebra; when you say x = 6 in mathematics, you are saying -that you want the symbol x to stand for the number six. -In ClojureScript, vars are represented by symbols and store a single value -together with metadata. -You can define a var using the def special form: -(def x 22) -(def y [1 2 3]) -Vars are always top level in the namespace (which we will -explain later). If you use def in a function call, the var will be defined at -the namespace level, but we do not recommend this - instead, you should use let to -define variables within a function. -
    -
    -Functions -
    -The first contact -It’s time to make things happen. ClojureScript has what are known as first class -functions. They behave like any other type; you can pass them as parameters and you -can return them as values, always respecting the lexical scope. ClojureScript also -has some features of dynamic scoping, but this will be discussed in another section. -If you want to know more about scopes, this -Wikipedia article is -very extensive and explains different types of scoping. -As ClojureScript is a Lisp dialect, it uses the prefix notation for calling a -function: -(inc 1) -;; => 2 -In the example above, inc is a function and is part of the ClojureScript -runtime, and 1 is the first argument for the inc function. -(+ 1 2 3) -;; => 6 -The + symbol represents an add function. It allows multiple parameters, whereas -in ALGOL-type languages, + is an operator and only allows two parameters. -The prefix notation has huge advantages, some of them not always -obvious. ClojureScript does not make a distinction between a function and an -operator; everything is a function. The immediate advantage is that the prefix -notation allows an arbitrary number of arguments per "operator". It also completely -eliminates the problem of operator precedence. -
    -
    -Defining your own functions -You can define an unnamed (anonymous) function with the fn special form. This is -one type of function definition; in the following example, the function takes two -parameters and returns their average. -(fn [param1 param2] - (/ (+ param1 param2) 2.0)) -You can define a function and call it at the same time (in a single expression): -((fn [x] (* x x)) 5) -;; => 25 -Let’s start creating named functions. But what does a named function really mean? -It is very simple; in ClojureScript, functions are first-class and behave like any -other value, so naming a function is done by simply binding the function to a -symbol: -(def square (fn [x] (* x x))) - -(square 12) -;; => 144 -ClojureScript also offers the defn macro as a little syntactic sugar for making -function definition more idiomatic: -(defn square - "Return the square of a given number." - [x] - (* x x)) -The string that comes between the function name and the parameter vector is called a -docstring (documentation string); programs that automatically create web -documentation from your source files will use these docstrings. -
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    -Functions with multiple arities -ClojureScript also comes with the ability to define functions with an arbitrary -number of arguments. (The term arity means the number of arguments that a function -takes.) The syntax is almost the same as for defining an ordinary function, with the -difference that it has more than one body. -Let’s see an example, which will explain it better: -(defn myinc - "Self defined version of parameterized `inc`." - ([x] (myinc x 1)) - ([x increment] - (+ x increment))) -This line: ([x] (myinc x 1)) says that if there is only one argument, call the -function myinc with that argument and the number 1 as the second argument. The -other function body ([x increment] (+ x increment)) says that if there are two -arguments, return the result of adding them. -Here are some examples using the previously defined multi-arity function. Observe -that if you call a function with the wrong number of arguments, the compiler will -emit an error message. -(myinc 1) -;; => 2 - -(myinc 1 3) -;; => 4 - -(myinc 1 3 3) -;; Compiler error - -Explaining the concept of "arity" is out of the scope of this book, however -you can read about that in this Wikipedia -article. - -
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    -Variadic functions -Another way to accept multiple parameters is defining variadic functions. Variadic -functions are functions that accept an arbitrary number of arguments: -(defn my-variadic-set - [& params] - (set params)) - -(my-variadic-set 1 2 3 1) -;; => #{1 2 3} -The way to denote a variadic function is using the & symbol prefix on its -arguments vector. -
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    -Short syntax for anonymous functions -ClojureScript provides a shorter syntax for defining anonymous functions using the -#() reader macro (usually leads to one-liners). Reader macros are "special" -expressions that will be transformed to the appropriate language form at compile -time; in this case, to some expression that uses the fn special form. -(def average #(/ (+ %1 %2) 2)) - -(average 3 4) -;; => 3.5 -The preceding definition is shorthand for: -(def average-longer (fn [a b] (/ (+ a b) 2))) - -(average-longer 7 8) -;; => 7.5 -The %1, %2…​ %N are simple markers for parameter positions that are -implicitly declared when the reader macro will be interpreted and converted to a -fn expression. -If a function only accepts one argument, you can omit the number after the % -symbol, e.g., a function that squares a number: #(* %1 %1)) can be written -#(* % %)). -Additionally, this syntax also supports the variadic form with the %& symbol: -(def my-variadic-set #(set %&)) - -(my-variadic-set 1 2 2) -;; => #{1 2} -
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    -
    -Flow control -ClojureScript has a very different approach to flow control than languages like -JavaScript, C, etc. -
    -Branching with <literal>if</literal> -Let’s start with a basic one: if. In ClojureScript, the if is an expression -and not a statement, and it has three parameters: the first one is the condition -expression, the second one is an expression that will be evaluated if the condition -expression evaluates to logical true, and the third expression will be evaluated -otherwise. -(defn discount - "You get 5% discount for ordering 100 or more items" - [quantity] - (if (>= quantity 100) - 0.05 - 0)) - -(discount 30) -;; => 0 - -(discount 130) -;; => 0.05 -The block expression do can be used to have multiple expressions in an if -branch. do is explained in the next section. -
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    -Branching with <literal>cond</literal> -Sometimes, the if expression can be slightly limiting because it does not have the -"else if" part to add more than one condition. The cond macro comes to the rescue. -With the cond expression, you can define multiple conditions: -(defn mypos? - [x] - (cond - (> x 0) "positive" - (< x 0) "negative" - :else "zero")) - -(mypos? 0) -;; => "zero" - -(mypos? -2) -;; => "negative" -Also, cond has another form, called condp, that works very similarly to the -simple cond but looks cleaner when the condition (also called a predicate) is the -same for all conditions: -(defn translate-lang-code - [code] - (condp = (keyword code) - :es "Spanish" - :en "English" - "Unknown")) - -(translate-lang-code "en") -;; => "English" - -(translate-lang-code "fr") -;; => "Unknown" -The line condp = (keyword code) means that, in each of the following lines, -ClojureScript will apply the = function to the result of evaluating (keyword -code). -
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    -Branching with <literal>case</literal> -The case branching expression has a similar use as our previous example with -condp. The main differences are that case always uses the = predicate/function -and its branching values are evaluated at compile time. This results in a more -performant form than cond or condp but has the disadvantage that the condition -value must be static. -Here is the previous example rewritten to use case: -(defn translate-lang-code - [code] - (case code - "es" "Spanish" - "en" "English" - "Unknown")) - -(translate-lang-code "en") -;; => "English" - -(translate-lang-code "fr") -;; => "Unknown" -
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    -
    -Truthiness -This is the aspect where each language has its own semantics (mostly wrongly). The -majority of languages consider empty collections, the integer 0, and other things -like this to be false. In ClojureScript, unlike in other languages, only two -values are considered as false: nil and false. Everything else is treated as -logical true. -Jointly with the ability to implement the callable protocol (the IFn, explained -more in detail later), data structures like sets can be used just as predicates, -without need of additional wrapping them in a function: -(def valid? #{1 2 3}) - -(filter valid? (range 1 10)) -;; => (1 2 3) -This is because set returns the a value if it exists or nil in case contrary: -(valid? 1) -;; => 1 - -(valid? 4) -;; => nil -
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    -Locals, Blocks, and Loops -
    -Locals -ClojureScript does not have the concept of variables as in ALGOL-like languages, -but it does have locals. Locals, as per usual, are immutable, and if you try to -mutate them, the compiler will throw an error. -Locals are defined with the let expression. The expression starts with a vector as -the first parameter followed by an arbitrary number of expressions. The first -parameter (the vector) should contain an arbitrary number of pairs that give a -binding form (usually a symbol) followed by an expression whose value will be -bound to this new local for the remainder of the let expression. -(let [x (inc 1) - y (+ x 1)] - (println "Simple message from the body of a let") - (* x y)) -;; Simple message from the body of a let -;; => 6 -In the preceding example, the symbol x is bound to the value (inc 1), which -comes out to 2, and the symbol y is bound to the sum of x and 1, which comes out -to 3. Given those bindings, the expressions (println "Simple message from the body -of a let") and (* x y) are evaluated. -
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    -Blocks -In JavaScript, braces { and } delimit a block of code that “belongs -together”. Blocks in ClojureScript are created using the do expression and are -usually used for side effects, like printing something to the console or writing a -log in a logger. -A side effect is something that is not necessary for the return value. -The do expression accepts as its parameter an arbitrary number of other -expressions, but it returns the return value only from the last one: -(do - (println "hello world") - (println "hola mundo") - (* 3 5) ;; this value will not be returned; it is thrown away - (+ 1 2)) - -;; hello world -;; hola mundo -;; => 3 -The body of the let expression, explained in the previous section, is very similar -to the do expression in that it allows multiple expressions. In fact, the let -has an implicit do. -
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    -Loops -The functional approach of ClojureScript means that it does not have standard, -well-known, statement-based loops such as for in JavaScript. The loops in -ClojureScript are handled using recursion. Recursion sometimes requires -additional thinking about how to model your problem in a slightly different way than -imperative languages. -Many of the common patterns for which for is used in other languages are achieved -through higher-order functions - functions that accept other functions as -parameters. -
    -Looping with loop/recur -Let’s take a look at how to express loops using recursion with the loop and -recur forms. loop defines a possibly empty list of bindings (notice the -symmetry with let) and recur jumps execution back to the looping point with new -values for those bindings. -Let’s see an example: -(loop [x 0] - (println "Looping with " x) - (if (= x 2) - (println "Done looping!") - (recur (inc x)))) -;; Looping with 0 -;; Looping with 1 -;; Looping with 2 -;; Done looping! -;; => nil -In the above snippet, we bind the name x to the value 0 and execute the -body. Since the condition is not met the first time, it’s rerun with recur, -incrementing the binding value with the inc function. We do this once more until -the condition is met and, since there aren’t any more recur calls, exit the loop. -Note that loop isn’t the only point we can recur to; using recur inside a -function executes the body of the function recursively with the new bindings: -(defn recursive-function - [x] - (println "Looping with" x) - (if (= x 2) - (println "Done looping!") - (recur (inc x)))) - -(recursive-function 0) -;; Looping with 0 -;; Looping with 1 -;; Looping with 2 -;; Done looping! -;; => nil -
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    -Replacing for loops with higher-order functions -In imperative programming languages it is common to use for loops to iterate over -data and transform it, usually with the intent being one of the following: - - -Transform every value in the iterable yielding another iterable - - -Filter the elements of the iterable by certain criteria - - -Convert the iterable to a value where each iteration depends on the result from -the previous one - - -Run a computation for every value in the iterable - - -The above actions are encoded in higher-order functions and syntactic constructs in -ClojureScript; let’s see an example of the first three. -For transforming every value in an iterable data structure we use the map -function, which takes a function and a sequence and applies the function to every -element: -(map inc [0 1 2]) -;; => (1 2 3) -The first parameter for map can be any function that takes one argument and -returns a value. For example, if you had a graphing application and you wanted to -graph the equation y = 3x + 5 for a set of x values, you -could get the y values like this: -(defn y-value [x] (+ (* 3 x) 5)) - -(map y-value [1 2 3 4 5]) -;; => (8 11 14 17 20) -If your function is short, you can use an anonymous function instead, either the -normal or short syntax: -(map (fn [x] (+ (* 3 x) 5)) [1 2 3 4 5]) -;; => (8 11 14 17 20) - -(map #(+ (* 3 %) 5) [1 2 3 4 5]) -;; => (8 11 14 17 20) -For filtering the values of a data structure we use the filter function, which -takes a predicate and a sequence and gives a new sequence with only the elements -that returned true for the given predicate: -(filter odd? [1 2 3 4]) -;; => (1 3) -Again, you can use any function that returns true or false as the first argument -to filter. Here is an example that keeps only words less than five characters -long. (The count function returns the length of its argument.) -(filter (fn [word] (< (count word) 5)) ["ant" "baboon" "crab" "duck" "echidna" "fox"]) -;; => ("ant" "crab" "duck" "fox") -Converting an iterable to a single value, accumulating the intermediate result at -every step of the iteration can be achieved with reduce, which takes a function -for accumulating values, an optional initial value and a collection: -(reduce + 0 [1 2 3 4]) -;; => 10 -Yet again, you can provide your own function as the first argument to reduce, but -your function must have two parameters. The first one is the "accumulated value" -and the second parameter is the collection item being processed. The function -returns a value that becomes the accumulator for the next item in the list. For -example, here is how you would find the sum of squares of a set of numbers (this is -an important calculation in statistics). Using a separate function: -(defn sum-squares - [accumulator item] - (+ accumulator (* item item))) - -(reduce sum-squares 0 [3 4 5]) -;; => 50 -…​and with an anonymous function: -(reduce (fn [acc item] (+ acc (* item item))) 0 [3 4 5]) -;; => 50 -Here is a reduce that finds the total number of characters in a set of words: -(reduce (fn [acc word] (+ acc (count word))) 0 ["ant" "bee" "crab" "duck"]) -;; => 14 -We have not used the short syntax here because, although it requires less typing, it -can be less readable, and when you are starting with a new language, it’s important -to be able to read what you wrote! If you are comfortable with the short syntax, -feel free to use it. -Remember to choose your starting value for the accumulator carefully. If you wanted -to use reduce to find the product of a series of numbers, you would have to start -with one rather than zero, otherwise all the numbers would be multiplied by zero! -;; wrong starting value -(reduce * 0 [3 4 5]) -;; => 0 - -;; correct starting accumulator -(reduce * 1 [3 4 5]) -;; => 60 -
    -
    -<literal>for</literal> sequence comprehensions -In ClojureScript, the for construct isn’t used for iteration but for generating -sequences, an operation also known as "sequence comprehension". In this section -we’ll learn how it works and use it to declaratively build sequences. -for takes a vector of bindings and an expression and generates a sequence of the -result of evaluating the expression. Let’s take a look at an example: -(for [x [1 2 3]] - [x (* x x)]) -;; => ([1 1] [2 4] [3 9]) -In this example, x is bound to each of the items in the vector [1 2 3] in turn, -and returns a new sequence of two-item vectors with the original item squared. -for supports multiple bindings, which will cause the collections to be iterated in -a nested fashion, much like nesting for loops in imperative languages. The -innermost binding iterates “fastest.” -(for [x [1 2 3] - y [4 5]] - [x y]) - -;; => ([1 4] [1 5] [2 4] [2 5] [3 4] [3 5]) -We can also follow the bindings with three modifiers: :let for creating local -bindings, :while for breaking out of the sequence generation, and :when for -filtering out values. -Here’s an example of local bindings using the :let modifier; note that the -bindings defined with it will be available in the expression: -(for [x [1 2 3] - y [4 5] - :let [z (+ x y)]] - z) -;; => (5 6 6 7 7 8) -We can use the :while modifier for expressing a condition that, when it is no -longer met, will stop the sequence generation. Here’s an example: -(for [x [1 2 3] - y [4 5] - :while (= y 4)] - [x y]) - -;; => ([1 4] [2 4] [3 4]) -For filtering out generated values, use the :when modifier as in the following -example: -(for [x [1 2 3] - y [4 5] - :when (= (+ x y) 6)] - [x y]) - -;; => ([1 5] [2 4]) -We can combine the modifiers shown above for expressing complex sequence generations -or more clearly expressing the intent of our comprehension: -(for [x [1 2 3] - y [4 5] - :let [z (+ x y)] - :when (= z 6)] - [x y]) - -;; => ([1 5] [2 4]) -When we outlined the most common usages of the for construct in imperative -programming languages, we mentioned that sometimes we want to run a computation for -every value in a sequence, not caring about the result. Presumably we do this for -achieving some sort of side-effect with the values of the sequence. -ClojureScript provides the doseq construct, which is analogous to for but -executes the expression, discards the resulting values, and returns nil. -(doseq [x [1 2 3] - y [4 5] - :let [z (+ x y)]] - (println x "+" y "=" z)) - -;; 1 + 4 = 5 -;; 1 + 5 = 6 -;; 2 + 4 = 6 -;; 2 + 5 = 7 -;; 3 + 4 = 7 -;; 3 + 5 = 8 -;; => nil -If you want just iterate and apply some side effectfull operation (like println) -over each item in the collection, you can just use the specialized function run! -that internally uses fast reduction: -(run! println [1 2 3]) -;; 1 -;; 2 -;; 3 -;; => nil -This function explicitly returns nil. -
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    -
    -
    -Collection types -
    -Immutable and persistent -We mentioned before that ClojureScript collections are persistent and immutable, but -we didn’t explain what that meant. -An immutable data structure, as its name suggests, is a data structure that cannot -be changed. In-place updates are not allowed in immutable data structures. -Let’s illustrate that with an example: appending values to a vector using the conj -(conjoin) operation. -(let [xs [1 2 3] - ys (conj xs 4)] - (println "xs:" xs) - (println "ys:" ys)) - -;; xs: [1 2 3] -;; ys: [1 2 3 4] -;; => nil -As you can see, we derived a new version of the xs vector appending an element -to it and got a new vector ys with the element added. However, the xs vector -remained unchanged because it is immutable. -A persistent data structure is a data structure that returns a new version of -itself when transforming it, leaving the original unmodified. ClojureScript makes -this memory and time efficient using an implementation technique called structural -sharing, where most of the data shared between two versions of a value is not -duplicated and transformations of a value are implemented by copying the minimal -amount of data required. -If you want to see an example of how structural sharing works, read on. If you’re -not interested in more details you can skip over to the -next section. -For illustrating the structural sharing of ClojureScript data structures, let’s -compare whether some parts of the old and new versions of a data structure are -actually the same object with the identical? predicate. We’ll use the list data -type for this purpose: -(let [xs (list 1 2 3) - ys (cons 0 xs)] - (println "xs:" xs) - (println "ys:" ys) - (println "(rest ys):" (rest ys)) - (identical? xs (rest ys))) - -;; xs: (1 2 3) -;; ys: (0 1 2 3) -;; (rest ys): (1 2 3) -;; => true -As you can see in the example, we used cons (construct) to prepend a value to -the xs list and we got a new list ys with the element added. The rest of -the ys list (all the values but the first) are the same object in memory as the -xs list, thus xs and ys share structure. -
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    -The sequence abstraction -One of the central ClojureScript abstractions is the sequence which can be -thought of as a list and can be derived from any of the collection types. It is -persistent and immutable like all collection types, and many of the core -ClojureScript functions return sequences. -The types that can be used to generate a sequence are called "seqables"; we can -call seq on them and get a sequence back. Sequences support two basic operations: -first and rest. They both call seq on the argument we provide them: -(first [1 2 3]) -;; => 1 - -(rest [1 2 3]) -;; => (2 3) -Calling seq on a seqable can yield different results if the seqable is empty or -not. It will return nil when empty and a sequence otherwise: -(seq []) -;; => nil - -(seq [1 2 3]) -;; => (1 2 3) -next is a similar sequence operation to rest, but it differs from the latter -in that it yields a nil value when called with a sequence with one or zero -elements. Note that, when given one of the aforementioned sequences, the empty -sequence returned by rest will evaluate as a boolean true whereas the nil -value returned by next will evaluate as false -(see the section on truthiness later in this chapter). -(rest []) -;; => () - -(next []) -;; => nil - -(rest [1 2 3]) -;; => (2 3) - -(next [1 2 3]) -;; => (2 3) -
    -nil-punning -Since seq returns nil when the collection is empty, and nil evaluates to -false in boolean context, you can check to see if a collection is empty by using -the seq function. The technical term for this is nil-punning. -(defn print-coll - [coll] - (when (seq coll) - (println "Saw " (first coll)) - (recur (rest coll)))) - -(print-coll [1 2 3]) -;; Saw 1 -;; Saw 2 -;; Saw 3 -;; => nil - -(print-coll #{1 2 3}) -;; Saw 1 -;; Saw 3 -;; Saw 2 -;; => nil -Though nil is neither a seqable nor a sequence, it is supported by all the -functions we saw so far: -(seq nil) -;; => nil - -(first nil) -;; => nil - -(rest nil) -;; => () -
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    -Functions that work on sequences -The ClojureScript core functions for transforming collections make sequences out -of their arguments and are implemented in terms of the generic sequence operations -we learned about in the preceding section. This makes them highly generic because -we can use them on any data type that is seqable. Let’s see how we can use map -with a variety of seqables: -(map inc [1 2 3]) -;; => (2 3 4) - -(map inc #{1 2 3}) -;; => (2 4 3) - -(map count {:a 41 :b 40}) -;; => (2 2) - -(map inc '(1 2 3)) -;; => (2 3 4) - -When you use the map function on a map collection, your higher-order -function will receive a two-item vector containing a key and value from the map. -The following example uses destructuring to access -the key and value. - -(map (fn [[key value]] (* value value)) - {:ten 10 :seven 7 :four 4}) -;; => (100 49 16) -Obviously the same operation can be done in more idiomatic way only obtaining a seq -of values: -(map (fn [value] (* value value)) - (vals {:ten 10 :seven 7 :four 4})) -;; => (100 49 16) -As you may have noticed, functions that operate on sequences are safe to use with -empty collections or even nil values since they don’t need to do anything but -return an empty sequence when encountering such values. -(map inc []) -;; => () - -(map inc #{}) -;; => () - -(map inc nil) -;; => () -We already saw examples with the usual suspects like map, filter, and reduce, -but ClojureScript offers a plethora of generic sequence operations in its core -namespace. Note that many of the operations we’ll learn about either work with -seqables or are extensible to user-defined types. -We can query a value to know whether it’s a collection type with the coll? -predicate: -(coll? nil) -;; => false - -(coll? [1 2 3]) -;; => true - -(coll? {:language "ClojureScript" :file-extension "cljs"}) -;; => true - -(coll? "ClojureScript") -;; => false -Similar predicates exist for checking if a value is a sequence (with seq?) or a -seqable (with seqable?): -(seq? nil) -;; => false -(seqable? nil) -;; => false - -(seq? []) -;; => false -(seqable? []) -;; => true - -(seq? #{1 2 3}) -;; => false -(seqable? #{1 2 3}) -;; => true - -(seq? "ClojureScript") -;; => false -(seqable? "ClojureScript") -;; => false -For collections that can be counted in constant time, we can use the count -operation. This operation also works on strings, even though, as you have seen, -they are not collections, sequences, or seqable. -(count nil) -;; => 0 - -(count [1 2 3]) -;; => 3 - -(count {:language "ClojureScript" :file-extension "cljs"}) -;; => 2 - -(count "ClojureScript") -;; => 13 -We can also get an empty variant of a given collection with the empty function: -(empty nil) -;; => nil - -(empty [1 2 3]) -;; => [] - -(empty #{1 2 3}) -;; => #{} -The empty? predicate returns true if the given collection is empty: -(empty? nil) -;; => true - -(empty? []) -;; => true - -(empty? #{1 2 3}) -;; => false -The conj operation adds elements to collections and may add them in different -"places" depending on the type of collection. It adds them where it is most -performant for the collection type, but note that not every collection has a -defined order. -We can pass as many elements as we want to add to conj; let’s see it in action: -(conj nil 42) -;; => (42) - -(conj [1 2] 3) -;; => [1 2 3] - -(conj [1 2] 3 4 5) -;; => [1 2 3 4 5] - -(conj '(1 2) 0) -;; => (0 1 2) - -(conj #{1 2 3} 4) -;; => #{1 3 2 4} - -(conj {:language "ClojureScript"} [:file-extension "cljs"]) -;; => {:language "ClojureScript", :file-extension "cljs"} -
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    -Laziness -Most of ClojureScript’s sequence-returning functions generate lazy sequences instead -of eagerly creating a whole new sequence. Lazy sequences generate their contents as -they are requested, usually when iterating over them. Laziness ensures that we don’t -do more work than we need to and gives us the possibility of treating potentially -infinite sequences as regular ones. -Consider the range function, which generates a range of integers: -(range 5) -;; => (0 1 2 3 4) -(range 1 10) -;; => (1 2 3 4 5 6 7 8 9) -(range 10 100 15) -;; (10 25 40 55 70 85) -If you just say (range), you will get an infinite sequence of all the integers. -Do not try this in the REPL, unless you are prepared to wait for a very, very long -time, because the REPL wants to fully evaluate the expression. -Here is a contrived example. Let’s say you are writing a graphing program and you -are graphing the equation y= 2 x 2 + 5, and you want only those values of x -for which the y value is less than 100. You can generate all the numbers 0 through -100, which will certainly be enough, and then take-while the condition holds: -(take-while (fn [x] (< (+ (* 2 x x) 5) 100)) - (range 0 100)) -;; => (0 1 2 3 4 5 6) -
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    -Collections in depth -Now that we’re acquainted with ClojureScript’s sequence abstraction and some of the -generic sequence manipulating functions, it’s time to dive into the concrete -collection types and the operations they support. -
    -Lists -In ClojureScript, lists are mostly used as a data structure for grouping symbols -together into programs. Unlike in other Lisps, many of the syntactic constructs of -ClojureScript use data structures different from the list (vectors and maps). This -makes code less uniform, but the gains in readability are well worth the price. -You can think of ClojureScript lists as singly linked lists, where each node -contains a value and a pointer to the rest of the list. This makes it natural (and -fast!) to add items to the front of the list, since adding to the end would require -traversal of the entire list. The prepend operation is performed using the cons -function. -(cons 0 (cons 1 (cons 2 ()))) -;; => (0 1 2) -We used the literal () to represent the empty list. Since it doesn’t contain any -symbols, it is not treated as a function call. However, when using list literals -that contain elements, we need to quote them to prevent ClojureScript from -evaluating them as a function call: -(cons 0 '(1 2)) -;; => (0 1 2) -Since the head is the position that has constant time addition in the list -collection, the conj operation on lists naturally adds items to the front: -(conj '(1 2) 0) -;; => (0 1 2) -Lists and other ClojureScript data structures can be used as stacks using the -peek, pop, and conj functions. Note that the top of the stack will be the -"place" where conj adds elements, making conj equivalent to the stack’s push -operation. In the case of lists, conj adds elements to the front of the list, -peek returns the first element of the list, and pop returns a list with all the -elements but the first one. -Note that the two operations that return a stack (conj and pop) don’t change the -type of the collection used for the stack. -(def list-stack '(0 1 2)) - -(peek list-stack) -;; => 0 - -(pop list-stack) -;; => (1 2) - -(type (pop list-stack)) -;; => cljs.core/List - -(conj list-stack -1) -;; => (-1 0 1 2) - -(type (conj list-stack -1)) -;; => cljs.core/List -One thing that lists are not particularly good at is random indexed access. Since -they are stored in a single linked list-like structure in memory, random access to a -given index requires a linear traversal in order to either retrieve the requested -item or throw an index out of bounds error. Non-indexed ordered collections like -lazy sequences also suffer from this limitation. -
    -
    -Vectors -Vectors are one of the most common data structures in ClojureScript. They are used -as a syntactic construct in many places where more traditional Lisps use lists, for -example in function argument declarations and let bindings. -ClojureScript vectors have enclosing brackets [] in their syntax literals. They -can be created with vector and from another collection with vec: -(vector? [0 1 2]) -;; => true - -(vector 0 1 2) -;; => [0 1 2] - -(vec '(0 1 2)) -;; => [0 1 2] -Vectors are, like lists, ordered collections of heterogeneous values. Unlike lists, -vectors grow naturally from the tail, so the conj operation appends items to the -end of a vector. Insertion on the end of a vector is effectively constant time: -(conj [0 1] 2) -;; => [0 1 2] -Another thing that differentiates lists and vectors is that vectors are indexed -collections and as such support efficient random index access and non-destructive -updates. We can use the nth function to retrieve values given an index: -(nth [0 1 2] 0) -;; => 0 -Since vectors associate sequential numeric keys (indexes) to values, we can treat -them as an associative data structure. ClojureScript provides the assoc function -that, given an associative data structure and a set of key-value pairs, yields a new -data structure with the values corresponding to the keys modified. Indexes begin at -zero for the first element in a vector. -(assoc ["cero" "uno" "two"] 2 "dos") -;; => ["cero" "uno" "dos"] -Note that we can only assoc to a key that is either contained in the vector -already or if it is the last position in a vector: -(assoc ["cero" "uno" "dos"] 3 "tres") -;; => ["cero" "uno" "dos" "tres"] - -(assoc ["cero" "uno" "dos"] 4 "cuatro") -;; Error: Index 4 out of bounds [0,3] -Perhaps surprisingly, associative data structures can also be used as -functions. They are functions of their keys to the values they are associated -with. In the case of vectors, if the given key is not present an exception is -thrown: -(["cero" "uno" "dos"] 0) -;; => "cero" - -(["cero" "uno" "dos"] 2) -;; => "dos" - -(["cero" "uno" "dos"] 3) -;; Error: Not item 3 in vector of length 3 -As with lists, vectors can also be used as stacks with the peek, pop, and conj -functions. Note, however, that vectors grow from the opposite end of the collection -as lists: -(def vector-stack [0 1 2]) - -(peek vector-stack) -;; => 2 - -(pop vector-stack) -;; => [0 1] - -(type (pop vector-stack)) -;; => cljs.core/PersistentVector - -(conj vector-stack 3) -;; => [0 1 2 3] - -(type (conj vector-stack 3)) -;; => cljs.core/PersistentVector -The map and filter operations return lazy sequences, but as it is common to need -a fully realized sequence after performing those operations, vector-returning -counterparts of such functions are available as mapv and filterv. They have the -advantages of being faster than building a vector from a lazy sequence and making -your intent more explicit: -(map inc [0 1 2]) -;; => (1 2 3) - -(type (map inc [0 1 2])) -;; => cljs.core/LazySeq - -(mapv inc [0 1 2]) -;; => [1 2 3] - -(type (mapv inc [0 1 2])) -;; => cljs.core/PersistentVector -
    -
    -Maps -Maps are ubiquitous in ClojureScript. Like vectors, they are also used as a -syntactic construct, particularly for attaching metadata to -vars. Any ClojureScript data structure can be used as a key in a map, although it’s -common to use keywords since they can also be called as functions. -ClojureScript maps are written literally as key-value pairs enclosed in braces -{}. Alternatively, they can be created with the hash-map function: -(map? {:name "Cirilla"}) -;; => true - -(hash-map :name "Cirilla") -;; => {:name "Cirilla"} - -(hash-map :name "Cirilla" :surname "Fiona") -;; => {:name "Cirilla" :surname "Fiona"} -Since regular maps don’t have a specific order, the conj operation just adds one -or more key-value pairs to a map. conj for maps expects one or more sequences of -key-value pairs as its last arguments: -(def ciri {:name "Cirilla"}) - -(conj ciri [:surname "Fiona"]) -;; => {:name "Cirilla", :surname "Fiona"} - -(conj ciri [:surname "Fiona"] [:occupation "Wizard"]) -;; => {:name "Cirilla", :surname "Fiona", :occupation "Wizard"} -In the preceding example, it just so happens that the order was preserved, but if -you have many keys, you will see that the order is not preserved. -Maps associate keys to values and, as such, are an associative data structure. They -support adding associations with assoc and, unlike vectors, removing them with -dissoc. assoc will also update the value of an existing key. Let’s explore these -functions: -(assoc {:name "Cirilla"} :surname "Fiona") -;; => {:name "Cirilla", :surname "Fiona"} -(assoc {:name "Cirilla"} :name "Alfonso") -;; => {:name "Alfonso"} -(dissoc {:name "Cirilla"} :name) -;; => {} -Maps are also functions of their keys, returning the values related to the given -keys. Unlike vectors, they return nil if we supply a key that is not present in -the map: -({:name "Cirilla"} :name) -;; => "Cirilla" - -({:name "Cirilla"} :surname) -;; => nil -ClojureScript also offers sorted hash maps which behave like their unsorted versions -but preserve order when iterating over them. We can create a sorted map with default -ordering with sorted-map: -(def sm (sorted-map :c 2 :b 1 :a 0)) -;; => {:a 0, :b 1, :c 2} - -(keys sm) -;; => (:a :b :c) -If we need a custom ordering we can provide a comparator function to -sorted-map-by, let’s see an example inverting the value returned by the built-in -compare function. Comparator functions take two items to compare and return -1 (if -the first item is less than the second), 0 (if they are equal), or 1 (if the first -item is greater than the second). -(defn reverse-compare [a b] (compare b a)) - -(def sm (sorted-map-by reverse-compare :a 0 :b 1 :c 2)) -;; => {:c 2, :b 1, :a 0} - -(keys sm) -;; => (:c :b :a) -
    -
    -Sets -Sets in ClojureScript have literal syntax as values enclosed in #{} and they can -be created with the set constructor. They are unordered collections of values -without duplicates. -(set? #{\a \e \i \o \u}) -;; => true - -(set [1 1 2 3]) -;; => #{1 2 3} -Set literals cannot contain duplicate values. If you accidentally write a set -literal with duplicates an error will be thrown: -#{1 1 2 3} -;; clojure.lang.ExceptionInfo: Duplicate key: 1 -There are many operations that can be performed with sets, although they are located -in the clojure.set namespace and thus need to be imported. You’ll learn -the details of namespacing later; for now, you only need to -know that we are loading a namespace called clojure.set and binding it to the s -symbol. -(require '[clojure.set :as s]) - -(def danish-vowels #{\a \e \i \o \u \æ \ø \å}) -;; => #{"a" "e" "å" "æ" "i" "o" "u" "ø"} - -(def spanish-vowels #{\a \e \i \o \u}) -;; => #{"a" "e" "i" "o" "u"} - -(s/difference danish-vowels spanish-vowels) -;; => #{"å" "æ" "ø"} - -(s/union danish-vowels spanish-vowels) -;; => #{"a" "e" "å" "æ" "i" "o" "u" "ø"} - -(s/intersection danish-vowels spanish-vowels) -;; => #{"a" "e" "i" "o" "u"} -A nice property of immutable sets is that they can be nested. Languages that have -mutable sets can end up containing duplicate values, but that can’t happen in -ClojureScript. In fact, all ClojureScript data structures can be nested arbitrarily -due to immutability. -Sets also support the generic conj operation just like every other collection does. -(def spanish-vowels #{\a \e \i \o \u}) -;; => #{"a" "e" "i" "o" "u"} - -(def danish-vowels (conj spanish-vowels \æ \ø \å)) -;; => #{"a" "e" "i" "o" "u" "æ" "ø" "å"} - -(conj #{1 2 3} 1) -;; => #{1 3 2} -Sets act as read-only associative data that associates the values it contains to -themselves. Since every value except nil and false is truthy in ClojureScript, -we can use sets as predicate functions: -(def vowels #{\a \e \i \o \u}) -;; => #{"a" "e" "i" "o" "u"} - -(get vowels \b) -;; => nil - -(contains? vowels \b) -;; => false - -(vowels \a) -;; => "a" - -(vowels \z) -;; => nil - -(filter vowels "Hound dog") -;; => ("o" "u" "o") -Sets have a sorted counterpart like maps do that are created using the functions -sorted-set and sorted-set-by which are analogous to map’s sorted-map and -sorted-map-by. -(def unordered-set #{[0] [1] [2]}) -;; => #{[0] [2] [1]} - -(seq unordered-set) -;; => ([0] [2] [1]) - -(def ordered-set (sorted-set [0] [1] [2])) -;; =># {[0] [1] [2]} - -(seq ordered-set) -;; => ([0] [1] [2]) -
    -
    -Queues -ClojureScript also provides a persistent and immutable queue. Queues are not used as -pervasively as other collection types. They can be created using the #queue [] -literal syntax, but there are no convenient constructor functions for them. -(def pq #queue [1 2 3]) -;; => #queue [1 2 3] -Using conj to add values to a queue adds items onto the rear: -(def pq #queue [1 2 3]) -;; => #queue [1 2 3] - -(conj pq 4 5) -;; => #queue [1 2 3 4 5] -A thing to bear in mind about queues is that the stack operations don’t follow the -usual stack semantics (pushing and popping from the same end). pop takes values -from the front position, and conj pushes (appends) elements to the back. -(def pq #queue [1 2 3]) -;; => #queue [1 2 3] - -(peek pq) -;; => 1 - -(pop pq) -;; => #queue [2 3] - -(conj pq 4) -;; => #queue [1 2 3 4] -Queues are not as frequently used as lists or vectors, but it is good to know that -they are available in ClojureScript, as they may occasionally come in handy. -
    -
    -
    -
    -Destructuring -Destructuring, as its name suggests, is a way of taking apart structured data such -as collections and focusing on individual parts of them. ClojureScript offers a -concise syntax for destructuring both indexed sequences and associative data -structures that can be used any place where bindings are declared. -Let’s see an example of what destructuring is useful for that will help us -understand the previous statements better. Imagine that you have a sequence but are -only interested in the first and third item. You could get a reference to them -easily with the nth function: -(let [v [0 1 2] - fst (nth v 0) - thrd (nth v 2)] - [thrd fst]) -;; => [2 0] -However, the previous code is overly verbose. Destructuring lets us extract values -of indexed sequences more succintly using a vector on the left-hand side of a -binding: -(let [[fst _ thrd] [0 1 2]] - [thrd fst]) -;; => [2 0] -In the above example, [fst _ thrd] is a destructuring form. It is represented as a -vector and used for binding indexed values to the symbols fst and thrd, -corresponding to the index 0 and 2, respectively. The _ symbol is used as a -placeholder for indexes we are not interested in — in this case 1. -Note that destructuring is not limited to the let binding form; it works in almost -every place where we bind values to symbols such as in the for and doseq special -forms or in function arguments. We can write a function that takes a pair and swaps -its positions very concisely using destructuring syntax in function arguments: -(defn swap-pair [[fst snd]] - [snd fst]) - -(swap-pair [1 2]) -;; => [2 1] - -(swap-pair '(3 4)) -;; => [4 3] -Positional destructuring with vectors is quite handy for taking indexed values out -of sequences, but sometimes we don’t want to discard the rest of the elements in the -sequence when destructuring. Similarly to how & is used for accepting variadic -function arguments, the ampersand can be used inside a vector destructuring form for -grouping together the rest of a sequence: -(let [[fst snd & more] (range 10)] - {:first fst - :snd snd - :rest more}) -;; => {:first 0, :snd 1, :rest (2 3 4 5 6 7 8 9)} -Notice how the value in the 0 index got bound to fst, the value in the 1 index -got bound to snd, and the sequence of elements from 2 onwards got bound to the -more symbol. -We may still be interested in a data structure as a whole even when we are -destructuring it. This can be achieved with the :as keyword. If used inside a -destructuring form, the original data structure is bound to the symbol following -that keyword: -(let [[fst snd & more :as original] (range 10)] - {:first fst - :snd snd - :rest more - :original original}) -;; => {:first 0, :snd 1, :rest (2 3 4 5 6 7 8 9), :original (0 1 2 3 4 5 6 7 8 9)} -Not only can indexed sequences be destructured, but associative data can also be -destructured. Its destructuring binding form is represented as a map instead of a -vector, where the keys are the symbols we want to bind values to and the values are -the keys that we want to look up in the associative data structure. Let’s see an -example: -(let [{language :language} {:language "ClojureScript"}] - language) -;; => "ClojureScript" -In the above example, we are extracting the value associated with the :language -key and binding it to the language symbol. When looking up keys that are not -present, the symbol will get bound to nil: -(let [{name :name} {:language "ClojureScript"}] - name) -;; => nil -Associative destructuring lets us give default values to bindings which will be used -if the key isn’t found in the data structure we are taking apart. A map following -the :or keyword is used for default values as the following examples show: -(let [{name :name :or {name "Anonymous"}} {:language "ClojureScript"}] - name) -;; => "Anonymous" - -(let [{name :name :or {name "Anonymous"}} {:name "Cirilla"}] - name) -;; => "Cirilla" -Associative destructuring also supports binding the original data structure to a -symbol placed after the :as keyword: -(let [{name :name :as person} {:name "Cirilla" :age 49}] - [name person]) -;; => ["Cirilla" {:name "Cirilla" :age 49}] -Keywords aren’t the only things that can be the keys of associative data structures. -Numbers, strings, symbols and many other data structures can be used as keys, so we -can destructure using those, too. Note that we need to quote the symbols to prevent -them from being resolved as a var lookup: -(let [{one 1} {0 "zero" 1 "one"}] - one) -;; => "one" - -(let [{name "name"} {"name" "Cirilla"}] - name) -;; => "Cirilla" - -(let [{lang 'language} {'language "ClojureScript"}] - lang) -;; => "ClojureScript" -Since the values corresponding to keys are usually bound to their equivalent symbol -representation (for example, when binding the value of :language to the symbol -language) and keys are usually keywords, strings, or symbols, ClojureScript offers -shorthand syntax for these cases. -We’ll show examples of all of these, starting with destructuring keywords using -:keys: -(let [{:keys [name surname]} {:name "Cirilla" :surname "Fiona"}] - [name surname]) -;; => ["Cirilla" "Fiona"] -As you can see in the example, if we use the :keys keyword and associate it with a -vector of symbols in a binding form, the values corresponding to the keywordized -version of the symbols will be bound to them. The {:keys [name surname]} -destructuring is equivalent to {name :name surname :surname}, only shorter. -The string and symbol shorthand syntax works exactly like :keys, but using the -:strs and :syms keywords respectively: -(let [{:strs [name surname]} {"name" "Cirilla" "surname" "Fiona"}] - [name surname]) -;; => ["Cirilla" "Fiona"] - -(let [{:syms [name surname]} {'name "Cirilla" 'surname "Fiona"}] - [name surname]) -;; => ["Cirilla" "Fiona"] -An interesting property of destructuring is that we can nest destructuring forms -arbitrarily, which makes code that accesses nested data on a collection very easy to -understand, as it mimics the collection’s structure: -(let [{[fst snd] :languages} {:languages ["ClojureScript" "Clojure"]}] - [snd fst]) -;; => ["Clojure" "ClojureScript"] -
    -
    -Threading Macros -Threading macros, also known as arrow functions, enables one to write more readable code -when multiple nested function calls are performed. -Imagine you have (f (g (h x))) where a function f receives as its first parameter the -result of executing function g, repeated multiple times. With the most basic threading -macro you can convert that into (-> x (h) (g) (f)) which is easier to read. -The result is syntactic sugar, because the arrow functions are defined as macros -and it does not imply any runtime performance. The (-> x (h) (g) (f)) is -automatically converted to (f (g (h x))) at compile time. -Take note that the parenthesis on h, g and f are optional, and can be ommited: -(f (g (h x))) is the same as (-> x h g f). -
    -The thread-first macro (<literal>-></literal>) -This is called thread first because it threads the first argument throught the -different expressions as first arguments. -Using a more concrete example, this is how the code looks without using threading -macros: -(def book {:name "Lady of the Lake" - :readers 0}) - -(update (assoc book :age 1999) :readers inc) -;; => {:name "Lady of the lake" :age 1999 :readers 1} -We can rewrite that code to use the -> threading macro: -(-> book - (assoc :age 1999) - (update :readers inc)) -;; => {:name "Lady of the lake" :age 1999 :readers 1} -This threading macro is especially useful for transforming data structures, because -ClojureScript (and Clojure) functions for data structures transformations -consistently uses the first argument for receive the data structure. -
    -
    -The thread-last macro (<literal>->></literal>) -The main difference between the thread-last and thread-first macros is that instead -of threading the first argument given as the first argument on the following expresions, -it threads it as the last argument. -Let’s look at an example: -(def numbers [1 2 3 4 5 6 7 8 9 0]) - -(take 2 (filter odd? (map inc numbers))) -;; => (3 5) -The same code written using ->> threading macro: -(->> numbers - (map inc) - (filter odd?) - (take 2)) -;; => (3 5) -This threading macro is especially useful for transforming sequences or collections -of data because ClojureScript functions that work with sequences and collections -consistently use the last argument position to receive them. -
    -
    -The thread-as macro (<literal>as-></literal>) -Finally, there are cases where neither -> nor ->> are applicable. In these -cases, you’ll need to use as->, the more flexible alternative, that allows you to -thread into any argument position, not just the first or last. -It expects two fixed arguments and an arbitrary number of expressions. As with -->, the first argument is a value to be threaded through the following forms. The -second argument is the name of a binding. In each of the subsequent forms, the bound -name can be used for the prior expression’s result. -Let’s see an example: -(as-> numbers $ - (map inc $) - (filter odd? $) - (first $) - (hash-map :result $ :id 1)) -;; => {:result 3 :id 1} -
    -
    -The thread-some macros (<literal>some-></literal> and <literal>some->></literal>) -Two of the more specialized threading macros that ClojureScript comes with. They work -in the same way as their analagous -> and ->> macros with the additional -support for short-circuiting the expression if one of the expresions evaluates -to nil. -Let’s see another example: -(some-> (rand-nth [1 nil]) - (inc)) -;; => 2 - -(some-> (rand-nth [1 nil]) - (inc)) -;; => nil -This is an easy way avoid null pointer exceptions. -
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    -The thread-cond macros (<literal>cond-></literal> and <literal>cond->></literal>) -The cond-> and cond->> macros are analgous to -> and ->> that offers -the ability to conditionally skip some steps from the pipeline. Let see an example: -(defn describe-number - [n] - (cond-> [] - (odd? n) (conj "odd") - (even? n) (conj "even") - (zero? n) (conj "zero") - (pos? n) (conj "positive"))) - -(describe-number 3) -;; => ["odd" "positive"] - -(describe-number 4) -;; => ["even" "positive"] -The value threading only happens when the corresponding condition evaluates to -logical true. -
    -
    -Additional Readings - - -http://www.spacjer.com/blog/2015/11/09/lesser-known-clojure-variants-of-threading-macro/ - - -http://clojure.org/guides/threading_macros - - -
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    -
    -Reader Conditionals -This language feature allows different dialects of Clojure to share common code that -is mostly platform independent but need some platform dependent code. -To use reader conditionals, all you need is to rename your source file with -.cljs extension to one with .cljc, because reader conditionals only work if -they are placed in files with .cljc extension. -
    -Standard (<literal>#?</literal>) -There are two types of reader conditionals, standard and splicing. The standard -reader conditional behaves similarly to a traditional cond and the syntax looks -like this: -(defn parse-int - [v] - #?(:clj (Integer/parseInt s) - :cljs (js/parseInt s))) -As you can observe, #? reading macro looks very similar to cond, the difference is -that the condition is just a keyword that identifies the platform, where :cljs is -for ClojureScript and :clj is for Clojure. The advantage of this approach, is -that it is evaluated at compile time so no runtime performance overhead exists for -using this. -
    -
    -Splicing (<literal>#?@</literal>) -The splicing reader conditional works in the same way as the standard and allows -splice lists into the containing form. The #?@ reader macro is used for that -and the code looks like this: -(defn make-list - [] - (list #?@(:clj [5 6 7 8] - :cljs [1 2 3 4]))) - -;; On ClojureScript -(make-list) -;; => (1 2 3 4) -The ClojureScript compiler will read that code as this: -(defn make-list - [] - (list 1 2 3 4)) -The splicing reader conditional can’t be used to splice multiple top level forms, -so the following code is ilegal: -#?@(:cljs [(defn func-a [] :a) - (defn func-b [] :b)]) -;; => #error "Reader conditional splicing not allowed at the top level." -If you need so, you can use multiple forms or just use do block for group -multiple forms together: -#?(:cljs (defn func-a [] :a)) -#?(:cljs (defn func-b [] :b)) - -;; Or - -#?(:cljs - (do - (defn func-a [] :a) - (defn func-b [] :b))) -
    -
    -More readings - - -http://clojure.org/guides/reader_conditionals - - -https://danielcompton.net/2015/06/10/clojure-reader-conditionals-by-example - - -https://github.com/funcool/cuerdas (example small project that uses -reader conditionals) - - -
    -
    -
    -Namespaces -
    -Defining a namespace -The namespace is ClojureScript’s fundamental unit of code modularity. Namespaces -are analogous to Java packages or Ruby and Python modules and can be defined with -the ns macro. If you have ever looked at a little bit of ClojureScript source, you -may have noticed something like this at the beginning of the file: -(ns myapp.core - "Some docstring for the namespace.") - -(def x "hello") -Namespaces are dynamic, meaning you can create one at any time. However, the -convention is to have one namespace per file. Naturally, a namespace definition is -usually at the beginning of the file, followed by an optional docstring. -Previously we have explained vars and symbols. Every var that you define will be -associated with its namespace. If you do not define a concrete namespace, then the -default one called "cljs.user" will be used: -(def x "hello") -;; => #'cljs.user/x -
    -
    -Loading other namespaces -Defining a namespace and the vars in it is really easy, but it’s not very useful if -we can’t use symbols from other namespaces. For this purpose, the ns macro offers -a simple way to load other namespaces. -Observe the following: -(ns myapp.main - (:require myapp.core - clojure.string)) - -(clojure.string/upper-case myapp.core/x) -;; => "HELLO" -As you can observe, we are using fully qualified names (namespace + var name) for -access to vars and functions from different namespaces. -While this will let you access other namespaces, it’s also repetitive and overly -verbose. It will be especially uncomfortable if the name of a namespace is very -long. To solve that, you can use the :as directive to create an additional -(usually shorter) alias to the namespace. This is how it can be done: -(ns myapp.main - (:require [myapp.core :as core] - [clojure.string :as str])) - -(str/upper-case core/x) -;; => "HELLO" -Additionally, ClojureScript offers a simple way to refer to specific vars or -functions from a concrete namespace using the :refer directive, followed by a -sequence of symbols that will refer to vars in the namespace. Effectively, it is as -if those vars and functions are now part of your namespace, and you do not need to -qualify them at all. -(ns myapp.main - (:require [clojure.string :refer [upper-case]])) -(upper-case x) -;; => "HELLO" -And finally, you should know that everything located in the cljs.core namespace is -automatically loaded and you should not require it explicitly. Sometimes you may -want to declare vars that will clash with some others defined in the cljs.core -namespace. To do this, the ns macro offers another directive that allows you to -exclude specific symbols and prevent them from being automatically loaded. -Observe the following: -(ns myapp.main - (:refer-clojure :exclude [min])) - -(defn min - [x y] - (if (> x y) - y - x)) -The ns macro also has other directives for loading host classes (with :import) -and macros (with :refer-macros), but these are explained in other sections. -
    -
    -Namespaces and File Names -When you have a namespace like myapp.core, the code must be in a file named -core.cljs inside the myapp directory. So, the preceding examples with -namespaces myapp.core and myapp.main would be found in project with a file -structure like this: -myapp -└── src - └── myapp - ├── core.cljs - └── main.cljs -
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    -
    -Abstractions and Polymorphism -I’m sure that at more than one time you have found yourself in this situation: you -have defined a great abstraction (using interfaces or something similar) for your -"business logic", and you have found the need to deal with another module over which -you have absolutely no control, and you probably were thinking of creating adapters, -proxies, and other approaches that imply a great amount of additional complexity. -Some dynamic languages allow "monkey-patching"; languages where the classes are open -and any method can be defined and redefined at any time. Also, it is well known that -this technique is a very bad practice. -We can not trust languages that allow you to silently overwrite methods that you are -using when you import third party libraries; you cannot expect consistent behavior -when this happens. -These symptoms are commonly called the "expression problem"; -see http://en.wikipedia.org/wiki/Expression_problem for more details -
    -Protocols -The ClojureScript primitive for defining "interfaces" is called a protocol. A -protocol consists of a name and set of functions. All the functions have at least -one argument corresponding to the this in JavaScript or self in Python. -Protocols provide a type-based polymorphism, and the dispatch is always done by the -first argument (equivalent to JavaScript’s this, as previously mentioned). -A protocol looks like this: -(ns myapp.testproto) - -(defprotocol IProtocolName - "A docstring describing the protocol." - (sample-method [this] "A doc string associated with this function.")) - -the "I" prefix is commonly used to designate the separation of protocols and -types. In the Clojure community, there are many different opinions about how the "I" -prefix should be used. In our opinion, it is an acceptable solution to avoid name -clashing and possible confusion. But not using the prefix is not considered bad -practice. - -From the user perspective, protocol functions are simply plain functions defined in -the namespace where the protocol is defined. This enables an easy and simple aproach -for avoid conflicts between different protocols implemented for the same type that -have conflicting function names. -Here is an example. Let’s create a protocol called IInvertible for data that can -be "inverted". It will have a single method named invert. -(defprotocol IInvertible - "This is a protocol for data types that are 'invertible'" - (invert [this] "Invert the given item.")) -
    -Extending existing types -One of the big strengths of protocols is the ability to extend existing and maybe -third party types. This operation can be done in different ways. -The majority of time you will tend to use the extend-protocol or the extend-type -macros. This is how extend-type syntax looks: -(extend-type TypeA - ProtocolA - (function-from-protocol-a [this] - ;; implementation here - ) - - ProtocolB - (function-from-protocol-b-1 [this parameter1] - ;; implementation here - ) - (function-from-protocol-b-2 [this parameter1 parameter2] - ;; implementation here - )) -You can observe that with extend-type you are extending a single type with -different protocols in a single expression. -Let’s play with our IInvertible protocol defined previously: -(extend-type string - IInvertible - (invert [this] (apply str (reverse this)))) - -(extend-type cljs.core.List - IInvertible - (invert [this] (reverse this))) - -(extend-type cljs.core.PersistentVector - IInvertible - (invert [this] (into [] (reverse this)))) -You may note that a special symbol string is used instead of js/String for -extend the protol for string. This is because the builtin javascript types have -special treatment and if you replace the string with js/String the compiler -will emit a warning about that. -So if you want extend your protocol to javascript primitive types, instead of using -js/Number, js/String, js/Object, js/Array, js/Boolean and js/Function -you should use the respective special symbols: number, string, object, -array, boolean and function. -Now, it’s time to try our protocol implementation: -(invert "abc") -;; => "cba" - -(invert 0) -;; => 0 - -(invert '(1 2 3)) -;; => (3 2 1) - -(invert [1 2 3]) -;; => [3 2 1] -In comparison, extend-protocol does the inverse; given a protocol, it adds -implementations for multiple types. This is how the syntax looks: -(extend-protocol ProtocolA - TypeA - (function-from-protocol-a [this] - ;; implementation here - ) - - TypeB - (function-from-protocol-a [this] - ;; implementation here - )) -Thus, the previous example could have been written equally well with this way: -(extend-protocol IInvertible - string - (invert [this] (apply str (reverse this))) - - cljs.core.List - (invert [this] (reverse this)) - - cljs.core.PersistentVector - (invert [this] (into [] (reverse this)))) -
    -
    -Participate in ClojureScript abstractions -ClojureScript itself is built up on abstractions defined as protocols. Almost all -behavior in the ClojureScript language itself can be adapted to third party -libraries. Let’s look at a real life example. -In previous sections, we have explained the different kinds of built-in -collections. For this example we will use a set. See this snippet of code: -(def mynums #{1 2}) - -(filter mynums [1 2 4 5 1 3 4 5]) -;; => (1 2 1) -What happened? In this case, the set type implements the ClojureScript internal -IFn protocol that represents an abstraction for functions or anything -callable. This way it can be used like a callable predicate in filter. -OK, but what happens if we want to use a regular expression as a predicate function -for filtering a collection of strings: -(filter #"^foo" ["haha" "foobar" "baz" "foobaz"]) -;; TypeError: Cannot call undefined -The exception is raised because the RegExp type does not implement the IFn -protocol so it cannot behave like a callable, but that can be easily fixed: -(extend-type js/RegExp - IFn - (-invoke - ([this a] - (re-find this a)))) -Let’s analyze this: we are extending the js/RegExp type so that it implements the -invoke function in the IFn protocol. To invoke a regular expression a as if it -were a function, call the re-find function with the object of the function and the -pattern. -Now, you will be able use the regex instances as predicates in a filter operation: -(filter #"^foo" ["haha" "foobar" "baz" "foobaz"]) -;; => ("foobar" "foobaz") -
    -
    -Introspection using Protocols -ClojureScript comes with a useful function that allows runtime introspection: -satisfies?. The purpose of this function is to determine at runtime if some object -(instance of some type) satisfies the concrete protocol. -So, with the previous examples, if we check if a set instance satisfies an IFn -protocol, it should return true: -(satisfies? IFn #{1}) -;; => true -
    -
    -
    -Multimethods -We have previously talked about protocols which solve a very common use case of -polymorphism: dispatch by type. But in some circumstances, the protocol approach can -be limiting. And here, multimethods come to the rescue. -These multimethods are not limited to type dispatch only; instead, they also offer -dispatch by types of multiple arguments and by value. They also allow ad-hoc -hierarchies to be defined. Also, like protocols, multimethods are an "Open System", -so you or any third parties can extend a multimethod for new types. -The basic constructions of multimethods are the defmulti and defmethod -forms. The defmulti form is used to create the multimethod with an initial -dispatch function. This is a model of what it looks like: -(defmulti say-hello - "A polymorphic function that return a greetings message - depending on the language key with default lang as `:en`" - (fn [param] (:locale param)) - :default :en) -The anonymous function defined within the defmulti form is a dispatch function. It -will be called in every call to the say-hello function and should return some kind -of marker object that will be used for dispatch. In our example, it returns the -contents of the :locale key of the first argument. -And finally, you should add implementations. That is done with the defmethod form: -(defmethod say-hello :en - [person] - (str "Hello " (:name person "Anonymous"))) - -(defmethod say-hello :es - [person] - (str "Hola " (:name person "Anónimo"))) -So, if you execute that function over a hash map containing the :locale and -optionally the :name key, the multimethod will first call the dispatch function to -determine the dispatch value, then it will search for an implementation for that -value. If an implementation is found, the dispatcher will execute it. Otherwise, the -dispatch will search for a default implementation (if one is specified) and execute -it. -(say-hello {:locale :es}) -;; => "Hola Anónimo" - -(say-hello {:locale :en :name "Ciri"}) -;; => "Hello Ciri" - -(say-hello {:locale :fr}) -;; => "Hello Anonymous" -If the default implementation is not specified, an exception will be raised -notifying you that some value does not have an implementation for that multimethod. -
    -
    -Hierarchies -Hierarchies are ClojureScript’s way to let you build whatever relations that your -domain may require. Hierarchies are defined in term of relations between named -objects, such as symbols, keywords, or types. -Hierarchies can be defined globally or locally, depending on your needs. Like -multimethods, hierarchies are not limited to a single namespace. You can extend a -hierarchy from any namespace, not only from the one in which it is defined. -The global namespace is more limited, for good reasons. Keywords or symbols that are -not namespaced can not be used in the global hierarchy. That behavior helps prevent -unexpected situations when two or more third party libraries use the same symbol for -different semantics. -
    -Defining a hierarchy -The hierarchy relations should be established using the derive function: -(derive ::circle ::shape) -(derive ::box ::shape) -We have just defined a set of relationships between namespaced keywords. In this -case the ::circle is a child of ::shape, and ::box is also a child of -::shape. - -The ::circle keyword syntax is a shorthand for :current.ns/circle. So if -you are executing it in a REPL, ::circle will be evaluated as :cljs.user/circle. - -
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    -Hierarchies and introspection -ClojureScript comes with a little toolset of functions that allows runtime -introspection of globally or locally defined hierarchies. This toolset consists of -three functions: isa?, ancestors, and descendants. -Let’s see an example of how it can be used with the hierarchy defined in the -previous example: -(ancestors ::box) -;; => #{:cljs.user/shape} - -(descendants ::shape) -;; => #{:cljs.user/circle :cljs.user/box} - -(isa? ::box ::shape) -;; => true - -(isa? ::rect ::shape) -;; => false -
    -
    -Locally defined hierarchies -As we mentioned previously, in ClojureScript you also can define local -hierarchies. This can be done with the make-hierarchy function. Here is an example -of how you can replicate the previous example using a local hierarchy: -(def h (-> (make-hierarchy) - (derive :box :shape) - (derive :circle :shape))) -Now you can use the same introspection functions with that locally defined -hierarchy: -(isa? h :box :shape) -;; => true - -(isa? :box :shape) -;; => false -As you can observe, in local hierarchies we can use normal (not namespace qualified) -keywords, and if we execute the isa? without passing the local hierarchy -parameter, it returns false as expected. -
    -
    -Hierarchies in multimethods -One of the big advantages of hierarchies is that they work very well together with -multimethods. This is because multimethods by default use the isa? function for -the last step of dispatching. -Let’s see an example to clearly understand what that means. First, we define the -multimethod with the defmulti form: -(defmulti stringify-shape - "A function that prints a human readable representation - of a shape keyword." - identity - :hierarchy #'h) -With the :hierarchy keyword parameter, we indicate to the multimethod what -hierarchy we want to use; if it is not specified, the global hierarchy will be used. -Second, we define an implementation for our multimethod using the defmethod form: -(defmethod stringify-shape :box - [_] - "A box shape") - -(defmethod stringify-shape :shape - [_] - "A generic shape") - -(defmethod stringify-shape :default - [_] - "Unexpected object") -Now, let’s see what happens if we execute that function with a box: -(stringify-shape :box) -;; => "A box shape" -Now everything works as expected; the multimethod executes the direct matching -implementation for the given parameter. Next, let’s see what happens if we execute -the same function but with the :circle keyword as the parameter which does not -have the direct matching dispatch value: -(stringify-shape :circle) -;; => "A generic shape" -The multimethod automatically resolves it using the provided hierarchy, and since -:circle is a descendant of :shape, the :shape implementation is executed. -Finally, if you give a keyword that isn’t part of the hierarchy, you get the -:default implementation: -(stringify-shape :triangle) -;; => "Unexpected object" -
    -
    -
    -
    -Data types -Until now, we have used maps, sets, lists, and vectors to represent our data. And in -most cases, this is a really great approach. But sometimes we need to define our own -types, and in this book we will call them data types. -A data type provides the following: - - -A unique host-backed type, either named or anonymous. - - -The ability to implement protocols (inline). - - -Explicitly declared structure using fields or closures. - - -Map-like behavior (via records, see below). - - -
    -Deftype -The most low-level construction in ClojureScript for creating your own types is -the deftype macro. As a demonstration, we will define a type called User: -(deftype User [firstname lastname]) -Once the type has been defined, we can create an instance of our User. In the -following example, the . after User indicates that we are calling a constructor. -(def person (User. "Triss" "Merigold")) -Its fields can be accessed using the prefix dot notation: -(.-firstname person) -;; => "Triss" -Types defined with deftype (and defrecord, which we will see later) create a -host-backed class-like object associated with the current namespace. For -convenience, ClojureScript also defines a constructor function called →User -that can be imported using the :require directive. -We personally do not like this type of function, and we prefer to define our own -constructors with more idiomatic names: -(defn make-user - [firstname lastname] - (User. firstname lastname)) -We use this in our code instead of →User. -
    -
    -Defrecord -The record is a slightly higher-level abstraction for defining types in -ClojureScript and should be the preferred way to do it. -As we know, ClojureScript tends to use plain data types such as maps, but in most -cases we need a named type to represent the entities of our application. Here come -the records. -A record is a data type that implements the map protocol and therefore can be used -like any other map. And since records are also proper types, they support -type-based polymorphism through protocols. -In summary: with records, we have the best of both worlds, maps that can play in -different abstractions. -Let’s start defining the User type but using records: -(defrecord User [firstname lastname]) -It looks really similar to the deftype syntax; in fact, it uses deftype behind -the scenes as a low-level primitive for defining types. -Now, look at the difference with raw types for access to its fields: -(def person (User. "Yennefer" "of Vengerberg")) - -(:firstname person) -;; => "Yennefer" - -(get person :firstname) -;; => "Yennefer" -As we mentioned previously, records are maps and act like them: -(map? person) -;; => true -And like maps, they support extra fields that are not initially defined: -(def person2 (assoc person :age 92)) - -(:age person2) -;; => 92 -As we can see, the assoc function works as expected and returns a new instance of -the same type but with new key value pair. But take care with dissoc! Its behavior -with records is slightly different than with maps; it will return a new record if -the field being dissociated is an optional field, but it will return a plain map if -you dissociate a mandatory field. -Another difference with maps is that records do not act like functions: -(def plain-person {:firstname "Yennefer", :lastname "of Vengerberg"}) - -(plain-person :firstname) -;; => "Yennefer" - -(person :firstname) -;; => person.User does not implement IFn protocol. -For convenience, the defrecord macro, like deftype, exposes a →User function, -as well as an additional map→User constructor function. We have the same opinion -about that constructor as with deftype defined ones: we recommend defining your -own instead of using the other ones. But as they exist, let’s see how they can be -used: -(def cirilla (->User "Cirilla" "Fiona")) -(def yen (map->User {:firstname "Yennefer" - :lastname "of Vengerberg"})) -
    -
    -Implementing protocols -Both type definition primitives that we have seen so far allow inline -implementations for protocols (explained in a previous section). Let’s define one -for example purposes: -(defprotocol IUser - "A common abstraction for working with user types." - (full-name [_] "Get the full name of the user.")) -Now, you can define a type with inline implementation for an abstraction, in our -case the IUser: -(defrecord User [firstname lastname] - IUser - (full-name [_] - (str firstname " " lastname))) - -;; Create an instance. -(def user (User. "Yennefer" "of Vengerberg")) - -(full-name user) -;; => "Yennefer of Vengerberg" -
    -
    -Reify -The reify macro is an ad hoc constructor you can use to create objects without -pre-defining a type. Protocol implementations are supplied the same as deftype -and defrecord, but in contrast, reify does not have accessible fields. -This is how we can emulate an instance of the user type that plays well with the -IUser abstraction: -(defn user - [firstname lastname] - (reify - IUser - (full-name [_] - (str firstname " " lastname)))) - -(def yen (user "Yennefer" "of Vengerberg")) -(full-name yen) -;; => "Yennefer of Vengerberg" -
    -
    -Specify -specify! is an advanced alternative to reify, allowing you to add protocol -implementations to an existing JavaScript object. This can be useful if you want to -graft protocols onto a JavaScript library’s components. -(def obj #js {}) - -(specify! obj - IUser - (full-name [_] - "my full name")) - -(full-name obj) -;; => "my full name" -specify is an immutable version of specify! that can be used on immutable, -copyable values implementing ICloneable (e.g. ClojureScript collections). -(def a {}) - -(def b (specify a - IUser - (full-name [_] - "my full name"))) - -(full-name a) -;; Error: No protocol method IUser.full-name defined for type cljs.core/PersistentArrayMap: {} - -(full-name b) -;; => "my full name" -
    -
    -
    -Host interoperability -ClojureScript, in the same way as its brother Clojure, is designed to be a "guest" -language. This means that the design of the language works well on top of an -existing ecosystem such as JavaScript for ClojureScript and the JVM for Clojure. -
    -The types -ClojureScript, unlike what you might expect, tries to take advantage of every type -that the platform provides. This is a (perhaps incomplete) list of things that -ClojureScript inherits and reuses from the underlying platform: - - -ClojureScript strings are JavaScript Strings. - - -ClojureScript numbers are JavaScript Numbers. - - -ClojureScript nil is a JavaScript null. - - -ClojureScript regular expressions are JavaScript RegExp instances. - - -ClojureScript is not interpreted; it is always compiled down to JavaScript. - - -ClojureScript allows easy call to platform APIs with the same semantics. - - -ClojureScript data types internally compile to objects in JavaScript. - - -On top of it, ClojureScript builds its own abstractions and types that do not -exist in the platform, such as Vectors, Maps, Sets, and others that are explained in -preceding sections of this chapter. -
    -
    -Interacting with platform types -ClojureScript comes with a little set of special forms that allows it to interact -with platform types such as calling object methods, creating new instances, and -accessing object properties. -
    -Access to the platform -ClojureScript has a special syntax for access to the entire platform environment -through the js/ special namespace. This is an example of an expression to execute -JavaScript’s built-in parseInt function: -(js/parseInt "222") -;; => 222 -
    -
    -Creating new instances -ClojureScript has two ways to create instances: -Using the new special form -(new js/RegExp "^foo$") -Using the . special form -(js/RegExp. "^foo$") -The last one is the recommended way to create instances. We are not aware of any -real differences between the two forms, but in the ClojureScript community, the last -one is used most often. -
    -
    -Invoke instance methods -To invoke methods of some object instance, as opposed to how it is done in -JavaScript (e.g., obj.method(), the method name comes first like any other -standard function in Lisp languages but with a little variation: the function name -starts with special form .. -Let’s see how we can call the .test() method of a regexp instance: -(def re (js/RegExp "^Clojure")) - -(.test re "ClojureScript") -;; => true -You can invoke instance methods on JavaScript objects. The first example follows the -pattern you have seen; the last one is a shortcut: -(.sqrt js/Math 2) -;; => 1.4142135623730951 -(js/Math.sqrt 2) -;; => 1.4142135623730951 -
    -
    -Access to object properties -Access to an object’s properties is really very similar to calling a method. The -difference is that instead of using the . you use .-. Let’s see an example: -(.-multiline re) -;; => false -(.-PI js/Math) -;; => 3.141592653589793 -
    -
    -Property access shorthand -Symbols with the js/ prefix can contain dots to denote nested property access. -Both of the following expressions invoke the same function: -(.log js/console "Hello World") - -(js/console.log "Hello World") -And both of the following expressions access the same property: -(.-PI js/Math) -;; => 3.141592653589793 - -js/Math.PI -;; => 3.141592653589793 -
    -
    -JavaScript objects -ClojureScript has different ways to create plain JavaScript objects; each one has -its own purpose. The basic one is the js-obj function. It accepts a variable -number of pairs of keys and values and returns a JavaScript object: -(js-obj "country" "FR") -;; => #js {:country "FR"} -The return value can be passed to some kind of third party library that accepts a -plain JavaScript object, but you can observe the real representation of the return -value of this function. It is really another form for doing the same thing. -Using the reader macro #js consists of prepending it to a ClojureScript map or -vector, and the result will be transformed to plain JavaScript: -(def myobj #js {:country "FR"}) -The translation of that to plain JavaScript is similar to this: -var myobj = {country: "FR"}; -As explained in the previous section, you can also access the plain object -properties using the .- syntax: -(.-country myobj) -;; => "FR" -And as JavaScript objects are mutable, you can set a new value for some property -using the set! function: -(set! (.-country myobj) "KR") -
    -
    -Conversions -The inconvenience of the previously explained forms is that they do not make -recursive transformations, so if you have nested objects, the nested objects will -not be converted. Consider this example that uses Clojurescript maps, then a -similar one with JavaScript objects: -(def clj-map {:country {:code "FR" :name "France"}}) -;; => {:country {:code "FR", :name "France"}} -(:code (:country clj-map) -;; => "FR" - -(def js-obj #js {:country {:code "FR" :name "France"}}) -;; => #js {:country {:code "FR", :name "France"} -(.-country js-obj) -;; => {:code "FR", :name "France"} -(.-code (.-country js-obj) -;; => nil -To solve that use case, ClojureScript comes with the clj→js and js→clj -functions that transform Clojure collection types into JavaScript and back. Note -that the conversion to ClojureScript changes the :country keyword to a string. -(clj->js {:foo {:bar "baz"}}) -;; => #js {:foo #js {:bar "baz"}} -(js->clj #js {:country {:code "FR" :name "France"}})) -;; => {"country" {:code "FR", :name "France"}} -In the case of arrays, there is a specialized function into-array that behaves as -expected: -(into-array ["France" "Korea" "Peru"]) -;; => #js ["France" "Korea" "Peru"] -
    -
    -Arrays -In the previous example, we saw how we can create an array from an existing -ClojureScript collection. But there is another function for creating arrays: -make-array. - -Creating a preallocated array with length 10 - -(def a (make-array 10)) -;; => #js [nil nil nil nil nil nil nil nil nil nil] - - -In ClojureScript, arrays also play well with sequence abstractions, so you can -iterate over them or simply get the number of elements with the count function: -(count a) -;; => 10 -As arrays in the JavaScript platform are a mutable collection type, you can access a -concrete index and set the value at that position: -(aset a 0 2) -;; => 2 -a -;; => #js [2 nil nil nil nil nil nil nil nil nil] -Or access in an indexed way to get its values: -(aget a 0) -;; => 2 -In JavaScript, array index access is equivalent to object property access, so you -can use the same functions for interacting with plain objects: -(def b #js {:hour 16}) -;; => #js {:hour 16} - -(aget b "hour") -;; => 16 - -(aset b "minute" 22) -;; => 22 - -b -;; => #js {:hour 16, :minute 22} -
    -
    -
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    -State management -We’ve learned that one of ClojureScript’s fundamental ideas is immutability. Both -scalar values and collections are immutable in ClojureScript, except those mutable -types present in the JS host like Date. -Immutability has many great properties but we are sometimes faced with the need to -model values that change over time. How can we achieve this if we can’t change data -structures in place? -
    -Vars -Vars can be redefined at will inside a namespace but there is no way to know when -they change. The inability to redefine vars from other namespaces is a bit limiting; -also, if we are modifying state, we’re probably interested in knowing when it -occurs. -
    -
    -Atoms -ClojureScript gives us the Atom type, which is an object containing a value that -can be altered at will. Besides altering its value, it also supports observation -through watcher functions that can be attached and detached from it and validation -for ensuring that the value contained in the atom is always valid. -If we were to model an identity corresponding to a person called Ciri, we could wrap -an immutable value containing Ciri’s data in an atom. Note that we can get the -atom’s value with the deref function or using its shorthand @ notation: -(def ciri (atom {:name "Cirilla" :lastname "Fiona" :age 20})) -;; #<Atom: {:name "Cirilla", :lastname "Fiona", :age 20}> - -(deref ciri) -;; {:name "Cirilla", :lastname "Fiona", :age 20} - -@ciri -;; {:name "Cirilla", :lastname "Fiona", :age 20} -We can use the swap! function on an atom to alter its value with a function. Since -Ciri’s birthday is today, let’s increment her age count: -(swap! ciri update :age inc) -;; {:name "Cirilla", :lastname "Fiona", :age 21} - -@ciri -;; {:name "Cirilla", :lastname "Fiona", :age 21} -The reset! functions replaces the value contained in the atom with a new one: -(reset! ciri {:name "Cirilla", :lastname "Fiona", :age 22}) -;; {:name "Cirilla", :lastname "Fiona", :age 22} - -@ciri -;; {:name "Cirilla", :lastname "Fiona", :age 22} -
    -Observation -We can add and remove watcher functions for atoms. Whenever the atom’s value is -changed through a swap! or reset!, all the atom’s watcher functions will be -called. Watchers are added with the add-watch function. Notice that each watcher -has a key associated (:logger in the example) to it which is later used to remove -the watch from the atom. -(def a (atom)) - -(add-watch a :logger (fn [key the-atom old-value new-value] - (println "Key:" key "Old:" old-value "New:" new-value))) - -(reset! a 42) -;; Key: :logger Old: nil New: 42 -;; => 42 - -(swap! a inc) -;; Key: :logger Old: 42 New: 43 -;; => 43 - -(remove-watch a :logger) -
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    -
    -Volatiles -Volatiles, like atoms, are objects containing a value that can be altered. However, -they don’t provide the observation and validation capabilities that atoms -provide. This makes them slightly more performant and a more suitable mutable -container to use inside stateful functions that don’t need observation nor -validation. -Their API closely resembles that of atoms. They can be dereferenced to grab the -value they contain and support swapping and resetting with vswap! and vreset! -respectively: -(def ciri (volatile! {:name "Cirilla" :lastname "Fiona" :age 20})) -;; #<Volatile: {:name "Cirilla", :lastname "Fiona", :age 20}> - -(volatile? ciri) -;; => true - -(deref ciri) -;; {:name "Cirilla", :lastname "Fiona", :age 20} - -(vswap! ciri update :age inc) -;; {:name "Cirilla", :lastname "Fiona", :age 21} - -(vreset! ciri {:name "Cirilla", :lastname "Fiona", :age 22}) -;; {:name "Cirilla", :lastname "Fiona", :age 22} -Note that another difference with atoms is that the constructor of volatiles uses a -bang at the end. You create volatiles with volatile! and atoms with atom. -
    -
    -
    - -Tooling & Compiler -This chapter will cover a little introduction to existing tooling for making things -easy when developing using ClojureScript. It will cover: - - -Using the REPL - - -Leiningen and cljsbuild - - -Google Closure Library - - -Modules - - -Unit testing - - -Library development - - -Browser based development - - -Server based development - - -Unlike the previous chapter, this chapter intends to tell different stories each -independent of the other. -
    -Getting Started with the Compiler -At this point, you are surely very bored with the constant theoretical explanations -about the language itself and will want to write and execute some code. The goal of -this section is to provide a little practical introduction to the ClojureScript -compiler. -The ClojureScript compiler takes the source code that has been split over numerous -directories and namespaces and compiles it down to JavaScript. Today, JavaScript has -a great number of different environments where it can be executed - each with its own -peculiarities. -This chapter intends to explain how to use ClojureScript without any additional -tooling. This will help you understand how the compiler works and how you can use it -when other tooling is not available (such as leiningen -cljsbuild or -boot). -
    -Execution environments -What is an execution environment? An execution environment is an engine where -JavaScript can be executed. For example, the most popular execution environment is a -browser (Chrome, Firefox, …​) followed by the second most popular - -nodejs. -There are others, such as Rhino (JDK 6+), Nashorn (JDK 8), QtQuick (QT),…​ but none -of them have significant differences from the first two. So, ClojureScript at the -moment may compile code to run in the browser or in nodejs-like environments out of -the box. -
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    -Download the compiler -Although the ClojureScript is self hosted, the best way to use it is just using the -JVM implementation. To use it, you should have jdk8 installed. ClojureScript itself -only requires JDK 7, but the standalone compiler that we are going to use in this -chapter requires JDK 8, which can be found at -http://www.oracle.com/technetwork/java/javase/downloads/jdk8-downloads-2133151.html -You can download the latest ClojureScript compiler using wget: -wget https://github.com/clojure/clojurescript/releases/download/r1.9.36/cljs.jar -The ClojureScript compiler is packaged in a standalone executable jar file, so this -is the only file (along with JDK 8) that you need to compile your ClojureScript -source code to JavaScript. -
    -
    -Compile for Node.js -Let’s start with a practical example compiling code that will target Node.js -(hereafter simply "nodejs"). For this example, you should have nodejs installed. -There are different ways to install nodejs, but the recommended way is using nvm -("Node.js Version Manager"). You can read the instructions on how to install and use -nvm on its home page. -When you have installed nvm, follow installing the latest version of nodejs: -nvm install v6.2.0 -nvm alias default v6.2.0 -You can test if nodejs is installed in your system with this command: -$ node --version -v6.2.0 -
    -Create the example application -For the first step of our practical example, we will create our application directory -structure and populate it with example code. -Start by creating the directory tree structure for our “hello world” application: -mkdir -p myapp/src/myapp -touch myapp/src/myapp/core.cljs -Resulting in this directory tree: -myapp -└── src - └── myapp - └── core.cljs -Second, write the example code into the previously created -myapp/src/myapp/core.cljs file: -(ns myapp.core - (:require [cljs.nodejs :as nodejs])) - -(nodejs/enable-util-print!) - -(defn -main - [& args] - (println "Hello world!")) - -(set! *main-cli-fn* -main) - -It is very important that the declared namespace in the file exactly matches -the directory structure. This is the way ClojureScript structures its source code. - -
    -
    -Compile the example application -In order to compile that source code, we need a simple build script that tells the -ClojureScript compiler the source directory and the output file. ClojureScript -has a lot of other options, but at this moment we can ignore that. -Let’s create the myapp/build.clj file with the following content: -(require '[cljs.build.api :as b]) - -(b/build "src" - {:main 'myapp.core - :output-to "main.js" - :output-dir "out" - :target :nodejs - :verbose true}) -This is a brief explanation of the compiler options used in this example: - - -The :output-to parameter indicates to the compiler the destination of the compiled -code, in this case to the "main.js" file. - - -The :main property indicates to the compiler the namespace that will act as the entry -point of your application when it’s executed. - - -The :target property indicates the platform where you want to execute the compiled -code. In this case, we are going to use nodejs. If you omit this -parameter, the source will be compiled to run in the browser environment. - - -To run the compilation, just execute the following command: -cd myapp -java -cp ../cljs.jar:src clojure.main build.clj -And when it finishes, execute the compiled file using node: -$ node main.js -Hello world! -
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    -
    -Compile for the Browser -In this section we are going to create an application similar to the "hello world" -example from the previous section to run in the browser environment. The minimal -requirement for this application is just a browser that can execute JavaScript. -The process is almost the same, and the directory structure is the same. The only -things that changes is the entry point of the application and the build script. So, -start re-creating the directory tree from previous example in a different directory. -mkdir -p mywebapp/src/mywebapp -touch mywebapp/src/mywebapp/core.cljs -Resulting in this directory tree: -mywebapp -└── src - └── mywebapp - └── core.cljs -Then, write new content to the mywebapp/src/mywebapp/core.cljs file: -(ns mywebapp.core) - -(enable-console-print!) - -(println "Hello world!") -In the browser environment we do not need a specific entry point for the application, -so the entry point is the entire namespace. -
    -Compile the example application -In order to compile the source code to run properly in a browser, overwrite the -mywebapp/build.clj file with the following content: -(require '[cljs.build.api :as b]) - -(b/build "src" - {:output-to "main.js" - :output-dir "out/" - :source-map "main.js.map" - :main 'mywebapp.core - :verbose true - :optimizations :none}) -This is a brief explanation of the compiler options we’re using: - - -The :output-to parameter indicates to the compiler the destination of the -compiled code, in this case the "main.js" file. - - -The :main property indicates to the compiler the namespace that will act as -the entry point of your application when it’s executed. - - -:source-map indicates the destination of the source map. (The source map -connects the ClojureScript source to the generated JavaScript so that error -messages can point you back to the original source.) - - -:output-dir indicates the destination directory for all file sources used in a -compilation. It is just for making source maps work properly with the rest of the -code, not only your source. - - -:optimizations indicates the compilation optimization. There are different -values for this option, but that will be covered in subsequent sections in -more detail. - - -To run the compilation, just execute the following command: -cd mywebapp; -java -cp ../cljs.jar:src clojure.main build.clj -This process can take some time, so do not worry; wait a little bit. The JVM -bootstrap with the Clojure compiler is slightly slow. In the following sections, we -will explain how to start a watch process to avoid constantly starting and stopping -this slow process. -While waiting for the compilation, let’s create a dummy HTML file to make it easy to -execute our example app in the browser. Create the index.html file with the -following content; it goes in the main mywebapp directory. -<!DOCTYPE html> -<html> - <header> - <meta charset="utf-8" /> - <title>Hello World from ClojureScript</title> - </header> - <body> - <script src="main.js"></script> - </body> -</html> -Now, when the compilation finishes and you have the basic HTML file you can just open -it with your favorite browser and take a look in the development tools console. The -"Hello world!" message should appear there. -
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    -Watch process -You may have already noticed the slow startup time of the ClojureScript -compiler. To solve this, the ClojureScript standalone compiler comes with a tool to -watch for changes in your source code, and re-compile modified files as soon as they -are written to disk -Start by creating another build script, but this time name it watch.clj: -(require '[cljs.build.api :as b]) - -(b/watch "src" - {:output-to "main.js" - :output-dir "out/" - :source-map "main.js.map" - :main 'mywebapp.core - :optimizations :none}) -Now, execute the script just like you have in previous sections: -$ java -cp ../cljs.jar:src clojure.main watch.clj -Building ... -Reading analysis cache for jar:file:/home/niwi/cljsbook/playground/cljs.jar!/cljs/core.cljs -Compiling src/mywebapp/core.cljs -Compiling out/cljs/core.cljs -Using cached cljs.core out/cljs/core.cljs -... done. Elapsed 0.754487937 seconds -Watching paths: /home/niwi/cljsbook/playground/mywebapp/src -Go back to the mywebapp.core namespace, and change the print text to "Hello World, -Again!". You’ll see that the file src/mywebapp/core.cljs the file is immediately -recompiled, and if you reload index.html in your browser the new text is displayed -in the developer console. Another advantage of this method is that it gives a little -bit more output. -
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    -Optimization levels -The ClojureScript compiler has different levels of optimization. Behind the scenes, -those compilation levels are coming from the Google Closure Compiler. -A simplified overview of the compilation process is: - - -The reader reads the code and does some analysis. This compiler may raise some -warnings during this phase. - - -Then, the ClojureScript compiler emits JavaScript code. The result is one -JavaScript output file for each ClojureScript input file. - - -The generated JavaScript files are passed through the Google Closure Compiler -which, depending on the optimization level and other options (sourcemaps, output -dir output to, …​), generates the final output file(s). - - -The final output format depends on the optimization level chosen: -
    -none -This optimization level causes the generated JavaScript to be written into separate -output files for each namespace, without any additional transformations to the code. -
    -
    -whitespace -This optimization level causes the generated JavaScript files to be concatenated into -a single output file, in dependency order. Line breaks and other whitespace are -removed. -This reduces compilation speed somewhat, resulting in a slower compilations. However, -it is not terribly slow and it is quite usable for small-to-medium sized -applications. -
    -
    -simple -The simple compilation level builds on the work from the whitespace optimization -level, and additionally performs optimizations within expressions and functions, such -as renaming local variables and function parameters to have shorter names. -Compilation with the :simple optimization always preserves the functionality of -syntactically valid JavaScript, so it does not interfere with the interaction between -the compiled ClojureScript and other JavaScript. -
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    -advanced -The advanced compilation level builds on the simple optimization level, and -additionally performs more aggressive optimizations and dead code elimination. This -results in a significantly smaller output file. -The :advanced optimizations only work for a strict subset of JavaScript which -follows the Google Closure Compiler rules. ClojureScript generates valid -JavaScript within this strict subset, but if you are interacting with third party -JavaScript code, some additional work is required to make everything work as -expected. -This interaction with third party javascript libraries will be explained in later -sections. -
    -
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    -
    -Working with the REPL -
    -Introduction -Although you can create a source file and compile it every time you want to try -something out in ClojureScript, it’s easier to use the REPL. REPL stands for: - - -Read - get input from the keyboard - - -Evaluate the input - - -Print the result - - -Loop back for more input - - -In other words, the REPL lets you try out ClojureScript concepts and get immediate -feedback. -ClojureScript comes with support for executing the REPL in different execution -environments, each of which has its own advantages and disadvantages. For example, -you can run a REPL in nodejs but in that environment you don’t have any access to the -DOM. Which REPL environment is best for you depends on your specific needs and -requirements. -
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    -Nashorn REPL -The Nashorn REPL is the easiest and perhaps most painless REPL environment because it -does not require any special stuff, just the JVM (JDK 8) that you have used in -previous examples for running the ClojureScript compiler. -Let’s start creating the repl.clj file with the following content: -(require '[cljs.repl] - '[cljs.repl.nashorn]) - -(cljs.repl/repl - (cljs.repl.nashorn/repl-env) - :output-dir "out" - :cache-analysis true) -Then, execute the following command to get the REPL up and running: -$ java -cp cljs.jar:src clojure.main repl.clj -To quit, type: :cljs/quit -cljs.user=> (+ 1 2) -3 -You may have noticed that the REPL does not have support for history and other -shell-like facilities. This is because the default REPL does not comes with -"readline" support. But this problem can be solved using a simple tool named rlwrap -which you should be able to find find with the package manager of your operating -system (e.g. for Ubuntu, type sudo apt install -y rlwrap to install). -The rlwrap tool gives the REPL "readline" capability, and will allow you to have -command history, code navigation, and other shell-like utilities that will make your -REPL experience much more pleasant. To use it, just prepend it to the previous -command that we used to start the REPL: -$ rlwrap java -cp cljs.jar:src clojure.main repl.clj -To quit, type: :cljs/quit -cljs.user=> (+ 1 2) -3 -
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    -Node.js REPL -You must, of course, have nodejs installed on your system to use this REPL. -You may be wondering why we might want a nodejs REPL, when we already have the -nashorn REPL available which doesn’t have any external dependencies. The answer is -very simple: nodejs is the most used JavaScript execution environment on the backend, -and it has a great number of community packages built around it. -The good news is that starting a nodejs REPL is very easy once you have it installed -in your system. Start writing this content to a new repl.clj file: -(require '[cljs.repl] - '[cljs.repl.node]) - -(cljs.repl/repl - (cljs.repl.node/repl-env) - :output-dir "out" - :cache-analysis true) -And start the REPL like you have done it previously with nashorn REPL: -$ rlwrap java -cp cljs.jar:src clojure.main repl.clj -To quit, type: :cljs/quit -cljs.user=> (+ 1 2) -3 -
    -
    -Browser REPL -This REPL is the most laborious to get up and running. This is because it uses a -browser for its execution environment and it has additional requirements. -Let’s start by creating a file named brepl.clj with the following content: -(require - '[cljs.build.api :as b] - '[cljs.repl :as repl] - '[cljs.repl.browser :as browser]) - -(b/build "src" - {:output-to "main.js" - :output-dir "out/" - :source-map "main.js.map" - :main 'myapp.core - :verbose true - :optimizations :none}) - -(repl/repl (browser/repl-env) - :output-dir "out") -This script builds the source, just as we did earlier, and then starts the REPL. -But the browser REPL also requires that some code be executed in the browser before -the REPL gets working. To do that, just re-create the application structure very -similar to the one that we have used in previous sections: -mkdir -p src/myapp -touch src/myapp/core.cljs -Then, write new content to the src/myapp/core.cljs file: -(ns myapp.core - (:require [clojure.browser.repl :as repl])) - -(defonce conn - (repl/connect "http://localhost:9000/repl")) - -(enable-console-print!) - -(println "Hello, world!") -And finally, create the missing index.html file that is going to be used as the -entry point for running the browser side code of the REPL: -<!DOCTYPE html> -<html> - <header> - <meta charset="utf-8" /> - <title>Hello World from ClojureScript</title> - </header> - <body> - <script src="main.js"></script> - </body> -</html> -Well, that was a lot of setup! But trust us, it’s all worth it when you see it in -action. To do that, just execute the brepl.clj in the same way that we have done -it in previous examples: -$ rlwrap java -cp cljs.jar:src clojure.main brepl.clj -Compiling client js ... -Waiting for browser to connect ... -And finally, open your favourite browser and go to http://localhost:9000/. Once the -page is loaded (the page will be blank), switch back to the console where you have -run the REPL and you will see that it is up and running: -[...] -To quit, type: :cljs/quit -cljs.user=> (+ 14 28) -42 -One of the big advantages of the browser REPL is that you have access to everything -in the browser environment. For example, type (js/alert "hello world") in the -REPL. This will cause the browser to display an alert box. Nice! -
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    -
    -The Closure Library -The Google Closure Library is a javascript library developed by Google. It has a -modular architecture, and provides cross-browser functions for DOM manipulations and -events, ajax and JSON, and other features. -The Google Closure Library is written specifically to take advantage of the Closure -Compiler (which is used internally by the ClojureScript compiler). -ClojureScript is built on the Google Closure Compiler and Closure Library. In fact, -ClojureScript namespaces are Closure modules. This means that you can interact with -the Closure Library very easily: -(ns yourapp.core - (:require [goog.dom :as dom])) - -(def element (dom/getElement "body")) -This code snippet shows how you can import the dom module of the Closure library -and use a function declared in that module. -Additionally, the closure library exposes "special" modules that behave like a class -or object. To use these features, you must use the :import directive in the (ns -…​) form: -(ns yourapp.core - (:import goog.History)) - -(def instance (History.)) -In a Clojure program, the :import directive is used for host (Java) interop to -import Java classes. If, however, you define types (classes) in ClojureScript, you -should use the standard :require directive and not the :import directive. -
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    -Dependency management -Until now, we have used the builtin ClojureScript toolchain to compile our source -files to JavaScript. This is the minimal setup required for working with and -understanding the compiler. For larger projects, however, we often want to use a more -powerful build tool that can manage a project’s dependencies on other libraries. -For this reason, the remainder of this chapter will explain how to use Leiningen, -the de facto clojure build and dependency management tool, for building -ClojureScript projects. The boot build tool is also growing in popularity, but -for the purposes of this book we will limit ourselves to Leiningen. -
    -Installing leiningen -The installation process of leiningen is quite simple; just follow these steps: -mkdir ~/bin -cd ~/bin -wget https://raw.githubusercontent.com/technomancy/leiningen/stable/bin/lein -chmod a+x ./lein -export PATH=$PATH:~/bin -Make sure that the ~/bin directory is always set on your path. To make it -permanent, add the line starting with export to your ~/.bashrc file (assuming you -are using the bash shell). -Now, open another clean terminal and execute lein version. You should see -something like the following: -$ lein version -Leiningen 2.5.1 on Java 1.8.0_45 OpenJDK 64-Bit Server VM - -We assume here that you are using a Unix-like system such as Linux or BSD. If -you are a Windows user, please check the instructions on the -Leiningen homepage. You can also get the Linux/Mac OS -X/BSD version of the leiningen script at the web site. - -
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    -First project -The best way to show how a tool works is by creating a toy project with it. In this -case, we will create a small application that determines if a year is a leap year or -not. To start, we will use the mies leiningen template. - -Templates are a facility in leiningen for creating an initial project -structure. The clojure community has a great many of them. In this case we’ll use -the mies template that was started by the clojurescript core developer. Consult -the leiningen docs to learn more about templates. - -Let’s start creating the project layout: -$ lein new mies leapyears -$ cd leapyears # move into newly created project directory -The project has the following structure: -leapyears -├── index.html -├── project.clj -├── README.md -├── scripts -│   ├── build -│   ├── release -│   ├── watch -│   ├── repl -│   └── brepl -└── src - └── leapyears - └── core.cljs -The project.clj file contains information that Leiningen uses to download -dependencies and build the project. For now, just trust that everything in that file -is exactly as it should be. -Open the index.html file and add the following content at the beginning of body: -<section class="viewport"> - <div id="result"> - ---- - </div> - <form action="" method=""> - <label for="year">Enter a year</label> - <input id="year" name="year" /> - </form> -</section> -The next step is adding some code to make the form interactive. Put the following -code into the src/leapyears/core.cljs: -(ns leapyears.core - (:require [goog.dom :as dom] - [goog.events :as events] - [cljs.reader :refer (read-string)])) - -(enable-console-print!) - -(def input (dom/getElement "year")) -(def result (dom/getElement "result")) - -(defn leap? - [year] - (or (zero? (js-mod year 400)) - (and (pos? (js-mod year 100)) - (zero? (js-mod year 4))))) - -(defn on-change - [event] - (let [target (.-target event) - value (read-string (.-value target))] - (if (leap? value) - (set! (.-innerHTML result) "YES") - (set! (.-innerHTML result) "NO")))) - -(events/listen input "keyup" on-change) -Now, compile the clojurescript code with: -$ ./scripts/watch -Behind the scenes, the watch script uses the lein build tool to execute a command -similar to the java build command from the previous sections: -rlwrap lein trampoline run -m clojure.main scripts/watch.clj - -You must have rlwrap installed on your system. - -Finally, open the index.html file in a browser. Typing a year in the textbox -should display an indication of its leap year status. -You may have noticed other files in the scripts directory, like build and -release. These are the same build scripts mentioned in the previous section, but -we will stick with watch here. -
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    -Managing dependencies -The real purpose of using Leiningen for the ClojureScript compilation process is to -automate the retrieval of dependencies. This is dramatically simpler than retrieving -them manually. -The dependencies, among other parameters, are declared in the project.clj file and -have this form (from the mies template): -(defproject leapyears "0.1.0-SNAPSHOT" - :description "FIXME: write this!" - :url "http://example.com/FIXME" - :dependencies [[org.clojure/clojure "1.8.0"] - [org.clojure/clojurescript "1.9.36"] - [org.clojure/data.json "0.2.6"]] - :jvm-opts ^:replace ["-Xmx1g" "-server"] - :node-dependencies [[source-map-support "0.3.2"]] - :plugins [[lein-npm "0.5.0"]] - :source-paths ["src" "target/classes"] - :clean-targets ["out" "release"] - :target-path "target") -And here is a brief explanation of the properties relevant for ClojureScript: - - -:dependencies: a vector of dependencies that your project needs. - - -:clean-targets: a vector of paths that lein clean should delete. - - -The dependencies in ClojureScript are packaged using jar files. If you are coming -from Clojure or any JVM language, jar files will be very familiar to you. But if -you aren’t familiar with them, do not worry: a .jar file is like a plain zip file -that contains the project.clj for the library, some metadata, and the ClojureScript -sources. The packaging will be explained in another section. -Clojure packages are often published on Clojars. You can -also find many third party libraries on the -ClojureScript Wiki. -
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    -External dependencies -In some circumstances you may found yourself that you need some library but that -does not exists in ClojureScript but it is already implemented in javascript -and you want to use it on your project. -There are many ways that you can do it mainly depending on the library that you -want to include. Let see some ways. -
    -Closure Module compatible library -If you have a library that is just writtent to be compatible with google closure -module system and you want to include it on your project you should just put -it in the source (classpath) and access it like any other clojure namespace. -This is the most simplest case, because google closure modules are directly -compatible and you can mix your clojure code with javascript code written using -google closure module system without any additional steps. -Let play with it creating new project using mies template: -lein new mies myextmods -cd myextmods -Create a simple google closure module for experiment: - -src/myextmods/myclosuremodule.js - -goog.provide("myextmods.myclosuremodule"); - -goog.scope(function() { - var module = myextmods.myclosuremodule; - module.get_greetings = function() { - return "Hello from google closure module."; - }; -}); - - -Now, open the repl, require the namespace and try to use the exposed function: -(require '[myextmods.myclosuremodule :as cm]) -(cm/get_greetings) -;; => "Hello from google closure module." - -you can open the nodejs repl just executing ./scripts/repl on the -root of the repository. - -
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    -CommonJS modules compatible libraries -Due to the Node.JS popularity the commonjs used in node is today the most used -module format for javascript libraries, independently if they will be used in server -side development using nodejs or using browser side applications. -Let’s play with that. Start creating a simple file using commonjs module format -(pretty analgous to the previous example using google closure modules): - -src/myextmods/mycommonjsmodule.js - -function getGreetings() { - return "Hello from commonjs module."; -} - -exports.getGreetings = getGreetings; - - -Later, in order to use that simple pet library you should indicate to the -ClojureScript compiler the path to that file and the used module type with -:foreign-libs attribute. -Open scripts/repl.clj and modify it to somethig like this: -(require - '[cljs.repl :as repl] - '[cljs.repl.node :as node]) - -(repl/repl - (node/repl-env) - :language-in :ecmascript5 - :language-out :ecmascript5 - :foreign-libs [{:file "myextmods/mycommonjsmodule.js" - :provides ["myextmods.mycommonjsmodule"] - :module-type :commonjs}] - :output-dir "out" - :cache-analysis false) - -Although the direct path is used to point to this pet library you can specify -a full URI to remote resource and it will be automatically downloaded. - -Now, let’s try to play with moment within the repl (executing the ./scripts/repl -script that uses the previously modified ./scripts/repl.clj file): -(require '[myextmods.mycommonjsmodule :as cm]) -(cm/getGreetings) -;; => "Hello from commonjs module." -
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    -Legacy, module-less (global scope) libraries -Although today is very common have libraries packaged using some kind of modules, -there are also a great amount of libraries that just exposes a global objects and -does not uses any kind of modules; and you may want to use them from -ClojureScript. -In order to use a library that exposes a global object, you should follow similar -steps as with commojs modules with the exception that you should omit the -:module-type attribute. -This will create a synthetic namespace that you should require in order to be able -to access to the global object through the js/ namespace. The namespace is called -synthetic because it does not expose any object behind it, it just indicates -to the compiler that you want that dependency. -Let’s play with that. Start creating a simple file declaring just a global function: - -src/myextmods/myglobalmodule.js - -function getGreetings() { - return "Hello from global scope."; -} - - -Open scripts/repl.clj and modify it to somethig like this: -(require - '[cljs.repl :as repl] - '[cljs.repl.node :as node]) - -(repl/repl - (node/repl-env) - :language-in :ecmascript5 - :language-out :ecmascript5 - :foreign-libs [{:file "myextmods/mycommonjsmodule.js" - :provides ["myextmods.mycommonjsmodule"] - :module-type :commonjs} - {:file "myextmods/myglobalmodule.js" - :provides ["myextmods.myglobalmodule"]}] - :output-dir "out" - :cache-analysis false) -And in the same way as in previous examples, let evaluate that in the repl: -(require 'myextmods.myglobalmodule) -(js/getGreetings) -;; => "Hello from global scope." -
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    -
    -Unit testing -As you might expect, testing in ClojureScript consists of the same concepts widely -used by other language such as Clojure, Java, Python, JavaScript, etc. -Regardless of the language, the main objective of unit testing is to run some test -cases, verifying that the code under test behaves as expected and returns without -raising unexpected exceptions. -The immutablity of ClojureScript data structures helps to make programs less error -prone, and facilitates testing a little bit. Another advantage of ClojureScript is -that it tends to use plain data instead of complex objects. Building "mock" objects -for testing is thus greatly simplified. -
    -First steps -The "official" ClojureScript testing framework is in the "cljs.test" namespace. It -is a very simple library, but it should be more than enough for our purposes. -There are other libraries that offer additional features or directly different -approaches to testing, such as -test.check. However, we will not cover -them here. -Start creating a new project using the mies leiningen template for experimenting -with tests: -$ lein new mies mytestingapp -$ cd mytestingapp -This project will contain the same layout as we have seen in the dependency -management subchapter, so we won’t explain it again. -The next step is a creating a directory tree for our tests: -$ mkdir -p test/mytestingapp -$ touch test/mytestingapp/core_tests.cljs -Also, we should adapt the existing watch.clj script to work with this newly -created test directory: -(require '[cljs.build.api :as b]) - -(b/watch (b/inputs "test" "src") - {:main 'mytestingapp.core_tests - :target :nodejs - :output-to "out/mytestingapp.js" - :output-dir "out" - :verbose true}) -This new script will compile and watch both directories "src" and "test", and it -sets the new entry point to the mytestingapp.core_tests namespace. -Next, put some test code in the core_tests.cljs file: -(ns mytestingapp.core-tests - (:require [cljs.test :as t])) - -(enable-console-print!) - -(t/deftest my-first-test - (t/is (= 1 2))) - -(set! *main-cli-fn* #(t/run-tests)) -The relevant part of that code snippet is: -(t/deftest my-first-test - (t/is (= 1 2))) -The deftest macro is a basic primitive for defining our tests. It takes a name as -its first parameter, followed by one or multiple assertions using the is macro. In -this example, we try to assert that (= 1 2) is true. -Let’s try to run this. First start the watch process: -$ ./scripts/watch -Building ... -Copying jar:file:/home/niwi/.m2/repository/org/clojure/clojurescript/1.9.36/clojurescript-1.9.36.jar!/cljs/core.cljs to out/cljs/core.cljs -Reading analysis cache for jar:file:/home/niwi/.m2/repository/org/clojure/clojurescript/1.9.36/clojurescript-1.9.36.jar!/cljs/core.cljs -Compiling out/cljs/core.cljs -... done. Elapsed 3.862126827 seconds -Watching paths: /home/niwi/cljsbook/playground/mytestingapp/test, /home/niwi/cljsbook/playground/mytestingapp/src -When the compilation is finished, try to run the compiled file with nodejs: -$ node out/mytestingapp.js - -Testing mytestingapp.core-tests - -FAIL in (my-first-test) (cljs/test.js:374:14) -expected: (= 1 2) - actual: (not (= 1 2)) - -Ran 1 tests containing 1 assertions. -1 failures, 0 errors. -You can see that the expected assert failure is successfully printed in the -console. To fix the test, just change the = with not= and run the file again: -$ node out/mytestingapp.js - -Testing mytestingapp.core-tests - -Ran 1 tests containing 1 assertions. -0 failures, 0 errors. -It is fine to test these kinds of assertions, but they are not very useful. Let’s go -to test some application code. For this, we will use a function to check if a year -is a leap year or not. Write the following content to the -src/mytestingapp/core.clj file: -(defn leap? - [year] - (and (zero? (js-mod year 4)) - (pos? (js-mod year 100)) - (pos? (js-mod year 400)))) -Next, write a new test case to check that our new leap? function works -properly. Make the core_tests.cljs file look like: -(ns mytestingapp.core-tests - (:require [cljs.test :as t] - [mytestingapp.core :as core])) - -(enable-console-print!) - -(t/deftest my-first-test - (t/is (not= 1 2))) - -(t/deftest my-second-test - (t/is (core/leap? 1980)) - (t/is (not (core/leap? 1981)))) - -(set! *main-cli-fn* #(t/run-tests)) -Run the compiled file again to see that there are now two tests running. The -first test passes as before, and our two new leap year tests pass as well. -
    -
    -Async Testing -One of the peculiarities of ClojureScript is that it runs in an asynchronous, -single-threaded execution environment, which has its challenges. -In an async execution environment, we should be able to test asynchronous functions. -To this end, the ClojureScript testing library offers the async macro, allowing -you to create tests that play well with asynchronous code. -First, we need to write a function that works in an asynchronous way. For this -purpose, we will create the async-leap? predicate that will do the same operation -but asychronously return a result using a callback: -(defn async-leap? - [year callback] - (js/setImmediate - (fn [] - (let [result (or (zero? (js-mod year 400)) - (and (pos? (js-mod year 100)) - (zero? (js-mod year 4))))] - (callback result))))) -The JavaScript function setImmediate is used to emulate an asynchronous task, and -the callback is executed with the result of that predicate. -To test it, we should write a test case using the previously mentioned async macro: -(t/deftest my-async-test - (t/async done - (core/async-leap? 1980 (fn [result] - (t/is (true? result)) - (done))))) -The done function exposed by the async macro should be called after the -asynchronous operation is finished and all assertions have run. -It is very important to execute the done function only once. Omitting it or -executing it twice may cause strange behavior and should be avoided. -
    -
    -Fixtures -TBD -
    -
    -Integrating with CI -Most continuous integration tools and services expect that test scripts you provide -return a standard exit code. But the ClojureScript test framework cannot customize -this exit code without some configuration, because JavaScript lacks a universal exit -code API for ClojureScript to use. -To fix this, the ClojureScript test framework provides an avenue for executing -custom code after the tests are done. This is where you are expected to set the -environment-specific exit code depending on the final test status: 0 for success, -1 for failure. -Insert this code at the end of core_tests.cljs: -(defmethod t/report [::t/default :end-run-tests] - [m] - (if (t/successful? m) - (set! (.-exitCode js/process) 0) - (set! (.-exitCode js/process) 1))) -Now, you may check the exit code of the test script after running: -$ node out/mytestingapp.js -$ echo $? -This code snippet obviously assumes that you are running the tests using nodejs. -If you are running your script in another execution environment, you should be aware -of how you can set the exit code in that environment and modify the previous snippet -accordingly. -
    -
    -
    - -Language (advanced topics) -This chapter intends to explain some advanced topics that are part of the language -and that does not fit in the first chapter. The good candidates for this section are -transducers, core protocols, transients, metadata. In summary: topics that are not -mandatory for understand the language. -
    -Transducers -
    -Data transformation -ClojureScript offers a rich vocabulary for data transformation in terms of the -sequence abstraction, which makes such transformations highly general and -composable. Let’s see how we can combine several collection processing functions to -build new ones. We will be using a simple problem throughout this section: splitting -grape clusters, filtering out the rotten ones, and cleaning them. We have a -collection of grape clusters like the following: -(def grape-clusters - [{:grapes [{:rotten? false :clean? false} - {:rotten? true :clean? false}] - :color :green} - {:grapes [{:rotten? true :clean? false} - {:rotten? false :clean? false}] - :color :black}]) -We are interested in splitting the grape clusters into individual grapes, discarding -the rotten ones and cleaning the remaining grapes so they are ready for eating. We -are well-equipped in ClojureScript for this data transformation task; we could -implement it using the familiar map, filter and mapcat functions: -(defn split-cluster - [c] - (:grapes c)) - -(defn not-rotten - [g] - (not (:rotten? g))) - -(defn clean-grape - [g] - (assoc g :clean? true)) - -(->> grape-clusters - (mapcat split-cluster) - (filter not-rotten) - (map clean-grape)) -;; => ({rotten? false :clean? true} {:rotten? false :clean? true}) -In the above example we succintly solved the problem of selecting and cleaning the -grapes, and we can even abstract such transformations by combining the mapcat, -filter and map operations using partial application and function composition: -(def process-clusters - (comp - (partial map clean-grape) - (partial filter not-rotten) - (partial mapcat split-cluster))) - -(process-clusters grape-clusters) -;; => ({rotten? false :clean? true} {:rotten? false :clean? true}) -The code is very clean, but it has a few problems. For example, each call to map, -filter and mapcat consumes and produces a sequence that, although lazy, generates -intermediate results that will be discarded. Each sequence is fed to the next step, -which also returns a sequence. Wouldn’t be great if we could do the transformation in -a single transversal of the grape-cluster collection? -Another problem is that even though our process-clusters function works with any -sequence, we can’t reuse it with anything that is not a sequence. Imagine that -instead of having the grape cluster collection available in memory it is being pushed -to us asynchronously in a stream. In that situation we couldn’t reuse -process-clusters since usually map, filter and mapcat have concrete -implementations depending on the type. -
    -
    -Generalizing to process transformations -The process of mapping, filtering or mapcatting isn’t necessarily tied to a concrete -type, but we keep reimplementing them for different types. Let’s see how we can -generalize such processes to be context independent. We’ll start by implementing -naive versions of map and filter first to see how they work internally: -(defn my-map - [f coll] - (when-let [s (seq coll)] - (cons (f (first s)) (my-map f (rest s))))) - -(my-map inc [0 1 2]) -;; => (1 2 3) - -(defn my-filter - [pred coll] - (when-let [s (seq coll)] - (let [f (first s) - r (rest s)] - (if (pred f) - (cons f (my-filter pred r)) - (my-filter pred r))))) - -(my-filter odd? [0 1 2]) -;; => (1) -As we can see, they both assume that they receive a seqable and return a -sequence. Like many recursive functions they can be implemented in terms of the -already familiar reduce function. Note that functions that are given to reduce -receive an accumulator and an input and return the next accumulator. We’ll call these -types of functions reducing functions from now on. -(defn my-mapr - [f coll] - (reduce (fn [acc input] ;; reducing function - (conj acc (f input))) - [] ;; initial value - coll)) ;; collection to reduce - -(my-mapr inc [0 1 2]) -;; => [1 2 3] - -(defn my-filterr - [pred coll] - (reduce (fn [acc input] ;; reducing function - (if (pred input) - (conj acc input) - acc)) - [] ;; initial value - coll)) ;; collection to reduce - -(my-filterr odd? [0 1 2]) -;; => [1] -We’ve made the previous versions more general since using reduce makes our -functions work on any thing that is reducible, not just sequences. However you may -have noticed that, even though my-mapr and my-filterr don’t know anything about -the source (coll) they are still tied to the output they produce (a vector) both -with the initial value of the reduce ([]) and the hardcoded conj operation in the -body of the reducing function. We could have accumulated results in another data -structure, for example a lazy sequence, but we’d have to rewrite the functions in -order to do so. -How can we make these functions truly generic? They shouldn’t know about either the -source of inputs they are transforming nor the output that is generated. Have you -noticed that conj is just another reducing function? It takes an accumulator and an -input and returns another accumulator. So, if we parameterise the reducing function -that my-mapr and my-filterr use, they won’t know anything about the type of the -result they are building. Let’s give it a shot: -(defn my-mapt - [f] ;; function to map over inputs - (fn [rfn] ;; parameterised reducing function - (fn [acc input] ;; transformed reducing function, now it maps `f`! - (rfn acc (f input))))) - -(def incer (my-mapt inc)) - -(reduce (incer conj) [] [0 1 2]) -;; => [1 2 3] - -(defn my-filtert - [pred] ;; predicate to filter out inputs - (fn [rfn] ;; parameterised reducing function - (fn [acc input] ;; transformed reducing function, now it discards values based on `pred`! - (if (pred input) - (rfn acc input) - acc)))) - -(def only-odds (my-filtert odd?)) - -(reduce (only-odds conj) [] [0 1 2]) -;; => [1] -That’s a lot of higher-order functions so let’s break it down for a better -understanding of what’s going on. We’ll examine how my-mapt works step by step. The -mechanics are similar for my-filtert, so we’ll leave it out for now. -First of all, my-mapt takes a mapping function; in the example we are giving it -inc and getting another function back. Let’s replace f with inc to see what we -are building: -(def incer (my-mapt inc)) -;; (fn [rfn] -;; (fn [acc input] -;; (rfn acc (inc input)))) -;; ^^^ -The resulting function is still parameterised to receive a reducing function to which -it will delegate, let’s see what happens when we call it with conj: -(incer conj) -;; (fn [acc input] -;; (conj acc (inc input))) -;; ^^^^ -We get back a reducing function which uses inc to transform the inputs and the -conj reducing function to accumulate the results. In essence, we have defined map -as the transformation of a reducing function. The functions that transform one -reducing function into another are called transducers in ClojureScript. -To ilustrate the generality of transducers, let’s use different sources and -destinations in our call to reduce: -(reduce (incer str) "" [0 1 2]) -;; => "123" - -(reduce (only-odds str) "" '(0 1 2)) -;; => "1" -The transducer versions of map and filter transform a process that carries inputs -from a source to a destination but don’t know anything about where the inputs come -from and where they end up. In their implementation they contain the essence of -what they accomplish, independent of context. -Now that we know more about transducers we can try to implement our own version of -mapcat. We already have a fundamental piece of it: the map transducer. What -mapcat does is map a function over an input and flatten the resulting structure one -level. Let’s try to implement the catenation part as a transducer: -(defn my-cat - [rfn] - (fn [acc input] - (reduce rfn acc input))) - -(reduce (my-cat conj) [] [[0 1 2] [3 4 5]]) -;; => [0 1 2 3 4 5] -The my-cat transducer returns a reducing function that catenates its inputs into -the accumulator. It does so reducing the input reducible with the rfn reducing -function and using the accumulator (acc) as the initial value for such -reduction. mapcat is simply the composition of map and cat. The order in which -transducers are composed may seem backwards but it’ll become clear in a moment. -(defn my-mapcat - [f] - (comp (my-mapt f) my-cat)) - -(defn dupe - [x] - [x x]) - -(def duper (my-mapcat dupe)) - -(reduce (duper conj) [] [0 1 2]) -;; => [0 0 1 1 2 2] -
    -
    -Transducers in ClojureScript core -Some of the ClojureScript core functions like map, filter and mapcat support an -arity 1 version that returns a transducer. Let’s revisit our definition of -process-cluster and define it in terms of transducers: -(def process-clusters - (comp - (mapcat split-cluster) - (filter not-rotten) - (map clean-grape))) -A few things changed since our previous definition process-clusters. First of all, -we are using the transducer-returning versions of mapcat, filter and map -instead of partially applying them for working on sequences. -Also you may have noticed that the order in which they are composed is reversed, they -appear in the order they are executed. Note that all map, filter and mapcat -return a transducer. filter transforms the reducing function returned by map, -applying the filtering before proceeding; mapcat transforms the reducing function -returned by filter, applying the mapping and catenation before proceeding. -One of the powerful properties of transducers is that they are combined using regular -function composition. What’s even more elegant is that the composition of various -transducers is itself a transducer! This means that our process-cluster is a -transducer too, so we have defined a composable and context-independent algorithmic -transformation. -Many of the core ClojureScript functions accept a transducer, let’s look at some -examples with our newly created process-cluster: -(into [] process-clusters grape-clusters) -;; => [{:rotten? false, :clean? true} {:rotten? false, :clean? true}] - -(sequence process-clusters grape-clusters) -;; => ({:rotten? false, :clean? true} {:rotten? false, :clean? true}) - -(reduce (process-clusters conj) [] grape-clusters) -;; => [{:rotten? false, :clean? true} {:rotten? false, :clean? true}] -Since using reduce with the reducing function returned from a transducer is so -common, there is a function for reducing with a transformation called transduce. We -can now rewrite the previous call to reduce using transduce: -(transduce process-clusters conj [] grape-clusters) -;; => [{:rotten? false, :clean? true} {:rotten? false, :clean? true}] -
    -
    -Initialisation -In the last example we provided an initial value to the transduce function ([]) -but we can omit it and get the same result: -(transduce process-clusters conj grape-clusters) -;; => [{:rotten? false, :clean? true} {:rotten? false, :clean? true}] -What’s going on here? How can transduce know what initial value use as an -accumulator when we haven’t specified it? Try calling conj without any arguments -and see what happens: -(conj) -;; => [] -The conj function has a arity 0 version that returns an empty vector but is not the -only reducing function that supports arity 0. Let’s explore some others: -(+) -;; => 0 - -(*) -;; => 1 - -(str) -;; => "" - -(= identity (comp)) -;; => true -The reducing function returned by transducers must support the arity 0 as well, which -will typically delegate to the transformed reducing function. There is no sensible -implementation of the arity 0 for the transducers we have implemented so far, so -we’ll simply call the reducing function without arguments. Here’s how our modified -my-mapt could look like: -(defn my-mapt - [f] - (fn [rfn] - (fn - ([] (rfn)) ;; arity 0 that delegates to the reducing fn - ([acc input] - (rfn acc (f input)))))) -The call to the arity 0 of the reducing function returned by a transducer will call -the arity 0 version of every nested reducing function, eventually calling the -outermost reducing function. Let’s see an example with our already defined -process-clusters transducer: -((process-clusters conj)) -;; => [] -The call to the arity 0 flows through the transducer stack, eventually calling -(conj). -
    -
    -Stateful transducers -So far we’ve only seen purely functional transducer; they don’t have any implicit -state and are very predictable. However, there are many data transformation functions -that are inherently stateful, like take. take receives a number n of elements -to keep and a collection and returns a collection with at most n elements. -(take 10 (range 100)) -;; => (0 1 2 3 4 5 6 7 8 9) -Let’s step back for a bit and learn about the early termination of the reduce -function. We can wrap an accumulator in a type called reduced for telling reduce -that the reduction process should terminate immediately. Let’s see an example of a -reduction that aggregates the inputs in a collection and finishes as soon as there -are 10 elements in the accumulator: -(reduce (fn [acc input] - (if (= (count acc) 10) - (reduced acc) - (conj acc input))) - [] - (range 100)) -;; => [0 1 2 3 4 5 6 7 8 9] -Since transducers are modifications of reducing functions they also use reduced for -early termination. Note that stateful transducers may need to do some cleanup before -the process terminates, so they must support an arity 1 as a "completion" -step. Usually, like with arity 0, this arity will simply delegate to the transformed -reducing function’s arity 1. -Knowing this we are able to write stateful transducers like take. We’ll be using -mutable state internally for tracking the number of inputs we have seen so far, and -wrap the accumulator in a reduced as soon as we’ve seen enough elements: -(defn my-take - [n] - (fn [rfn] - (let [remaining (volatile! n)] - (fn - ([] (rfn)) - ([acc] (rfn acc)) - ([acc input] - (let [rem @remaining - nr (vswap! remaining dec) - result (if (pos? rem) - (rfn acc input) ;; we still have items to take - acc)] ;; we're done, acc becomes the result - (if (not (pos? nr)) - (ensure-reduced result) ;; wrap result in reduced if not already - result))))))) -This is a simplified version of the take function present in ClojureScript -core. There are a few things to note here so let’s break it up in pieces to -understand it better. -The first thing to notice is that we are creating a mutable value inside the -transducer. Note that we don’t create it until we receive a reducing function to -transform. If we created it before returning the transducer we couldn’t use my-take -more than once. Since the transducer is handed a reducing function to transform each -time it is used, we can use it multiple times and the mutable variable will be -created in every use. -(fn [rfn] - (let [remaining (volatile! n)] ;; make sure to create mutable variables inside the transducer - (fn - ;; ... -))) - -(def take-five (my-take 5)) - -(transduce take-five conj (range 100)) -;; => [0 1 2 3 4] - -(transduce take-five conj (range 100)) -;; => [0 1 2 3 4] -Let’s now dig into the reducing function returned from my-take. First of all we -deref the volatile to get the number of elements that remain to be taken and -decrement it to get the next remaining value. If there are still remaining items to -take, we call rfn passing the accumulator and input; if not, we already have the -final result. -([acc input] - (let [rem @remaining - nr (vswap! remaining dec) - result (if (pos? rem) - (rfn acc input) - acc)] - ;; ... -)) -The body of my-take should be obvious by now. We check whether there are still -items to be processed using the next remainder (nr) and, if not, wrap the result in -a reduced using the ensure-reduced function. ensure-reduced will wrap the value -in a reduced if it’s not reduced already or simply return the value if it’s already -reduced. In case we are not done yet, we return the accumulated result for further -processing. -(if (not (pos? nr)) - (ensure-reduced result) - result) -We’ve seen an example of a stateful transducer but it didn’t do anything in its -completion step. Let’s see an example of a transducer that uses the completion step -to flush an accumulated value. We’ll implement a simplified version of -partition-all, which given a n number of elements converts the inputs in vectors -of size n. For understanding its purpose better let’s see what the arity 2 version -gives us when providing a number and a collection: -(partition-all 3 (range 10)) -;; => ((0 1 2) (3 4 5) (6 7 8) (9)) -The transducer returning function of partition-all will take a number n and -return a transducer that groups inputs in vectors of size n. In the completion step -it will check if there is an accumulated result and, if so, add it to the -result. Here’s a simplified version of ClojureScript core partition-all function, -where array-list is a wrapper for a mutable JavaScript array: -(defn my-partition-all - [n] - (fn [rfn] - (let [a (array-list)] - (fn - ([] (rfn)) - ([result] - (let [result (if (.isEmpty a) ;; no inputs accumulated, don't have to modify result - result - (let [v (vec (.toArray a))] - (.clear a) ;; flush array contents for garbage collection - (unreduced (rfn result v))))] ;; pass to `rfn`, removing the reduced wrapper if present - (rfn result))) - ([acc input] - (.add a input) - (if (== n (.size a)) ;; got enough results for a chunk - (let [v (vec (.toArray a))] - (.clear a) - (rfn acc v)) ;; the accumulated chunk becomes input to `rfn` - acc)))))) - -(def triples (my-partition-all 3)) - -(transduce triples conj (range 10)) -;; => [[0 1 2] [3 4 5] [6 7 8] [9]] -
    -
    -Eductions -Eductions are a way to combine a collection and one or more transformations that can -be reduced and iterated over, and that apply the transformations every time we do -so. If we have a collection that we want to process and a transformation over it that -we want others to extend, we can hand them a eduction, encapsulating the source -collection and our transformation. We can create an eduction with the eduction -function: -(def ed (eduction (filter odd?) (take 5) (range 100))) - -(reduce + 0 ed) -;; => 25 - -(transduce (partition-all 2) conj ed) -;; => [[1 3] [5 7] [9]] -
    -
    -More transducers in ClojureScript core -We learned about map, filter, mapcat, take and partition-all, but there are -a lot more transducers available in ClojureScript. Here is an incomplete list of some -other intersting ones: - - -drop is the dual of take, dropping up to n values before passing inputs to -the reducing function - - -distinct only allows inputs to occur once - - -dedupe removes succesive duplicates in input values - - -We encourage you to explore ClojureScript core to see what other transducers are out -there. -
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    -Defining our own transducers -There a few things to consider before writing our own transducers so in this section -we will learn how to properly implement one. First of all, we’ve learned that the -general structure of a transducer is the following: -(fn [xf] - (fn - ([] ;; init - ...) - ([r] ;; completion - ...) - ([acc input] ;; step - ...))) -Usually only the code represented with …​ changes between transducers, these are -the invariants that must be preserved in each arity of the resulting function: - - -arity 0 (init): must call the arity 0 of the nested transform xf - - -arity 1 (completion): used to produce a final value and potentially flush state, -must call the arity 1 of the nested transform xf exactly once - - -arity 2 (step): the resulting reducing function which will call the arity 2 of -the nested transform xf zero, one or more times - - -
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    -Transducible processes -A transducible process is any process that is defined in terms of a succession of -steps ingesting input values. The source of input varies from one process to -another. Most of our examples dealt with inputs from a collection or a lazy sequence, -but it could be an asynchronous stream of values or a core.async channel. The -outputs produced by each step are also different for every process; into creates a -collection with every output of the transducer, sequence yields a lazy sequence, -and asynchronous streams would probably push the outputs to their listeners. -In order to improve our understanding of transducible processes, we’re going to -implement an unbounded queue, since adding values to a queue can be thought in terms -of a succession of steps ingesting input. First of all we’ll define a protocol and a -data type that implements the unbounded queue: -(defprotocol Queue - (put! [q item] "put an item into the queue") - (take! [q] "take an item from the queue") - (shutdown! [q] "stop accepting puts in the queue")) - -(deftype UnboundedQueue [^:mutable arr ^:mutable closed] - Queue - (put! [_ item] - (assert (not closed)) - (assert (not (nil? item))) - (.push arr item) - item) - (take! [_] - (aget (.splice arr 0 1) 0)) - (shutdown! [_] - (set! closed true))) -We defined the Queue protocol and as you may have noticed the implementation of -UnboundedQueue doesn’t know about transducers at all. It has a put! operation as -its step function and we’re going to implement the transducible process on top of -that interface: -(defn unbounded-queue - ([] - (unbounded-queue nil)) - ([xform] - (let [put! (completing put!) - xput! (if xform (xform put!) put!) - q (UnboundedQueue. #js [] false)] - (reify - Queue - (put! [_ item] - (when-not (.-closed q) - (let [val (xput! q item)] - (if (reduced? val) - (do - (xput! @val) ;; call completion step - (shutdown! q) ;; respect reduced - @val) - val)))) - (take! [_] - (take! q)) - (shutdown! [_] - (shutdown! q)))))) -As you can see, the unbounded-queue constructor uses an UnboundedQueue instance -internally, proxying the take! and shutdown! calls and implementing the -transducible process logic in the put! function. Let’s deconstruct it to understand -what’s going on. -(let [put! (completing put!) - xput! (if xform (xform put!) put!) - q (UnboundedQueue. #js [] false)] - ;; ... -) -First of all, we use completing for adding the arity 0 and arity 1 to the Queue -protocol’s put! function. This will make it play nicely with transducers in case -we give this reducing function to xform to derive another. After that, if a -transducer (xform) was provided, we derive a reducing function applying the -transducer to put!. If we’re not handed a transducer we will just use put!. q -is the internal instance of UnboundedQueue. -(reify - Queue - (put! [_ item] - (when-not (.-closed q) - (let [val (xput! q item)] - (if (reduced? val) - (do - (xput! @val) ;; call completion step - (shutdown! q) ;; respect reduced - @val) - val)))) - ;; ... -) -The exposed put! operation will only be performed if the queue hasn’t been shut -down. Notice that the put! implementation of UnboundedQueue uses an assert to -verify that we can still put values to it and we don’t want to break that -invariant. If the queue isn’t closed we can put values into it, we use the possibly -transformed xput! for doing so. -If the put operation gives back a reduced value it’s telling us that we should -terminate the transducible process. In this case that means shutting down the queue -to not accept more values. If we didn’t get a reduced value we can happily continue -accepting puts. -Let’s see how our queue behaves without transducers: -(def q (unbounded-queue)) -;; => #<[object Object]> - -(put! q 1) -;; => 1 -(put! q 2) -;; => 2 - -(take! q) -;; => 1 -(take! q) -;; => 2 -(take! q) -;; => nil -Pretty much what we expected, let’s now try with a stateless transducer: -(def incq (unbounded-queue (map inc))) -;; => #<[object Object]> - -(put! incq 1) -;; => 2 -(put! incq 2) -;; => 3 - -(take! incq) -;; => 2 -(take! incq) -;; => 3 -(take! incq) -;; => nil -To check that we’ve implemented the transducible process, let’s use a stateful -transducer. We’ll use a transducer that will accept values while they aren’t equal to -4 and will partition inputs in chunks of 2 elements: -(def xq (unbounded-queue (comp - (take-while #(not= % 4)) - (partition-all 2)))) - -(put! xq 1) -(put! xq 2) -;; => [1 2] -(put! xq 3) -(put! xq 4) ;; shouldn't accept more values from here on -(put! xq 5) -;; => nil - -(take! xq) -;; => [1 2] -(take! xq) ;; seems like `partition-all` flushed correctly! -;; => [3] -(take! xq) -;; => nil -The example of the queue was heavily inspired by how core.async channels use -transducers in their internal step. We’ll discuss channels and their usage with -transducers in a later section. -Transducible processes must respect reduced as a way for signaling early -termination. For example, building a collection stops when encountering a reduced -and core.async channels with transducers are closed. The reduced value must be -unwrapped with deref and passed to the completion step, which must be called -exactly once. -Transducible processes shouldn’t expose the reducing function they generate when -calling the transducer with their own step function since it may be stateful and -unsafe to use from elsewhere. -
    -
    -
    -Transients -Although ClojureScript’s immutable and persistent data structures are reasonably -performant there are situations in which we are transforming large data structures -using multiple steps to only share the final result. For example, the core into -function takes a collection and eagerly populates it with the contents of a sequence: -(into [] (range 100)) -;; => [0 1 2 ... 98 99] -In the above example we are generating a vector of 100 elements conj-ing one at a -time. Every intermediate vector that is not the final result won’t be seen by anybody -except the into function and the array copying required for persistence is an -unnecesary overhead. -For these situations ClojureScript provides a special version of some of its -persistent data structures, which are called transients. Maps, vectors and sets have -a transient counterpart. Transients are always derived from a persistent data -structure using the transient function, which creates a transient version in -constant time: -(def tv (transient [1 2 3])) -;; => #<[object Object]> -Transients support the read API of their persistent counterparts: -(def tv (transient [1 2 3])) - -(nth tv 0) -;; => 1 - -(get tv 2) -;; => 3 - -(def tm (transient {:language "ClojureScript"})) - -(:language tm) -;; => "ClojureScript" - -(def ts (transient #{:a :b :c})) - -(contains? ts :a) -;; => true - -(:a ts) -;; => :a -Since transients don’t have persistent and immutable semantics for updates they can’t -be transformed using the already familiar conj or assoc functions. Instead, the -transforming functions that work on transients end with a bang. Let’s look at an -example using conj! on a transient: -(def tv (transient [1 2 3])) - -(conj! tv 4) -;; => #<[object Object]> - -(nth tv 3) -;; => 4 -As you can see, the transient version of the vector is neither immutable nor -persistent. Instead, the vector is mutated in place. Although we could transform tv -repeatedly using conj! on it we shouldn’t abandon the idioms used with the -persistent data structures: when transforming a transient, use the returned version -of it for further modifications like in the following example: -(-> [1 2 3] - transient - (conj! 4) - (conj! 5)) -;; => #<[object Object]> -We can convert a transient back to a persistent and immutable data structure by -calling persistent! on it. This operation, like deriving a transient from a -persistent data structure, is done in constant time. -(-> [1 2 3] - transient - (conj! 4) - (conj! 5) - persistent!) -;; => [1 2 3 4 5] -A peculiarity of transforming transients into persistent structures is that the -transient version is invalidated after being converted to a persistent data structure -and we can’t do further transformations to it. This happens because the derived -persistent data structure uses the transient’s internal nodes and mutating them would -break the immutability and persistent guarantees: -(def tm (transient {})) -;; => #<[object Object]> - -(assoc! tm :foo :bar) -;; => #<[object Object]> - -(persistent! tm) -;; => {:foo :bar} - -(assoc! tm :baz :frob) -;; Error: assoc! after persistent! -Going back to our initial example with into, here’s a very simplified -implementation of it that uses a transient for performance, returning a persistent -data structure and thus exposing a purely functional interface although it uses -mutation internally: -(defn my-into - [to from] - (persistent! (reduce conj! (transient to) from))) - -(my-into [] (range 100)) -;; => [0 1 2 ... 98 99] -
    -
    -Metadata -ClojureScript symbols, vars and persistent collections support attaching metadata to -them. Metadata is a map with information about the entity it’s attached to. The -ClojureScript compiler uses metadata for several purposes such as type hints, and the -metadata system can be used by tooling, library and application developers too. -There may not be many cases in day-to-day ClojureScript programming where you need -metadata, but it is a nice language feature to have and know about; it may come in -handy at some point. It makes things like runtime code introspection and -documentation generation very easy. You’ll see why throughout this section. -
    -Vars -Let’s define a var and see what metadata is attached to it by default. Note that this -code is executed in a REPL, and thus the metadata of a var defined in a source file -may vary. We’ll use the meta function to retrieve the metadata of the given value: -(def answer-to-everything 42) -;; => 42 - -#'answer-to-everything -;; => #'cljs.user/answer-to-everyhing - -(meta #'answer-to-everything) -;; => {:ns cljs.user, -;; :name answer-to-everything, -;; :file "NO_SOURCE_FILE", -;; :source "answer-to-everything", -;; :column 6, -;; :end-column 26, -;; :line 1, -;; :end-line 1, -;; :arglists (), -;; :doc nil, -;; :test nil} -Few things to note here. First of all, #'answer-to-everything gives us a reference -to the Var that holds the value of the answer-to-everything symbol. We see that -it includes information about the namespace (:ns) in which it was defined, its -name, file (although, since it was defined at a REPL doesn’t have a source file), -source, position in the file where it was defined, argument list (which only makes -sense for functions), documentation string and test function. -Let’s take a look at a function var’s metadata: -(defn add - "A function that adds two numbers." - [x y] - (+ x y)) - -(meta #'add) -;; => {:ns cljs.user, -;; :name add, -;; :file "NO_SOURCE_FILE", -;; :source "add", -;; :column 7, -;; :end-column 10, -;; :line 1, -;; :end-line 1, -;; :arglists (quote ([x y])), -;; :doc "A function that adds two numbers.", -;; :test nil} -We see that the argument lists are stored in the :arglists field of the var’s -metadata and its documentation in the :doc field. We’ll now define a test function -to learn about what :test is used for: -(require '[cljs.test :as t]) - -(t/deftest i-pass - (t/is true)) - -(meta #'i-pass) -;; => {:ns cljs.user, -;; :name i-pass, -;; :file "NO_SOURCE_FILE", -;; :source "i-pass", -;; :column 12, -;; :end-column 18, -;; :line 1, -;; :end-line 1, -;; :arglists (), -;; :doc "A function that adds two numbers.", -;; :test #<function (){ ... }>} -The :test attribute (truncated for brevity) in the i-pass var’s metadata is a -test function. This is used by the cljs.test library for discovering and running -tests in the namespaces you tell it to. -
    -
    -Values -We learned that vars can have metadata and what kind of metadata is added to them for -consumption by the compiler and the cljs.test testing library. Persistent -collections can have metadata too, although they don’t have any by default. We can -use the with-meta function to derive an object with the same value and type with -the given metadata attached. Let’s see how: -(def map-without-metadata {:language "ClojureScript"}) -;; => {:language "ClojureScript"} - -(meta map-without-metadata) -;; => nil - -(def map-with-metadata (with-meta map-without-metadata - {:answer-to-everything 42})) -;; => {:language "ClojureScript"} - -(meta map-with-metadata) -;; => {:answer-to-everything 42} - -(= map-with-metadata - map-without-metadata) -;; => true - -(identical? map-with-metadata - map-without-metadata) -;; => false -It shouldn’t come as a surprise that metadata doesn’t affect equality between two -data structures since equality in ClojureScript is based on value. Another -interesting thing is that with-meta creates another object of the same type and -value as the given one and attaches the given metadata to it. -Another open question is what happens with metadata when deriving new values from a -persistent data structure. Let’s find out: -(def derived-map (assoc map-with-metadata :language "Clojure")) -;; => {:language "Clojure"} - -(meta derived-map) -;; => {:answer-to-everything 42} -As you can see in the example above, metadata is preserved in derived versions of -persistent data structures. There are some subtleties, though. As long as the -functions that derive new data structures return collections with the same type, -metadata will be preserved; this is not true if the types change due to the -transformation. To ilustrate this point, let’s see what happens when we derive a seq -or a subvector from a vector: -(def v (with-meta [0 1 2 3] {:foo :bar})) -;; => [0 1 2 3] - -(def sv (subvec v 0 2)) -;; => [0 1] - -(meta sv) -;; => nil - -(meta (seq v)) -;; => nil -
    -
    -Syntax for metadata -The ClojureScript reader has syntactic support for metadata annotations, which can be -written in different ways. We can prepend var definitions or collections with a caret -(^) followed by a map for annotating it with the given metadata map: -(def ^{:doc "The answer to Life, Universe and Everything."} answer-to-everything 42) -;; => 42 - -(meta #'answer-to-everything) -;; => {:ns cljs.user, -;; :name answer-to-everything, -;; :file "NO_SOURCE_FILE", -;; :source "answer-to-everything", -;; :column 6, -;; :end-column 26, -;; :line 1, -;; :end-line 1, -;; :arglists (), -;; :doc "The answer to Life, Universe and Everything.", -;; :test nil} - -(def map-with-metadata ^{:answer-to-everything 42} {:language "ClojureScript"}) -;; => {:language "ClojureScript"} - -(meta map-with-metadata) -;; => {:answer-to-everything 42} -Notice how the metadata given in the answer-to-everything var definition is merged -with the var metadata. -A very common use of metadata is to set certain keys to a true value. For example -we may want to add to a var’s metadata that the variable is dynamic or a -constant. For such cases, we have a shorthand notation that uses a caret followed by -a keyword. Here are some examples: -(def ^:dynamic *foo* 42) -;; => 42 - -(:dynamic (meta #'*foo*)) -;; => true - -(def ^:foo ^:bar answer 42) -;; => 42 - -(select-keys (meta #'answer) [:foo :bar]) -;; => {:foo true, :bar true} -There is another shorthand notation for attaching metadata. If we use a caret -followed by a symbol it will be added to the metadata map under the :tag -key. Using tags such as ^boolean gives the ClojureScript compiler hints about the -type of expressions or function return types. -(defn ^boolean will-it-blend? [_] true) -;; => #<function ... > - -(:tag (meta #'will-it-blend?)) -;; => boolean - -(not ^boolean (js/isNaN js/NaN)) -;; => false -
    -
    -Functions for working with metadata -We’ve learned about meta and with-meta so far but ClojureScript offers a few -functions for transforming metadata. There is vary-meta which is similar to -with-meta in that it derives a new object with the same type and value as the -original but it doesn’t take the metadata to attach directly. Instead, it takes a -function to apply to the metadata of the given object to transform it for deriving -new metadata. This is how it works: -(def map-with-metadata ^{:foo 40} {:language "ClojureScript"}) -;; => {:language "ClojureScript"} - -(meta map-with-metadata) -;; => {:foo 40} - -(def derived-map (vary-meta map-with-metadata update :foo + 2)) -;; => {:language "ClojureScript"} - -(meta derived-map) -;; => {:foo 42} -If instead we want to change the metadata of an existing var or value we can use -alter-meta! for changing it by applying a function or reset-meta! for replacing -it with another map: -(def map-with-metadata ^{:foo 40} {:language "ClojureScript"}) -;; => {:language "ClojureScript"} - -(meta map-with-metadata) -;; => {:foo 40} - -(alter-meta! map-with-metadata update :foo + 2) -;; => {:foo 42} - -(meta map-with-metadata) -;; => {:foo 42} - -(reset-meta! map-with-metadata {:foo 40}) -;; => {:foo 40} - -(meta map-with-metadata) -;; => {:foo 40} -
    -
    -
    -Core protocols -One of the greatest qualities of the core ClojureScript functions is that they are -implemented around protocols. This makes them open to work on any type that we -extend with such protocols, be it defined by us or a third party. -
    -Functions -As we’ve learned in previous chapters not only functions can be invoked. Vectors are -functions of their indexes, maps are functions of their keys and sets are functions -of their values. -We can extend types to be callable as functions implementing the IFn protocol. A -collection that doesn’t support calling it as a function is the queue, let’s -implement IFn for the PersistentQueue type so we’re able to call queues as -functions of their indexes: -(extend-type PersistentQueue - IFn - (-invoke - ([this idx] - (nth this idx)))) - -(def q #queue[:a :b :c]) -;; => #queue [:a :b :c] - -(q 0) -;; => :a - -(q 1) -;; => :b - -(q 2) -;; => :c -
    -
    -Printing -For learning about some of the core protocols we’ll define a Pair type, which will -hold a pair of values. -(deftype Pair [fst snd]) -If we want to customize how types are printed we can implement the -IPrintWithWriter protocol. It defines a function called -pr-writer that receives -the value to print, a writer object and options; this function uses the writer -object’s -write function to write the desired Pair string representation: -(extend-type Pair - IPrintWithWriter - (-pr-writer [p writer _] - (-write writer (str "#<Pair " (.-fst p) "," (.-snd p) ">")))) -
    -
    -Sequences -In a previous section we learned about sequences, one -of ClojureScript’s main abstractions. Remember the first and rest functions for -working with sequences? They are defined in the ISeq protocol, so we can extend -types for responding to such functions: -(extend-type Pair - ISeq - (-first [p] - (.-fst p)) - - (-rest [p] - (list (.-snd p)))) - -(def p (Pair. 1 2)) -;; => #<Pair 1,2> - -(first p) -;; => 1 - -(rest p) -;; => (2) -Another handy function for working with sequences is next. Although next works -as long as the given argument is a sequence, we can implement it explicitly with the -INext protocol: -(def p (Pair. 1 2)) - -(next p) -;; => (2) - -(extend-type Pair - INext - (-next [p] - (println "Our next") - (list (.-snd p)))) - -(next p) -;; Our next -;; => (2) -Finally, we can make our own types seqable implementing the ISeqable -protocol. This means we can pass them to seq for getting a sequence back. -ISeqable -(def p (Pair. 1 2)) - -(extend-type Pair - ISeqable - (-seq [p] - (list (.-fst p) (.-snd p)))) - -(seq p) -;; => (1 2) -Now our Pair type works with the plethora of ClojureScript functions for working -with sequences: -(def p (Pair. 1 2)) -;; => #<Pair 1,2> - -(map inc p) -;; => (2 3) - -(filter odd? p) -;; => (1) - -(reduce + p) -;; => 3 -
    -
    -Collections -Collection functions are also defined in terms of protocols. For this section -examples we will make the native JavaScript string act like a collection. -The most important function for working with collection is conj, defined in the -ICollection protocol. Strings are the only type which makes sense to conj to a -string, so the conj operation for strings will be simply a concatenation: -(extend-type string - ICollection - (-conj [this o] - (str this o))) - -(conj "foo" "bar") -;; => "foobar" - -(conj "foo" "bar" "baz") -;; => "foobarbaz" -Another handy function for working with collections is empty, which is part of the -IEmptyableCollection protocol. Let’s implement it for the string type: -(extend-type string - IEmptyableCollection - (-empty [_] - "")) - -(empty "foo") -;; => "" -We used the string special symbol for extending the native JavaScript string. If -you want to learn more about it check the section -about extending JavaScript types. -
    -Collection traits -There are some qualities that not all collections have, such as being countable in -constant time or being reversible. These traits are splitted into different -protocols since not all of them make sense for every collection. For illustrating -these protocols we’ll use the Pair type we defined earlier. -For collections that can be counted in constant time using the count function we -can implement the ICounted protocol. It should be easy to implement it for the -Pair type: -(extend-type Pair - ICounted - (-count [_] - 2)) - -(def p (Pair. 1 2)) - -(count p) -;; => 2 -Some collection types such as vectors and lists can be indexed by a number using the -nth function. If our types are indexed we can implement the IIndexed protocol: -(extend-type Pair - IIndexed - (-nth - ([p idx] - (case idx - 0 (.-fst p) - 1 (.-snd p) - (throw (js/Error. "Index out of bounds")))) - ([p idx default] - (case idx - 0 (.-fst p) - 1 (.-snd p) - default)))) - -(nth p 0) -;; => 1 - -(nth p 1) -;; => 2 - -(nth p 2) -;; Error: Index out of bounds - -(nth p 2 :default) -;; => :default -
    -
    -
    -Associative -There are many data structures that are associative: they map keys to values. We’ve -encountered a few of them already and we know many functions for working with them -like get, assoc or dissoc. Let’s explore the protocols that these functions -build upon. -First of all, we need a way to look up keys on an associative data structure. The -ILookup protocol defines a function for doing so, let’s add the ability to look up -keys in our Pair type since it is an associative data structure that maps the indices -0 and 1 to values. -(extend-type Pair - ILookup - (-lookup - ([p k] - (-lookup p k nil)) - ([p k default] - (case k - 0 (.-fst p) - 1 (.-snd p) - default)))) - -(get p 0) -;; => 1 - -(get p 1) -;; => 2 - -(get p :foo) -;; => nil - -(get p 2 :default) -;; => :default -For using assoc on a data structure it must implement the IAssociative -protocol. For our Pair type only 0 and 1 will be allowed as keys for associating -values. IAssociative also has a function for asking whether a key is present or -not. -(extend-type Pair - IAssociative - (-contains-key? [_ k] - (contains? #{0 1} k)) - - (-assoc [p k v] - (case k - 0 (Pair. v (.-snd p)) - 1 (Pair. (.-fst p) v) - (throw (js/Error. "Can only assoc to 0 and 1 keys"))))) - -(def p (Pair. 1 2)) -;; => #<Pair 1,2> - -(assoc p 0 2) -;; => #<Pair 2,2> - -(assoc p 1 1) -;; => #<Pair 1,1> - -(assoc p 0 0 1 1) -;; => #<Pair 0,1> - -(assoc p 2 3) -;; Error: Can only assoc to 0 and 1 keys -The complementary function for assoc is dissoc and it’s part of the IMap -protocol. It doesn’t make much sense for our Pair type but we’ll implement it -nonetheless. Dissociating 0 or 1 will mean putting a nil in such position and -invalid keys will be ignored. -(extend-type Pair - IMap - (-dissoc [p k] - (case k - 0 (Pair. nil (.-snd p)) - 1 (Pair. (.-fst p) nil) - p))) - -(def p (Pair. 1 2)) -;; => #<Pair 1,2> - -(dissoc p 0) -;; => #<Pair ,2> - -(dissoc p 1) -;; => #<Pair 1,> - -(dissoc p 2) -;; => #<Pair 1,2> - -(dissoc p 0 1) -;; => #<Pair ,> -Associative data structures are made of key and value pairs we can call entries. The -key and val functions allow us to query the key and value of such entries and -they are built upon the IMapEntry protocol. Let’s see a few examples of key and -val and how map entries can be used to build up maps: -(key [:foo :bar]) -;; => :foo - -(val [:foo :bar]) -;; => :bar - -(into {} [[:foo :bar] [:baz :xyz]]) -;; => {:foo :bar, :baz :xyz} -Pairs can be map entries too, we treat their first element as the key and the second -as the value: -(extend-type Pair - IMapEntry - (-key [p] - (.-fst p)) - - (-val [p] - (.-snd p))) - -(def p (Pair. 1 2)) -;; => #<Pair 1,2> - -(key p) -;; => 1 - -(val p) -;; => 2 - -(into {} [p]) -;; => {1 2} -
    -
    -Comparison -For checking whether two or more values are equivalent with = we must implement -the IEquiv protocol. Let’s do it for our Pair type: -(def p (Pair. 1 2)) -(def p' (Pair. 1 2)) -(def p'' (Pair. 1 2)) - -(= p p') -;; => false - -(= p p' p'') -;; => false - -(extend-type Pair - IEquiv - (-equiv [p other] - (and (instance? Pair other) - (= (.-fst p) (.-fst other)) - (= (.-snd p) (.-snd other))))) - -(= p p') -;; => true - -(= p p' p'') -;; => true -We can also make types comparable. The function compare takes two values and -returns a negative number if the first is less than the second, 0 if both are equal -and 1 if the first is greater than the second. For making our types comparable we -must implement the IComparable protocol. -For pairs, comparison will mean checking if the two first values are equal. If they -are, the result will be the comparison of the second values. If not, we will return -the result of the first comparison: -(extend-type Pair - IComparable - (-compare [p other] - (let [fc (compare (.-fst p) (.-fst other))] - (if (zero? fc) - (compare (.-snd p) (.-snd other)) - fc)))) - -(compare (Pair. 0 1) (Pair. 0 1)) -;; => 0 - -(compare (Pair. 0 1) (Pair. 0 2)) -;; => -1 - -(compare (Pair. 1 1) (Pair. 0 2)) -;; => 1 - -(sort [(Pair. 1 1) (Pair. 0 2) (Pair. 0 1)]) -;; => (#<Pair 0,1> #<Pair 0,2> #<Pair 1,1>) -
    -
    -Metadata -The meta and with-meta functions are also based upon two protocols: IMeta and -IWithMeta respectively. We can make our own types capable of carrying metadata -adding an extra field for holding the metadata and implementing both protocols. -Let’s implement a version of Pair that can have metadata: -(deftype Pair [fst snd meta] - IMeta - (-meta [p] meta) - - IWithMeta - (-with-meta [p new-meta] - (Pair. fst snd new-meta))) - - -(def p (Pair. 1 2 {:foo :bar})) -;; => #<Pair 1,2> - -(meta p) -;; => {:foo :bar} - -(def p' (with-meta p {:bar :baz})) -;; => #<Pair 1,2> - -(meta p') -;; => {:bar :baz} -
    -
    -Interoperability with JavaScript -Since ClojureScript is hosted in a JavaScript VM we often need to convert -ClojureScript data structures to JavaScript ones and viceversa. We also may want to -make native JS types participate in an abstraction represented by a protocol. -
    -Extending JavaScript types -When extending JavaScript objects instead of using JS globals like js/String, -js/Date and such, special symbols are used. This is done for avoiding mutating -global JS objects. -The symbols for extending JS types are: object, array, number, string, -function, boolean and nil is used for the null object. The dispatch of the -protocol to native objects uses Google Closure’s -goog.typeOf -function. There’s a special default symbol that can be used for making a default -implementation of a protocol for every type. -For illustrating the extension of JS types we are going to define a MaybeMutable -protocol that’ll have a mutable? predicate as its only function. Since in -JavaScript mutability is the default we’ll extend the default JS type returning true -from mutable?: -(defprotocol MaybeMutable - (mutable? [this] "Returns true if the value is mutable.")) - -(extend-type default - MaybeMutable - (mutable? [_] true)) - -;; object -(mutable? #js {}) -;; => true - -;; array -(mutable? #js []) -;; => true - -;; string -(mutable? "") -;; => true - -;; function -(mutable? (fn [x] x)) -;; => true -Since fortunately not all JS object’s values are mutable we can refine the -implementation of MaybeMutable for returning false for strings and functions. -(extend-protocol MaybeMutable - string - (mutable? [_] false) - - function - (mutable? [_] false)) - - -;; object -(mutable? #js {}) -;; => true - -;; array -(mutable? #js []) -;; => true - -;; string -(mutable? "") -;; => false - -;; function -(mutable? (fn [x] x)) -;; => false -There is no special symbol for JavaScript dates so we have to extend js/Date -directly. The same applies to the rest of the types found in the global js -namespace. -
    -
    -Converting data -For converting values from ClojureScript types to JavaScript ones and viceversa we -use the clj→js and js→clj functions, which are based in the IEncodeJS and -IEncodeClojure protocols respectively. -For the examples we’ll use the Set type introduced in ES6. Note that is not -available in every JS runtime. -
    -From ClojureScript to JS -First of all we’ll extend ClojureScript’s set type for being able to convert it to -JS. By default sets are converted to JavaScript arrays: -(clj->js #{1 2 3}) -;; => #js [1 3 2] -Let’s fix it, clj→js is supposed to convert values recursively so we’ll make sure -to convert all the set contents to JS and creating the set with the converted -values: -(extend-type PersistentHashSet - IEncodeJS - (-clj->js [s] - (js/Set. (into-array (map clj->js s))))) - -(def s (clj->js #{1 2 3})) -(es6-iterator-seq (.values s)) -;; => (1 3 2) - -(instance? js/Set s) -;; => true - -(.has s 1) -;; => true -(.has s 2) -;; => true -(.has s 3) -;; => true -(.has s 4) -;; => false -The es6-iterator-seq is an experimental function in ClojureScript core for -obtaining a seq from an ES6 iterable. -
    -
    -From JS to ClojureScript -Now it’s time to extend the JS set to convert to ClojureScript. As with clj→js, -js→clj recursively converts the value of the data structure: -(extend-type js/Set - IEncodeClojure - (-js->clj [s options] - (into #{} (map js->clj (es6-iterator-seq (.values s)))))) - -(= #{1 2 3} - (js->clj (clj->js #{1 2 3}))) -;; => true - -(= #{[1 2 3] [4 5] [6]} - (js->clj (clj->js #{[1 2 3] [4 5] [6]}))) -;; => true -Note that there is no one-to-one mapping between ClojureScript and JavaScript -values. For example, ClojureScript keywords are converted to JavaScript strings when -passed to clj→js. -
    -
    -
    -
    -Reductions -The reduce function is based on the IReduce protocol, which enables us to make -our own or third-party types reducible. Apart from using them with reduce they -will automatically work with transduce too, which will allow us to make a -reduction with a transducer. -The JS array is already reducible in ClojureScript: -(reduce + #js [1 2 3]) -;; => 6 - -(transduce (map inc) conj [] [1 2 3]) -;; => [2 3 4] -However, the new ES6 Set type isn’t so let’s implement the IReduce protocol. We’ll -get an iterator using the Set’s values method and convert it to a seq with the -es6-iterator-seq function; after that we’ll delegate to the original reduce -function to reduce the obtained sequence. -(extend-type js/Set - IReduce - (-reduce - ([s f] - (let [it (.values s)] - (reduce f (es6-iterator-seq it)))) - ([s f init] - (let [it (.values s)] - (reduce f init (es6-iterator-seq it)))))) - -(reduce + (js/Set. #js [1 2 3])) -;; => 6 - -(transduce (map inc) conj [] (js/Set. #js [1 2 3])) -;; => [2 3 4] -Associative data structures can be reduced with the reduce-kv function, which is -based in the IKVReduce protocol. The main difference between reduce and -reduce-kv is that the latter uses a three-argument function as a reducer, -receiving the accumulator, key and value for each item. -Let’s look at an example, we will reduce a map to a vector of pairs. Note that, -since vectors associate indexes to values, they can also be reduced with -reduce-kv. -(reduce-kv (fn [acc k v] - (conj acc [k v])) - [] - {:foo :bar - :baz :xyz}) -;; => [[:foo :bar] [:baz :xyz]] -We’ll extend the new ES6 map type to support reduce-kv, we’ll do this by getting a -sequence of key-value pairs and calling the reducing function with the accumulator, -key and value as positional arguments: -(extend-type js/Map - IKVReduce - (-kv-reduce [m f init] - (let [it (.entries m)] - (reduce (fn [acc [k v]] - (f acc k v)) - init - (es6-iterator-seq it))))) - -(def m (js/Map.)) -(.set m "foo" "bar") -(.set m "baz" "xyz") - -(reduce-kv (fn [acc k v] - (conj acc [k v])) - [] - m) -;; => [["foo" "bar"] ["baz" "xyz"]] -In both examples we ended up delegating to the reduce function, which is aware of -reduced values and terminates when encountering one. Take into account that if you -don’t implement these protocols in terms of reduce you will have to check for -reduced values for early termination. -
    -
    -Asynchrony -There are some types that have the notion of asynchronous computation, the value -they represent may not be realized yet. We can ask whether a value is realized using -the realized? predicate. -Let’s ilustrate it with the Delay type, which takes a computation and executes it -when the result is needed. When we dereference a delay the computation is run and -the delay is realized: -(defn computation [] - (println "running!") - 42) - -(def d (Delay. computation nil)) - -(realized? d) -;; => false - -(deref d) -;; running! -;; => 42 - -(realized? d) -;; => true - -@d -;; => 42 -Both realized? and deref sit atop two protocols: IPending and IDeref. -ES6 introduced a type that captures the notion of an asynchronous computation that -might fail: the Promise. A Promise represents an eventual value and can be in one -of three states: - - -pending: there is still no value available for this computation. - - -rejected: an error occurred and the promise contains a value that indicates -the error. - - -resolved: the computation succesfully executed and the promise contains a -value with the result. - - -Since the ES6 defined interface for promises doesn’t support querying its state -we’ll use Bluebird library’s Promise type for the examples. You can use Bluebird’s -promise type with the Promesa library. -First of all we’ll add the ability to check if a promise is realized (either -resolved or rejected) using the realized? predicate. We just have to implement the -IPending protocol: -(require '[promesa.core :as p]) - -(extend-type js/Promise - IPending - (-realized? [p] - (not (.isPending p)))) - - -(p/promise (fn [resolve reject])) -;; => #<Promise {:status :pending}> - -(realized? (p/promise (fn [resolve reject]))) -;; => false - -(p/resolved 42) -;; => #<Promise {:status :resolved, :value 42}> - -(realized? (p/resolved 42)) -;; => true - -(p/rejected (js/Error. "OH NO")) -;; => #<Promise {:status :rejected, :error #object[Error Error: OH NO]}> - -(realized? (p/rejected (js/Error. "OH NO"))) -;; => true -Now we’ll extend promises to be derefable. When a promise that is still pending is -dereferenced we will return a special keyword: :promise/pending. If it’s not we’ll -just return the value it contains, be it an error or a result: -(require '[promesa.core :as pro]) - -(extend-type js/Promise - IDeref - (-deref [p] - (cond - (.isPending p) - :promise/pending - - (.isRejected p) - (.reason p) - - :else - (.value p)))) - -@(p/promise (fn [resolve reject])) -;; => :promise/pending - -@(p/resolved 42) -;; => 42 - -@(p/rejected (js/Error. "OH NO")) -;; => #object[Error Error: OH NO] -
    -
    -State -The ClojureScript state constructs such as the Atom and the Volatile have different -characteristics and semantics, and the operations on them like add-watch, reset! -or swap! are backed by protocols. -
    -Atom -For ilustrating such protocols we will implement our own simplified version of an -Atom. It won’t support validators nor metadata, but we will be able to: - - -deref the atom for getting its current value - - -reset! the value contained in the atom - - -swap! the atom with a function for transforming its state - - -deref is based on the IDeref protocol. reset! is based on the IReset -protocol and swap! on ISwap. We’ll start by defining a data type and a -constructor for our atom implementation: -(deftype MyAtom [^:mutable state ^:mutable watches] - IPrintWithWriter - (-pr-writer [p writer _] - (-write writer (str "#<MyAtom " (pr-str state) ">")))) - -(defn my-atom - ([] - (my-atom nil)) - ([init] - (MyAtom. init {}))) - -(my-atom) -;; => #<MyAtom nil> - -(my-atom 42) -;; => #<MyAtom 42> -Note that we’ve marked both the current state of the atom (state) and the map of -watchers (watches) with the {:mutable true} metadata. We’ll be modifying them -and we’re making this explicit with the annotations. -Our MyAtom type is not very useful yet, we’ll start by implementing the IDeref -protocol so we can dereference its current value: -(extend-type MyAtom - IDeref - (-deref [a] - (.-state a))) - -(def a (my-atom 42)) - -@a -;; => 42 -Now that we can dereference it we’ll implement the IWatchable protocol, which will -let us add and remove watches to our custom atom. We’ll store the watches in the -watches map of MyAtom, associating keys to callbacks. -(extend-type MyAtom - IWatchable - (-add-watch [a key f] - (let [ws (.-watches a)] - (set! (.-watches a) (assoc ws key f)))) - - (-remove-watch [a key] - (let [ws (.-watches a)] - (set! (.-watches a) (dissoc ws key)))) - - (-notify-watches [a oldval newval] - (doseq [[key f] (.-watches a)] - (f key a oldval newval)))) -We can now add watches to our atom but is not very useful since we still can’t -change it. For incorporating change we have to implement the IReset protocol and -make sure we notify the watches every time we reset the atom’s value. -(extend-type MyAtom - IReset - (-reset! [a newval] - (let [oldval (.-state a)] - (set! (.-state a) newval) - (-notify-watches a oldval newval) - newval))) -Now let’s check that we got it right. We’ll add a watch, change the atom’s value -making sure the watch gets called and then remove it: -(def a (my-atom 41)) -;; => #<MyAtom 41> - -(add-watch a :log (fn [key a oldval newval] - (println {:key key - :old oldval - :new newval}))) -;; => #<MyAtom 41> - -(reset! a 42) -;; {:key :log, :old 41, :new 42} -;; => 42 - -(remove-watch a :log) -;; => #<MyAtom 42> - -(reset! a 43) -;; => 43 -Our atom is still missing the swapping functionality so we’ll add that now, let’s -implement the ISwap protocol. There are four arities for the -swap! method of -the protocol since the function passed to swap! may take one, two, three or more -arguments: -(extend-type MyAtom - ISwap - (-swap! - ([a f] - (let [oldval (.-state a) - newval (f oldval)] - (reset! a newval))) - - ([a f x] - (let [oldval (.-state a) - newval (f oldval x)] - (reset! a newval))) - - ([a f x y] - (let [oldval (.-state a) - newval (f oldval x y)] - (reset! a newval))) - - ([a f x y more] - (let [oldval (.-state a) - newval (apply f oldval x y more)] - (reset! a newval))))) -We now have a custom implementation of the atom abstraction, let’s test it in the -REPL and see if it behaves like we expect: -(def a (my-atom 0)) -;; => #<MyAtom 0> - -(add-watch a :log (fn [key a oldval newval] - (println {:key key - :old oldval - :new newval}))) -;; => #<MyAtom 0> - -(swap! a inc) -;; {:key :log, :old 0, :new 1} -;; => 1 - -(swap! a + 2) -;; {:key :log, :old 1, :new 3} -;; => 3 - -(swap! a - 2) -;; {:key :log, :old 3, :new 1} -;; => 1 - -(swap! a + 2 3) -;; {:key :log, :old 1, :new 6} -;; => 6 - - -(swap! a + 4 5 6) -;; {:key :log, :old 6, :new 21} -;; => 21 - -(swap! a * 2) -;; {:key :log, :old 21, :new 42} -;; => 42 - -(remove-watch a :log) -;; => #<MyAtom 42> -We did it! We implemented a version of ClojureScript Atom without support for -metadata nor validators, extending it to support such features is left as an -exercise for the reader. Note that you’ll need to modify the MyAtom type for being -able to store metadata and a validator. -
    -
    -Volatile -Volatiles are simpler than atoms in that they don’t support watching for -changes. All changes override the previous value much like the mutable variables -present in almost every programming language. Volatiles are based on the IVolatile -protocol that only defines a method for vreset!, since vswap! is implemented as -a macro. -Let’s start by creating our own volatile type and constructor: -(deftype MyVolatile [^:mutable state] - IPrintWithWriter - (-pr-writer [p writer _] - (-write writer (str "#<MyVolatile " (pr-str state) ">")))) - -(defn my-volatile - ([] - (my-volatile nil)) - ([v] - (MyVolatile. v))) - -(my-volatile) -;; => #<MyVolatile nil> - -(my-volatile 42) -;; => #<MyVolatile 42> -Our MyVolatile still needs to support dereferencing and reseting it, let’s -implement IDeref and IVolatile, which will enable use to use deref, vreset! -and vswap! in our custom volatile: -(extend-type MyVolatile - IDeref - (-deref [v] - (.-state v)) - - IVolatile - (-vreset! [v newval] - (set! (.-state v) newval) - newval)) - -(def v (my-volatile 0)) -;; => #<MyVolatile 42> - -(vreset! v 1) -;; => 1 - -@v -;; => 1 - -(vswap! v + 2 3) -;; => 6 - -@v -;; => 6 -
    -
    -
    -Mutation -In the section about transients we learned about the mutable -counterparts of the immutable and persistent data structures that ClojureScript -provides. These data structures are mutable, and the operations on them end with a -bang (!) to make that explicit. As you may have guessed every operation on -transients is based on protocols. -
    -From persistent to transient and viceversa -We’ve learned that we can transform a persistent data structure with the transient -function, which is based on the IEditableCollection protocol; for transforming a -transient data structure to a persistent one we use persistent!, based on -ITransientCollection. -Implementing immutable and persistent data structures and their transient -counterparts is out of the scope of this book but we recommend taking a look at -ClojureScript’s data structure implementation if you are curious. -
    -
    -Case study: the hodgepodge library -Hodgepodge is a ClojureScript library -for treating the browser’s local and session storage as if it were a transient data -structure. It allows you to insert, read and delete ClojureScript data structures -without worrying about encoding and decoding them. -Browser’s storage is a simple key-value store that only supports strings. Since all -of ClojureScript data structures can be dumped into a string and reified from a -string using the reader we can store arbitrary ClojureScript data -in storage. We can also extend the reader for being able to read custom data types -so we’re able to put our types in storage and hodgepodge will handle the encoding -and decoding for us. -We’ll start by wrapping the low-level storage methods with functions. The following -operations are supported by the storage: - - -getting the value corresponding to a key - - -setting a key to a certain value - - -removing a value given its key - - -counting the number of entries - - -clearing the storage - - -Let’s wrap them in a more idiomatic API for ClojureScript: -(defn contains-key? - [^js/Storage storage ^string key] - (let [ks (.keys js/Object storage) - idx (.indexOf ks key)] - (>= idx 0))) - -(defn get-item - ([^js/Storage storage ^string key] - (get-item storage key nil)) - ([^js/Storage storage ^string key ^string default] - (if (contains-key? storage key) - (.getItem storage key) - default))) - -(defn set-item - [^js/Storage storage ^string key ^string val] - (.setItem storage key val) - storage) - -(defn remove-item - [^js/Storage storage ^string key] - (.removeItem storage key) - storage) - -(defn length - [^js/Storage storage] - (.-length storage)) - -(defn clear! - [^js/Storage storage] - (.clear storage)) -Nothing too interesting going on there, we just wrapped the storage methods in a -nicer API. Now we will define a couple functions for serializing and deserializing -ClojureScript data structures to strings: -(require '[cljs.reader :as reader]) - -(defn serialize [v] - (binding [*print-dup* true - *print-readably* true] - (pr-str v))) - -(def deserialize - (memoize reader/read-string)) -The serialize function is used for converting a ClojureScript data structure into -a string using the pr-str function, configuring a couple dynamic variables for -obtaining the desired behaviour: - - -print-dup is set to true for a printed object to preserve its type -when read later - - -print-readably is set to true for not converting non-alphanumeric -characters to their escape sequences - - -The deserialize function simply invokes the reader’s function for reading a string -into a ClojureScript data structure: read-string. It’s memoized for not having to -call the reader each time we deserialize a string since we can assume that a -repeated string always corresponds to the same data structure. -Now we can start extending the browser’s Storage type for acting like a transient -data structure. Take into account that the Storage type is only available in -browsers. We’ll start by implementing the ICounted protocol for counting the items -in the storage, we’ll simply delegate to our previously defined length function: -(extend-type js/Storage - ICounted - (-count [^js/Storage s] - (length s))) -We want to be able to use assoc! and dissoc! for inserting and deleting -key-value pairs in the storage, as well as the ability to read from it. We’ll -implement the ITransientAssociative protocol for assoc!, ITransientMap for -dissoc! and ILookup for reading storage keys. -(extend-type js/Storage - ITransientAssociative - (-assoc! [^js/Storage s key val] - (set-item s (serialize key) (serialize val)) - s) - - ITransientMap - (-dissoc! [^js/Storage s key] - (remove-item s (serialize key)) - s) - - ILookup - (-lookup - ([^js/Storage s key] - (-lookup s key nil)) - ([^js/Storage s key not-found] - (let [sk (serialize key)] - (if (contains-key? s sk) - (deserialize (get-item s sk)) - not-found))))) -Now we’re able to perform some operations on either session or local storage, let’s -give them a try: -(def local-storage js/localStorage) -(def session-storage js/sessionStorage) - -(assoc! local-storage :foo :bar) - -(:foo local-storage) -;; => :bar - -(dissoc! local-storage :foo) - -(get local-storage :foo) -;; => nil - -(get local-storage :foo :default) -;; => :default -Finally, we want to be able to use conj! and persistent! on local storage so we -must implement the ITransientCollection protocol, let’s give it a go: -(extend-type js/Storage - ITransientCollection - (-conj! [^js/Storage s ^IMapEntry kv] - (assoc! s (key kv) (val kv)) - s) - - (-persistent! [^js/Storage s] - (into {} - (for [i (range (count s)) - :let [k (.key s i) - v (get-item s k)]] - [(deserialize k) (deserialize v)])))) -conj! simply obtains the key and value from the map entry and delegates to -assoc!. persistent! deserializes every key-value pair in the storage and returns -an immutable snapshot of the storage as a ClojureScript map. Let’s try it out: -(clear! local-storage) - -(persistent! local-storage) -;; => {} - -(conj! local-storage [:foo :bar]) -(conj! local-storage [:baz :xyz]) - -(persistent! local-storage) -;; => {:foo :bar, :baz :xyz} -
    -
    -Transient vectors and sets -We’ve learned about most of the protocols for transient data structures but we’re -missing two: ITransientVector for using assoc! on transient vectors and -ITransientSet for using disj! on transient sets. -For illustrating the ITransientVector protocol we’ll extend the JavaScript array -type for making it an associative transient data structure: -(extend-type array - ITransientAssociative - (-assoc! [arr key val] - (if (number? key) - (-assoc-n! arr key val) - (throw (js/Error. "Array's key for assoc! must be a number.")))) - - ITransientVector - (-assoc-n! [arr n val] - (.splice arr n 1 val) - arr)) - -(def a #js [1 2 3]) -;; => #js [1 2 3] - -(assoc! a 0 42) -;; => #js [42 2 3] - -(assoc! a 1 43) -;; => #js [42 43 3] - -(assoc! a 2 44) -;; => #js [42 43 44] -For illustrating the ITransientSet protocol we’ll extend the ES6 Set type for -making it a transient set, supporting the conj!, disj! and persistent! -operations. Note that we’ve extended the Set type previously for being able to -convert it to ClojureScript and we’ll take advantage of that fact. -(extend-type js/Set - ITransientCollection - (-conj! [s v] - (.add s v) - s) - - (-persistent! [s] - (js->clj s)) - - ITransientSet - (-disjoin! [s v] - (.delete s v) - s)) - -(def s (js/Set.)) - -(conj! s 1) -(conj! s 1) -(conj! s 2) -(conj! s 2) - -(persistent! s) -;; => #{1 2} - -(disj! s 1) - -(persistent! s) -;; => #{2} -
    -
    -
    -
    -CSP (with core.async) -CSP stands for Communicating Sequential Processes, which is a formalism for -describing concurrent systems pioneered by C. A. R. Hoare in 1978. It is a -concurrency model based on message passing and synchronization through channels. An -in-depth look at the theoretical model behind CSP is beyond the scope of this book; -instead we’ll focus on presenting the concurrency primitives that core.async -offers. -core.async is not part of ClojureScript core but it’s implemented as a library. -Even though it is not part of the core language it’s widely used. Many libraries build -on top of the core.async primitives, so we think it is worth covering in the book. -It’s also a good example of the syntactic abstractions that can be achieved by -transforming code with ClojureScript macros, so we’ll jump right in. You’ll need to -have core.async installed to run the examples presented in this section. -
    -Channels -Channels are like conveyor belts, we can put and take a single value at a time from -them. They can have multiple readers and writers, and they are the fundamental -message-passing mechanism of core.async. In order to see how it works, we’ll -create a channel to perform some operations on it. -(require '[cljs.core.async :refer [chan put! take!]]) - -(enable-console-print!) - -(def ch (chan)) - -(take! ch #(println "Got a value:" %)) -;; => nil - -;; there is a now a pending take operation, let's put something on the channel - -(put! ch 42) -;; Got a value: 42 -;; => 42 -In the above example we created a channel ch using the chan constructor. After -that we performed a take operation on the channel, providing a callback that will be -invoked when the take operation succeeds. After using put! to put a value on the -channel the take operation completed and the "Got a value: 42" string was -printed. Note that put! returned the value that was just put to the channel. -The put! function accepts a callback like take! does but we didn’t provide any -in the last example. For puts the callback will be called whenever the value we -provided has been taken. Puts and takes can happen in any order, let’s do a few puts -followed by takes to illustrate the point: -(require '[cljs.core.async :refer [chan put! take!]]) - -(def ch (chan)) - -(put! ch 42 #(println "Just put 42")) -;; => true -(put! ch 43 #(println "Just put 43")) -;; => true - -(take! ch #(println "Got" %)) -;; Got 42 -;; Just put 42 -;; => nil - -(take! ch #(println "Got" %)) -;; Got 43 -;; Just put 43 -;; => nil -You may be asking yourself why the put! operations return true. It signals that -the put operation could be performed, even though the value hasn’t yet been taken. -Channels can be closed, which will cause the put operations to not succeed: -(require '[cljs.core.async :refer [chan put! close!]]) - -(def ch (chan)) - -(close! ch) -;; => nil - -(put! ch 42) -;; => false -The above example was the simplest possible situation but what happens with pending -operations when a channel is closed? Let’s do a few takes and close the channel and -see what happens: -(require '[cljs.core.async :refer [chan put! take! close!]]) - -(def ch (chan)) - -(take! ch #(println "Got value:" %)) -;; => nil -(take! ch #(println "Got value:" %)) -;; => nil - -(close! ch) -;; Got value: nil -;; Got value: nil -;; => nil -We see that if the channel is closed all the take! operations receive a nil -value. nil in channels is a sentinel value that signals to takers that the channel -has been closed. Because of that, putting a nil value on a channel is not allowed: -(require '[cljs.core.async :refer [chan put!]]) - -(def ch (chan)) - -(put! ch nil) -;; Error: Assert failed: Can't put nil in on a channel -
    -Buffers -We’ve seen that pending take and put operations are enqueued in a channel but, what -happens when there are many pending take or put operations? Let’s find out by -hammering a channel with many puts and takes: -(require '[cljs.core.async :refer [chan put! take!]]) - -(def ch (chan)) - -(dotimes [n 1025] - (put! ch n)) -;; Error: Assert failed: No more than 1024 pending puts are allowed on a single channel. - -(def ch (chan)) - -(dotimes [n 1025] - (take! ch #(println "Got" %))) -;; Error: Assert failed: No more than 1024 pending takes are allowed on a single channel. -As the example above shows there’s a limit of pending puts or takes on a channel, -it’s currently 1024 but that is an implementation detail that may change. Note that -there can’t be both pending puts and pending takes on a channel since puts will -immediately succeed if there are pending takes and viceversa. -Channels support buffering of put operations. If we create a channel with a buffer -the put operations will succeed immediately if there’s room in the buffer and be -enqueued otherwise. Let’s illustrate the point creating a channel with a buffer of -one element. The chan constructors accepts a number as its first argument which -will cause it to have a buffer with the given size: -(require '[cljs.core.async :refer [chan put! take!]]) - -(def ch (chan 1)) - -(put! ch 42 #(println "Put succeeded!")) -;; Put succeeded! -;; => true - -(dotimes [n 1024] - (put! ch n)) -;; => nil - -(put! ch 42) -;; Error: Assert failed: No more than 1024 pending puts are allowed on a single channel. -What happened in the example above? We created a channel with a buffer of size 1 and -performed a put operation on it that succeeded immediately because the value was -buffered. After that we did another 1024 puts to fill the pending put queue and, -when trying to put one value more the channel complained about not being able to -enqueue more puts. -Now that we know about how channels work and what are buffers used for let’s explore -the different buffers that core.async implements. Different buffers have different -policies and it’s interesting to know all of them to know when to use what. Channels -are unbuffered by default. -
    -Fixed -The fixed size buffer is the one that is created when we give the chan constructor -a number and it will have the size specified by the given number. It is the simplest -possible buffer: when full, puts will be enqueued. -The chan constructor accepts either a number or a buffer as its first argument. -The two channels created in the following example both use a fixed buffer of size -32: -(require '[cljs.core.async :refer [chan buffer]]) - -(def a-ch (chan 32)) - -(def another-ch (chan (buffer 32))) -
    -
    -Dropping -The fixed buffer allows put operations to be enqueued. However, as we saw before, -puts are still queued when the fixed buffer is full. If we wan’t to discard the put -operations that happen when the buffer is full we can use a dropping buffer. -Dropping buffers have a fixed size and, when they are full puts will complete but -their value will be discarded. Let’s illustrate the point with an example: -(require '[cljs.core.async :refer [chan dropping-buffer put! take!]]) - -(def ch (chan (dropping-buffer 2))) - -(put! ch 40) -;; => true -(put! ch 41) -;; => true -(put! ch 42) -;; => true - -(take! ch #(println "Got" %)) -;; Got 40 -;; => nil -(take! ch #(println "Got" %)) -;; Got 41 -;; => nil -(take! ch #(println "Got" %)) -;; => nil -We performed three put operations and the three of them succeded but, since the -dropping buffer of the channel has size 2, only the first two values were delivered -to the takers. As you can observe the third take is enqueued since there is no value -available, the third put’s value (42) was discarded. -
    -
    -Sliding -The sliding buffer has the opposite policy than the dropping buffer. When full puts -will complete and the oldest value will be discarded in favor of the new one. The -sliding buffer is useful when we are interested in processing the last puts only and -we can afford discarding old values. -(require '[cljs.core.async :refer [chan sliding-buffer put! take!]]) - -(def ch (chan (sliding-buffer 2))) - -(put! ch 40) -;; => true -(put! ch 41) -;; => true -(put! ch 42) -;; => true - -(take! ch #(println "Got" %)) -;; Got 41 -;; => nil -(take! ch #(println "Got" %)) -;; Got 42 -;; => nil -(take! ch #(println "Got" %)) -;; => nil -We performed three put operations and the three of them succeded but, since the -sliding buffer of the channel has size 2, only the last two values were delivered to -the takers. As you can observe the third take is enqueued since there is no value -available since the first put’s value was discarded. -
    -
    -
    -Transducers -As mentioned in the section about transducers, putting values in a channel can be -thought as a transducible process. This means that we can create channels and hand -them a transducer, giving us the ability to transform the input values before being -put in the channel. -If we want to use a transducer with a channel we must supply a buffer since the -reducing function that will be modified by the transducer will be the buffer’s add -function. A buffer’s add function is a reducing function since it takes a buffer and -an input and returns a buffer with such input incorporated. -(require '[cljs.core.async :refer [chan put! take!]]) - -(def ch (chan 1 (map inc))) - -(put! ch 41) -;; => true - -(take! ch #(println "Got" %)) -;; Got 42 -;; => nil -You may be wondering what happens to a channel when the reducing function returns a -reduced value. It turns out that the notion of termination for channels is being -closed, so channels will be closed when a reduced value is encountered: -(require '[cljs.core.async :refer [chan put! take!]]) - -(def ch (chan 1 (take 2))) - -(take! ch #(println "Got" %)) -;; => nil -(take! ch #(println "Got" %)) -;; => nil -(take! ch #(println "Got" %)) -;; => nil - -(put! ch 41) -;; => true -(put! ch 42) -;; Got 41 -;; => true -(put! ch 43) -;; Got 42 -;; Got nil -;; => false -We used the take stateful transducer to allow maximum 2 puts into the channel. We -then performed three take operations on the channel and we expect only two to -receive a value. As you can see in the above example the third take got the sentinel -nil value which indicates that the channel was closed. Also, the third put -operation returned false indicating that it didn’t take place. -
    -
    -Handling exceptions -If adding a value to a buffer throws an exception core.async the operation will -fail and the exception will be logged to the console. However, channel constructors -accept a third argument: a function for handling exceptions. -When creating a channel with an exception handler it will be called with the -exception whenever an exception occurs. If the handler returns nil the operation -will fail silently and if it returns another value the add operation will be retried -with such value. -(require '[cljs.core.async :refer [chan put! take!]]) - -(enable-console-print!) - -(defn exception-xform - [rfn] - (fn [acc input] - (throw (js/Error. "I fail!")))) - -(defn handle-exception - [ex] - (println "Exception message:" (.-message ex)) - 42) - -(def ch (chan 1 exception-xform handle-exception)) - -(put! ch 0) -;; Exception message: I fail! -;; => true - -(take! ch #(println "Got:" %)) -;; Got: 42 -;; => nil -
    -
    -Offer and Poll -We’ve learned about the two basic operations on channels so far: put! and take!. -They either take or put a value and are enqueued if they can’t be performed -immediately. Both functions are asynchronous because of their nature: they can -succeed but be completed at a later time. -core.async has two synchronous operations for putting or taking values: offer! -and poll!. Let’s see how they work through examples. -offer! puts a value in a channel if it’s possible to do so immediately. It returns -true if the channel received the value and false otherwise. Note that, unlike -with put!, offer! cannot distinguish between closed and open channels. -(require '[cljs.core.async :refer [chan offer!]]) - -(def ch (chan 1)) - -(offer! ch 42) -;; => true - -(offer! ch 43) -;; => false -poll! takes a value from a channel if it’s possible to do so immediately. Returns -the value if succesful and nil otherwise. Unlike take!, poll! cannot -distinguish closed and open channels. -(require '[cljs.core.async :refer [chan offer! poll!]]) - -(def ch (chan 1)) - -(poll! ch) -;; => nil - -(offer! ch 42) -;; => true - -(poll! ch) -;; => 42 -
    -
    -
    -Processes -We learned all about channels but there is still a missing piece in the puzzle: -processes. Processes are pieces of logic that run independently and use channels -for communication and coordination. Puts and takes inside a process will stop the -process until the operation completes. Stopping a process doesn’t block the only -thread we have in the environments where ClojureScript runs. Instead, it will be -resumed at a later time when the operation is waiting for being performed. -Processes are launched using the go macro and puts and takes use the <! and >! -placeholders. The go macro rewrites your code to use callbacks but inside go -everything looks like synchronous code, which makes understanding it -straightforward: -(require '[cljs.core.async :refer [chan <! >!]]) -(require-macros '[cljs.core.async.macros :refer [go]]) - -(enable-console-print!) - -(def ch (chan)) - -(go - (println [:a] "Gonna take from channel") - (println [:a] "Got" (<! ch))) - -(go - (println [:b] "Gonna put on channel") - (>! ch 42) - (println [:b] "Just put 42")) - -;; [:a] Gonna take from channel -;; [:b] Gonna put on channel -;; [:b] Just put 42 -;; [:a] Got 42 -In the above example we are launching a process with go that takes a value from -ch and prints it to the console. Since the value isn’t immediately available it -will park until it can resume. After that we launch another process that puts a -value on the channel. -Since there is a pending take the put operation succeeds and the value is delivered -to the first process, then both processes terminate. -Both go blocks run independently and, even though they are executed -asynchronously, they look like synchronous code. The above go blocks are fairly -simple but being able to write concurrent processes that coordinate via channels is -a very powerful tool for implementing complex asynchronous workflows. Channels also -offer a great decoupling of producers and consumers. -Processes can wait for an arbitrary amount of time too, there is a timeout -function that return a channel that will be closed after the given amount of -miliseconds. Combining a timeout channel with a take operation inside a go block -gives us the ability to sleep: -(require '[cljs.core.async :refer [<! timeout]]) -(require-macros '[cljs.core.async.macros :refer [go]]) - -(enable-console-print!) - -(defn seconds - [] - (.getSeconds (js/Date.))) - -(println "Launching go block") - -(go - (println [:a] "Gonna take a nap" (seconds)) - (<! (timeout 1000)) - (println [:a] "I slept one second, bye!" (seconds))) - -(println "Block launched") - -;; Launching go block -;; Block launched -;; [:a] Gonna take a nap 9 -;; [:a] I slept one second, bye! 10 -As we can see in the messages printed, the process does nothing for one second when -it blocks in the take operation of the timeout channel. The program continues and -after one second the process resumes and terminates. -
    -Choice -Apart from putting and taking one value at a time inside a go block we can also make -a non-deterministic choice on multiple channel operations using alts!. alts! is -given a series of channel put or take operations (note that we can also try to put -and take in a channel at the same time) and only performs one as soon as is ready; -if multiple operations can be performed when calling alts! it will do a pseudo -random choice by default. -We can easily try an operation on a channel and cancel it after a certain amount of -time combining the timeout function and alts!. Let’s see how: -(require '[cljs.core.async :refer [chan <! timeout alts!]]) -(require-macros '[cljs.core.async.macros :refer [go]]) - -(enable-console-print!) - -(def ch (chan)) - -(go - (println [:a] "Gonna take a nap") - (<! (timeout 1000)) - (println [:a] "I slept one second, trying to put a value on channel") - (>! ch 42) - (println [:a] "I'm done!")) - -(go - (println [:b] "Gonna try taking from channel") - (let [cancel (timeout 300) - [value ch] (alts! [ch cancel])] - (if (= ch cancel) - (println [:b] "Too slow, take from channel cancelled") - (println [:b] "Got" value)))) - -;; [:a] Gonna take a nap -;; [:b] Gonna try taking from channel -;; [:b] Too slow, take from channel cancelled -;; [:a] I slept one second, trying to put a value on channel -In the example above we launched a go block that, after waiting for a second, puts a -value in the ch channel. The other go block creates a cancel channel, which will -be closed after 300 miliseconds. After that, it tries to read from both ch and -cancel at the same time using alts!, which will succeed whenever it can take a -value from either of those channels. Since cancel is closed after 300 miliseconds, -alts! will succeed since takes from closed channel return the nil sentinel. Note -that alts! returns a two-element vector with the returned value of the operation -and the channel where it was performed. -This is why we are able to detect whether the read operation was performed in the -cancel channel or in ch. I suggest you copy this example and set the first -process timeout to 100 miliseconds to see how the read operation on ch succeeds. -We’ve learned how to choose between read operations so let’s look at how to express -a conditional write operation in alts!. Since we need to provide the channel and a -value to try to put on it, we’ll use a two element vector with the channel and the -value for representing write operations. -Let’s see an example: -(require '[cljs.core.async :refer [chan <! alts!]]) -(require-macros '[cljs.core.async.macros :refer [go]]) - -(enable-console-print!) - -(def a-ch (chan)) -(def another-ch (chan)) - -(go - (println [:a] "Take a value from `a-ch`") - (println [:a] "Got" (<! a-ch)) - (println [:a] "I'm done!")) - -(go - (println [:b] "Take a value from `another-ch`") - (println [:a] "Got" (<! another-ch)) - (println [:b] "I'm done!")) - -(go - (println [:c] "Gonna try putting in both channels simultaneously") - (let [[value ch] (alts! [[a-ch 42] - [another-ch 99]])] - (if (= ch a-ch) - (println [:c] "Put a value in `a-ch`") - (println [:c] "Put a value in `another-ch`")))) - -;; [:a] Take a value from `a-ch` -;; [:b] Take a value from `another-ch` -;; [:c] Gonna try putting in both channels simultaneously -;; [:c] Put a value in `a-ch` -;; [:a] Got 42 -;; [:a] I'm done! -When running the above example only the put operation on the a-ch channel has -succeeded. Since both channels are ready to take a value when the alts! occurs you -may get different results when running this code. -
    -
    -Priority -alts! default is to make a non-deterministic choice whenever several operations -are ready to be performed. We can instead give priority to the operations passing -the :priority option to alts!. Whenever :priority is true, if more than one -operation is ready they will be tried in order. -(require '[cljs.core.async :refer [chan >! alts!]]) -(require-macros '[cljs.core.async.macros :refer [go]]) - -(enable-console-print!) - -(def a-ch (chan)) -(def another-ch (chan)) - -(go - (println [:a] "Put a value on `a-ch`") - (>! a-ch 42) - (println [:a] "I'm done!")) - -(go - (println [:b] "Put a value on `another-ch`") - (>! another-ch 99) - (println [:b] "I'm done!")) - -(go - (println [:c] "Gonna try taking from both channels with priority") - (let [[value ch] (alts! [a-ch another-ch] :priority true)] - (if (= ch a-ch) - (println [:c] "Got" value "from `a-ch`") - (println [:c] "Got" value "from `another-ch`")))) - -;; [:a] Put a value on `a-ch` -;; [:a] I'm done! -;; [:b] Put a value on `another-ch` -;; [:b] I'm done! -;; [:c] Gonna try taking from both channels with priority -;; [:c] Got 42 from `a-ch` -Since both a-ch and another-ch had a value to read when the alts! was executed -and we set the :priority option to true, a-ch has preference. You can try -deleting the :priority option and running the example multiple times to see that, -without priority, alts! makes a non-deterministic choice. -
    -
    -Defaults -Another interesting bit of alts! is that it can return immediately if no operation -is ready and we provide a default value. We can conditionally do a choice on the -operations if and only if any of them is ready, returning a default value if it’s -not. -(require '[cljs.core.async :refer [chan alts!]]) -(require-macros '[cljs.core.async.macros :refer [go]]) - -(def a-ch (chan)) -(def another-ch (chan)) - -(go - (println [:a] "Gonna try taking from any of the channels without blocking") - (let [[value ch] (alts! [a-ch another-ch] :default :not-ready)] - (if (and (= value :not-ready) - (= ch :default)) - (println [:a] "No operation is ready, aborting") - (println [:a] "Got" value)))) - -;; [:a] Gonna try taking from any of the channels without blocking -;; [:a] No operation is ready, aborting -As you can see in the above example, if no operation is ready the value returned by -alts! is the one we supplied after the :default key when calling it and the -channel is the :default keyword itself. -
    -
    -
    -Combinators -Now that we’re acquainted with channels and processes it’s time to explore some -interesting combinators for working with channels that are present in core.async. -This section includes a brief description of all of them together with a simple -example of their usage. -
    -pipe -pipe takes an input and output channels and pipes all the values put on the input -channel to the output one. The output channel is closed whenever the source is -closed unless we provide a false third argument: -(require '[cljs.core.async :refer [chan pipe put! <! close!]]) -(require-macros '[cljs.core.async.macros :refer [go-loop]]) - -(def in (chan)) -(def out (chan)) - -(pipe in out) - -(go-loop [value (<! out)] - (if (nil? value) - (println [:a] "I'm done!") - (do - (println [:a] "Got" value) - (println [:a] "Waiting for a value") - (recur (<! out))))) - -(put! in 0) -;; => true -(put! in 1) -;; => true -(close! in) - -;; [:a] Got 0 -;; [:a] Waiting for a value -;; [:a] Got 1 -;; [:a] Waiting for a value -;; [:a] I'm done! -In the above example we used the go-loop macro for reading values recursively -until the out channel is closed. Notice that when we close the in channel the -out channel is closed too, making the go-loop terminate. -
    -
    -pipeline-async -pipeline-async takes a number for controlling parallelism, an output channel, an -asynchronous function and an input channel. The asynchronous function has two -arguments: the value put in the input channel and a channel where it should put the -result of its asynchronous operation, closing the result channel after finishing. -The number controls the number of concurrent go blocks that will be used for calling -the asynchronous function with the inputs. -The output channel will receive outputs in an order relative to the input channel, -regardless the time each asynchronous function call takes to complete. It has an -optional last parameter that controls whether the output channel will be closed when -the input channel is closed, which defaults to true. -(require '[cljs.core.async :refer [chan pipeline-async put! <! close!]]) -(require-macros '[cljs.core.async.macros :refer [go-loop]]) - -(def in (chan)) -(def out (chan)) -(def parallelism 3) - -(defn wait-and-put [value ch] - (let [wait (rand-int 1000)] - (js/setTimeout (fn [] - (println "Waiting" wait "miliseconds for value" value) - (put! ch wait) - (close! ch)) - wait))) - -(pipeline-async parallelism out wait-and-put in) - -(go-loop [value (<! out)] - (if (nil? value) - (println [:a] "I'm done!") - (do - (println [:a] "Got" value) - (println [:a] "Waiting for a value") - (recur (<! out))))) - -(put! in 1) -(put! in 2) -(put! in 3) -(close! in) - -;; Waiting 164 miliseconds for value 3 -;; Waiting 304 miliseconds for value 2 -;; Waiting 908 miliseconds for value 1 -;; [:a] Got 908 -;; [:a] Waiting for a value -;; [:a] Got 304 -;; [:a] Waiting for a value -;; [:a] Got 164 -;; [:a] Waiting for a value -;; [:a] I'm done! -
    -
    -pipeline -pipeline is similar to pipeline-async but instead of taking and asynchronous -function it takes a transducer instead. The transducer will be applied independently -to each input. -(require '[cljs.core.async :refer [chan pipeline put! <! close!]]) -(require-macros '[cljs.core.async.macros :refer [go-loop]]) - -(def in (chan)) -(def out (chan)) -(def parallelism 3) - -(pipeline parallelism out (map inc) in) - -(go-loop [value (<! out)] - (if (nil? value) - (println [:a] "I'm done!") - (do - (println [:a] "Got" value) - (println [:a] "Waiting for a value") - (recur (<! out))))) - -(put! in 1) -(put! in 2) -(put! in 3) -(close! in) - -;; [:a] Got 2 -;; [:a] Waiting for a value -;; [:a] Got 3 -;; [:a] Waiting for a value -;; [:a] Got 4 -;; [:a] Waiting for a value -;; [:a] I'm done! -
    -
    -split -split takes a predicate and a channel and returns a vector with two channels, the -first of which will receive the values for which the predicate is true, the second -will receive those for which the predicate is false. We can optionally pass a buffer -or number for the channels with the third (true channel) and fourth (false channel) -arguments. -(require '[cljs.core.async :refer [chan split put! <! close!]]) -(require-macros '[cljs.core.async.macros :refer [go-loop]]) - -(def in (chan)) -(def chans (split even? in)) -(def even-ch (first chans)) -(def odd-ch (second chans)) - -(go-loop [value (<! even-ch)] - (if (nil? value) - (println [:evens] "I'm done!") - (do - (println [:evens] "Got" value) - (println [:evens] "Waiting for a value") - (recur (<! even-ch))))) - -(go-loop [value (<! odd-ch)] - (if (nil? value) - (println [:odds] "I'm done!") - (do - (println [:odds] "Got" value) - (println [:odds] "Waiting for a value") - (recur (<! odd-ch))))) - -(put! in 0) -(put! in 1) -(put! in 2) -(put! in 3) -(close! in) - -;; [:evens] Got 0 -;; [:evens] Waiting for a value -;; [:odds] Got 1 -;; [:odds] Waiting for a value -;; [:odds] Got 3 -;; [:odds] Waiting for a value -;; [:evens] Got 2 -;; [:evens] Waiting for a value -;; [:evens] I'm done! -;; [:odds] I'm done! -
    -
    -reduce -reduce takes a reducing function, initial value and an input channel. It returns a -channel with the result of reducing over all the values put on the input channel -before closing it using the given initial value as the seed. -(require '[cljs.core.async :as async :refer [chan put! <! close!]]) -(require-macros '[cljs.core.async.macros :refer [go]]) - -(def in (chan)) - -(go - (println "Result" (<! (async/reduce + (+) in)))) - -(put! in 0) -(put! in 1) -(put! in 2) -(put! in 3) -(close! in) - -;; Result: 6 -
    -
    -onto-chan -onto-chan takes a channel and a collection and puts the contents of the collection -into the channel. It closes the channel after finishing although it accepts a third -argument for specifying if it should close it or not. Let’s rewrite the reduce -example using onto-chan: -(require '[cljs.core.async :as async :refer [chan put! <! close! onto-chan]]) -(require-macros '[cljs.core.async.macros :refer [go]]) - -(def in (chan)) - -(go - (println "Result" (<! (async/reduce + (+) in)))) - -(onto-chan in [0 1 2 3]) - -;; Result: 6 -
    -
    -to-chan -to-chan takes a collection and returns a channel where it will put every value in -the collection, closing the channel afterwards. -(require '[cljs.core.async :refer [chan put! <! close! to-chan]]) -(require-macros '[cljs.core.async.macros :refer [go-loop]]) - -(def ch (to-chan (range 3))) - -(go-loop [value (<! ch)] - (if (nil? value) - (println [:a] "I'm done!") - (do - (println [:a] "Got" value) - (println [:a] "Waiting for a value") - (recur (<! ch))))) - -;; [:a] Got 0 -;; [:a] Waiting for a value -;; [:a] Got 1 -;; [:a] Waiting for a value -;; [:a] Got 2 -;; [:a] Waiting for a value -;; [:a] I'm done! -
    -
    -merge -merge takes a collection of input channels and returns a channel where it will put -every value that is put on the input channels. The returned channel will be closed -when all the input channels have been closed. The returned channel will be -unbuffered by default but a number or buffer can be provided as the last argument. -(require '[cljs.core.async :refer [chan put! <! close! merge]]) -(require-macros '[cljs.core.async.macros :refer [go-loop]]) - -(def in1 (chan)) -(def in2 (chan)) -(def in3 (chan)) - -(def out (merge [in1 in2 in3])) - -(go-loop [value (<! out)] - (if (nil? value) - (println [:a] "I'm done!") - (do - (println [:a] "Got" value) - (println [:a] "Waiting for a value") - (recur (<! out))))) - -(put! in1 1) -(close! in1) -(put! in2 2) -(close! in2) -(put! in3 3) -(close! in3) - -;; [:a] Got 3 -;; [:a] Waiting for a value -;; [:a] Got 2 -;; [:a] Waiting for a value -;; [:a] Got 1 -;; [:a] Waiting for a value -;; [:a] I'm done! -
    -
    -
    -Higher-level abstractions -We’ve learned the about the low-level primitives of core.async and the combinators -that it offers for working with channels. core.async also offers some useful, -higher-level abstractions on top of channels that can serve as building blocks for -more advanced functionality. -
    -Mult -Whenever we have a channel whose values have to be broadcasted to many others, we -can use mult for creating a multiple of the supplied channel. Once we have a mult, -we can attach channels to it using tap and dettach them using untap. Mults also -support removing all tapped channels at once with untap-all. -Every value put in the source channel of a mult is broadcasted to all the tapped -channels, and all of them must accept it before the next item is broadcasted. For -preventing slow takers from blocking the mult’s values we must use buffering on the -tapped channels judiciously. -Closed tapped channels are removed automatically from the mult. When putting a value -in the source channels when there are still no taps such value will be dropped. -(require '[cljs.core.async :refer [chan put! <! close! timeout mult tap]]) -(require-macros '[cljs.core.async.macros :refer [go-loop]]) - -;; Source channel and mult -(def in (chan)) -(def m-in (mult in)) - -;; Sink channels -(def a-ch (chan)) -(def another-ch (chan)) - -;; Taker for `a-ch` -(go-loop [value (<! a-ch)] - (if (nil? value) - (println [:a] "I'm done!") - (do - (println [:a] "Got" value) - (recur (<! a-ch))))) - -;; Taker for `another-ch`, which sleeps for 3 seconds between takes -(go-loop [value (<! another-ch)] - (if (nil? value) - (println [:b] "I'm done!") - (do - (println [:b] "Got" value) - (println [:b] "Resting 3 seconds") - (<! (timeout 3000)) - (recur (<! another-ch))))) - -;; Tap the two channels to the mult -(tap m-in a-ch) -(tap m-in another-ch) - -;; See how the values are delivered to `a-ch` and `another-ch` -(put! in 1) -(put! in 2) - -;; [:a] Got 1 -;; [:b] Got 1 -;; [:b] Resting for 3 seconds -;; [:a] Got 2 -;; [:b] Got 2 -;; [:b] Resting for 3 seconds -
    -
    -Pub-sub -After learning about mults you could imagine how to implement a pub-sub abstraction -on top of mult, tap and untap but since it’s a widely used communication -mechanism core.async already implements this functionality. -Instead of creating a mult from a source channel, we create a publication with pub -giving it a channel and a function that will be used for extracting the topic of the -messages. -We can subscribe to a publication with sub, giving it the publication we want to -subscribe to, the topic we are interested in and a channel to put the messages that -have the given topic. Note that we can subscribe a channel to multiple topics. -unsub can be given a publication, topic and channel for unsubscribing such channel -from the topic. unsub-all can be given a publication and a topic to unsubscribe -every channel from the given topic. -(require '[cljs.core.async :refer [chan put! <! close! pub sub]]) -(require-macros '[cljs.core.async.macros :refer [go-loop]]) - -;; Source channel and publication -(def in (chan)) -(def publication (pub in :action)) - -;; Sink channels -(def a-ch (chan)) -(def another-ch (chan)) - -;; Channel with `:increment` action -(sub publication :increment a-ch) - -(go-loop [value (<! a-ch)] - (if (nil? value) - (println [:a] "I'm done!") - (do - (println [:a] "Increment:" (inc (:value value))) - (recur (<! a-ch))))) - -;; Channel with `:double` action -(sub publication :double another-ch) - -(go-loop [value (<! another-ch)] - (if (nil? value) - (println [:b] "I'm done!") - (do - (println [:b] "Double:" (* 2 (:value value))) - (recur (<! another-ch))))) - -;; See how values are delivered to `a-ch` and `another-ch` depending on their action -(put! in {:action :increment :value 98}) -(put! in {:action :double :value 21}) - -;; [:a] Increment: 99 -;; [:b] Double: 42 -
    -
    -Mixer -As we learned in the section about core.async combinators, we can use the merge -function for combining multiple channels into one. When merging multiple channels, -every value put in the input channels will end up in the merged channel. However, we -may want more finer-grained control over which values put in the input channels end -up in the output channel, that’s where mixers come in handy. -core.async gives us the mixer abstraction, which we can use to combine multiple -input channnels into an output channel. The interesting part of the mixer is that we -can mute, pause and listen exclusively to certain input channels. -We can create a mixer given an output channel with mix. Once we have a mixer we -can add input channels into the mix using admix, remove it using unmix or remove -every input channel with unmix-all. -For controlling the state of the input channel we use the toggle function giving -it the mixer and a map from channels to their states. Note that we can add channels -to the mix using toggle, since the map will be merged with the current state of -the mix. The state of a channel is a map which can have the keys :mute, :pause -and :solo mapped to a boolean. -Let’s see what muting, pausing and soloing channels means: - - -A muted input channel means that, while still taking values from it, they won’t -be forwarded to the output channel. Thus, while a channel is muted, all the values -put in it will be discarded. - - -A paused input channel means that no values will be taken from it. This means -that values put in the channel won’t be forwarded to the output channel nor -discarded. - - -When soloing one or more channels the output channel will only receive the values -put in soloed channels. By default non-soloed channels are muted but we can use -solo-mode to decide between muting or pausing non-soloed channels. - - -That was a lot of information so let’s see an example to improve our understanding. -First of all, we’ll set up a mixer with an out channel and add three input -channels to the mix. After that, we’ll be printing all the values received on the -out channel to illustrate the control over input channels: -(require '[cljs.core.async :refer [chan put! <! close! mix admix - unmix toggle solo-mode]]) -(require-macros '[cljs.core.async.macros :refer [go-loop]]) - -;; Output channel and mixer -(def out (chan)) -(def mixer (mix out)) - -;; Input channels -(def in-1 (chan)) -(def in-2 (chan)) -(def in-3 (chan)) - -(admix mixer in-1) -(admix mixer in-2) -(admix mixer in-3) - -;; Let's listen to the `out` channel and print what we get from it -(go-loop [value (<! out)] - (if (nil? value) - (println [:a] "I'm done") - (do - (println [:a] "Got" value) - (recur (<! out))))) -By default, every value put in the input channels will be put in the out channel: -(do - (put! in-1 1) - (put! in-2 2) - (put! in-3 3)) - -;; [:a] Got 1 -;; [:a] Got 2 -;; [:a] Got 3 -Let’s pause the in-2 channel, put a value in every input channel and resume in-2: -(toggle mixer {in-2 {:pause true}}) -;; => true - -(do - (put! in-1 1) - (put! in-2 2) - (put! in-3 3)) - -;; [:a] Got 1 -;; [:a] Got 3 - -(toggle mixer {in-2 {:pause false}}) - -;; [:a] Got 2 -As you can see in the example above, the values put in the paused channels aren’t -discarded. For discarding values put in an input channel we have to mute it, let’s -see an example: -(toggle mixer {in-2 {:mute true}}) -;; => true - -(do - (put! in-1 1) - (put! in-2 2) ;; `out` will never get this value since it's discarded - (put! in-3 3)) - -;; [:a] Got 1 -;; [:a] Got 3 - -(toggle mixer {in-2 {:mute false}}) -We put a value 2 in the in-2 channel and, since the channel was muted at the -time, the value is discarded and never put into out. Let’s look at the third state -a channel can be inside a mixer: solo. -As we mentioned before, soloing channels of a mixer implies muting the rest of them -by default: -(toggle mixer {in-1 {:solo true} - in-2 {:solo true}}) -;; => true - -(do - (put! in-1 1) - (put! in-2 2) - (put! in-3 3)) ;; `out` will never get this value since it's discarded - -;; [:a] Got 1 -;; [:a] Got 2 - -(toggle mixer {in-1 {:solo false} - in-2 {:solo false}}) -However, we can set the mode the non-soloed channels will be in while there are -soloed channels. Let’s set the default non-solo mode to pause instead of the default -mute: -(solo-mode mixer :pause) -;; => true -(toggle mixer {in-1 {:solo true} - in-2 {:solo true}}) -;; => true - -(do - (put! in-1 1) - (put! in-2 2) - (put! in-3 3)) - -;; [:a] Got 1 -;; [:a] Got 2 - -(toggle mixer {in-1 {:solo false} - in-2 {:solo false}}) - -;; [:a] Got 3 -
    -
    -
    -
    - -Appendix -
    -Appendix A: Interactive development with Figwheel -
    -Introduction -In this project, we will not do “Hello World”— that has been done to death. -Instead, this project will be a web page that asks you for your age in years and -tells you how many days that is, using an approximation of 365 days per year. -For this project, we will use the figwheel leiningen plugin. This plugin creates a -fully interactive, REPL-based, autoreloading environment. -
    -
    -First steps -The first step is to create the new project using the figwheel lein template. We -will name the project age, and create it by typing: -$ lein new figwheel age -Retrieving figwheel/lein-template/0.3.5/lein-template-0.3.5.pom from clojars -Retrieving figwheel/lein-template/0.3.5/lein-template-0.3.5.jar from clojars -Generating fresh 'lein new' figwheel project. -$ cd age # move into newly created project directory -The project has the following structure: -> tree age # the linux "tree" utility displays dir structure -age -├── .gitignore -├── project.clj -├── README.md -├── resources -│   └── public -│   ├── css -│   │   └── style.css -│   └── index.html -└── src - └── age - └── core.cljs -The project.clj file contains information that Leiningen uses to download -dependencies and build the project. For now, just trust that everything in that file -is exactly as it should be. -Open the index.html file and make it look like the following: -<!DOCTYPE html> -<html> - <head> - <link href="css/style.css" rel="stylesheet" type="text/css"> - <meta http-equiv="Content-Type" content="text/html;charset=utf-8" /> - </head> - <body> - <div id="app"> - <h1>Age in Days</h1> - <p> - Enter your age in years: - <input type="text" size="5" id="years"> - <button id="calculate">Calculate</button> - </p> - <p id="feedback"></p> - </div> - <script src="js/compiled/age.js" type="text/javascript"></script> - </body> -</html> -The core.cljs file is where all the action takes place. For now, leave it exactly -as it is, and start the figwheel environment, which will load a large number of -dependencies and start a server. -$ lein figwheel -Retrieving lein-figwheel/lein-figwheel/0.5.2/lein-figwheel-0.5.2.pom from clojars -Retrieving figwheel-sidecar/figwheel-sidecar/0.5.2/figwheel-sidecar-0.5.2.pom from clojars -Retrieving org/clojure/clojurescript/1.7.228/clojurescript-1.7.228.pom from central -... # much more output -Prompt will show when Figwheel connects to your application -If you are using Linux or Mac OS X, type the command as rlwrap lein figwheel. -In your browser, go to URL http://localhost:3449, and you will see something -like the following screenshot if you open up the web console. - - - - - -Screenshot of web page and console - - -The terminal will then give you a REPL prompt: -$ rlwrap lein figwheel -To quit, type: :cljs/quit -cljs.user=> -For now, do what it says in the core.cljs file — change the (println…​) and -then save the file. When you do so, you will see the change reflected immediately in -the browser. -Then make an error by adding an extra closing parenthesis to the println. When you -save the file, will see a compile error in the browser window. -
    -
    -Interacting with JavaScript -In the REPL window, type the following to invoke JavaScript’s window.alert() -function: -(.alert js/window "It works!") -;; => nil -The general format for invoking a JavaScript function from ClojureScript is to give -the function name (preceded by a dot), the object that “owns” the function, and any -parameters to that function. You should see an alert appear in your browser window; -when you dismiss the alert, the REPL will print nil and give you another -prompt. You can also do it this way: -(js/alert "It works!") -;; => nil -However, the first version always works, so, for consistency, we will use that -notation throughout this tutorial. -JavaScript objects may be instanciated from ClojureScript using the same interop -syntax as for Java/Clojure interop, using the class name followed by a dot. -JavaScript methods may also be called using the familiar interop syntax: -> (def d (js/Date.)) -;; => #'cljs.user/d -> d -;; => #inst "2016-04-03T21:04:29.908-00:00" -> (.getFullYear d) -;; => 2016 - -> (.toUpperCase "doh!") -;; => "DOH!" - -> (.getElementById js/document "years") -;; => #object[HTMLInputElement [object HTMLInputElement]] -The next example shows where we’re headed. To retrieve an object’s property, use the -dot-dash or "access" syntax .- before the property name. In the browser window, -type a number into the input field (in the example, we typed 24), then do this in -the REPL. -(def year-field (.getElementById js/document "years")) -;; => #'cljs.user/year-field - -(.-value year-field) -;; => "24" - -(set! (.-value year-field) "25") -;; => "25" -This works, but it is little more than a direct translation of JavaScript to -ClojureScript. The next step is to add event handling to the button. Event handling -is loaded with all sorts of cross-platform compatibility issues, so we’d like a step -up from plain ClojureScript. -The solution is the Google Closure library. To use it, you have to modify the -:require clause at the beginning of core.cljs: -(ns ^:figwheel-always age.core - (:require [goog.dom :as dom] - [goog.events :as events])) -Getting an element and setting its value is now slightly easier. Do this in the REPL -and see the results in the browser window. -(in-ns 'age.core) -(def y (dom/getElement "years")) -;; => #'age.core/y - -(set! (.-value y) "26") -;; => "26" - -(dom/setTextContent (dom/getElement "feedback") "This works!") -;; => nil -To add an event, you define a function that takes a single argument (the event to be -handled), and then tell the appropriate HTML element to listen for it. The -events/listen function takes three arguments: the element to listen to, the event -to listen for, and the function that will handle the event. -(defn testing [evt] (js/alert "Responding to click")) -;; => #'age.core/testing - -(events/listen (dom/getElement "calculate") "click" testing) -;; => #<[object Object]> -After doing this, the browser should respond to a click on the button. If you would -like to remove the listener, use unlisten. -(events/unlisten (dom/getElement "calculate") "click" testing) -;; => true -Now, put that all together in the core.cljs file as follows: -(ns ^:figwheel-always age.core - (:require [goog.dom :as dom] - [goog.events :as events])) - -(enable-console-print!) - -(defn calculate - [event] - (let [years (.parseInt js/window (.-value (dom/getElement "years"))) - days (* 365 years)] - (dom/setTextContent (dom/getElement "feedback") - (str "That is " days " days old.")))) - -(defn on-js-reload []) - -(events/listen (dom/getElement "calculate") "click" calculate) -
    -
    -
    -Appendix B: Setting up a ClojureScript development environment -
    -Cursive -TODO -
    -
    -Emacs -TODO -
    -
    -Vim -TODO -
    -
    -
    - -Acknowledgments -Special thanks to: - - -J David Eisenberg: For the huge amount of time spend in fixing all kind of errors and -writing entire sections of the book, as well as making very valuable suggestions. - - -And here is an inevitably incomplete list of MUCH-APPRECIATED CONTRIBUTORS — people who have submitted corrections, new ideas and generally made the -ClojureScript Unraveled book much better: - - -Anler Hernández Peral (@anler) - - -Diego Sevilla Ruiz (@dsevilla) - - -Eduardo Ferro Aldama (@eferro) - - -Tyler Anderson (@Tyler-Anderson) - - -Chris Ulrich (@chrisulrich) - - -Jean Hadrien Chabran (@jhchabran) - - -Tienson Qin (@tiensonqin) - - -FungusHumungus (@FungusHumungus), - - -Chris Charles (@ccharles) - - -Jearvon Dharrie (@iamjarvo) - - -Shaun LeBron (@shaunlebron) - - -Wodin (@wodin) - - -Crocket (@crocket) - - - - -Further Reading -Here is a list of more resources about ClojureScript. - - -ClojureScript wiki: a community-mantained wiki about ClojureScript. - - -API Reference: a community-maintained complete language api reference. - - -ClojureScript Cheatsheet: a comprehensive reference of the ClojureScript language. - - -Études for ClojureScript: a collection of exercises for learning ClojureScript. - - -ClojureScript made easy: a collection of short articles about solving common problems in ClojureScript. - - -The Google Closure Library API reference - - - - \ No newline at end of file diff --git a/fonts/monoid-regular-webfont.eot b/fonts/monoid-regular-webfont.eot deleted file mode 100644 index 1785715ec6721f251cdb8f1a658c3078a3f155d9..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 21742 zcmZU4WlSVa@Z}8d?mD=;>*DV2?(XjH?mD=;%d&$zi~Hhk3oNj(!0!F-^8av`t4`%r zzkcBL0W}ZGeC@AmBevN$npLAk0z?2IIfu|6`^9 zgQjZ#&i*I-zW@cG3~&Xw{O9%ntN(a3fCj)CU<>dDI04K79{({!0GMIO5w-ls zio5#?W~M9Bs4;$aK}?X{n^)aU&{lNi*utwegGT{y3p{s(SWAb4U1aJZxF)vS!S&Vs zDBx@?vG7s8zH7W4=vR{zkX$_=HLqFCNV`9u%ectiS*tMyi?SGKSQuoRQY&yG%XA6$ 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    1. About this b spread the ideas about programming that Clojure has helped popularize, as we see a lot of value in them.

    +
    +

    This is a list of translations of the book:

    +
    +
    @@ -402,8 +418,7 @@

    3.2.2. Keywords

    :foobar
     :2
    -:?
    -:foo/bar
    +:?
    @@ -421,6 +436,48 @@

    3.2.2. Keywords

    ;; => :foo
    +
    +
    Namespaced keywords
    +
    +

    When prefixing keywords with a double colon ::, the keyword will be prepended by the name of the current namespace. +Note that namespacing keywords affects equality comparisons.

    +
    +
    +
    +
    ---
    +::foo
    +;; => :cljs.user/foo
    +
    +
    +
    +

    (= ::foo :foo) +;; ⇒ false +---

    +
    +
    +

    Another alternative is to include the namespace in the keyword literal, this is useful when creating namespaced keywords +for other namespaces:

    +
    +
    +
    +
    ---
    +:cljs.unraveled/foo
    +;; => :cljs.unraveled/foo
    +---
    +
    +
    +
    +

    The keyword function has an arity-2 variant where we can specify the namespace as the first parameter:

    +
    +
    +
    +
    ---
    +(keyword "cljs.unraveled" "foo")
    +;; => :cljs.unraveled/foo
    +---
    +
    +
    +
    @@ -4726,7 +4783,7 @@
    -
    cd mywebapp;
    +
    cd mywebapp;
     java -cp ../cljs.jar:src clojure.main build.clj
    @@ -4744,15 +4801,15 @@
    <!DOCTYPE html>
    -<html>
    -  <header>
    -    <meta charset="utf-8" />
    -    <title>Hello World from ClojureScript</title>
    -  </header>
    -  <body>
    -    <script src="main.js"></script>
    -  </body>
    -</html>
    +<html> + <header> + <meta charset="utf-8" /> + <title>Hello World from ClojureScript</title> + </header> + <body> + <script src="main.js"></script> + </body> +</html>
    @@ -4790,13 +4847,13 @@

    4.1.5. Watch proces
    -
    $ java -cp ../cljs.jar:src clojure.main watch.clj
    +
    $ java -cp ../cljs.jar:src clojure.main watch.clj
     Building ...
     Reading analysis cache for jar:file:/home/niwi/cljsbook/playground/cljs.jar!/cljs/core.cljs
     Compiling src/mywebapp/core.cljs
     Compiling out/cljs/core.cljs
     Using cached cljs.core out/cljs/core.cljs
    -... done. Elapsed 0.754487937 seconds
    +... done. Elapsed 0.754487937 seconds
     Watching paths: /home/niwi/cljsbook/playground/mywebapp/src
    @@ -4953,10 +5010,10 @@

    4.2.2. Nashorn REPL
    -
    $ java -cp cljs.jar:src clojure.main repl.clj
    -To quit, type: :cljs/quit
    -cljs.user=> (+ 1 2)
    -3
    +
    $ java -cp cljs.jar:src clojure.main repl.clj
    +To quit, type: :cljs/quit
    +cljs.user=> (+ 1 2)
    +3
    @@ -5012,10 +5069,10 @@

    4.2.3. Node.js REPL
    -
    $ rlwrap java -cp cljs.jar:src clojure.main repl.clj
    -To quit, type: :cljs/quit
    -cljs.user=> (+ 1 2)
    -3
    +
    $ rlwrap java -cp cljs.jar:src clojure.main repl.clj
    +To quit, type: :cljs/quit
    +cljs.user=> (+ 1 2)
    +3
    @@ -5038,7 +5095,7 @@

    4.2.4. Browser REPL(b/build "src" {:output-to "main.js" :output-dir "out/" - :source-map "main.js.map" + :source-map true :main 'myapp.core :verbose true :optimizations :none}) @@ -5084,15 +5141,15 @@

    4.2.4. Browser REPL
    <!DOCTYPE html>
    -<html>
    -  <header>
    -    <meta charset="utf-8" />
    -    <title>Hello World from ClojureScript</title>
    -  </header>
    -  <body>
    -    <script src="main.js"></script>
    -  </body>
    -</html>
    +<html> + <header> + <meta charset="utf-8" /> + <title>Hello World from ClojureScript</title> + </header> + <body> + <script src="main.js"></script> + </body> +</html>
    -
    $ lein version
    -Leiningen 2.5.1 on Java 1.8.0_45 OpenJDK 64-Bit Server VM
    +
    $ lein version
    +Leiningen 2.5.1 on Java 1.8.0_45 OpenJDK 64-Bit Server VM
    -
    $ lein new mies leapyears
    -$ cd leapyears # move into newly created project directory
    +
    $ lein new mies leapyears
    +$ cd leapyears # move into newly created project directory
    -
    <section class="viewport">
    -  <div id="result">
    +
    <section class="viewport">
    +  <div id="result">
         ----
    -  </div>
    -  <form action="" method="">
    -    <label for="year">Enter a year</label>
    -    <input id="year" name="year" />
    -  </form>
    -</section>
    + </div> + <form action="" method=""> + <label for="year">Enter a year</label> + <input id="year" name="year" /> + </form> +</section>
    -
    $ ./scripts/watch
    +
    $ ./scripts/watch
    -
    $ lein new mies mytestingapp
    -$ cd mytestingapp
    +
    $ lein new mies mytestingapp
    +$ cd mytestingapp
    @@ -5686,8 +5743,8 @@

    4.6.1. First steps<

    -
    $ mkdir -p test/mytestingapp
    -$ touch test/mytestingapp/core_tests.cljs
    +
    $ mkdir -p test/mytestingapp
    +$ touch test/mytestingapp/core_tests.cljs
    @@ -5745,12 +5802,12 @@

    4.6.1. First steps<

    -
    $ ./scripts/watch
    +
    $ ./scripts/watch
     Building ...
     Copying jar:file:/home/niwi/.m2/repository/org/clojure/clojurescript/1.9.36/clojurescript-1.9.36.jar!/cljs/core.cljs to out/cljs/core.cljs
     Reading analysis cache for jar:file:/home/niwi/.m2/repository/org/clojure/clojurescript/1.9.36/clojurescript-1.9.36.jar!/cljs/core.cljs
     Compiling out/cljs/core.cljs
    -... done. Elapsed 3.862126827 seconds
    +... done. Elapsed 3.862126827 seconds
     Watching paths: /home/niwi/cljsbook/playground/mytestingapp/test, /home/niwi/cljsbook/playground/mytestingapp/src
    @@ -5759,13 +5816,13 @@

    4.6.1. First steps<
    -
    $ node out/mytestingapp.js
    +
    $ node out/mytestingapp.js
     
     Testing mytestingapp.core-tests
     
     FAIL in (my-first-test) (cljs/test.js:374:14)
    -expected: (= 1 2)
    -  actual: (not (= 1 2))
    +expected: (= 1 2)
    +  actual: (not (= 1 2))
     
     Ran 1 tests containing 1 assertions.
     1 failures, 0 errors.
    @@ -5777,7 +5834,7 @@

    4.6.1. First steps<

    -
    $ node out/mytestingapp.js
    +
    $ node out/mytestingapp.js
     
     Testing mytestingapp.core-tests
     
    @@ -5917,8 +5974,8 @@ 

    4.6.4.

    -
    $ node out/mytestingapp.js
    -$ echo $?
    +
    $ node out/mytestingapp.js
    +$ echo $?
    -
    $ lein new figwheel age
    +
    $ lein new figwheel age
     Retrieving figwheel/lein-template/0.3.5/lein-template-0.3.5.pom from clojars
     Retrieving figwheel/lein-template/0.3.5/lein-template-0.3.5.jar from clojars
     Generating fresh 'lein new' figwheel project.
    -$ cd age # move into newly created project directory
    +$ cd age # move into newly created project directory
    -
    $ rlwrap lein figwheel
    -To quit, type: :cljs/quit
    +
    $ rlwrap lein figwheel
    +To quit, type: :cljs/quit
     cljs.user=>
    @@ -10667,7 +10724,7 @@

    8. Further Read

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l0^I)h7G3S!-0b3PmRMV2tTn_=e5Xkx+10Gsq;*rf{{r5bstf=C diff --git a/clojurescript-unraveled.xml b/clojurescript-unraveled.xml deleted file mode 100644 index 86d6959..0000000 --- a/clojurescript-unraveled.xml +++ /dev/null @@ -1,7138 +0,0 @@ - - - - - - -ClojureScript Unraveled -2016-07-25 - - -Andrey -Antukh -niwi@niwi.nz - - -Alejandro -Gómez -alejandro@dialelo.com - - - - -6 -2016-07-25 -AA - - - - -About this book -This book covers the ClojureScript programming language, serves as a detailed guide -of its tooling for development, and presents a series of articles about topics that -are applicable to day-to-day programming in ClojureScript. -It is not an introductory book to programming in that it assumes the reader has -experience programming in at least one language. However, it doesn’t assume -experience with Clojure or functional programming. We’ll try to include links to -reference material when talking about the theoretical underpinnings of ClojureScript -that may not be familiar to everyone. -Since the ClojureScript documentation is good but sparse, we wanted to write a -compendium of reference information and extensive examples to serve as a -ClojureScript primer as well as a series of practical how-to’s. This document will -evolve with the ClojureScript language, both as a reference of the language features -and as a sort of cookbook with practical programming recipes. -You’ll get the most out of this book if you: - - -are curious about ClojureScript or functional programming and have some programming -experience; - - -write JavaScript or any other language that compiles to it and want to know what -ClojureScript has to offer; - - -already know some Clojure and want to learn how ClojureScript differs from it, plus -practical topics like how to target both languages with the same code base. - - -Don’t be turned off if you don’t see yourself in any of the above groups. We -encourage you to give this book a try and to give us feedback on how we can make it -more accessible. Our goal is to make ClojureScript more friendly to newcomers and -spread the ideas about programming that Clojure has helped popularize, as we see a -lot of value in them. - - -Introduction -

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