Getting Started with Functional Programming in Clojure (Japanese Edition)

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Contents

  1. Hello stranger!
  2. Functional Programming in C#: Purity and Concurrency
  3. Clojure - Functional Programming

The REPL prompt will show logic-tutorial. Unlike most programming systems, with relational programming we can actually ask the computer questions. But before we ask the computer questions, we need define some facts! The first thing we want the computer to know about is that there are men:.

Now we can ask who are men. By convention we'll declare a logic variable q and ask the computer to give use the possible values for q. Here's an example. We're asking the computer to give us at least one answer to the question - "Who is a man? We can ask for more than one answer:. The same result. It can't give results for things it doesn't know about.

Let's define another kind of relationship and a fact:. There's a couple of new things going on here. This means we want all the answers the computer can find.


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The question itself is formulated differently than before because we're asking who is a man and is fun. Enter in the following:. We have now switched to a more generic name for the database of 'facts', which we will expand with facts about different relations. Relations don't have to be about a single entity. We can define relationship between things! Hmm that doesn't work. This is because we never actually said who Mary liked , only that Bob liked Mary. Try the following:. Wow that's a lot of new information. The fresh expression isn't something we've seen before.

Why do we need it? By convention run returns single values for q which answer the question. In this case we want to know who likes who. This means we need to create logic variables to store these values in. We then assign both these values to q by putting them in a Clojure vector which is like an array in other programming languages.

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Here we only want the list of people who like each other. Note that the order of how we pose our question doesn't matter:. We've actually predefined some interesting relations in the tut1 file that we'll try out first before we take a closer look:. We can define relations in terms of other relations!


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Composition to the rescue. But how does this work exactly? Let's take a moment to look at what's in the file. At the top of the file after the namespace declaration you'll see that some relations have been defined:. We can define relations as functions! Play around with defining some new facts and using these relations to pose questions about these facts. What is list comprehension? First of all, let's look at an example. In short, list comprehension is a way to create a list from existing lists.

Hello stranger!

The idea of list comprehension comes from the world of math. It's used in order to write sets in simpler and easier way. So if x is the set of -1, 1, and 2, then the notation refers to the set of 1 and 2 but not It's useful to create a combination of all elements in given collections. Function is recursive when the function calls itself inside it's definition. This is the most simple way of doing recursion.

We will start from the example of fibo-recursive function that computes Nth Fibonacci number in the Fibonacci sequence because writing function that computes the Fibonacci numbers is a recursive programming version of hello world. The Fibonacci sequence is consisted of numbers characterized by the fact that every number after the first two is the sum of the two preceding ones.

As you can see, we are calling fibo-recursive function inside the function body of fibo-recursive function. Calling the function inside the function body is the most basic way to do recursive programming in Clojure and many other programming languages. The simple recursion, calling itself inside it's definition, is not the only way to make recursive function in Clojure. We can write a Fibonacci function by using recur as well.

Here is another example of the use of recur. It will keep calling count-down function with updated arguments until n becomes 0.

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Why do we have recur when you can write a recursive function with the simple recursion like we do in fibo-recursive? One of the most important reasons is the performance optimization. You cannot compute large Fibonacci number with fibo-recursive. When you try to do that, you will get StackOverflowError. This is because, with simple recursion, each recursive call creates a stack frame which is a data to store the information of the called function on memory. Doing deep recursion requires large memory for stack frames, but since it cannot, we get StackOverflowError.

Although we don't go deeply into details, one of techniques to avoid this problem is making your function tail recursive. A function is tail recursive when the recursion is happening at the end of it's definition. In other words, a tail recursive function must return itself as it's returned value. When you use recur , it makes sure you are doing tail recursion. In fact, you will get an error when you try to call recur not at the end of a function. Because recur does tail recursion, you don't get StackOverflowError with big Fibonacci number although it takes very long time to compute.

No, Clojure doesn't provide a way to write an imperative loop because there is no mutable local variable in Clojure. However, you can use loop to write code that works like an imperative loop. Hopefully, this code looks similar to a simple counting loop in non-functional programming languages you've had experienced with before.

In this example, recur increments count at the end of each loop and loop uses it in the next loop. A recursion point is a function entry point that recur can go back to do recursion. However, recur doesn't necessary need loop to do it's job as long as a recursion point is provided. You can rewrite count-up function without loop.

In count-up-no-loop , the recursion point for recur is the function itself. Note that recur takes two arguments now. This is because the number of arguments of recur must match that of it's recursion point function. All imperative loops can be converted to recursions and all recursions can be converted to loops, so Clojure chose recursions.

Clojure's Macros gives you the power to restructure your Clojure code as you like. For example, you can create your own code syntax, invent new control flow, new types of values, etc. To define a macro, use defmacro. Like function, you can give it a name, docs, and arguments. Note that you are using quotes ' followed by if and not.

This is because you don't want them to be evaluated when you define the macro. Macros are replaced with Clojure code before it's evaluated. To see how it will be replaced without actually evaluating the macro, use macroexpand. Note that you have to use ' because you want it to be unevaluated list.

However, when an expression is surrounded by quote , it does not evaluate the expression but returns the expression itself. It does the exactly same thing with quote. You can see quoting at work in macros. In this unless macro, you need to use ' followed by if and not because you don't want them to be evaluated inside the macro definition. You need to quote clojure. This is because resolving symbol is the default treatment but clojure. However, you see the difference from quoting when the expression contains symbols.

Unlike quoting, syntax-quoting returns the fully qualified namespace. Using fully qualified namespace is very important in order to avoid name conflicts when defining macro. Threading Macros are macros that helps you to write nested forms in a cleaner and more readable way. Despite it's name, threading macros are nothing to do with threads in the parallel computing. It's first because it's passing down the evaluation of former forms to the first argument of preceding forms.

Suppose if you want to start from an empty vector and adding numbers to the vector one by one. Here is nested version of the code. As you add more numbers, the nesting gets deeper and makes your code harder to read. The thread-first macro solves this nesting problem. The first argument is the initial value that you want to start from. After the first argument is evaluated, it is then passed to the first argument of conj 1. This is equivalent to conj [] 1. The evaluated value is then passed to to the first argument of conj 2.

This is equivalent to conj [1] 2. Finally, we are evaluating conj [1 2] 3 which returns [1 2 3]. It's last because it's passing down the evaluation of former forms to the last argument of preceding forms. This code converts country names to upper case and say hello to the countries. The vector of country names are passed to the last argument of the first map which is equivalent to map clojure. This is the example of immediately evaluating an expression. Nothing special is involved here.

When you use delay , the expression is not evaluated immediately, so "Adding" is not printed.

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Functional Programming in C#: Purity and Concurrency

You can achieve the same thing by using an anonymous function and def. Then, why do we get bothered with delay? The difference from a plain function is that delay is only evaluated once and caches the result. This is very obvious because these lines of the code are executed synchronously. If you use future , println "hello" is evaluated immediately, and after three seconds, println "after sleep" will be evaluated. This is because Clojure puts the expression grouped by future into another thread and moves the current thread forward.

Calls inside future still blocks. So, in this case, "after sleep" is printed after 3 secs. This returned value is the current state of the future, not the returned value of inc 1. To obtain the returned value of inc 1 , you need to dereference the future with deref. You can tell deref how long you want to wait along with a value to return if it does time out. Finally, you can do a useful thing by combining future and deref. You can run multiple time consuming tasks in different threads and block until they finish. When you want to defer the evaluation of expressions until you obtain values to pass to them, use promise.

The easiest example why you want to use promise is implementing a callback. Creating a listener that listens to the promise and fire the callback when a value is delivered to the promise. Just like future, promise will block when you dereference it. Now let's start the listener and wait for the time consuming job. After being blocked by the dereference of my-promise for 5 seconds, you will see the callback is fired. You've might hear this statement before: there is no state in Clojure. Thus, the language is impractical and cannot be used to build real applications.

However, this is not true. Clojure has built-in mechanisms to manage application state. Atom is one of the mechanisms. Use atom to create an atom that points to a value. You can create an atom of any values. You can set the value of an atom with reset! It is used when you are setting the value without regard for the current value, normally the first time you create the atom.

The function that you pass to swap! You can pass a function that takes multiple arguments. The first argument of the function is the current atom. Atoms are very similar to mutable variables in other programming languages. You can assign value to an atom and update anytime you want. However, Clojure's atom has one big advantage over them: it's thread safe.

This will update x ten times and increment x by 1 every time. The final value of x will be Similarly, this will update x ten times and increment x every time like the previous example. However, with this code, def x inc x will be executed in parallel on different threads because we are using future. When you do this, the final value of x will not be deterministic anymore. Sometimes it is 5, and sometimes 9 because each thread access and update the same x in its own timing.

Now atom comes to rescue. Unlike vars, atom is thread safe, so x will be updated by one thread at one time. Thus, the final value of x is guaranteed to be This is achieved thanks to the Clojure's use of compare-and-swap in atom. While Atom is handy to manage a state in a consistent way, Ref allows you to manage multiple states while ensuring they are consistent. The update of refs must be done inside dosync block. To set a ref to a new value, use ref-set. Any updates to refs always has to be done inside dosync in order to make transactional updates.

Otherwise, Clojure complains with No transaction running exception. Suppose we are trying to create an user record in database. Each alter tries to update user-record ref with user info and you want the ref to be updated only when both alter succeed. As you see, the user-record ref is still empty. This is because alter inside dosync doesn't update the ref until getting out of dosync block successfully. This is the atom version that doesn't work. As you see, user-record atom is half updated when there is the exception. The other way to see how transaction works is trying to observe the value of ref outside dosync block.

We use future to run the whole transaction in the separate thread and wait two seconds before exiting the dosync block. The value of the ref is still 0 at this moment because the update to the ref is still not committed.

Clojure - Functional Programming

One of the great traits of Clojure is that you can use Java code from your Clojure code. This trait is called Java interop. Although Clojure has very rich standard libraries, sometimes you cannot find libraries that you need to solve your problems. If the library exists in Java, you can borrow it from your Clojure code. There is also. Clojure doesn't provide an exponential calculation function in the standard library, so let's borrow pow method from Math class.

You can call Java's method just like Clojure's function. About the author Renzo Borgatti is a software engineer with more than 15 years of experience in the field. MEAP combo. Clojure combo added to cart. Your book will ship via to:. Commercial Address. MEAP eBook. Clojure eBook added to cart. Total: Don't refresh or navigate away from the page. Math for Programmers 3D graphics, machine learning, and simulations with Python. Paul Orland. Rust in Action. Tim McNamara. Clojure in Action, Second Edition. Amit Rathore and Francis Avila.

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