Let’s Talk Functional Programming

Most of what I will discuss in this article is knowledge accumulated from reading, “Functional Programming in JavaScript”, by Luis Atencio. Let’s dig right in…

What is functional programming?

In simple terms, functional programming is a software development style that places a major emphasis on the use of functions. You might say, “Well, I already use functions daily, what’s the difference?” Well, it’s not a matter of just applying functions to come up with a result. The goal, rather, is to abstract control flows and operations on data with functions in order to avoid side effects and reduce mutation of state in your application.

#programming #javascript #functional #web-development #functional-programming

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Let’s Talk Functional Programming

Let’s Talk Functional Programming

Most of what I will discuss in this article is knowledge accumulated from reading, “Functional Programming in JavaScript”, by Luis Atencio. Let’s dig right in…

What is functional programming?

In simple terms, functional programming is a software development style that places a major emphasis on the use of functions. You might say, “Well, I already use functions daily, what’s the difference?” Well, it’s not a matter of just applying functions to come up with a result. The goal, rather, is to abstract control flows and operations on data with functions in order to avoid side effects and reduce mutation of state in your application.

#programming #javascript #functional #web-development #functional-programming

Angela  Dickens

Angela Dickens


Functional Programming

Functional Programming is a Declarative style of Programming Paradigm for writing computer programs.
But, What are Functions ?
Functions in general, applies computation on given input and returns the output. It relates input to an output.
f(x) = x + 2;
f(1) = 1 + 2 = 3;
f(2) = 2 + 2 = 4;
Above mentioned is a simple function that adds 2 to the input value and returns output. It relates value [1,2] => [3,4]. Similarly, a function in computer programming is a block of instruction that performs computation on given input and returns the output.
Functional Programming is such a style of writing computer programs using these tiny functions that works together and perform required computation.
Functions in Functional Programming
The philosophy of functional programming is to maintain certain characteristics while writing functions in a computer program. These characteristics are the fundamental nature of functional programming that describe what shall be the behaviour of a function. These are as follows :
A function must be declarative, it simply tells what to compute, without specifying how to compute it.
f(x) = x * 4; 👍
Declarative function that tells to multiply input by 4;
f(x) = { y = x + x; z = x + x; return y + z;} 👎
Non-Declarative function that specify how to multiply input by 4;
A function must give the same output for a given input value, at any period of time. It is not dependent upon anything outside the function definition.
f(x) = It’s never too late; 👍
Pure function that will always return It’s never too late
f(x) = If today’s Friday or Saturday then It’s never too late else It’s late. 👎
Impure function that consider day for returning value. The value is not predictable. It can change. So a function that performs anything which is unpredictable is not a pure function. The condition or the execution is dynamic or unfixed in an impure function.

#development #functional-programming #software #software-programming #declarative-programming #function

Are functions from programming really functions?

If you are reading this, then most probably you already know quite well what functions are in programming. A function is quite a common and spread programming construct that is present in almost all programming languages.

Generally, a function is a block of code that takes some parameters from outside, executes some operations in which these parameters may be used, then it returns an output value. Actually, in many programming languages functions are allowed to not return something or to return multiple values, not only one. But these cases can be also be represented, for the sake of generality, as only one value. For the “no return” case we can use a special value to represent that (in Python that special value is None; whenever you don’t return something from a function it’s returned None). And for the case of more values, we can use a vector of multiple values as a single object.

For example, in Python a function definition looks like this:

def func_name(param1, param2, ...):

    ## do some stuff with input parameters
    return output_value

Now, the question I want to ask: Are these functions from programming true mathematical functions?

Well…, let’s first recall what a mathematical function is.

In mathematics, a function is just a mapping from a set A to a set B, in which any element from A has only one associated element in B.

#python #programming #function #mathematics #functional-programming

Rust  Language

Rust Language


Std Library Types in Rust - The Rust Programming Language

Std Library Types - Rust By Example

The std library provides many custom types which expands drastically on the primitives. Some of these include:

  • growable Strings like: "hello world"
  • growable vectors: [1, 2, 3]
  • optional types: Option<i32>
  • error handling types: Result<i32, i32>
  • heap allocated pointers: Box<i32>

Box, stack and heap

All values in Rust are stack allocated by default. Values can be boxed (allocated on the heap) by creating a Box<T>. A box is a smart pointer to a heap allocated value of type T. When a box goes out of scope, its destructor is called, the inner object is destroyed, and the memory on the heap is freed.

Boxed values can be dereferenced using the * operator; this removes one layer of indirection.

use std::mem;

#[derive(Debug, Clone, Copy)]
struct Point {
    x: f64,
    y: f64,

// A Rectangle can be specified by where its top left and bottom right 
// corners are in space
struct Rectangle {
    top_left: Point,
    bottom_right: Point,

fn origin() -> Point {
    Point { x: 0.0, y: 0.0 }

fn boxed_origin() -> Box<Point> {
    // Allocate this point on the heap, and return a pointer to it
    Box::new(Point { x: 0.0, y: 0.0 })

fn main() {
    // (all the type annotations are superfluous)
    // Stack allocated variables
    let point: Point = origin();
    let rectangle: Rectangle = Rectangle {
        top_left: origin(),
        bottom_right: Point { x: 3.0, y: -4.0 }

    // Heap allocated rectangle
    let boxed_rectangle: Box<Rectangle> = Box::new(Rectangle {
        top_left: origin(),
        bottom_right: Point { x: 3.0, y: -4.0 },

    // The output of functions can be boxed
    let boxed_point: Box<Point> = Box::new(origin());

    // Double indirection
    let box_in_a_box: Box<Box<Point>> = Box::new(boxed_origin());

    println!("Point occupies {} bytes on the stack",
    println!("Rectangle occupies {} bytes on the stack",

    // box size == pointer size
    println!("Boxed point occupies {} bytes on the stack",
    println!("Boxed rectangle occupies {} bytes on the stack",
    println!("Boxed box occupies {} bytes on the stack",

    // Copy the data contained in `boxed_point` into `unboxed_point`
    let unboxed_point: Point = *boxed_point;
    println!("Unboxed point occupies {} bytes on the stack",


Vectors are re-sizable arrays. Like slices, their size is not known at compile time, but they can grow or shrink at any time. A vector is represented using 3 parameters:

  • pointer to the data
  • length
  • capacity

The capacity indicates how much memory is reserved for the vector. The vector can grow as long as the length is smaller than the capacity. When this threshold needs to be surpassed, the vector is reallocated with a larger capacity.

fn main() {
    // Iterators can be collected into vectors
    let collected_iterator: Vec<i32> = (0..10).collect();
    println!("Collected (0..10) into: {:?}", collected_iterator);

    // The `vec!` macro can be used to initialize a vector
    let mut xs = vec![1i32, 2, 3];
    println!("Initial vector: {:?}", xs);

    // Insert new element at the end of the vector
    println!("Push 4 into the vector");
    println!("Vector: {:?}", xs);

    // Error! Immutable vectors can't grow
    // FIXME ^ Comment out this line

    // The `len` method yields the number of elements currently stored in a vector
    println!("Vector length: {}", xs.len());

    // Indexing is done using the square brackets (indexing starts at 0)
    println!("Second element: {}", xs[1]);

    // `pop` removes the last element from the vector and returns it
    println!("Pop last element: {:?}", xs.pop());

    // Out of bounds indexing yields a panic
    println!("Fourth element: {}", xs[3]);
    // FIXME ^ Comment out this line

    // `Vector`s can be easily iterated over
    println!("Contents of xs:");
    for x in xs.iter() {
        println!("> {}", x);

    // A `Vector` can also be iterated over while the iteration
    // count is enumerated in a separate variable (`i`)
    for (i, x) in xs.iter().enumerate() {
        println!("In position {} we have value {}", i, x);

    // Thanks to `iter_mut`, mutable `Vector`s can also be iterated
    // over in a way that allows modifying each value
    for x in xs.iter_mut() {
        *x *= 3;
    println!("Updated vector: {:?}", xs);

More Vec methods can be found under the std::vec module


There are two types of strings in Rust: String and &str.

A String is stored as a vector of bytes (Vec<u8>), but guaranteed to always be a valid UTF-8 sequence. String is heap allocated, growable and not null terminated.

&str is a slice (&[u8]) that always points to a valid UTF-8 sequence, and can be used to view into a String, just like &[T] is a view into Vec<T>.

fn main() {
    // (all the type annotations are superfluous)
    // A reference to a string allocated in read only memory
    let pangram: &'static str = "the quick brown fox jumps over the lazy dog";
    println!("Pangram: {}", pangram);

    // Iterate over words in reverse, no new string is allocated
    println!("Words in reverse");
    for word in pangram.split_whitespace().rev() {
        println!("> {}", word);

    // Copy chars into a vector, sort and remove duplicates
    let mut chars: Vec<char> = pangram.chars().collect();

    // Create an empty and growable `String`
    let mut string = String::new();
    for c in chars {
        // Insert a char at the end of string
        // Insert a string at the end of string
        string.push_str(", ");

    // The trimmed string is a slice to the original string, hence no new
    // allocation is performed
    let chars_to_trim: &[char] = &[' ', ','];
    let trimmed_str: &str = string.trim_matches(chars_to_trim);
    println!("Used characters: {}", trimmed_str);

    // Heap allocate a string
    let alice = String::from("I like dogs");
    // Allocate new memory and store the modified string there
    let bob: String = alice.replace("dog", "cat");

    println!("Alice says: {}", alice);
    println!("Bob says: {}", bob);

More str/String methods can be found under the std::str and std::string modules

Literals and escapes

There are multiple ways to write string literals with special characters in them. All result in a similar &str so it's best to use the form that is the most convenient to write. Similarly there are multiple ways to write byte string literals, which all result in &[u8; N].

Generally special characters are escaped with a backslash character: \. This way you can add any character to your string, even unprintable ones and ones that you don't know how to type. If you want a literal backslash, escape it with another one: \\

String or character literal delimiters occuring within a literal must be escaped: "\"", '\''.

fn main() {
    // You can use escapes to write bytes by their hexadecimal values...
    let byte_escape = "I'm writing \x52\x75\x73\x74!";
    println!("What are you doing\x3F (\\x3F means ?) {}", byte_escape);

    // ...or Unicode code points.
    let unicode_codepoint = "\u{211D}";
    let character_name = "\"DOUBLE-STRUCK CAPITAL R\"";

    println!("Unicode character {} (U+211D) is called {}",
                unicode_codepoint, character_name );

    let long_string = "String literals
                        can span multiple lines.
                        The linebreak and indentation here ->\
                        <- can be escaped too!";
    println!("{}", long_string);

Sometimes there are just too many characters that need to be escaped or it's just much more convenient to write a string out as-is. This is where raw string literals come into play.

fn main() {
    let raw_str = r"Escapes don't work here: \x3F \u{211D}";
    println!("{}", raw_str);

    // If you need quotes in a raw string, add a pair of #s
    let quotes = r#"And then I said: "There is no escape!""#;
    println!("{}", quotes);

    // If you need "# in your string, just use more #s in the delimiter.
    // There is no limit for the number of #s you can use.
    let longer_delimiter = r###"A string with "# in it. And even "##!"###;
    println!("{}", longer_delimiter);

Want a string that's not UTF-8? (Remember, str and String must be valid UTF-8). Or maybe you want an array of bytes that's mostly text? Byte strings to the rescue!

use std::str;

fn main() {
    // Note that this is not actually a `&str`
    let bytestring: &[u8; 21] = b"this is a byte string";

    // Byte arrays don't have the `Display` trait, so printing them is a bit limited
    println!("A byte string: {:?}", bytestring);

    // Byte strings can have byte escapes...
    let escaped = b"\x52\x75\x73\x74 as bytes";
    // ...but no unicode escapes
    // let escaped = b"\u{211D} is not allowed";
    println!("Some escaped bytes: {:?}", escaped);

    // Raw byte strings work just like raw strings
    let raw_bytestring = br"\u{211D} is not escaped here";
    println!("{:?}", raw_bytestring);

    // Converting a byte array to `str` can fail
    if let Ok(my_str) = str::from_utf8(raw_bytestring) {
        println!("And the same as text: '{}'", my_str);

    let _quotes = br#"You can also use "fancier" formatting, \
                    like with normal raw strings"#;

    // Byte strings don't have to be UTF-8
    let shift_jis = b"\x82\xe6\x82\xa8\x82\xb1\x82\xbb"; // "ようこそ" in SHIFT-JIS

    // But then they can't always be converted to `str`
    match str::from_utf8(shift_jis) {
        Ok(my_str) => println!("Conversion successful: '{}'", my_str),
        Err(e) => println!("Conversion failed: {:?}", e),

For conversions between character encodings check out the encoding crate.

A more detailed listing of the ways to write string literals and escape characters is given in the 'Tokens' chapter of the Rust Reference.


Sometimes it's desirable to catch the failure of some parts of a program instead of calling panic!; this can be accomplished using the Option enum.

The Option<T> enum has two variants:

  • None, to indicate failure or lack of value, and
  • Some(value), a tuple struct that wraps a value with type T.
// An integer division that doesn't `panic!`
fn checked_division(dividend: i32, divisor: i32) -> Option<i32> {
    if divisor == 0 {
        // Failure is represented as the `None` variant
    } else {
        // Result is wrapped in a `Some` variant
        Some(dividend / divisor)

// This function handles a division that may not succeed
fn try_division(dividend: i32, divisor: i32) {
    // `Option` values can be pattern matched, just like other enums
    match checked_division(dividend, divisor) {
        None => println!("{} / {} failed!", dividend, divisor),
        Some(quotient) => {
            println!("{} / {} = {}", dividend, divisor, quotient)

fn main() {
    try_division(4, 2);
    try_division(1, 0);

    // Binding `None` to a variable needs to be type annotated
    let none: Option<i32> = None;
    let _equivalent_none = None::<i32>;

    let optional_float = Some(0f32);

    // Unwrapping a `Some` variant will extract the value wrapped.
    println!("{:?} unwraps to {:?}", optional_float, optional_float.unwrap());

    // Unwrapping a `None` variant will `panic!`
    println!("{:?} unwraps to {:?}", none, none.unwrap());


We've seen that the Option enum can be used as a return value from functions that may fail, where None can be returned to indicate failure. However, sometimes it is important to express why an operation failed. To do this we have the Result enum.

The Result<T, E> enum has two variants:

  • Ok(value) which indicates that the operation succeeded, and wraps the value returned by the operation. (value has type T)
  • Err(why), which indicates that the operation failed, and wraps why, which (hopefully) explains the cause of the failure. (why has type E)
mod checked {
    // Mathematical "errors" we want to catch
    pub enum MathError {

    pub type MathResult = Result<f64, MathError>;

    pub fn div(x: f64, y: f64) -> MathResult {
        if y == 0.0 {
            // This operation would `fail`, instead let's return the reason of
            // the failure wrapped in `Err`
        } else {
            // This operation is valid, return the result wrapped in `Ok`
            Ok(x / y)

    pub fn sqrt(x: f64) -> MathResult {
        if x < 0.0 {
        } else {

    pub fn ln(x: f64) -> MathResult {
        if x <= 0.0 {
        } else {

// `op(x, y)` === `sqrt(ln(x / y))`
fn op(x: f64, y: f64) -> f64 {
    // This is a three level match pyramid!
    match checked::div(x, y) {
        Err(why) => panic!("{:?}", why),
        Ok(ratio) => match checked::ln(ratio) {
            Err(why) => panic!("{:?}", why),
            Ok(ln) => match checked::sqrt(ln) {
                Err(why) => panic!("{:?}", why),
                Ok(sqrt) => sqrt,

fn main() {
    // Will this fail?
    println!("{}", op(1.0, 10.0));


Chaining results using match can get pretty untidy; luckily, the ? operator can be used to make things pretty again. ? is used at the end of an expression returning a Result, and is equivalent to a match expression, where the Err(err) branch expands to an early Err(From::from(err)), and the Ok(ok) branch expands to an ok expression.

mod checked {
    enum MathError {

    type MathResult = Result<f64, MathError>;

    fn div(x: f64, y: f64) -> MathResult {
        if y == 0.0 {
        } else {
            Ok(x / y)

    fn sqrt(x: f64) -> MathResult {
        if x < 0.0 {
        } else {

    fn ln(x: f64) -> MathResult {
        if x <= 0.0 {
        } else {

    // Intermediate function
    fn op_(x: f64, y: f64) -> MathResult {
        // if `div` "fails", then `DivisionByZero` will be `return`ed
        let ratio = div(x, y)?;

        // if `ln` "fails", then `NonPositiveLogarithm` will be `return`ed
        let ln = ln(ratio)?;


    pub fn op(x: f64, y: f64) {
        match op_(x, y) {
            Err(why) => panic!("{}", match why {
                    => "logarithm of non-positive number",
                    => "division by zero",
                    => "square root of negative number",
            Ok(value) => println!("{}", value),

fn main() {
    checked::op(1.0, 10.0);

Be sure to check the documentation, as there are many methods to map/compose Result.


The panic! macro can be used to generate a panic and start unwinding its stack. While unwinding, the runtime will take care of freeing all the resources owned by the thread by calling the destructor of all its objects.

Since we are dealing with programs with only one thread, panic! will cause the program to report the panic message and exit.

// Re-implementation of integer division (/)
fn division(dividend: i32, divisor: i32) -> i32 {
    if divisor == 0 {
        // Division by zero triggers a panic
        panic!("division by zero");
    } else {
        dividend / divisor

// The `main` task
fn main() {
    // Heap allocated integer
    let _x = Box::new(0i32);

    // This operation will trigger a task failure
    division(3, 0);

    println!("This point won't be reached!");

    // `_x` should get destroyed at this point

Let's check that panic! doesn't leak memory.

$ rustc panic.rs && valgrind ./panic
==4401== Memcheck, a memory error detector
==4401== Copyright (C) 2002-2013, and GNU GPL'd, by Julian Seward et al.
==4401== Using Valgrind-3.10.0.SVN and LibVEX; rerun with -h for copyright info
==4401== Command: ./panic
thread '<main>' panicked at 'division by zero', panic.rs:5
==4401== HEAP SUMMARY:
==4401==     in use at exit: 0 bytes in 0 blocks
==4401==   total heap usage: 18 allocs, 18 frees, 1,648 bytes allocated
==4401== All heap blocks were freed -- no leaks are possible
==4401== For counts of detected and suppressed errors, rerun with: -v
==4401== ERROR SUMMARY: 0 errors from 0 contexts (suppressed: 0 from 0)


Where vectors store values by an integer index, HashMaps store values by key. HashMap keys can be booleans, integers, strings, or any other type that implements the Eq and Hash traits. More on this in the next section.

Like vectors, HashMaps are growable, but HashMaps can also shrink themselves when they have excess space. You can create a HashMap with a certain starting capacity using HashMap::with_capacity(uint), or use HashMap::new() to get a HashMap with a default initial capacity (recommended).

use std::collections::HashMap;

fn call(number: &str) -> &str {
    match number {
        "798-1364" => "We're sorry, the call cannot be completed as dialed. 
            Please hang up and try again.",
        "645-7689" => "Hello, this is Mr. Awesome's Pizza. My name is Fred.
            What can I get for you today?",
        _ => "Hi! Who is this again?"

fn main() { 
    let mut contacts = HashMap::new();

    contacts.insert("Daniel", "798-1364");
    contacts.insert("Ashley", "645-7689");
    contacts.insert("Katie", "435-8291");
    contacts.insert("Robert", "956-1745");

    // Takes a reference and returns Option<&V>
    match contacts.get(&"Daniel") {
        Some(&number) => println!("Calling Daniel: {}", call(number)),
        _ => println!("Don't have Daniel's number."),

    // `HashMap::insert()` returns `None`
    // if the inserted value is new, `Some(value)` otherwise
    contacts.insert("Daniel", "164-6743");

    match contacts.get(&"Ashley") {
        Some(&number) => println!("Calling Ashley: {}", call(number)),
        _ => println!("Don't have Ashley's number."),


    // `HashMap::iter()` returns an iterator that yields 
    // (&'a key, &'a value) pairs in arbitrary order.
    for (contact, &number) in contacts.iter() {
        println!("Calling {}: {}", contact, call(number)); 

For more information on how hashing and hash maps (sometimes called hash tables) work, have a look at Hash Table Wikipedia

Alternate/custom key types

Any type that implements the Eq and Hash traits can be a key in HashMap. This includes:

  • bool (though not very useful since there is only two possible keys)
  • int, uint, and all variations thereof
  • String and &str (protip: you can have a HashMap keyed by String and call .get() with an &str)

Note that f32 and f64 do not implement Hash, likely because floating-point precision errors would make using them as hashmap keys horribly error-prone.

All collection classes implement Eq and Hash if their contained type also respectively implements Eq and Hash. For example, Vec<T> will implement Hash if T implements Hash.

You can easily implement Eq and Hash for a custom type with just one line: #[derive(PartialEq, Eq, Hash)]

The compiler will do the rest. If you want more control over the details, you can implement Eq and/or Hash yourself. This guide will not cover the specifics of implementing Hash.

To play around with using a struct in HashMap, let's try making a very simple user logon system:

use std::collections::HashMap;

// Eq requires that you derive PartialEq on the type.
#[derive(PartialEq, Eq, Hash)]
struct Account<'a>{
    username: &'a str,
    password: &'a str,

struct AccountInfo<'a>{
    name: &'a str,
    email: &'a str,

type Accounts<'a> = HashMap<Account<'a>, AccountInfo<'a>>;

fn try_logon<'a>(accounts: &Accounts<'a>,
        username: &'a str, password: &'a str){
    println!("Username: {}", username);
    println!("Password: {}", password);
    println!("Attempting logon...");

    let logon = Account {

    match accounts.get(&logon) {
        Some(account_info) => {
            println!("Successful logon!");
            println!("Name: {}", account_info.name);
            println!("Email: {}", account_info.email);
        _ => println!("Login failed!"),

fn main(){
    let mut accounts: Accounts = HashMap::new();

    let account = Account {
        username: "j.everyman",
        password: "password123",

    let account_info = AccountInfo {
        name: "John Everyman",
        email: "j.everyman@email.com",

    accounts.insert(account, account_info);

    try_logon(&accounts, "j.everyman", "psasword123");

    try_logon(&accounts, "j.everyman", "password123");


Consider a HashSet as a HashMap where we just care about the keys ( HashSet<T> is, in actuality, just a wrapper around HashMap<T, ()>).

"What's the point of that?" you ask. "I could just store the keys in a Vec."

A HashSet's unique feature is that it is guaranteed to not have duplicate elements. That's the contract that any set collection fulfills. HashSet is just one implementation. (see also: BTreeSet)

If you insert a value that is already present in the HashSet, (i.e. the new value is equal to the existing and they both have the same hash), then the new value will replace the old.

This is great for when you never want more than one of something, or when you want to know if you've already got something.

But sets can do more than that.

Sets have 4 primary operations (all of the following calls return an iterator):

union: get all the unique elements in both sets.

difference: get all the elements that are in the first set but not the second.

intersection: get all the elements that are only in both sets.

symmetric_difference: get all the elements that are in one set or the other, but not both.

Try all of these in the following example:

use std::collections::HashSet;

fn main() {
    let mut a: HashSet<i32> = vec![1i32, 2, 3].into_iter().collect();
    let mut b: HashSet<i32> = vec![2i32, 3, 4].into_iter().collect();


    // `HashSet::insert()` returns false if
    // there was a value already present.
    assert!(b.insert(4), "Value 4 is already in set B!");
    // FIXME ^ Comment out this line


    // If a collection's element type implements `Debug`,
    // then the collection implements `Debug`.
    // It usually prints its elements in the format `[elem1, elem2, ...]`
    println!("A: {:?}", a);
    println!("B: {:?}", b);

    // Print [1, 2, 3, 4, 5] in arbitrary order
    println!("Union: {:?}", a.union(&b).collect::<Vec<&i32>>());

    // This should print [1]
    println!("Difference: {:?}", a.difference(&b).collect::<Vec<&i32>>());

    // Print [2, 3, 4] in arbitrary order.
    println!("Intersection: {:?}", a.intersection(&b).collect::<Vec<&i32>>());

    // Print [1, 5]
    println!("Symmetric Difference: {:?}",

(Examples are adapted from the documentation.)


When multiple ownership is needed, Rc(Reference Counting) can be used. Rc keeps track of the number of the references which means the number of owners of the value wrapped inside an Rc.

Reference count of an Rc increases by 1 whenever an Rc is cloned, and decreases by 1 whenever one cloned Rc is dropped out of the scope. When an Rc's reference count becomes zero, which means there are no owners remained, both the Rc and the value are all dropped.

Cloning an Rc never performs a deep copy. Cloning creates just another pointer to the wrapped value, and increments the count.

use std::rc::Rc;

fn main() {
    let rc_examples = "Rc examples".to_string();
        println!("--- rc_a is created ---");
        let rc_a: Rc<String> = Rc::new(rc_examples);
        println!("Reference Count of rc_a: {}", Rc::strong_count(&rc_a));
            println!("--- rc_a is cloned to rc_b ---");
            let rc_b: Rc<String> = Rc::clone(&rc_a);
            println!("Reference Count of rc_b: {}", Rc::strong_count(&rc_b));
            println!("Reference Count of rc_a: {}", Rc::strong_count(&rc_a));
            // Two `Rc`s are equal if their inner values are equal
            println!("rc_a and rc_b are equal: {}", rc_a.eq(&rc_b));
            // We can use methods of a value directly
            println!("Length of the value inside rc_a: {}", rc_a.len());
            println!("Value of rc_b: {}", rc_b);
            println!("--- rc_b is dropped out of scope ---");
        println!("Reference Count of rc_a: {}", Rc::strong_count(&rc_a));
        println!("--- rc_a is dropped out of scope ---");
    // Error! `rc_examples` already moved into `rc_a`
    // And when `rc_a` is dropped, `rc_examples` is dropped together
    // println!("rc_examples: {}", rc_examples);
    // TODO ^ Try uncommenting this line


When shared ownership between threads is needed, Arc(Atomic Reference Counted) can be used. This struct, via the Clone implementation can create a reference pointer for the location of a value in the memory heap while increasing the reference counter. As it shares ownership between threads, when the last reference pointer to a value is out of scope, the variable is dropped.

fn main() {
use std::sync::Arc;
use std::thread;

// This variable declaration is where its value is specified.
let apple = Arc::new("the same apple");

for _ in 0..10 {
    // Here there is no value specification as it is a pointer to a reference
    // in the memory heap.
    let apple = Arc::clone(&apple);

    thread::spawn(move || {
        // As Arc was used, threads can be spawned using the value allocated
        // in the Arc variable pointer's location.
        println!("{:?}", apple);

Original article source at https://doc.rust-lang.org

#rust #programming #developer 

Tia  Gottlieb

Tia Gottlieb


Functional Programming Series (2): What Is a Monoid?

For those interested in functional programming, I’ll talk about monoids and why they’re very important to understand ahead of time.

Don’t get confused: This isn’t monad — it’s monoid. I’m pretty sure you already know of monoids and you use them almost every day — you just didn’t know the term for them.

Prior to Reading

This is a series on functional programming, so you might not understand what this article is going to talk about if you haven’t read the previous posts.

You can check out other posts related to this topic

Identity Function

Let’s assume there’s a function named identity that takes A and returns A.

const identity: <A>(a: A): A => a;

interface Student {
  name: string;
  age: number;
identity<number>(3) // 3
identity<string>('hello') // hello
  name: 'Bincent',
  age: 5
}); // { name: 'Bincent', age: 5 }

In functional programming, this useless function (seems useless) is an important factor for many other concepts (such as monoids) that we’re about to talk about.

Image for post

Basically, a monoid is a set of elements that holds the rules of the semigroup and the identity-element rule.

If S is a set of elements, a is a member of S, and · is a proper binary operation, a·e = e·a ∈ S must be satisfied to be a monoid.

Identity: a ∈ S, a·e = e·a = a ∈ S

Some documentation calls this using the number 1 and the any alphabet in subscript — for example, 1x referring to the identity on the variable x. Or some documentation uses just a single alphabet letter, such as or e.

That’s all there is to know about monoids, let’s practice with some simple examples.

#typescript #programming #functional-programming #javascript #coding #function