In this article, I'll focus on Rust. I'll use the last compiler version as of today:
rustc 1.34.1 (fc50f328b 2019-04-24)
I'll just cover some basic or more advanced features of Rust, but not as advanced as trait objects for example. You can reach my previous articles on Python an Ruby here:
Rust vectors can contain any number of elements (depending on memory) of the same type. Vectors are heap-allocated in Rust.
You can either use type inference or precise elements' type when declaring a variable holding a vector:
// Vec<T> is a built-in type. No need to import
// uninitialized vector of unsigned 64-bit integers
let v1: Vec<u64>;
// initialized empty vector of unsigned 64-bit integers
let v2: Vec<u64> = Vec::new();
// initialized vector of unsigned 64-bit integers. Uses the vec! built-in macro. Note the mut modifier because I'll that vector later on. Otherwise, variable is immutable.
let mut digits = vec![0u64,1,2,3,4,5,6,7,8,9];
// initialized vector of 10 unsigned 64-bit integers equal to 1
let all_1 = vec![1u64;10];
For sure, you can create a vector of vectors:
let binomial_coefficients = vec![
vec![1u16],
vec![1u16,1],
vec![1u16,2,1],
vec![1u16,3,3,1],
vec![1u16,4,6,4,1],
vec![1u16,5,10,10,5,1]
];
The number of elements of a vector is given by len() method:
// use of the assert_eq! macro which fails in case of error
assert_eq!(digits.len(), 10);
assert_eq!(binomial_coefficients.len(), 6);
You can store functions in a vector:
// in that case, you need to provide the type of vector elements
let mut trigo: Vec<fn(f64) -> f64> = vec![f64::sin, f64::cos, f64::tan];
// or store closures (a.k.a. lambdas)
let powers: Vec<fn(u64) -> u64> = vec![
|x: u64| x.pow(2),
|x: u64| x.pow(3),
|x: u64| x.pow(4),
];
Accessing elements
Accessing vector elements is business as usual:
// get first element reference
let first_binomial = &binomial_coefficients[0];
// need to clone if you really want a copy
let first_binomial_cloned = binomial_coefficients[0].clone();
// no negative indexes but you can implement the Index/IndexMut traits for your structs
use std::ops::Index;
struct BinomialCoefficient {
coeff: Vec<Vec<u16>>,
}
impl Index<isize> for BinomialCoefficient {
type Output = Vec<u16>;
fn index(&self, i: isize) -> &Vec<u16> {
if i >= 0 {
&self.coeff[i as usize]
}
else {
&self.coeff[self.coeff.len()-i.abs() as usize]
}
}
}
// Use clone to re-use the binomial_coefficients variable afterwards, otherwise it's moved and gone.
let my_binomials = BinomialCoefficient { coeff: binomial_coefficients.clone() };
assert_eq!(my_binomials[-1], vec![1u16,5,10,10,5,1]);
Sub-vectors are possible using index ranges:
let first3_binomials = &binomial_coefficients[0..3];
assert_eq!(first3_binomials.len(), 3);
let first4_binomials = &binomial_coefficients[0..=3];
assert_eq!(first4_binomials.len(), 4);
Note the difference between the open range .. and the closed one ..=.
Vector operations
- adding an element
digits.push(10);
assert_eq!(digits, vec![0,1,2,3,4,5,6,7,8,9,10]);
- deleting an element by index
digits.remove(10);
assert_eq!(digits, vec![0,1,2,3,4,5,6,7,8,9]);
- concatenating vectors
digits = vec![0,1,2,3,4];
digits.append(&mut vec![5,6]);
digits.append(&mut vec![7,8,9]);
assert_eq!(digits, vec![0,1,2,3,4,5,6,7,8,9]);
- testing element membership
// need to use the reference on element (&)
if digits.contains(&9) {
println!("9 is a digit ! Such a surprise ;-)");
}
Looping through a vector
Use the for-in construct, but depends on how you want to use the vector later on:
// use reference: digits is borrowed (in the ownership sense of Rust) and
// so is usable afterwards
for d in &digits {
println!("{}", d);
}
// use mutable reference: allows to modify elements
for d in &mut digits {
*d += 1u64;
println!("{}", d);
}
// beware: digits elements are modified due to the previous loop
assert_eq!(digits, vec![1,2,3,4,5,6,7,8,9,10]);
// digits ownership is moved due to the underlying construct implementation. digits is gone
for d in digits {
println!("{}", d);
}
but a more functional oriented way is to use the for_each method:
// reset digits
digits = vec![0u64,1,2,3,4,5,6,7,8,9];
// need to add the iter() because digits is not an iterator
// (i.e. doesn't implement the Iterator trait )
digits.iter().for_each( |d| println!("{}", d) );
To get the element index when looping, use the enumerate() method:
// enumerate() yields a tuple
digits.iter().enumerate().for_each( |(i,d)|
println!("{} is the {}-th digit", d, i)
);
More advanced usage
Some useful functions on vectors
// note the type specification (<u64>) for hint the compiler about type
assert_eq!(digits.iter().sum::<u64>(), 45);
// min & max return an Option<>, need to unwrap()
assert_eq!(digits.iter().max().unwrap(), &9);
assert_eq!(digits.iter().min().unwrap(), &0);
assert_eq!(Vec::<u64>::new().iter().min(), None);
// build lipsum vector using split() and collect()
// beware: str references are returned
let lipsum: Vec<&str> = "Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.".split(" ").collect();
assert_eq!(lipsum.iter().max_by_key(|w| w.len()).unwrap(), &"consectetur");
The zip() built-in vector method combines several vectors to create a resulting one, created by taking the i-th element of each source vector:
let a = vec![0,1,2,3];
let b = vec![4,5,6,7];
// collect() is used to create a vector from the iterator
let zipped: Vec<_> = a.iter().zip(b.iter()).collect();
assert_eq!(zipped, vec![(&0,&4), (&1,&5), (&2,&6), (&3,&7)]);
No vector comprehensions
In Rust as in Ruby, there's no clean syntax as list comprehensions in Python.
But similar to rust, higher order functions like map() or filter() come to the rescue. So you can achieve the same result:
// extract words ending with 't'
let end_with_t: Vec<_> = lipsum.iter().filter( |w| w.ends_with("t") ).collect();
assert_eq!(end_with_t, vec![&"sit", &"incididunt", &"ut", &"et"]);
// convert to uppercase
let upper: Vec<_> = lipsum.iter().map( |w| w.to_uppercase() ).collect();
assert_eq!(upper[0], "LOREM");
// get only words of length 5 (including commas)
let words5: Vec<_> = lipsum.iter().filter( |w| w.len() == 5 ).collect();
assert_eq!(words5, vec![&"Lorem", &"ipsum", &"dolor", &"amet,", &"elit,", &"magna"]);
// trigo is already declared earlier...
trigo = vec![f64::sin, f64::cos, f64::tan];
let values: Vec<_> = trigo.iter().map( |f| f(std::f64::consts::PI/4f64)).collect();
// cannot check exact equality for floats. Uses this trick
assert!(f64::abs(values[0] - f64::sqrt(2f64)/2f64) < 10E-6f64);
Using the collect() method on an iterable
Similar to the built-in list() function in Python or to_a in Ruby, Rust comes with the collect() function which creates a vector from an iterable:
// this creates a vector of a-z chars
let mut a_to_z: Vec<_> = "abcdefghijklmnopqrstuvwxyz".chars().collect();
assert_eq!(a_to_z.len(), 26);
// create digits and the first 100 even numbers. Note the closed range 0..=9 notation. No need to use *iter()* because a range is implements the Iterator trait
digits = (0..=9).collect();
digits = vec![0,1,2,3,4,5,6,7,8,9];
let even: Vec<_> = (0..100).step_by(2).collect();
assert_eq!(even.last().unwrap(), &98);
This also works for user defined iterators:
// Keep track of n-1 and n values
struct Fibonacci {
fib_n_1: u64,
fib_n: u64,
}
// Fibonacci sequence is well known
impl Fibonacci {
fn new() -> Fibonacci {
Fibonacci {
// use of max_value() to handle fib_0 and fib_1
fib_n_1: u64::max_value(),
fib_n: u64::max_value(),
}
}
}
// only implements Iterator and not IntoIterator
impl Iterator for Fibonacci {
type Item = u64;
fn next(&mut self) -> Option<Self::Item> {
let next_fib: u64;
// also handle fib_0
if self.fib_n_1 == u64::max_value() {
next_fib = 0;
self.fib_n_1 = 1;
}
// handle fib_1
else if self.fib_n == u64::max_value() {
next_fib = 1;
self.fib_n_1 = 0;
self.fib_n = 1;
}
else {
// Fibonacci sequence is well known
next_fib = self.fib_n + self.fib_n_1;
self.fib_n_1 = self.fib_n;
self.fib_n = next_fib;
}
Some(next_fib)
}
}
let fibo = Fibonacci::new();
// use take() adapter because the iterator is infinite
let first_values: Vec<_> = fibo.take(11).collect();
assert_eq!(first_values, vec![0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55]);
Acting on vectors
Using functional programming built-in functions, you can extract values from a vector, or get another vector from the source one.
map() or collect()
Using the map() built-in function, it's possible to get an image of a mapping on the vector. If you consider a vector as a mathematical set of elements, map() gives the image set through the considered function.
a_to_z = "abcdefghijklmnopqrstuvwxyz".chars().collect();
let A_to_Z: Vec<_> = a_to_z.iter().map( |c| c.to_uppercase() ).collect();
// map() uses a block which can be more advanced
let greek = vec!['α', 'β', 'γ', 'δ', 'ε', 'ζ', 'η', 'θ', 'ι', 'κ', 'λ', 'μ', 'ν', 'ξ', 'ο', 'π', 'ρ', 'σ', 'τ', 'υ', 'φ', 'χ', 'ψ', 'ω'];
let translated: Vec<_> = greek.iter().map( |g|
match g {
'α' => 'A',
'β' => 'B',
'γ' => 'C',
// and so on
_ => 'X',
}
).collect();
assert_eq!(&translated[0..4], &['A', 'B', 'C', 'X']);
Of course, the map function to pass as the first argument could be any function, and any closure having one argument is possible:
digits = (0..=9).collect();
let tenths: Vec<_> = digits.iter().map( |x| x*10 ).collect();
assert_eq!(tenths, vec![0, 10, 20, 30, 40, 50, 60, 70, 80, 90]);
or even a user-defined function:
// contrived example
fn square(x: u64) -> u64 {
x*x
}
// calculate the first 9 perfect squares
let squares: Vec<_> = digits.iter().map( |x| square(*x) ).collect();
assert_eq!(squares, vec![0, 1, 4, 9, 16, 25, 36, 49, 64, 81]);
- filter()
This built-in function is used to sieve elements from a vector, using some criteria. Elements kept are those where the function given as argument to filter() returns true.
// extract even numbers
let even: Vec<_> = digits.iter().filter( |n| *n%2 == 0 ).collect();
assert_eq!(even, vec![&0, &2, &4, &6, &8]);
// extract words less than 4 chars
let words4: Vec<_> = lipsum.iter().filter( |w| w.len() < 4 ).collect();
assert_eq!(words4, vec![&"sit", &"sed", &"do", &"ut", &"et"]);
- fold()
Refer to my previous article on Python's reduce() or Ruby's inject() methods to get some details on the fold() function.
Examples:
// sum of first 10 digits
assert_eq!(digits.iter().fold(0, |x, y| x + y), 45);
fn nested(coeff: &[u64], z: u64) -> u64 {
coeff.iter().fold(0, |x, y| z*x + y)
}
assert_eq!(nested(&[1,5,10,10,5,1], 1), 32);
// easy computation of the nested square root which converges to the golden ratio
let golden = (1.0+f64::sqrt(5.0))/2.0;
let mut approx_golden = vec![1f64;100].iter().fold(1f64, |x,y| f64::sqrt(x+y));
assert!(f64::abs(approx_golden - golden) < 10E-6f64);
approx_golden = vec![1f64;100].iter().fold(1f64, |x,y| y+1f64/x);
assert!(f64::abs(approx_golden - golden) < 10E-6f64);
Note: to be sure every example compiles, I've written a simple Python script to extract the code examples and compile them as a single Rust source file for execution.
This concludes my 3-fold series of linear collections in Python, Ruby and Rust. Hope you enjoyed them. Feel free to comment.
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