3 · Reliability and project · 25 MIN

Iterators, vectors and map entries

Iterator adapters describe work; a consumer performs it.

filter creates a lazy adapter and collect consumes it to build a new collection. The source vector remains borrowed while iteration proceeds. A HashMap entry gives one place to handle both inserting a missing key and modifying an existing value. HashMap order is unspecified, so the example checks a named entry instead of relying on printed iteration order. Keep numeric overflow and case-normalization rules explicit before using a frequency counter on arbitrary text.

Use entry for updates and a separate sorted key list for presentation.

Read the example

use std::collections::HashMap;
fn main() {
    let values = vec![1,2,2,3];
    let evens: Vec<i32> = values.iter().copied().filter(|n| n % 2 == 0).collect();
    let mut counts = HashMap::new();
    for value in &values { *counts.entry(*value).or_insert(0_u32) += 1; }
    println!("{:?}", evens);
    println!("{}", counts[&2]);
    println!("{}", values.len());
}

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Your challenge

Build a case-sensitive word-frequency function returning a HashMap and render sorted keys for a stable report.

Solution cost: Expected O(n) counting with O(k) distinct-key storage. time · Account for collection storage separately from the returned result. space

Common trap

An iterator that is never consumed does not execute its transformation pipeline.

use std::collections::HashMap;
fn main() {
    let values = vec![1,2,2,3];
    let evens: Vec<i32> = values.iter().copied().filter(|n| n % 2 == 0).collect();
    let mut counts = HashMap::new();
    for value in &values { *counts.entry(*value).or_insert(0_u32) += 1; }
    println!("{:?}", evens);
    println!("{}", counts[&2]);
    println!("{}", values.len());
}

Further reading: Official documentation