🦀/⚙️/Iterator Power Tools

Iterator Power Tools Reference

What you'll learn: Advanced iterator combinators beyond filter/map/collect — enumerate, zip, chain, flat_map, scan, windows, and chunks. Essential for replacing C-style indexed for loops with safe, expressive Rust iterators.

The basic filter/map/collect chain covers many cases, but Rust's iterator library is far richer. This section covers the tools you'll reach for daily — especially when translating C loops that manually track indices, accumulate results, or process data in fixed-size chunks.

Quick Reference Table

MethodC EquivalentWhat it doesReturns
enumerate()for (int i=0; ...)Pairs each element with its index(usize, T)
zip(other)Parallel arrays with same indexPairs elements from two iterators(A, B)
chain(other)Process array1 then array2Concatenates two iteratorsT
flat_map(f)Nested loopsMaps then flattens one levelU
windows(n)for (int i=0; i<len-n+1; i++) &arr[i..i+n]Overlapping slices of size n&[T]
chunks(n)Process n elements at a timeNon-overlapping slices of size n&[T]
fold(init, f)int acc = init; for (...) acc = f(acc, x);Reduce to single valueAcc
scan(init, f)Running accumulator with outputLike fold but yields intermediate resultsOption<B>
take(n) / skip(n)Start loop at offset / limitFirst n / skip first n elementsT
take_while(f) / skip_while(f)while (pred) {...}Take/skip while predicate holdsT
peekable()Lookahead with arr[i+1]Allows .peek() without consumingT
step_by(n)for (i=0; i<len; i+=n)Take every nth elementT
unzip()Split parallel arraysCollect pairs into two collections(A, B)
sum() / product()Accumulate sum/productReduce with + or *T
min() / max()Find extremesReturn Option<T>Option<T>
any(f) / all(f)bool found = false; for (...) ...Short-circuit boolean searchbool
position(f)for (i=0; ...) if (pred) return i;Index of first matchOption<usize>

enumerate — Index + Value (replaces C index loops)

fn main() {
    let sensors = ["GPU_TEMP", "CPU_TEMP", "FAN_RPM", "PSU_WATT"];

    // C style: for (int i = 0; i < 4; i++) printf("[%d] %s\n", i, sensors[i]);
    for (i, name) in sensors.iter().enumerate() {
        println!("[{i}] {name}");
    }

    // Find the index of a specific sensor
    let gpu_idx = sensors.iter().position(|&s| s == "GPU_TEMP");
    println!("GPU sensor at index: {gpu_idx:?}");  // Some(0)
}

zip — Parallel Iteration (replaces parallel array loops)

fn main() {
    let names = ["accel_diag", "nic_diag", "cpu_diag"];
    let statuses = [true, false, true];
    let durations_ms = [1200, 850, 3400];

    // C: for (int i=0; i<3; i++) printf("%s: %s (%d ms)\n", names[i], ...);
    for ((name, passed), ms) in names.iter().zip(&statuses).zip(&durations_ms) {
        let status = if *passed { "PASS" } else { "FAIL" };
        println!("{name}: {status} ({ms} ms)");
    }
}

chain — Concatenate Iterators

fn main() {
    let critical = vec!["ECC error", "Thermal shutdown"];
    let warnings = vec!["Link degraded", "Fan slow"];

    // Process all events in priority order
    let all_events: Vec<_> = critical.iter().chain(warnings.iter()).collect();
    println!("{all_events:?}");
    // ["ECC error", "Thermal shutdown", "Link degraded", "Fan slow"]
}

flat_map — Flatten Nested Results

fn main() {
    let lines = vec!["gpu:42:ok", "nic:99:fail", "cpu:7:ok"];

    // Extract all numeric values from colon-separated lines
    let numbers: Vec<u32> = lines.iter()
        .flat_map(|line| line.split(':'))
        .filter_map(|token| token.parse::<u32>().ok())
        .collect();
    println!("{numbers:?}");  // [42, 99, 7]
}

windows and chunks — Sliding and Fixed-Size Groups

fn main() {
    let temps = [65, 68, 72, 71, 75, 80, 78, 76];

    // windows(3): overlapping groups of 3 (like a sliding average)
    // C: for (int i = 0; i <= len-3; i++) avg(arr[i], arr[i+1], arr[i+2]);
    let moving_avg: Vec<f64> = temps.windows(3)
        .map(|w| w.iter().sum::<i32>() as f64 / 3.0)
        .collect();
    println!("Moving avg: {moving_avg:.1?}");

    // chunks(2): non-overlapping groups of 2
    // C: for (int i = 0; i < len; i += 2) process(arr[i], arr[i+1]);
    for pair in temps.chunks(2) {
        println!("Chunk: {pair:?}");
    }

    // chunks_exact(2): same but panics if remainder exists
    // Also: .remainder() gives leftover elements
}

fold and scan — Accumulation

fn main() {
    let values = [10, 20, 30, 40, 50];

    // fold: single final result (like C's accumulator loop)
    let sum = values.iter().fold(0, |acc, &x| acc + x);
    println!("Sum: {sum}");  // 150

    // Build a string with fold
    let csv = values.iter()
        .fold(String::new(), |acc, x| {
            if acc.is_empty() { format!("{x}") }
            else { format!("{acc},{x}") }
        });
    println!("CSV: {csv}");  // "10,20,30,40,50"

    // scan: like fold but yields intermediate results
    let running_sum: Vec<i32> = values.iter()
        .scan(0, |state, &x| {
            *state += x;
            Some(*state)
        })
        .collect();
    println!("Running sum: {running_sum:?}");  // [10, 30, 60, 100, 150]
}

Exercise: Sensor Data Pipeline

Given raw sensor readings (one per line, format "sensor_name:value:unit"), write an iterator pipeline that:

  1. Parses each line into (name, f64, unit)
  2. Filters out readings below a threshold
  3. Groups by sensor name using fold into a HashMap
  4. Prints the average reading per sensor
// Starter code
fn main() {
    let raw_data = vec![
        "gpu_temp:72.5:C",
        "cpu_temp:65.0:C",
        "gpu_temp:74.2:C",
        "fan_rpm:1200.0:RPM",
        "cpu_temp:63.8:C",
        "gpu_temp:80.1:C",
        "fan_rpm:1150.0:RPM",
    ];
    let threshold = 70.0;
    // TODO: Parse, filter values >= threshold, group by name, compute averages
}
<details><summary>Solution (click to expand)</summary> 
use std::collections::HashMap;

fn main() {
    let raw_data = vec![
        "gpu_temp:72.5:C",
        "cpu_temp:65.0:C",
        "gpu_temp:74.2:C",
        "fan_rpm:1200.0:RPM",
        "cpu_temp:63.8:C",
        "gpu_temp:80.1:C",
        "fan_rpm:1150.0:RPM",
    ];
    let threshold = 70.0;

    // Parse → filter → group → average
    let grouped = raw_data.iter()
        .filter_map(|line| {
            let parts: Vec<&str> = line.splitn(3, ':').collect();
            if parts.len() == 3 {
                let value: f64 = parts[1].parse().ok()?;
                Some((parts[0], value, parts[2]))
            } else {
                None
            }
        })
        .filter(|(_, value, _)| *value >= threshold)
        .fold(HashMap::<&str, Vec<f64>>::new(), |mut acc, (name, value, _)| {
            acc.entry(name).or_default().push(value);
            acc
        });

    for (name, values) in &grouped {
        let avg = values.iter().sum::<f64>() / values.len() as f64;
        println!("{name}: avg={avg:.1} ({} readings)", values.len());
    }
}
// Output (order may vary):
// gpu_temp: avg=75.6 (3 readings)
// fan_rpm: avg=1175.0 (2 readings)
</details>

Rust iterators