Remove rows and reuse storage

Use remove(index) when you need to take one complete record out of a columnar list. It returns Some(record) or Nothing for an out-of-bounds index. Remaining records keep their order, and negative indices count from the end.

class Reading:
    station: i64
    temperature: f64

def main() -> Result[(), AllocError | AppendError[Reading] | IoError]:
    mut readings = clist[Reading].with_capacity(3)?
    readings.append(Reading(10, 18.0))?
    readings.append(Reading(20, 21.0))?
    readings.append(Reading(30, 24.0))?
    match readings.remove(1):
        case Some(reading):
            print("removed", reading.station, reading.temperature)?
        case Nothing:
            ()
    for station in readings.column(Reading.station):
        print(station)?

    capacity = readings.capacity()
    readings.clear()
    print(len(readings), readings.capacity() == capacity)?
    readings.append(Reading(40, 19.0))?
    print(readings[0].station)?
    Ok(())

removed 20 21.0
10
30
0 True
40

Removal assembles an independent ordinary object, just like copy_row, then shifts the later values left in every column. It allocates nothing, but removing near the front of a large collection moves much more data than removing the last row. Repeated front removals are a poor way to filter a whole dataset.

clear() empties all columns in constant time and retains their allocation. This is useful when processing successive batches: clear the old batch and append the next one into the same storage. Removal also retains capacity. Appends within that capacity do not allocate, although their return type still requires error handling. Use drop(readings) when you want to release the storage instead of reusing it.

Both methods require mutable access. A live column pipeline borrows the entire collection, so finish its traversal before removing rows or clearing the owner. See the reference for the complete contract and costs.