Are you a rusty little thing?

Do you want to write 10,000-line functions and just chain iterators forever?

Do you love watching your compiler cry while it's trying to figure out WTF is a Fold<Map<Filter<TakeWhile<Map<StepBy<Zip<SkipWhile...

Do you get insecure about your ugly, disgusting, imperative code?

Introducing...

validiter (version 0.3.0)

validiter is meant to provide a nice rusty api for performing validations on iterators. Here is a very simple example for an adapter it provides:

(0..10).validate().at_most(7, |_, val| val) // wraps the first 7 elements in Ok(i32) and the rest in a Err(i32)

Earlier versions of this crate were weirdly complicated, but this version is simply iterator adapters with some extra metadata on the iteration that allow us to decide when element is just no good. Best served with an example:

use std::{num::ParseFloatError, vec};

use validiter::{AtLeast, ConstOver, Ensure};

fn main() {
    // In this example we will use the 'cast_errs' method to
    // create a 'Vec<Vec<f64>>' collection, while ensuring
    // the mathematical validity if this collection as a numerical
    // matrix. To exercise the 'ensure' adapter, we'll force all
    // elements to be non-negative as well

    // Here we define the errors we expect to encounter in
    // the parsing process:
    #[derive(Debug)]
    enum MatParseErr {
        NotAFloat(usize, usize, ParseFloatError),
        NoColumns(usize),
        Negative(usize, usize, f64),
        NoRows,
        JaggedArray(usize, Vec<f64>, usize, usize),
    }

    // this is a CSV format str, with 2 rows and 2 columns
    let csv = "1.2, 3.0
                4.2, 0.5";

    // we'll use iterator methods on the CSV to build an actual matrix over f64
    let mat = csv
        .lines()
        .enumerate()
        .map(|(i, line)| {
            line.split(",")
                .map(|s| s.trim())
                .enumerate()
                .map(|(j, s)| {
                    s.parse::<f64>()
                        .map_err(|parse_err| MatParseErr::NotAFloat(i, j, parse_err))
                })
                .ensure(|val| *val >= 0.0, |j, val| MatParseErr::Negative(i, j, val))
                .at_least(1, |_| MatParseErr::NoColumns(i))
                .collect::<Result<Vec<f64>, MatParseErr>>()
        })
        .at_least(1, |_| MatParseErr::NoRows)
        .const_over(
            |vec| vec.len(),
            |i, vec, len, expected_len| MatParseErr::JaggedArray(i, vec, len, *expected_len),
        )
        .collect::<Result<Vec<_>, _>>();

    match mat {
        Ok(mat) => {
            assert_eq!(mat, vec![vec![1.2, 3.0], vec![4.2, 0.5]]);
            println!("{mat:?}")
        }
        Err(mperr) => match mperr {
            MatParseErr::NotAFloat(i, j, err) => println!("Got {err} at pos [{i}, {j}]"),
            MatParseErr::NoColumns(i) => {
                println!("Row {i} is without any data, which would force the matrix to be empty")
            }
            MatParseErr::Negative(i, j, val) => {
                println!("value {val} at pos [{i}, {j}] is negative")
            }
            MatParseErr::NoRows => println!("There are no rows in the matrix"),
            MatParseErr::JaggedArray(i, _vec, len, expected_len) => {
                println!("Row {i} has len {len}, when all rows should have length {expected_len}")
            }
        },
    }
}

License

Licensed under either of

• Apache License, Version 2.0 (LICENSE-APACHE or http://www.apache.org/licenses/LICENSE-2.0)
• MIT license (LICENSE-MIT or http://opensource.org/licenses/MIT)

at your option.

Contribution

Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in the work by you, as defined in the Apache-2.0 license, shall be dual licensed as above, without any additional terms or conditions.