quick-csv

Fast Csv reader which performs very well.

Example

First, create a Csv, either from a file or from a BufRead reader.

```rust extern crate quick_csv;

fn main() { let csv = quickcsv::Csv::fromfile("test.csv").unwrap(); for row in csv.into_iter() { // work on csv row ... } } ```

Row is on the other hand provides 3 methods to access csv columns: - columns: - iterator over columns. - Iterator item is a &str, which means you only have to parse() it to the needed type and you're done

rust let mut cols = row.columns(); let fifth = cols.nth(5).unwrap().parse::<f64>(); println!("Doubled fifth column: {}", fifth * 2.0);

• decode:

  • deserialize into you Decodable struct, a-la rust-csv.
  • most convenient way to deal with your csv data

  rust if let Ok((col1, col2, col3)) = rust::decode::<(String, u64, f64)>() { println!("col1: '{}',, col2: {}, col3: {}", col1, col2, col3); }

• bytes_columns:

  • similar to columns but columns are of type &[u8], which means you may want to convert it to &str first
  • performance gain compared to columns is minimal, use it only if you really need to as it is less convenient

Benchmarks

I mainly benchmarked this to rust-csv, which is supposed to be already very fast. I tried to provide similar methods even if I don't have raw version.

• quick-csv test bytes_records ... bench: 4,799,100 ns/iter (+/- 119,638) = 283 MB/s test decoded_records ... bench: 10,813,981 ns/iter (+/- 423,758) = 125 MB/s test str_records ... bench: 5,318,667 ns/iter (+/- 133,288) = 256 MB/s

• rust-csv test byte_records ... bench: 10,528,780 ns/iter (+/- 2,080,735) = 128 MB/s test decoded_records ... bench: 18,458,365 ns/iter (+/- 2,415,059) = 73 MB/s test raw_records ... bench: 6,555,447 ns/iter (+/- 830,423) = 207 MB/s test string_records ... bench: 12,813,284 ns/iter (+/- 2,324,424) = 106 MB/s

License

MIT