quick-csv
Quick Csv reader which performs very well.
This library has been hugely inspired by Andrew Gallant's (@BurntSuchi) excellent rust-csv. In particular, most tests and benchmarks are a simple copy-paste from there.
Example
First, create a Csv
from a BufRead
reader, a file or a string
extern crate quick_csv;
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 toparse()
it to the needed type and you're done
let row = from_string.next.unwrap.unwrap; let mut cols = row.columns.expect; let fifth = cols.nth.unwrap..unwrap; println!;
-
decode
:- deserialize into you
Decodable
struct, a-la rust-csv. - most convenient way to deal with your csv data
let row = from_string.next.unwrap.unwrap; if let Ok = row.
- deserialize into you
-
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
- similar to
Benchmarks
rust-csv
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.
Normal bench
quick-csv
test bytes_records ... bench: 3,955,041 ns/iter (+/- 95,122) = 343 MB/s
test decoded_records ... bench: 10,133,448 ns/iter (+/- 151,735) = 133 MB/s
test str_records ... bench: 4,419,434 ns/iter (+/- 104,107) = 308 MB/s
rust-csv (0.14.3)
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
Bench large
With the 3.6GB file, as described in the bench large README:
go: 187 seconds
rust-csv: 23 seconds
quick-csv: 9 seconds
csv-game
When writing this, quick-csv is the fastest csv on csv-game
License
MIT