#data #data-reader


A data loading library for data scientist

8 releases (4 breaking)

0.5.0 Aug 22, 2023
0.4.0 Jul 19, 2021
0.3.0 Apr 29, 2019
0.2.0 Mar 21, 2019
0.1.1 Jan 7, 2019

#32 in Science

45 downloads per month



Rust Data Reader

So far this code provides similar capabilities as Numpy's loadtxt to Rust. You can read up on the documentation at doc.rs. It is currently intended to read in data that you know how it's been generated. The default delimiter is any whitespace character. The following caviates currently exist:

  1. New line and commented lines are not counted in the lines that you want skipped or that have been read.
  2. If the code fails to convert from a string to the supported type it will fail.
  3. Whitespaces are stripped from the front and end of whatever string is between delimeters.
  4. All of the data being read in needs to be the same type when converted to that type.

It provides support for the following primitive types:

u8 u16 u32 u64 u128 usize
i8 i16 i32 i64 i128
f32 f64
char bool String

The primitive uint and int use the lexical crate to provide a faster conversion from string to the given type. Floats are converted from strings to the given type using the fast-float crate. The other types use the built in standard library from_str conversion. The read in data is all stored into a vector. A struct is returned from the method load_text_* that provides the number of lines read, the number of columns read from the data, and a vector containing the data. This struct is wrapped into a Result that is returned to the user. For a 1GB float64 type file read from an SSD, I was able to obtain 190MB/s for the read in speeds.

If the type you're intrested in supports the FromStr trait you can also use this crate you can use the bottom example for how to use the load_txt! macro to load up a custom data type.


Examine ways to get even larger performance wins for reading in large files.


An example of how to use the code can be seen down below:

extern crate anyhow;
extern crate data_reader;
use data_reader::reader::*;
use anyhow::Error;

use std::str;
use std::str::FromStr;
use std::vec::*;

//This example shows us how we might skip a footer file
fn load_txt_i32_test_sk_f(){
    //The file here is the one included in the main folder.
    let file = String::from("int_testv2.txt");

    //A default constructor could look like this:
    //let params = ReaderParams::default();
    //The below could also look like the following:
    //let params = ReaderParams{
    //     comments: Some(b'%'),
    //     skip_footer: Some(5),
    //     ..Default::default()
    let params = ReaderParams{
        comments: Some(b'%'),
        delimiter: Delimiter::WhiteSpace,
        skip_header: None,
        skip_footer: Some(5_usize),
        usecols: None,
        max_rows: None,

    let results = load_txt_i32(&file, &params);

    // Pattern matching for our results could look something like this.
    // match results{
    //     Ok(results) => println!("Number of lines {}\nNumber of fields {}\nResults {:?}",results.num_lines, results.num_fields, results.results),
    //     Err(err) => println!("Error {:?}", err),
    // }

    assert_eq!(results.unwrap().results, vec![1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]);


Here's a more extensive example showing how to use custom types.

extern crate anyhow;
extern crate data_reader;
use data_reader::reader::*;
use anyhow::Error;

use std::str;
use std::str::FromStr;
use std::vec::*;

//Everything needed for our custom type
#[derive(Debug, PartialEq, Clone)]
struct MinInt{
    x: i32,
//A simple example of implementing the FromStr trait for our custom type
impl FromStr for MinInt{
    type Err = Error;

    fn from_str(s: &str) -> Result<MinInt, anyhow::Error> {
        let temp = -1 * i32::from_str(s)?;
        Ok(MinInt{x: temp})

//The test file for this has 0 commented lines in it but using a custom type
//The returned error is needed if we doing anything that's not in a function
fn load_txt_custom_test() -> Result<(), anyhow::Error> {
    let file = String::from("int_testv2.txt");

    let params = ReaderParams {
        comments: Some(b'%'),
        delimiter: Delimiter::WhiteSpace,
        skip_header: None,
        skip_footer: None,
        usecols: None,
        max_rows: None,

    let ref_file = &file;
    let ref_params = &params;

    //I found the type annotation was needed for this to compile
    let results: Result<Box<dyn ReaderResults<MinInt>>, Error> = load_text!(ref_file, ref_params, MinInt);

    let temp = results.unwrap().results.clone();

    let vals: Vec<i32> = temp.iter().map(|x| x.x).collect();

            -1, -2, -3, -4, -5, -6, -7, -8, -9, -10, -11, -12, -13, -14,
            -15, -16, -17, -18, -19, -20, -21, -22, -23, -24, -25, -26, -27,
            -28, -29, -30



  • 0.5.0 - Moved to anyhow from failure crate. Updated lexical crate to version 6.0 which allows us to get rid of dependency of fast-float crate as the performance wins in that crate had been ported over to lexical more or less. Update the memmap2 crate to 0.5.0. A number of changes exist for end-users. First, they'll need to swap failure::Error to anyhow::Error if they were using those previously. Next, the returned results are now Box::<dyn ReaderResults<T>>. The parse_text function now requires users to provide a type that implements the trait RawReaderParse such as parse_txt::<RawReaderResultsRows> which was the old default method. These changes were done so that users could now have data parsed either as row or column major order. As part of these changes, a new field has been added to ReaderParams is the row_format field. It defaults to being true which results in row major ordering of the data. The ReaderResults* now contain a ton of useful functions implemented on them that allow one to directly manipulate or get out portions of the data that are of interest to them.

  • 0.4.0 - Updated UseCols to be 0 based. Updated several public facing functions to take in different types. Added a mmap version of the parser behind a feature flag. Updated a number of crates and swapped the float parsing backend from lexical to the fast-float crate for a large increase in performance (135MB/s to 190MB/s on my machine). Added a number of functions to the ReaderResults struct to allow users to pull out given row(s) or col(s).

  • 0.3.0 - A bug was noted in the use_cols field of the ReaderParams struct that allowed you to input values that weren't useable. Also, the ReaderParams comment field was updated to being an option. Additional documentation was also added to note that the use_cols field assumes values start with an index of 1.

  • 0.2.0 - A new parsing backend has been added which saw a 40% improvement parsing/reading in a large 1GB file of all f64s. Exposed the parser to the end user so the user can deal with the raw bytes if they would enjoy doing so. Any type that now supports the FromStr trait can be converted over.

  • 0.1.3 - Updated the code to provide a bug fix that was within the v2.0 of the lexical crate.

  • 0.1.2 - Updated the comment and newline tracking portion of the code. The code now properly skips over new lines and commented lines that start with whitespace. It also can no handle lines with multiple comment characters in it without counting that line multiple times. A performance regression was created by properly handling these cases from the 0.1.1 and 0.1.0 releases.

  • 0.1.1 - Needed to update documentation for docs.rs

  • 0.1.0 - Initial crates.io release


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