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0.2.0 Jan 13, 2021
0.1.0 Jan 10, 2021

#49 in Parser tooling

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Used in 23 crates (12 directly)

MIT/Apache

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fast-float

Build Latest Version Documentation Apache 2.0 MIT Rustc 1.37+

This crate provides a super-fast decimal number parser from strings into floats.

[dependencies]
fast-float = "0.2"

There are no dependencies and the crate can be used in a no_std context by disabling the "std" feature.

Compiler support: rustc 1.37+.

Usage

There's two top-level functions provided: parse() and parse_partial(), both taking either a string or a bytes slice and parsing the input into either f32 or f64:

  • parse() treats the whole string as a decimal number and returns an error if there are invalid characters or if the string is empty.
  • parse_partial() tries to find the longest substring at the beginning of the given input string that can be parsed as a decimal number and, in the case of success, returns the parsed value along the number of characters processed; an error is returned if the string doesn't start with a decimal number or if it is empty. This function is most useful as a building block when constructing more complex parsers, or when parsing streams of data.

Example:

// Parse the entire string as a decimal number.
let s = "1.23e-02";
let x: f32 = fast_float::parse(s).unwrap();
assert_eq!(x, 0.0123);

// Parse as many characters as possible as a decimal number.
let s = "1.23e-02foo";
let (x, n) = fast_float::parse_partial::<f32, _>(s).unwrap();
assert_eq!(x, 0.0123);
assert_eq!(n, 8);
assert_eq!(&s[n..], "foo");

Details

This crate is a direct port of Daniel Lemire's fast_float C++ library (valuable discussions with Daniel while porting it helped shape the crate and get it to the performance level it's at now), with some Rust-specific tweaks. Please see the original repository for many useful details regarding the algorithm and the implementation.

The parser is locale-independent. The resulting value is the closest floating-point values (using either f32 or f64), using the "round to even" convention for values that would otherwise fall right in-between two values. That is, we provide exact parsing according to the IEEE standard.

Infinity and NaN values can be parsed, along with scientific notation.

Both little-endian and big-endian platforms are equally supported, with extra optimizations enabled on little-endian architectures.

Testing

There are a few ways this crate is tested:

  • A suite of explicit tests (taken from the original library) covering lots of edge cases.
  • A file-based test suite (taken from the original library; credits to Nigel Tao), ~5M tests.
  • All 4B float32 numbers are exhaustively roundtripped via ryu formatter.
  • Roundtripping a large quantity of random float64 numbers via ryu formatter.
  • Roundtripping float64 numbers and fuzzing random input strings via cargo-fuzz.
  • All explicit test suites run on CI; roundtripping and fuzzing are run manually.

Performance

The presented parser seems to beat all of the existing C/C++/Rust float parsers known to us at the moment by a large margin, in all of the datasets we tested it on so far – see detailed benchmarks below (the only exception being the original fast_float C++ library, of course – performance of which is within noise bounds of this crate). On modern machines like Apple M1, parsing throughput can reach up to 1.5 GB/s.

In particular, it is faster than Rust standard library's FromStr::from_str() by a factor of 2-8x (larger factor for longer float strings), and is typically 2-3x faster than the nearest competitors.

While various details regarding the algorithm can be found in the repository for the original C++ library, here are few brief notes:

  • The parser is specialized to work lightning-fast on inputs with at most 19 significant digits (which constitutes the so called "fast-path"). We believe that most real-life inputs should fall under this category, and we treat longer inputs as "degenerate" edge cases since it inevitable causes overflows and loss of precision.
  • If the significand happens to be longer than 19 digits, the parser falls back to the "slow path", in which case its performance roughly matches that of the top Rust/C++ libraries (and still beats them most of the time, although not by a lot).
  • On little-endian systems, there's additional optimizations for numbers with more than 8 digits after the decimal point.

Benchmarks

Below are tables of best timings in nanoseconds for parsing a single number into a 64-bit float.

Intel i7-4771

Intel i7-4771 3.5GHz, macOS, Rust 1.49.

canada mesh uniform iidi iei rec32
fast-float 21.58 10.70 19.36 40.50 26.07 29.13
lexical 65.90 23.28 54.75 75.80 52.18 75.36
from_str 174.43 22.30 99.93 227.76 111.31 204.46
fast_float (C++) 22.78 10.99 20.05 41.12 27.51 30.85
abseil (C++) 42.66 32.88 46.01 50.83 46.33 49.95
netlib (C++) 57.53 24.86 64.72 56.63 36.20 67.29
strtod (C) 286.10 31.15 258.73 295.73 205.72 315.95

Apple M1

Apple M1, macOS, Rust 1.49.

canada mesh uniform iidi iei rec32
fast-float 14.84 5.98 11.24 33.24 21.30 17.86
lexical 47.09 16.51 43.46 56.06 36.68 55.48
from_str 136.00 13.84 74.64 179.87 77.91 154.53
fast_float (C++) 13.71 7.28 11.71 32.94 20.64 18.30
abseil (C++) 36.55 24.20 38.48 40.86 35.46 40.09
netlib (C++) 47.19 14.12 48.85 52.28 33.70 48.79
strtod (C) 176.13 21.48 165.43 187.98 132.19 190.63

AMD Rome

AMD Rome, Linux, Rust 1.49.

canada mesh uniform iidi iei rec32
fast-float 25.90 12.12 20.54 47.01 29.23 32.36
lexical 63.18 22.13 54.78 81.23 55.06 79.14
from_str 190.06 26.10 102.44 239.87 119.04 211.73
fast_float (C++) 21.29 10.47 18.31 42.33 24.56 29.76
abseil (C++) 44.54 34.13 47.38 52.64 43.77 53.03
netlib (C++) 69.43 23.31 79.98 72.17 35.81 86.91
strtod (C) 123.37 65.68 101.58 118.36 118.61 123.72

Parsers

  • fast-float - this very crate
  • lexicallexical_core, v0.7 (non-lossy; same performance as lossy)
  • from_str – Rust standard library, FromStr trait
  • fast_float (C++) – original C++ implementation of 'fast-float' method
  • abseil (C++) – Abseil C++ Common Libraries
  • netlib (C++) – C++ Network Library
  • strtod (C) – C standard library

Datasets

  • canada – numbers in canada.txt file
  • mesh – numbers in mesh.txt file
  • uniform – uniform random numbers from 0 to 1
  • iidi – random numbers of format %d%d.%d
  • iei – random numbers of format %de%d
  • rec32 – reciprocals of random 32-bit integers

Notes

  • The two test files referred above can be found in this repository.
  • The Rust part of the table (along with a few other benchmarks) can be generated via the benchmark tool that can be found under extras/simple-bench of this repo.
  • The C/C++ part of the table (along with a few other benchmarks and parsers) can be generated via a C++ utility that can be found in this repository.

License

Licensed under either of Apache License, Version 2.0 or MIT license at your option.
Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in this crate by you, as defined in the Apache-2.0 license, shall be dual licensed as above, without any additional terms or conditions.

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