[issue41310] micro-optimization: increase our float parsing speed by Nx

[Antoine Pitrou]

Antoine Pitrou  added the comment:

FTR, no formal description of the algorithm seems to have been published, but 
the source code is amply commented:
https://github.com/lemire/fast_double_parser/blob/master/include/fast_double_parser.h

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nosy: +pitrou

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[issue41310] micro-optimization: increase our float parsing speed by Nx

[Antoine Pitrou]

Change by Antoine Pitrou :


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priority: normal -> low

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[issue41310] micro-optimization: increase our float parsing speed by Nx

[Eric V. Smith]

Eric V. Smith  added the comment:

I don't think we'd want to fall back to strtod, but rather to the code we 
already use (Gay's). So this would increase our maintenance burden.

I'm also not convinced that we actually spend a lot of time in this code, but 
of course profiling would be needed to make sure.

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[issue41310] micro-optimization: increase our float parsing speed by Nx

[Tim Peters]

Tim Peters  added the comment:

Gregory, care to take their code and time it against Python?

I'm not inclined to: reading the comments in the code, they're trying "fast 
paths" already described in papers by Clinger and - later - by Gay.  When those 
fast paths don't apply, they fall back on the system `strtod`. But Python's 
current implementation builds on Gay's fastest code (and never falls back to 
the system).

It's possible they "improved" on Gay by building relatively giant tables of 
static data.

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[issue41310] micro-optimization: increase our float parsing speed by Nx

[Mark Dickinson]

Mark Dickinson  added the comment:

Is there a description of the algorithms or ideas used anywhere? The blog post 
you link to has no details, and I don't see any useful descriptions in the 
GitHub README or the source; trawling through the source to figure out what the 
key ideas are is not ideal. I don't find the tests particularly convincing, 
either.

I think this is too immature to consider for CPython, right now. Maybe it would 
make sense to revisit some day in the future if/when the library is more mature.

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[issue41310] micro-optimization: increase our float parsing speed by Nx

[Serhiy Storchaka]

Serhiy Storchaka  added the comment:

CPython is written on C, not C++, so we cannot use std::from_chars.

Note also that to parse a number in JSON we need first to scan the PyUnicode 
object character-by-character using PyUnicode_READ() which is slower than just 
reading a byte from a memory, then convert a substring to a nul-terminated 
bytes string, and finally use the conversion function  which creates a new 
PyFloat or PyLong objects. The overhead of scanning a string and memory 
management may be larger than the parsing time itself.

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nosy: +serhiy.storchaka

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[issue41310] micro-optimization: increase our float parsing speed by Nx

[Raymond Hettinger]

Change by Raymond Hettinger :


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nosy: +rhettinger, tim.peters

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[issue41310] micro-optimization: increase our float parsing speed by Nx

[Eric V. Smith]

Change by Eric V. Smith :


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nosy: +eric.smith, mark.dickinson

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[issue41310] micro-optimization: increase our float parsing speed by Nx

[Gregory P. Smith]

New submission from Gregory P. Smith :

See https://lemire.me/blog/2020/03/10/fast-float-parsing-in-practice/ for 
inspiration and a reference (possibly a library to use, but if not the 
techniques still apply).

Primarily usable when creating the float objects from the string data as is 
common in python code and particularly common in JSON serialized data.

--
components: Interpreter Core
messages: 373730
nosy: gregory.p.smith
priority: normal
severity: normal
stage: needs patch
status: open
title: micro-optimization: increase our float parsing speed by Nx
type: enhancement
versions: Python 3.10

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