Runtime optimization of regular expressions
php editor Youzi will introduce you to the runtime optimization of regular expressions. Regular expressions are a powerful tool for string matching and processing, but can cause performance issues when working with large-scale data. In order to improve the execution efficiency of regular expressions, we can adopt some optimization strategies, such as using lazy matching, avoiding the use of backtracking, and using more precise matching patterns. These optimization techniques can help us use regular expressions more efficiently in actual development and improve program performance.
Question content
Most regular expressions are "constant" during their lifetime. Is it a good idea to use global regular expressions to speed up execution? For example:
func work() { r := regexp.mustcompile(`...`) if r.matchstring(...) { ... } }
Compare:
var r *regexp.Regexp func work() { if r.MatchString(...) { ... } } func init() { r = regexp.MustCompile(`...`) }
Are there any meaningful differences between the two versions?
- Regular expressions are very cheap to compile, so from a cpu cost and garbage collection perspective, it is not worth using global regular expressions (assuming
work()
is called heavily) - It is best to use global regular expressions when appropriate.
Which of the above is correct, or is the answer not simply black/white?
Workaround
It's not worth using a global regular expression if you only use the same regular expression once (e.g. "\d
") ->
If you often use the same regular expression (e.g. "\d
") ->, then it's worth using
func benchmark01(b *testing.b) { for i := 0; i < b.n; i++ { r := regexp.mustcompile(`\d+`) r.matchstring("aaaaaaa123bbbbbbb") } } func benchmark02(b *testing.b) { r := regexp.mustcompile(`\d+`) for i := 0; i < b.n; i++ { r.matchstring("aaaaaaa123bbbbbbb") } }
Benchmark01 Benchmark01-4 886909 1361 ns/op Benchmark02 Benchmark02-4 5368380 232.8 ns/op
The above is the detailed content of Runtime optimization of regular expressions. For more information, please follow other related articles on the PHP Chinese website!

Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

AI Hentai Generator
Generate AI Hentai for free.

Hot Article

Hot Tools

Notepad++7.3.1
Easy-to-use and free code editor

SublimeText3 Chinese version
Chinese version, very easy to use

Zend Studio 13.0.1
Powerful PHP integrated development environment

Dreamweaver CS6
Visual web development tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)

Hot Topics

This article explains Go's package import mechanisms: named imports (e.g., import "fmt") and blank imports (e.g., import _ "fmt"). Named imports make package contents accessible, while blank imports only execute t

This article explains Beego's NewFlash() function for inter-page data transfer in web applications. It focuses on using NewFlash() to display temporary messages (success, error, warning) between controllers, leveraging the session mechanism. Limita

This article details efficient conversion of MySQL query results into Go struct slices. It emphasizes using database/sql's Scan method for optimal performance, avoiding manual parsing. Best practices for struct field mapping using db tags and robus

This article explores Go's custom type constraints for generics. It details how interfaces define minimum type requirements for generic functions, improving type safety and code reusability. The article also discusses limitations and best practices

This article demonstrates creating mocks and stubs in Go for unit testing. It emphasizes using interfaces, provides examples of mock implementations, and discusses best practices like keeping mocks focused and using assertion libraries. The articl

This article details efficient file writing in Go, comparing os.WriteFile (suitable for small files) with os.OpenFile and buffered writes (optimal for large files). It emphasizes robust error handling, using defer, and checking for specific errors.

The article discusses writing unit tests in Go, covering best practices, mocking techniques, and tools for efficient test management.

This article explores using tracing tools to analyze Go application execution flow. It discusses manual and automatic instrumentation techniques, comparing tools like Jaeger, Zipkin, and OpenTelemetry, and highlighting effective data visualization
