Pros of RE2

• Faster performance for large-scale text processing
• Guaranteed linear time complexity, preventing catastrophic backtracking
• Better memory efficiency, especially for large inputs

Cons of RE2

• Limited support for advanced regex features (e.g., backreferences, lookaround assertions)
• Less flexible syntax compared to PCRE-style engines
• May require code changes when migrating from other regex libraries

Code Comparison

Oniguruma:

regex_t* reg;
OnigErrorInfo einfo;
int r = onig_new(&reg, pattern, pattern + strlen(pattern),
                 ONIG_OPTION_DEFAULT, ONIG_ENCODING_UTF8,
                 ONIG_SYNTAX_DEFAULT, &einfo);

RE2:

RE2 re(pattern);
if (!re.ok()) {
    // Handle error
}

Key Differences

• Oniguruma offers more extensive regex features, including Unicode support and complex pattern matching
• RE2 focuses on performance and safety, sacrificing some advanced regex functionality
• Oniguruma is commonly used in scripting languages (e.g., Ruby), while RE2 is often employed in large-scale applications
• RE2 provides a simpler API, making it easier to use for basic regex operations
• Oniguruma's flexibility makes it suitable for a wider range of text processing tasks

Pros of regex

• Written in Rust, offering memory safety and thread safety
• Designed for high performance with linear-time matching for most regular expressions
• Extensive documentation and examples for ease of use

Cons of regex

• Limited to Rust ecosystem, not as widely portable as Oniguruma
• May lack some advanced features found in Oniguruma, such as certain Unicode properties

Code Comparison

Oniguruma (C):

regex_t* reg;
OnigErrorInfo einfo;
int r = onig_new(&reg, pattern, pattern + strlen(pattern),
                 ONIG_OPTION_DEFAULT, ONIG_ENCODING_UTF8,
                 ONIG_SYNTAX_DEFAULT, &einfo);

regex (Rust):

use regex::Regex;

let re = Regex::new(r"pattern").unwrap();
let matches = re.is_match("test string");

Summary

Oniguruma is a C library for regular expressions with wide language support and extensive Unicode features. It's highly portable and used in many projects across different programming languages.

regex is a Rust-specific regular expression engine focused on safety and performance within the Rust ecosystem. It provides a more modern and safe API but is limited to Rust applications.

The choice between these libraries depends on the specific project requirements, target language, and desired features.

Pros of ripgrep

• Significantly faster performance for searching large codebases
• User-friendly command-line interface with intuitive options
• Built-in support for various file types and automatic encoding detection

Cons of ripgrep

• Limited regular expression engine compared to Oniguruma
• Not designed as a standalone library for integration into other projects
• Lacks some advanced features found in Oniguruma, like syntax highlighting

Code Comparison

Oniguruma (C):

regex_t* reg;
OnigErrorInfo einfo;
int r = onig_new(&reg, pattern, pattern + strlen(pattern),
                 ONIG_OPTION_DEFAULT, ONIG_ENCODING_UTF8,
                 ONIG_SYNTAX_DEFAULT, &einfo);

ripgrep (Rust):

use grep_regex::RegexMatcher;
let matcher = RegexMatcher::new(pattern)?;
let printer = StandardBuilder::new().build(stdout());
searcher.search_path(&matcher, path, printer)?;

While Oniguruma provides a powerful regular expression engine as a library, ripgrep is designed as a command-line tool for fast searching. Oniguruma offers more flexibility for integration into other projects, while ripgrep excels in performance and ease of use for developers searching through codebases.

Pros of Phobos

• Comprehensive standard library for D programming language
• Extensive range of modules covering various programming needs
• Active development and community support

Cons of Phobos

• Larger codebase and potentially steeper learning curve
• Specific to D language, limiting its use in other environments

Code Comparison

Phobos (D language):

import std.regex;
auto pattern = regex("\\d+");
auto text = "123 abc 456";
auto matches = matchAll(text, pattern);

Oniguruma (C language):

#include <oniguruma.h>
regex_t* reg;
OnigRegion* region;
onig_new(&reg, (UChar*)"\\d+", (UChar*)"\\d+"+4, ONIG_OPTION_DEFAULT, ONIG_ENCODING_UTF8, ONIG_SYNTAX_DEFAULT, NULL);
region = onig_region_new();
onig_search(reg, (UChar*)"123 abc 456", (UChar*)"123 abc 456"+11, (UChar*)"123 abc 456", (UChar*)"123 abc 456"+11, region, ONIG_OPTION_NONE);

Summary

Phobos is a full-featured standard library for D, offering a wide range of functionalities beyond regular expressions. Oniguruma is a specialized regular expression library with multi-language support. Phobos provides a more high-level and integrated approach for D developers, while Oniguruma offers a lower-level, portable solution for regular expression handling across different programming languages.

Pros of Hyperscan

• High-performance regex matching optimized for Intel architectures
• Supports simultaneous matching of large pattern sets
• Offers both streaming and block mode scanning

Cons of Hyperscan

• Limited to x86 platforms, less portable than Oniguruma
• More complex API and setup compared to Oniguruma
• Lacks some advanced regex features found in Oniguruma

Code Comparison

Oniguruma:

regex_t* reg;
OnigRegion* region;
onig_new(&reg, pattern, pattern + strlen(pattern), ONIG_OPTION_DEFAULT, ONIG_ENCODING_UTF8, ONIG_SYNTAX_DEFAULT, &einfo);
region = onig_region_new();
onig_search(reg, str, str + strlen(str), str, str + strlen(str), region, ONIG_OPTION_NONE);

Hyperscan:

hs_database_t *database;
hs_compile_error_t *compile_err;
hs_compile(pattern, HS_FLAG_DOTALL, HS_MODE_BLOCK, NULL, &database, &compile_err);
hs_scratch_t *scratch = NULL;
hs_alloc_scratch(database, &scratch);
hs_scan(database, str, strlen(str), 0, scratch, event_handler, NULL);

Both libraries offer regex matching capabilities, but Hyperscan focuses on high-performance scanning for large pattern sets, while Oniguruma provides a more traditional regex engine with broader language support. Hyperscan's API is more complex, reflecting its specialized use cases, while Oniguruma offers a simpler interface for general-purpose regex operations.