re2

Pros of ripgrep

• Faster performance for searching large codebases
• Built-in support for various file types and gitignore rules
• User-friendly command-line interface with colored output

Cons of ripgrep

• Limited to text search and not a general-purpose regex library
• Less flexibility for complex pattern matching compared to RE2

Code Comparison

RE2:

#include <re2/re2.h>
RE2 pattern("\\w+");
RE2::FullMatch(text, pattern);

ripgrep:

use grep_regex::RegexMatcher;
let matcher = RegexMatcher::new(r"\w+").unwrap();
matcher.is_match(text.as_bytes()).unwrap()

Key Differences

RE2 is a C++ library focused on efficient regular expression matching, while ripgrep is a command-line search tool written in Rust. RE2 provides a more comprehensive regex engine suitable for various applications, whereas ripgrep excels in fast, user-friendly code searching.

RE2 offers better support for complex pattern matching and can be integrated into larger applications. ripgrep, on the other hand, is optimized for searching through large codebases quickly and provides a more intuitive interface for developers working directly from the command line.

Pros of Hyperscan

• Designed for high-performance, multi-pattern matching
• Supports advanced features like stream matching and vectorized processing
• Optimized for Intel architectures, leveraging hardware acceleration

Cons of Hyperscan

• Limited platform support (primarily x86)
• More complex API and usage compared to RE2
• Larger memory footprint for pattern compilation

Code Comparison

RE2:

re2::RE2 pattern("\\w+");
re2::StringPiece input("Hello, world!");
re2::StringPiece match;
while (re2::RE2::FindAndConsume(&input, pattern, &match)) {
    std::cout << match << std::endl;
}

Hyperscan:

hs_database_t *database;
hs_compile_error_t *compile_err;
hs_compile("\\w+", 0, HS_FLAG_DOTALL, NULL, &database, &compile_err);
hs_scratch_t *scratch;
hs_alloc_scratch(database, &scratch);
hs_scan(database, "Hello, world!", 13, 0, scratch, onMatch, NULL);
hs_free_scratch(scratch);
hs_free_database(database);

Both RE2 and Hyperscan are powerful regular expression engines, but they cater to different use cases. RE2 focuses on simplicity and safety, while Hyperscan prioritizes high-performance matching for large sets of patterns. RE2 is more portable and easier to use, making it suitable for general-purpose regex needs. Hyperscan excels in scenarios requiring fast processing of multiple patterns simultaneously, particularly in network security and content inspection applications.

Pros of Oniguruma

• Supports a wider range of regular expression syntax, including Perl, Python, and Emacs styles
• Offers better support for Unicode and multi-byte character sets
• Provides more advanced features like look-behind assertions and recursive patterns

Cons of Oniguruma

• Generally slower performance compared to RE2, especially for complex patterns
• Less memory-efficient, particularly for large-scale text processing tasks
• Not as well-suited for high-throughput, production environments

Code Comparison

RE2:

RE2 pattern("\\w+");
re2::StringPiece input("Hello, World!");
std::string word;
while (RE2::FindAndConsume(&input, pattern, &word)) {
    std::cout << word << std::endl;
}

Oniguruma:

regex_t* reg;
OnigRegion* region;
onig_new(&reg, (UChar*)"\\w+", (UChar*)"\\w+"+4, ONIG_OPTION_DEFAULT, ONIG_ENCODING_UTF8, ONIG_SYNTAX_DEFAULT, NULL);
region = onig_region_new();
const char* str = "Hello, World!";
while (onig_search(reg, (UChar*)str, (UChar*)(str + strlen(str)), (UChar*)str, (UChar*)(str + strlen(str)), region, ONIG_OPTION_NONE) >= 0) {
    // Process matches
}

Both RE2 and Oniguruma are powerful regular expression libraries, but they cater to different use cases. RE2 focuses on speed and safety, making it ideal for high-performance applications. Oniguruma offers more extensive feature support and flexibility, suitable for complex pattern matching scenarios.