glugify

A slugification library for Gleam that converts text into URL-friendly slugs.

gleam add glugify

Quick Start

import glugify

// Simple usage - always returns a string
glugify.slugify("Hello, World!")
// -> "hello-world"

// Error-aware usage - returns Result
glugify.try_slugify("My Blog Post Title!")
// -> Ok("my-blog-post-title")

Three-Tier API

Tier 1: Simple API

Zero-configuration slugification that always returns a string:

import glugify

glugify.slugify("My awesome blog post!")
// -> "my-awesome-blog-post"

glugify.slugify("Café & Restaurant")
// -> "cafe-and-restaurant"

Tier 2: Error-Aware API

Returns Result(String, SlugifyError) for explicit error handling:

import glugify

case glugify.try_slugify("") {
  Ok(slug) -> "Generated slug: " <> slug
  Error(error) -> "Failed to generate slug"
}

Tier 3: Configurable API

Full control with custom configuration:

import glugify
import glugify/config

let custom_config = config.default()
  |> config.with_separator("_")
  |> config.with_max_length(20)
  |> config.with_word_boundary(True)

glugify.slugify_with("A Very Long Title That Needs Truncation", custom_config)
// -> Ok("a_very_long_title")

Configuration Options

import glugify/config

config.default()
  |> config.with_separator("_")           // Default: "-"
  |> config.with_lowercase(False)         // Default: True
  |> config.with_max_length(50)           // Default: None
  |> config.with_word_boundary(True)      // Default: False
  |> config.with_transliterate(False)     // Default: True
  |> config.with_allow_unicode(True)      // Default: False
  |> config.with_custom_replacements([    // Default: []
    #("&", " and "),
    #("@", " at ")
  ])
  |> config.with_stop_words(["the", "a"]) // Default: []

Advanced Examples

Custom Replacements

let config = config.default()
  |> config.with_custom_replacements([
    #("&", " and "),
    #("@", " at "),
    #("%", " percent ")
  ])

glugify.slugify_with("Cats & Dogs @ 100%", config)
// -> Ok("cats-and-dogs-at-100-percent")

Unicode Handling

// With transliteration (default)
glugify.slugify("Café naïve résumé")
// -> "cafe-naive-resume"

// Preserving Unicode
let unicode_config = config.default()
  |> config.with_transliterate(False)
  |> config.with_allow_unicode(True)

glugify.slugify_with("Café naïve résumé", unicode_config)
// -> Ok("caf-na-ve-r-sum")

Stop Words

let config = config.default()
  |> config.with_stop_words(["the", "a", "an", "and", "or"])

glugify.slugify_with("The Quick Brown Fox and the Lazy Dog", config)
// -> Ok("quick-brown-fox-lazy-dog")

Error Handling

The library provides explicit error types for robust error handling:

import glugify/errors

case glugify.try_slugify("") {
  Ok(slug) -> slug
  Error(errors.EmptyInput) -> "Please provide some text"
  Error(errors.TransliterationFailed(char)) -> "Cannot transliterate: " <> char
  Error(errors.ConfigurationError(msg)) -> "Config error: " <> msg
}

Performance

Benchmark Results

Erlang Target

Erlang Summary: 800 total operations executed with an average of 6 operations per second.

JavaScript Target

JavaScript Summary: 800 total operations executed with an average of 2,030 operations per second.

Performance Characteristics

• Target Performance: JavaScript target significantly outperforms Erlang (300-700x faster for simple operations)
• Simple strings: Optimized for common use cases with minimal processing overhead
• Unicode handling: Efficient transliteration with character mapping tables on both targets
• Configuration impact: Minimal performance penalty when using custom configurations
• String length scaling: Performance decreases predictably with input length on both targets
• Memory efficiency: Uses string trees for optimal memory allocation patterns

Things of note:

• JavaScript target excels at simple text processing (2,700+ ops/sec vs 4-21 ops/sec)
• Both targets show similar relative performance patterns across different input types
• Long text processing is the primary bottleneck on both platforms
• Custom configuration actually improves performance on JavaScript target

The benchmarks were run with 100 iterations per test case on both Erlang and JavaScript targets. Performance may vary depending on your specific use case and runtime environment.

Installation

Add glugify to your Gleam project:

gleam add glugify

Development

gleam run   # Run the project
gleam test  # Run the tests
gleam format # Format the code

Contributing

Contributions are welcome! Please feel free to submit a Pull Request!

Documentation

Further documentation can be found at https://hexdocs.pm/glugify.