Pros of Parsimmon

• More flexible and expressive, allowing for easier creation of complex parsers
• Better performance for certain types of grammars
• Easier to integrate with existing JavaScript code and workflows

Cons of Parsimmon

• Steeper learning curve for those unfamiliar with parser combinators
• Less suitable for generating parsers from formal grammar specifications
• May require more manual optimization for large-scale parsing tasks

Code Comparison

Nearley example:

main -> "hello" ws "world" {% function(d) { return d.join(""); } %}
ws -> [ \t\n\v\f]+

Parsimmon example:

const parser = Parsimmon.seq(
  Parsimmon.string("hello"),
  Parsimmon.regexp(/[ \t\n\v\f]+/),
  Parsimmon.string("world")
).map(parts => parts.join(""));

Both Nearley and Parsimmon are popular parsing libraries for JavaScript, but they take different approaches. Nearley uses a more traditional grammar-based approach, while Parsimmon uses parser combinators. The choice between them depends on the specific requirements of your project, your familiarity with different parsing techniques, and the complexity of the language you're parsing.

Pros of PEG.js

• More mature and widely adopted project with a larger community
• Supports both browser and Node.js environments out of the box
• Offers an online playground for quick testing and experimentation

Cons of PEG.js

• Limited to PEG (Parsing Expression Grammar) syntax, which may be less flexible for certain use cases
• Can be slower for parsing large inputs compared to some alternatives

Code Comparison

PEG.js grammar example:

start
  = additive

additive
  = left:multiplicative "+" right:additive { return left + right; }
  / multiplicative

multiplicative
  = left:primary "*" right:multiplicative { return left * right; }
  / primary

primary
  = integer
  / "(" additive:additive ")" { return additive; }

integer "integer"
  = digits:[0-9]+ { return parseInt(digits.join(""), 10); }

Nearley grammar example:

main -> AS {% id %}

AS -> AS "+" MD {% ([a, _, b]) => a + b %}
    | MD {% id %}

MD -> MD "*" P  {% ([a, _, b]) => a * b %}
    | P  {% id %}

P -> "(" AS ")" {% ([_, a, _]) => a %}
   | N {% id %}

N -> [0-9]:+ {% ([digits]) => parseInt(digits.join("")) %}

Both examples demonstrate arithmetic expression parsing, showcasing the syntax differences between PEG.js and Nearley.

Pros of Ohm

• More flexible and expressive grammar syntax
• Better support for incremental parsing and error recovery
• Extensive documentation and examples

Cons of Ohm

• Steeper learning curve for beginners
• Slightly slower parsing performance for some use cases

Code Comparison

Nearley grammar example:

main -> "hello" ws noun ws "!" {% ([,, noun]) => `Hello, ${noun}!` %}
noun -> "world" | "universe"
ws -> [ \t\n\v\f\r]*

Ohm grammar example:

Main {
  greeting = "hello" ws noun ws "!"
  noun = "world" | "universe"
  ws = (" " | "\t" | "\n")*
}

Both Nearley and Ohm are powerful parser generators, but they have different approaches to grammar definition and parsing. Nearley uses a more traditional BNF-like syntax, while Ohm employs a custom grammar language that resembles extended BNF.

Ohm offers more flexibility in grammar definition and better support for incremental parsing, making it suitable for complex language processing tasks. However, this flexibility comes at the cost of a steeper learning curve for newcomers.

Nearley, on the other hand, is generally easier to get started with and may offer better performance for simpler grammars. It also provides built-in support for ambiguous grammars, which can be useful in certain scenarios.

Ultimately, the choice between Nearley and Ohm depends on the specific requirements of your project and your familiarity with parser generators.

Pros of Chevrotain

• Better performance, especially for large inputs
• More flexible and customizable parsing options
• Extensive documentation and examples

Cons of Chevrotain

• Steeper learning curve
• More verbose syntax for grammar definition
• Requires more boilerplate code

Code Comparison

Nearley grammar example:

expression -> number "+" number {% ([a, _, b]) => a + b %}
number -> [0-9]:+ {% ([digits]) => parseInt(digits.join("")) %}

Chevrotain grammar example:

const Expression = createToken({ name: "Expression", pattern: Lexer.NA });
const Plus = createToken({ name: "Plus", pattern: /\+/ });
const Number = createToken({ name: "Number", pattern: /[0-9]+/ });

class Calculator extends CstParser {
  constructor() {
    super([Expression, Plus, Number]);
    this.RULE("expression", () => {
      this.CONSUME(Number);
      this.CONSUME(Plus);
      this.CONSUME(Number);
    });
  }
}

Nearley uses a more concise syntax for grammar definition, while Chevrotain requires more setup but offers greater flexibility and control over the parsing process. Chevrotain's approach may be more familiar to developers used to object-oriented programming, while Nearley's syntax is closer to traditional BNF notation.

Pros of Jison

• More mature and widely adopted project with a larger community
• Supports both LR and LALR parsing algorithms
• Offers a command-line interface for easier integration into build processes

Cons of Jison

• Less active development in recent years
• Steeper learning curve for beginners
• Limited support for streaming input

Code Comparison

Jison:

%lex
%%
\s+                   /* skip whitespace */
[0-9]+("."[0-9]+)?    return 'NUMBER'
"+"                   return '+'
"-"                   return '-'
"*"                   return '*'
"/"                   return '/'

Nearley:

@{%
const moo = require("moo");
const lexer = moo.compile({
  ws:     /[ \t]+/,
  number: /[0-9]+(?:\.[0-9]+)?/,
  plus:   '+',
  minus:  '-',
  times:  '*',
  divide: '/'
});
%}

@lexer lexer

Both Jison and Nearley are popular parser generators for JavaScript. Jison is more established and offers multiple parsing algorithms, while Nearley is newer and focuses on ease of use. Jison's syntax is more similar to Bison, while Nearley uses a custom grammar format with JavaScript integration. The code examples show how lexical rules are defined in each system, with Jison using a more compact syntax and Nearley leveraging the Moo lexer library for tokenization.