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PetitParser is a dynamic parser framework for Dart that enables developers to build efficient, reusable grammars and parsers with minimal effort. It supports a fluent API for defining parsing rules and is optimized for performance, making it ideal for processing structured text such as configuration files, domain-specific languages, or data formats. The framework is highly modular and extensible, allowing custom parsing logic to be composed easily. With support across all major platforms, PetitParser is suitable for both client-side and server-side applications requiring robust text analysis.
Use cases
Parsing configuration files
Implementing domain-specific languages
Processing structured data formats
Building code analyzers
Creating custom DSLs
Key features
Fluent grammar definition API
High performance parsing
Modular and composable rules
Cross-platform compatibility
Support for recursive grammars
Extensible plugin system
Suitable for
Developers building custom parsers
Teams working with structured text input
Applications requiring DSL support
Projects needing efficient text processing
Considerations
Steeper learning curve for beginners
Requires understanding of parsing concepts
Limited built-in support for error recovery
Best suited for complex parsing tasks over simple string operations
Original README
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PetitParser for Dart
PetitParser makes writing parsers in Dart fast, enjoyable, and fully type-safe.
Instead of writing fragile regular expressions or configuring complex external code generators, PetitParser lets you build parsers directly in plain Dart code. You assemble small, specialized parsers like LEGO bricks to model everything from simple configuration values to full programming languages.
✨ Why PetitParser?
🧩 Composable: Combine simple parsers into rich grammars using familiar operators and methods.
🛡️ Type-Safe: Take advantage of modern Dart records, generics, and pattern matching without casting dynamic types.
⚡ Fast & Efficient: Optimized character predicates and dedicated fast-path parsing keep execution blazing fast.
🔍 Debuggable: Step through parsing in your IDE, inspect tokens, and visualize execution trees with built-in tools.
🛠️ Extensible: Transform raw text directly into strongly typed models, syntax trees, or domain objects on the fly.
🌐 Open Source & Battle-Tested: Highly tested, well-documented, and trusted across production Dart and Flutter applications.
🚀 Quick Start
Add PetitParser to your Dart or Flutter project:
dart pub add petitparser
Import the package, assemble your parser, and parse key-value pairs:
import'package:petitparser/petitparser.dart';
voidmain() {
// 1. Match a key of one or more letters:final key = letter().plus().flatten();
// 2. Match a numeric value and convert it directly into an integer:final value = digit().plus().flatten().map(int.parse);
// 3. Combine them: match key, discard '=', and match value:final entry = key.trim().skip(after: char('=')).then(value.trim());
// 4. Transform the parsed pair into a typed Dart record:final parser = entry.map2((k, v) => (key: k, value: v));
// 5. Parse the input:final result = parser.parse('port = 8080');
print(result.value); // (key: port, value: 8080)
}
Notice what happened here:
letter().plus() matched consecutive letters, and .flatten() turned them into a String.
digit().plus() matched consecutive digits, and .map(int.parse) transformed them immediately into an int.
.skip(after: char('=')) consumed the separator without cluttering the result.
.then(...) combined both parts into a strongly typed record (String, int).
.map2(...) mapped both positional values into a readable named record.
🧩 Core Building Blocks
Every grammar in PetitParser is constructed from three fundamental concepts: matching text, combining parsers, and transforming results.
🔡 Matching Text
Primitive parsers recognize basic character patterns:
char('a') matches an exact single character:
char('a').parse('a').value; // 'a'
string('dart') matches an entire string:
string('dart').parse('dart').value; // 'dart'
digit() matches any digit from 0 to 9:
digit().parse('7').value; // '7'
letter() matches any uppercase or lowercase letter:
letter().parse('x').value; // 'x'
word() matches a letter, digit, or underscore:
word().parse('_').value; // '_'
whitespace() matches spaces, tabs, and newlines:
whitespace().parse(' ').value; // ' '
pattern('0-9a-fA-F') matches any character within a range:
pattern('0-9a-fA-F').parse('f').value; // 'f'
any() matches any character:
any().parse('!').value; // '!'
Most character parsers accept optional parameters such as ignoreCase: true for case-insensitive matching and unicode: true for full Unicode code-point support.
🔗 Combining Parsers
Snap individual parsers together to recognize structured input:
Sequences: Run parsers in order. letter().then(digit()) returns a typed Dart record with each result:
Calling parse on a string returns a Result. You can inspect the outcome using Dart pattern matching:
final parser = digit().plus().flatten().map(int.parse);
voidhandleResult(Result<int> result) {
switch (result) {
caseSuccess(value: final value):
print('Parsed $value');
caseFailure(message: final message, position: final position):
print('Error at $position: $message');
}
}
handleResult(parser.parse('123')); // Parsed 123handleResult(parser.parse('abc')); // Error at 0: digit expected
If you only need to know whether an input string conforms to your grammar, use accept:
if (parser.accept('123')) {
print('Valid input');
}
To extract all matching occurrences across a larger body of text, use allMatches:
final words = letter().plus().flatten();
final matches = words.allMatches('two words 123');
print(matches); // ('two', 'words')
🛠️ Practical Examples
📋 Delimited Lists
This example parses a comma-separated list of integers like '1, 2, 3' into a Dart List<int>:
final number = digit().plus().flatten().map(int.parse);
final numbers = number
.plusSeparated(char(',').trim())
.map((list) => list.elements);
final result = numbers.parse('1, 2, 3');
print(result.value); // [1, 2, 3]
list.elements gives you a typed List<int> containing only the parsed numbers, neatly dropping the comma characters.
🧮 Expression Builder
This example parses and evaluates mathematical expressions containing numbers, parentheses, negation, exponentiation, multiplication, division, addition, and subtraction:
This example parses nested JSON-style arrays of numbers like '[1, [2, 3], 4]' into a hierarchy of Dart lists:
final value = undefined<Object>();
// An array contains zero or more values separated by commas:final array = char('[')
.trim()
.then(value.starSeparated(char(',').trim()))
.then(char(']').trim())
.map3((open, elements, close) => elements.elements);
final number = digit().plus().flatten().map(int.parse);
// Wire the recursive definition into the placeholder:
value.set([number, array].toChoiceParser());
final parser = value.end();
print(parser.parse('[1, [2, 3], 4]').value); // [1, [2, 3], 4]
🏛️ Large Grammars
When a grammar grows to dozens or hundreds of productions, organizing rules as separate variables can become difficult to maintain. Subclassing GrammarDefinition lets you organize rules as methods on a class, resolving complex mutual recursions cleanly.
This example parses and evaluates arithmetic expressions using a modular, strongly typed grammar definition:
You can also build a parser starting from any specific production rule in the grammar using buildFrom:
final numberParser = definition.buildFrom(ref0(definition.number));
print(numberParser.parse('42').value); // 42
Organizing grammars this way makes them easy to navigate, refactor, and test production by production in your IDE.
🔬 Advanced Capabilities
📍 Source Positions and Tokens
If you are writing a compiler, linter, or syntax highlighter, you often need to know exactly where in the source file an element appeared. Wrap any parser with .token() to capture its start and stop offsets, line number, and column number:
final id = letter().plus().flatten().token();
final token = id.parse('hello').value;
print(token.value); // 'hello'print(token.start); // 0print(token.stop); // 5print(token.line); // 1print(token.column); // 1
🔭 Lookaheads and Semantic Guards
You can inspect the upcoming input stream without consuming characters:
parser.and() performs positive lookahead, succeeding only if parser matches next without advancing the input position.
parser.not() performs negative lookahead, succeeding only if parser fails to match next.
parser.where(predicate) rejects a match dynamically if a condition is not met.
For example, match a keyword like let only when it is not immediately followed by more word characters:
final keyword = string('let').skip(after: word().not());
print(keyword.parse('let').value); // 'let'print(keyword.accept('letter')); // false
⏳ Lazy Repetition
Standard repetition combinators like star() are possessive and consume as much input as possible. When matching delimited content like multi-line comments or quoted strings, use starLazy or plusLazy to stop as soon as a boundary parser succeeds:
Grammars can contain subtle issues such as unreachable branches, infinite loops, or accidental left-recursions. PetitParser provides a built-in linter in package:petitparser/reflection.dart that you can run in your tests:
For performance tuning, import package:petitparser/debug.dart and use profile(parser) to measure invocation counts and execution time per parser, or progress(parser) to inspect backtracking behavior.
📚 Resources
Website: Interactive web demos and ports to other languages.
Examples Repository: Full implementations for JSON, Lisp, Math, Smalltalk, and more.
📜 History
Grammars for programming languages are traditionally specified statically. They are hard to compose and reuse due to ambiguities that inevitably arise. PetitParser combines ideas from scannerless parsing, parser combinators, parsing expression grammars (PEG), and packrat parsers to model grammars and parsers as objects that can be reconfigured dynamically.
PetitParser was originally created in Smalltalk. Later on, as a way to learn and explore these platforms, I reimplemented PetitParser in Java and Dart. All implementations share a consistent architecture while adopting the idioms and modern best practices of each target language.