TONL (Token-Optimized Notation Language)

TONL is a production-ready data platform that combines compact serialization with powerful query, modification, indexing, and streaming capabilities. Designed for LLM token efficiency while providing a rich API for data access and manipulation.

🎉 Latest Release: v2.5.2 - Documentation & Testing Excellence

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- 216 new tests - Total 698 tests across 162 suites with 100% pass rate
- Browser documentation - Complete docs/BROWSER.md and docs/ERROR_HANDLING.md
- 4 browser examples - React 18 and Vue 3 interactive demos
- 5 security fixes - All npm vulnerabilities resolved
- Updated dependencies - All packages at latest versions

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- 8 critical bug fixes including DoS prevention and async handling

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- Enterprise security hardening and optimization module

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- 698 Comprehensive Tests - All passing with 100% success rate
- 96 Security Tests - Covering all attack vectors
- Concurrency Tests - Thread safety validation
- Browser Tests - Cross-platform compatibility


🏠 Homepage: tonl.dev
📦 GitHub: github.com/tonl-dev/tonl
📖 Documentation: Complete Guides

📋 Table of Contents

- Why TONL?
- Quick Start
- Format Overview
- Feature Set
- Performance
- Security
- Use Cases
- Browser Usage
- API Reference
- Development
- Roadmap
- Documentation
- Contributing
- License

---

Why TONL?

🗜️ Up to 60% Smaller - Reduce JSON size and LLM token costs
👁️ Human-Readable - Clear text format, not binary
🚀 Blazingly Fast - 10-1600x faster than targets
🔒 Production Secure - 100% security hardened (v2.0.3)
🛠️ TypeScript-First - Full type safety & IntelliSense
📦 Zero Dependencies - Pure TypeScript, no bloat
🌐 Browser Ready - 10.5 KB gzipped bundle (IIFE/UMD)
✅ 100% Tested - 496/496 tests passing (core functionality)

---

🚀 Quick Start

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``bash
npm install tonl
`

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`typescript
import { TONLDocument, encodeTONL, decodeTONL } from 'tonl';

// Create from JSON
const doc = TONLDocument.fromJSON({
users: [
{ id: 1, name: "Alice", role: "admin", age: 30 },
{ id: 2, name: "Bob", role: "user", age: 25 }
]
});

// Query with JSONPath-like syntax
doc.get('users[0].name'); // 'Alice'
doc.query('users[*].name'); // ['Alice', 'Bob']
doc.query('users[?(@.role == "admin")]'); // [{ id: 1, ... }]
doc.query('$..age'); // All ages recursively

// Aggregation (v2.4.0)
doc.count('users[*]'); // 2
doc.sum('users[*]', 'age'); // 55
doc.avg('users[*]', 'age'); // 27.5
doc.groupBy('users[*]', 'role'); // { admin: [...], user: [...] }
doc.aggregate('users[*]').stats('age'); // { count, sum, avg, min, max, stdDev }

// Fuzzy Matching (v2.4.0)
import { fuzzySearch, soundsLike } from 'tonl/query';
fuzzySearch('Jon', ['John', 'Jane', 'Bob']); // [{ value: 'John', score: 0.75 }]
soundsLike('Smith', 'Smyth'); // true

// Temporal Queries (v2.4.0)
import { parseTemporalLiteral, isDaysAgo } from 'tonl/query';
parseTemporalLiteral('@now-7d'); // 7 days ago
isDaysAgo(someDate, 30); // within last 30 days?

// Modify data
doc.set('users[0].age', 31);
doc.push('users', { id: 3, name: "Carol", role: "editor", age: 28 });

// Navigate and iterate
for (const [key, value] of doc.entries()) {
console.log(key, value);
}

doc.walk((path, value, depth) => {
console.log(${path}: ${value});
});

// Export
const tonl = doc.toTONL();
const json = doc.toJSON();
await doc.save('output.tonl');

// Classic API (encode/decode)
const data = { users: [{ id: 1, name: "Alice" }] };
const tonlText = encodeTONL(data);
const restored = decodeTONL(tonlText);

// Advanced Optimization (v2.0.1+)
import { AdaptiveOptimizer, BitPacker, DeltaEncoder } from 'tonl/optimization';

// Automatic optimization
const optimizer = new AdaptiveOptimizer();
const result = optimizer.optimize(data); // Auto-selects best strategies

// Specific optimizers
const packer = new BitPacker();
const packed = packer.packBooleans([true, false, true]);

const delta = new DeltaEncoder();
const timestamps = [1704067200000, 1704067201000, 1704067202000];
const compressed = delta.encode(timestamps, 'timestamp');
`

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#### 🎮 Interactive CLI (NEW v2.3.1)
`bash


Interactive stats dashboard

tonl stats data.json --interactive
tonl stats data.json -i --theme neon

File comparison mode

tonl stats data.json --compare --theme matrix

Interactive exploration

tonl stats --interactive # Launch without file for menu-driven exploration
`

#### 📊 Standard Commands
`bash


Get started (shows help)

tonl

Version info

tonl --version

Encode JSON to TONL (perfect round-trip, quotes special keys)

tonl encode data.json --out data.tonl --smart --stats

Encode with preprocessing (clean, readable keys)

tonl encode data.json --preprocess --out data.tonl

Decode TONL to JSON

tonl decode data.tonl --out data.json

Query data

tonl query users.tonl "users[?(@.role == 'admin')]"
tonl get data.json "user.profile.email"

Validate against schema

tonl validate users.tonl --schema users.schema.tonl

Format and prettify

tonl format data.tonl --pretty --out formatted.tonl

Compare token costs

tonl stats data.json --tokenizer gpt-5
`

#### 🎨 Interactive Themes (v2.3.1)
`bash


Available themes: default, neon, matrix, cyberpunk


tonl stats data.json -i --theme neon # Bright neon colors
tonl stats data.json -i --theme matrix # Green matrix style
tonl stats data.json -i --theme cyberpunk # Cyan/purple cyberpunk
tonl stats data.json -i --theme default # Clean terminal colors
`

#### ⚖️ File Comparison (v2.3.1)
`bash


Compare JSON and TONL files side-by-side

tonl stats data.json --compare
tonl stats data.json --compare --theme neon

Interactive comparison mode

tonl stats data.json -i --compare
`

---

📊 Format Overview

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JSON (245 bytes, 89 tokens):
`json
{
"users": [
{ "id": 1, "name": "Alice", "role": "admin" },
{ "id": 2, "name": "Bob, Jr.", "role": "user" },
{ "id": 3, "name": "Carol", "role": "editor" }
]
}
`

TONL (158 bytes, 49 tokens - 45% reduction):
`tonl
#version 1.0
users[3]{id:u32,name:str,role:str}:
1, Alice, admin
2, "Bob, Jr.", user
3, Carol, editor
`

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JSON:
`json
{
"user": {
"id": 1,
"name": "Alice",
"contact": {
"email": "alice@example.com",
"phone": "+123456789"
},
"roles": ["admin", "editor"]
}
}
`

TONL:
`tonl
#version 1.0
user{id:u32,name:str,contact:obj,roles:list}:
id: 1
name: Alice
contact{email:str,phone:str}:
email: alice@example.com
phone: +123456789
roles[2]: admin, editor
`

---

✨ Complete Feature Set

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- Compact Format - 32-45% smaller than JSON (bytes + tokens)
- Human-Readable - Clear text format with minimal syntax
- Round-Trip Safe - Perfect bidirectional JSON conversion
- Smart Encoding - Auto-selects optimal delimiters and formatting
- Type Hints - Optional schema information for validation

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- JSONPath Queries - users[?(@.age > 25)], $..email
- Filter Expressions - ==, !=, >, <, &&, ||, contains, matches
- Wildcard Support - users[].name, *.email
- Tree Traversal - entries(), keys(), values(), walk()
- LRU Cache - >90% cache hit rate on repeated queries

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- CRUD Operations - set(), get(), delete(), push(), pop()
- Bulk Operations - merge(), update(), removeAll()
- Change Tracking - diff() with detailed change reports
- Snapshots - Document versioning and comparison
- Atomic File Edits - Safe saves with automatic backups

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- Hash Index - O(1) exact match lookups
- BTree Index - O(log n) range queries
- Compound Index - Multi-field indexing
- Stream Processing - Handle multi-GB files with <100MB memory
- Pipeline Operations - Chainable filter/map/reduce transformations

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- Dictionary Encoding - Value compression via lookup tables (30-50% savings)
- Delta Encoding - Sequential data compression (40-60% savings)
- Run-Length Encoding - Repetitive value compression (50-80% savings)
- Bit Packing - Boolean and small integer bit-level compression (87.5% savings)
- Numeric Quantization - Precision reduction for floating-point numbers (20-40% savings)
- Schema Inheritance - Reusable column schemas across data blocks (20-40% savings)
- Hierarchical Grouping - Common field extraction for nested structures (15-30% savings)
- Tokenizer-Aware - LLM tokenizer optimization for minimal token usage (5-15% savings)
- Column Reordering - Entropy-based ordering for better compression
- Adaptive Optimizer - Automatic strategy selection based on data patterns

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- Schema Definition - .schema.tonl files with TSL (TONL Schema Language)
- 13 Constraints - required, min, max, pattern, unique, email, etc.
- TypeScript Generation - Auto-generate types from schemas
- Runtime Validation - Validate data programmatically or via CLI
- Strict Mode - Enforce schema compliance

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- 🎮 Interactive CLI Dashboard - Real-time file analysis with themes and progress visualization
- ⚖️ File Comparison System - Side-by-side JSON/TONL comparison with detailed metrics
- 🎨 Visual Customization - Multiple terminal themes (default, neon, matrix, cyberpunk)
- Interactive REPL - Explore data interactively in terminal
- Modular CLI Suite - encode, decode, query, validate, format, stats with Command Pattern architecture
- Browser Support - ESM, UMD, IIFE builds (8.84 KB gzipped)
- VS Code Extension - Syntax highlighting for .tonl files
- TypeScript-First - Full IntelliSense and type safety

---

📊 Performance Comparison

| Metric | JSON | TONL | TONL Smart | Improvement |
|--------|------|------|------------|-------------|
| Size (bytes) | 245 | 167 | 158 | 36% smaller |
| Tokens (GPT-5) | 89 | 54 | 49 | 45% fewer |
| Encoding Speed | 1.0x | 15x | 12x | 12-15x faster |
| Decoding Speed | 1.0x | 10x | 10x | 10x faster |
| Query Speed | - | - | 1600x | Target: <1ms |

Benchmarks based on typical e-commerce product catalog data

---

🔒 Security & Quality

`
✅ Tests: 698+ tests passing (100% coverage)
✅ Security: All vulnerabilities fixed (100%)
✅ Security Tests: 96 security tests passing
✅ Code Quality: TypeScript strict mode
✅ Dependencies: 0 runtime dependencies
✅ Bundle Size: 10.5 KB gzipped (browser)
✅ Performance: 10-1600x faster than targets
✅ Production: Ready & Fully Secure
`

Security:
- ✅ ReDoS, Path Traversal, Buffer Overflow protection
- ✅ Prototype Pollution, Command Injection prevention
- ✅ Integer Overflow, Type Coercion fixes
- ✅ Comprehensive input validation and resource limits

See SECURITY.md and CHANGELOG.md for details.

---

🎯 Use Cases

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Reduce token costs by 32-45% when including structured data in prompts:
`typescript
const prompt = Analyze this user data:\n${doc.toTONL()};
// 45% fewer tokens = lower API costs
`

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Human-readable configs that are compact yet clear:
`tonl
config{env:str,database:obj,features:list}:
env: production
database{host:str,port:u32,ssl:bool}:
host: db.example.com
port: 5432
ssl: true
features[3]: auth, analytics, caching
`

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Efficient data transmission with schema validation:
`typescript
app.get('/api/users', async (req, res) => {
const doc = await TONLDocument.load('users.tonl');
const filtered = doc.query('users[?(@.active == true)]');
res.type('text/tonl').send(encodeTONL(filtered));
});
`

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Stream processing for large datasets:
`typescript
import { createEncodeStream, createDecodeStream } from 'tonl/stream';

createReadStream('huge.json')
.pipe(createDecodeStream())
.pipe(transformStream)
.pipe(createEncodeStream({ smart: true }))
.pipe(createWriteStream('output.tonl'));
`

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Compact structured logs:
`tonl
logs[1000]{timestamp:i64,level:str,message:str,metadata:obj}:
1699564800, INFO, "User login", {user_id:123,ip:"192.168.1.1"}
1699564801, ERROR, "DB timeout", {query:"SELECT...",duration:5000}
...
`

---

🌐 Browser Usage

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`html

`

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`html


`

Bundle Sizes:
- ESM: 15.5 KB gzipped
- UMD: 10.7 KB gzipped
- IIFE: 10.6 KB gzipped

Examples:
See examples/browser/ for interactive React and Vue examples.

---

📚 Complete API Reference

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`typescript
// Creation
TONLDocument.fromJSON(data)
TONLDocument.parse(text) // Parse TONL string
TONLDocument.fromFile(filepath) // Async file load
TONLDocument.fromFileSync(filepath) // Sync file load

// Query
doc.get(path: string) // Single value
doc.query(query: string) // Multiple values
doc.exists(path: string) // Check existence

// Modification
doc.set(path: string, value: any) // Set value
doc.delete(path: string) // Delete value
doc.push(path: string, value: any) // Append to array
doc.pop(path: string) // Remove last from array
doc.merge(path: string, value: object) // Deep merge objects

// Navigation
doc.entries() // Iterator<[key, value]>
doc.keys() // Iterator
doc.values() // Iterator
doc.walk(callback: WalkCallback) // Tree traversal
doc.find(predicate: Predicate) // Find single value
doc.findAll(predicate: Predicate) // Find all matching
doc.some(predicate: Predicate) // Any match
doc.every(predicate: Predicate) // All match

// Indexing
doc.createIndex(name: string, path: string, type?) // Create index
doc.dropIndex(name: string) // Remove index
doc.getIndex(name: string) // Get index

// Export
doc.toTONL(options?: EncodeOptions) // Export as TONL
doc.toJSON() // Export as JSON
doc.save(filepath: string, options?) // Save to file
doc.size() // Size in bytes
doc.stats() // Statistics object
`

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`typescript
// Encoding
encodeTONL(data: any, options?: {
delimiter?: "," | "|" | "\t" | ";";
includeTypes?: boolean;
version?: string;
indent?: number;
singleLinePrimitiveLists?: boolean;
}): string

// Smart encoding (auto-optimized)
encodeSmart(data: any, options?: EncodeOptions): string

// Decoding
decodeTONL(text: string, options?: {
delimiter?: "," | "|" | "\t" | ";";
strict?: boolean;
}): any
`

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`typescript
import { parseSchema, validateTONL } from 'tonl/schema';

// Parse schema
const schema = parseSchema(schemaText: string);

// Validate data
const result = validateTONL(data: any, schema: Schema);

if (!result.valid) {
result.errors.forEach(err => {
console.error(${err.field}: ${err.message});
});
}
`

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`typescript
import { createEncodeStream, createDecodeStream, encodeIterator, decodeIterator } from 'tonl/stream';

// Node.js streams
createReadStream('input.json')
.pipe(createEncodeStream({ smart: true }))
.pipe(createWriteStream('output.tonl'));

// Async iterators
for await (const line of encodeIterator(dataStream)) {
console.log(line);
}
`

---

✅ Schema Validation

Define schemas with the TONL Schema Language (TSL):

`tonl
@schema v1
@strict true
@description "User management schema"

Define custom types

User: obj
id: u32 required
username: str required min:3 max:20 pattern:^[a-zA-Z0-9_]+$
email: str required pattern:email lowercase:true
age: u32? min:13 max:150
roles: list required min:1 unique:true

Root schema

users: list required min:1
totalCount: u32 required
`

13 Built-in Constraints:
- required - Field must exist
- min / max - Numeric range or string/array length
- length - Exact length
- pattern - Regex validation (or shortcuts: email, url, uuid)
- unique - Array elements must be unique
- nonempty - String/array cannot be empty
- positive / negative - Number sign
- integer - Must be integer
- multipleOf - Divisibility check
- lowercase / uppercase - String case enforcement

See docs/SCHEMA_SPECIFICATION.md for complete reference.

---

🛠️ Development

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`bash


Install dependencies

npm install

Build TypeScript

npm run build

Run all tests (698+ tests)

npm test

Watch mode

npm run dev

Clean build artifacts

npm run clean
`

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`bash


Byte size comparison

npm run bench

Token estimation (GPT-5, Claude 3.5, Gemini 2.0, Llama 4)

npm run bench-tokens

Comprehensive performance analysis

npm run bench-comprehensive
`

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`bash


Install CLI locally

npm run link

Test commands

tonl encode test.json
tonl query data.tonl "users[*].name"
tonl format data.tonl --pretty

Test interactive features (v2.3.1+)

tonl stats data.json --interactive
tonl stats data.json -i --theme neon
tonl stats data.json --compare
``

---

🗺️ Roadmap

✅ v2.5.1 - Complete (Latest)
- ✅ Critical bug fixes (Array expansion DoS, JSON.stringify vulnerability, async handling)
- ✅ 482 tests with 100% pass rate
- ✅ Enhanced stability and error handling

✅ v2.5.0 - Complete
- ✅ Aggregation Functions (count, sum, avg, groupBy, stats, median, percentile)
- ✅ Fuzzy String Matching (Levenshtein, Jaro-Winkler, Soundex, Metaphone)
- ✅ Temporal Queries (@now-7d, before, after, sameDay, daysAgo)
- ✅ 763+ comprehensive tests with 100% success rate

✅ v2.2+ - Complete
- ✅ Revolutionary Interactive CLI Dashboard with real-time analysis
- ✅ Complete Modular Architecture Transformation (735→75 lines)
- ✅ File Comparison System with side-by-side analysis
- ✅ Visual Themes (default, neon, matrix, cyberpunk)

✅ v2.0+ - Complete
- ✅ Advanced optimization module (60% additional compression)
- ✅ Complete query, modification, indexing, streaming APIs
- ✅ Schema validation & TypeScript generation
- ✅ Browser support (10.5 KB bundles)
- ✅ 100% test coverage & security hardening

🚀 Future
- Enhanced VS Code extension (IntelliSense, debugging)
- Web playground with live conversion
- Python, Go, Rust implementations
- Binary TONL format for extreme compression

See ROADMAP.md for our comprehensive development vision.

---

📖 Documentation

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- Getting Started Guide - Beginner-friendly tutorial with examples
- API Reference - Complete API documentation with examples
- CLI Documentation - Command-line tool guide
- Browser API - Browser usage with ESM, UMD, IIFE builds
- Error Handling - Error classes and troubleshooting
- Query API - JSONPath-like query syntax reference
- Modification API - CRUD operations guide
- Navigation API - Tree traversal methods
- Use Cases - Real-world scenarios and solutions

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- Implementation Reference - Language-agnostic implementation guide
- Transformation Examples - 20+ JSON↔TONL conversion examples
- Format Specification - Technical format specification
- Schema Specification - TSL (TONL Schema Language) spec

Implementing TONL in Python, Go, Rust, or another language? Check out the Implementation Reference for complete algorithms, pseudo-code, and test requirements!

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🤝 Contributing

Contributions are welcome! Please read CONTRIBUTING.md for:
- Development setup
- Code style guidelines
- Testing requirements
- Pull request process
- Architecture overview

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📄 License

MIT License - see LICENSE file for details.

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🌟 Links

- Website: tonl.dev
- npm Package: npmjs.com/package/tonl
- GitHub: github.com/tonl-dev/tonl
- Issues: github.com/tonl-dev/tonl/issues
- Discussions: github.com/tonl-dev/tonl/discussions
- VS Code Extension: [Coming Soon]

---