import { TONLDocument } from 'tonl';

// Create from JSON
const doc = TONLDocument.fromJSON({
  users: [{ name: 'Alice', age: 30 }]
});

// Query
const result = doc.query('users[*].name');

// Modify
doc.set('users[0].age', 31);

// Save
await doc.save('data.tonl');

@schema v1
@strict true

User: obj
  id: u32 required
  username: str required min:3 max:20
  email: str required pattern:email
  age: u32? min:13 max:150
  roles: list<str> required

users: list<User> required min:1

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

// Load and parse schema
const schema = parseSchema(schemaContent);

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

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

import { createEncodeStream } from 'tonl/stream';
import { createReadStream, createWriteStream } from 'fs';

// Stream encode large JSON files
createReadStream('huge.json')
  .pipe(createEncodeStream({ smart: true }))
  .pipe(createWriteStream('huge.tonl'));

import { streamQuery } from 'tonl/stream';

// Query huge files efficiently
await streamQuery(
  'large-dataset.tonl',
  'users[?(@.active)]',
  (chunk) => {
    // Process each matching chunk
    console.log(chunk);
  }
);

// Memory stays constant ~10MB

import { AdaptiveOptimizer } from 'tonl';

// Create optimizer
const optimizer = new AdaptiveOptimizer();

// Analyze dataset
const analysis = optimizer.analyzeDataset(data);
console.log(`Estimated savings: ${analysis.estimatedSavings}%`);

// Apply optimization
const result = optimizer.optimize(data);
console.log(`Directives: ${result.directives.length}`);

import { TONLDocument } from 'tonl';

const doc = TONLDocument.fromJSON({ users: [...], orders: [...] });

// Count users
doc.count('users[*]');                    // 42

// Sum order totals
doc.sum('orders[*]', 'total');           // 15420.50

// Average age
doc.avg('users[*]', 'age');             // 29.5

// Group by country
doc.groupBy('users[*]', 'country');    // { TR: [...], US: [...] }

// Chained operations
doc.aggregate('users[*]')
  .filter(u => u.active)
  .orderBy('age', 'desc')
  .take(10)
  .toArray();

const stats = doc.aggregate('products[*]').stats('price');
// Returns:
// {
//   count: 150,
//   sum: 7499.50,
//   avg: 49.99,
//   min: 9.99,
//   max: 999.99,
//   variance: 12500.25,
//   stdDev: 111.80
// }

import {
  levenshteinDistance,
  fuzzyMatch,
  soundsLike,
  fuzzySearch
} from 'tonl/query/fuzzy-matcher';

// Levenshtein distance
levenshteinDistance('kitten', 'sitting');  // 3

// Fuzzy match with threshold
fuzzyMatch('John', 'Jon', { threshold: 0.8 });  // true

// Phonetic matching
soundsLike('Smith', 'Smyth');  // true

// Search with ranking
fuzzySearch('JavaScrpt', ['JavaScript', 'TypeScript', 'Python']);
// [{ value: 'JavaScript', similarity: 0.9, index: 0 }]

// Events in the last 7 days
doc.query('events[?(@.date > @now-7d)]');

// Orders from today
doc.query('orders[?(@.createdAt sameDay @today)]');

// Logs before a specific date
doc.query('logs[?(@.timestamp before @2025-01-01)]');

// Tasks due this week
doc.query('tasks[?(@.dueDate sameWeek @now)]');

// Records older than 3 months
doc.query('records[?(@.date daysAgo 90)]');

import {
  parseTemporalLiteral,
  isBefore,
  isAfter,
  isSameDay
} from 'tonl/query/temporal-evaluator';

// Parse temporal literal
const lastWeek = parseTemporalLiteral('@now-7d');
console.log(lastWeek.timestamp);  // Unix timestamp

// Compare dates
isBefore(new Date('2025-01-01'), new Date('2025-12-31'));  // true
isAfter(new Date('2025-12-31'), new Date('2025-01-01'));   // true
isSameDay(new Date(), new Date());  // true