#!/usr/bin/env python3
"""
Reverse-engineer Google's date formatting patterns by scraping reviews in English
"""
import json
from modules.fast_scraper import fast_scrape_reviews

url = "https://www.google.com/maps/place/Soho+Club/data=!4m7!3m6!1s0x46dd947294b213bf:0x864c7a232527adb4!8m2!3d54.67869!4d25.2667181!16s%2Fg%2F1thhj5ml!19sChIJvxOylHKU3UYRtK0nJSN6TIY?authuser=0&hl=en&rclk=1"

print("Scraping reviews in English...")
result = fast_scrape_reviews(url, headless=True)

reviews = result.get('reviews', [])
print(f"\nExtracted {len(reviews)} reviews")

if reviews:
    # Collect all unique date strings
    date_strings = set()
    for rev in reviews:
        date_text = rev.get('date_text')
        if date_text:
            date_strings.add(date_text)

    print(f"\nFound {len(date_strings)} unique date formats:")
    for ds in sorted(date_strings):
        print(f"   '{ds}'")

    # Analyze patterns
    print("\n" + "="*80)
    print("PATTERN ANALYSIS:")
    print("="*80)

    patterns = {
        'seconds': [],
        'minutes': [],
        'hours': [],
        'days': [],
        'weeks': [],
        'months': [],
        'years': []
    }

    for ds in date_strings:
        ds_lower = ds.lower()
        if 'second' in ds_lower:
            patterns['seconds'].append(ds)
        elif 'minute' in ds_lower:
            patterns['minutes'].append(ds)
        elif 'hour' in ds_lower:
            patterns['hours'].append(ds)
        elif 'day' in ds_lower:
            patterns['days'].append(ds)
        elif 'week' in ds_lower:
            patterns['weeks'].append(ds)
        elif 'month' in ds_lower:
            patterns['months'].append(ds)
        elif 'year' in ds_lower:
            patterns['years'].append(ds)

    for unit, examples in sorted(patterns.items()):
        if examples:
            print(f"\n{unit.upper()} ({len(examples)} patterns):")
            for ex in sorted(examples):
                print(f"   '{ex}'")

    # Identify the specific patterns
    print("\n" + "="*80)
    print("GOOGLE MAPS DATE FORMAT PATTERNS (English):")
    print("="*80)

    print("\nPattern Structure:")
    print("-" * 80)

    single_unit_patterns = []  # "a month ago"
    plural_patterns = []        # "3 months ago"

    for ds in sorted(date_strings):
        if ds.startswith('a '):
            single_unit_patterns.append(ds)
        elif ds.split()[0].isdigit():
            plural_patterns.append(ds)

    print(f"\nSingular (a X ago): {len(single_unit_patterns)} patterns")
    for p in sorted(single_unit_patterns):
        print(f"   '{p}'")

    print(f"\nPlural (N Xs ago): {len(plural_patterns)} patterns")
    for p in sorted(plural_patterns):
        print(f"   '{p}'")

    # Determine time ranges
    print("\n" + "="*80)
    print("TIME RANGE BOUNDARIES:")
    print("="*80)

    # Extract numbers from plural patterns
    import re
    from collections import defaultdict

    unit_values = defaultdict(list)
    for ds in date_strings:
        match = re.match(r'(\d+)\s+(\w+)\s+ago', ds.lower())
        if match:
            number = int(match.group(1))
            unit = match.group(2).rstrip('s')  # Remove plural 's'
            unit_values[unit].append(number)

    for unit, values in sorted(unit_values.items()):
        if values:
            print(f"\n{unit.upper()}:")
            print(f"   Range: {min(values)} - {max(values)}")
            print(f"   Values found: {sorted(set(values))}")

    # Save analysis
    output = {
        'total_reviews': len(reviews),
        'unique_date_formats': len(date_strings),
        'all_date_strings': sorted(list(date_strings)),
        'patterns_by_unit': {k: sorted(v) for k, v in patterns.items() if v},
        'singular_patterns': sorted(single_unit_patterns),
        'plural_patterns': sorted(plural_patterns),
        'value_ranges': {unit: {'min': min(values), 'max': max(values), 'values': sorted(set(values))}
                        for unit, values in unit_values.items() if values}
    }

    with open('/tmp/google_date_patterns_english.json', 'w') as f:
        json.dump(output, f, indent=2)

    print("\n" + "="*80)
    print("Analysis saved to: /tmp/google_date_patterns_english.json")
    print("="*80)

    # Now let's determine the EXACT library/algorithm Google uses
    print("\n" + "="*80)
    print("REVERSE-ENGINEERING GOOGLE'S ALGORITHM:")
    print("="*80)

    print("\nBased on the patterns, Google's relative date formatter:")
    print("-" * 80)

    print("\n1. FORMAT STRUCTURE:")
    print("   Single unit: 'a {unit} ago'")
    print("   Multiple: '{number} {unit}s ago'")

    print("\n2. UNIT SELECTION (hypothesis):")
    if 'second' in unit_values:
        print(f"   - Seconds: Used for 0-59 seconds ago")
    if 'minute' in unit_values:
        print(f"   - Minutes: Used for 1-59 minutes ago")
    if 'hour' in unit_values:
        print(f"   - Hours: Used for 1-23 hours ago")
    if 'day' in unit_values:
        print(f"   - Days: Used for 1-6 days ago")
    if 'week' in unit_values:
        print(f"   - Weeks: Used for 1-3 weeks ago")
    if 'month' in unit_values:
        print(f"   - Months: Used for 1-11 months ago")
    if 'year' in unit_values:
        print(f"   - Years: Used for 1+ years ago")

    print("\n3. BOUNDARY THRESHOLDS (estimated):")
    print("   60 seconds = switch to minutes")
    print("   60 minutes = switch to hours")
    print("   24 hours = switch to days")
    print("   7 days = switch to weeks")
    print("   ~30 days (4 weeks) = switch to months")
    print("   12 months = switch to years")

    print("\n4. UNCERTAINTY RANGES:")
    print("   'a month ago' = 30-59 days ago (±15 days)")
    print("   '2 months ago' = 60-89 days ago (±15 days)")
    print("   'a year ago' = 365-729 days ago (±6 months)")

else:
    print("No reviews extracted!")