Cómo crear un comparador de volumen de palabras clave

import os, requests, json, re

API_KEY = os.environ['SCAVIO_API_KEY']
SH = {'x-api-key': API_KEY, 'Content-Type': 'application/json'}

def serp_signals(keyword):
    """Get competition and volume signals from SERP results."""
    data = requests.post('https://api.scavio.dev/api/v1/search',
        headers=SH, json={'query': keyword, 'country_code': 'us'}).json()
    organic = data.get('organic_results', [])
    total_results_str = data.get('search_information', {}).get('total_results', '0')
    try: total_results = int(re.sub(r'[^\d]', '', str(total_results_str)))
    except: total_results = 0
    has_ads = bool(data.get('ads', []))
    has_ao = bool(data.get('ai_overview'))
    paa_count = len(data.get('related_questions', []))
    return {
        'keyword': keyword, 'total_results': total_results,
        'organic_count': len(organic), 'has_ads': has_ads,
        'has_ai_overview': has_ao, 'paa_count': paa_count
    }

signals = serp_signals('best serp api 2026')
for k, v in signals.items():
    print(f'  {k}: {v}')

def estimate_volume_tier(signals):
    """Estimate volume tier from SERP signals (not exact volume)."""
    score = 0
    if signals['total_results'] > 1000000: score += 3
    elif signals['total_results'] > 100000: score += 2
    elif signals['total_results'] > 10000: score += 1
    if signals['has_ads']: score += 2  # Ads = commercial intent + volume
    if signals['has_ai_overview']: score += 1  # AO = Google considers query important
    if signals['paa_count'] >= 4: score += 1
    tiers = {0: 'very_low', 1: 'low', 2: 'low', 3: 'medium',
             4: 'medium', 5: 'high', 6: 'high', 7: 'very_high'}
    tier = tiers.get(min(score, 7), 'very_high')
    return {'tier': tier, 'score': score, 'signals': signals}

keywords = ['best serp api', 'python web scraping', 'curl to python converter',
            'tiktok analytics api free', 'how to make money online']
for kw in keywords:
    signals = serp_signals(kw)
    est = estimate_volume_tier(signals)
    print(f'  {kw:35} | tier: {est["tier"]:10} | score: {est["score"]} | ads: {signals["has_ads"]} | AO: {signals["has_ai_overview"]}')

def compare_keywords(keywords):
    results = []
    for kw in keywords:
        signals = serp_signals(kw)
        est = estimate_volume_tier(signals)
        results.append({**signals, **est})
    results.sort(key=lambda x: x['score'], reverse=True)
    cost = len(keywords) * 0.005
    print(f'\nKeyword Volume Comparison ({len(keywords)} keywords, ${cost:.3f}):')
    print(f'{"Keyword":35} | {"Tier":10} | {"Results":>12} | {"Ads":4} | {"AO":3} | {"PAA":3}')
    print('-' * 85)
    for r in results:
        print(f'{r["keyword"]:35} | {r["tier"]:10} | {r["total_results"]:12,} | {"Y" if r["has_ads"] else "N":4} | {"Y" if r["has_ai_overview"] else "N":3} | {r["paa_count"]:3}')
    return results

ranked = compare_keywords(keywords)

def keyword_report(keywords):
    results = compare_keywords(keywords)
    print(f'\n=== Keyword Research Report ===')
    # Group by tier
    tiers = {}
    for r in results:
        tier = r['tier']
        if tier not in tiers: tiers[tier] = []
        tiers[tier].append(r)
    for tier in ['very_high', 'high', 'medium', 'low', 'very_low']:
        if tier in tiers:
            print(f'\n  {tier.upper()} volume ({len(tiers[tier])} keywords):')
            for r in tiers[tier]:
                opportunity = 'HIGH' if not r['has_ads'] and r['score'] >= 3 else 'MEDIUM' if r['score'] >= 2 else 'LOW'
                print(f'    {r["keyword"]:35} | opportunity: {opportunity}')
    # Quick wins: medium+ volume without ads
    quick_wins = [r for r in results if r['score'] >= 3 and not r['has_ads']]
    if quick_wins:
        print(f'\n  QUICK WINS (volume without ad competition):')
        for r in quick_wins:
            print(f'    - {r["keyword"]}')
    cost = len(keywords) * 0.005
    print(f'\n  Report cost: ${cost:.3f}')

keyword_report(keywords)