No es necesario ser propietario de una cuenta para analizar las métricas públicas de TikTok. La API de Scavio TikTok le permite extraer cualquier perfil público y sus publicaciones recientes para calcular las tasas de participación, la frecuencia de publicación, los indicadores de crecimiento de la audiencia y los patrones de rendimiento del contenido. Cada llamada cuesta $0,005, lo que hace que una auditoría completa de la cuenta sea inferior a $0,02.
Requisitos previos
- Python 3.8+
- solicita biblioteca
- Una clave API de Scavio de scavio.dev
- Apunte a los nombres de usuario de TikTok para analizar
Guia paso a paso
Paso 1: Obtener datos de perfil público
Extraiga métricas de perfil para cualquier cuenta pública de TikTok.
Python
import os, requests, json
from datetime import datetime
API_KEY = os.environ['SCAVIO_API_KEY']
TH = {'Authorization': f'Bearer {API_KEY}', 'Content-Type': 'application/json'}
def get_profile(username):
data = requests.post('https://api.scavio.dev/api/v1/tiktok/profile',
headers=TH, json={'username': username}).json()
user = data.get('user', data.get('data', {}).get('user', data))
return {
'username': username,
'followers': user.get('followerCount', user.get('fans', 0)),
'following': user.get('followingCount', 0),
'likes': user.get('heartCount', user.get('heart', 0)),
'videos': user.get('videoCount', 0),
'verified': user.get('verified', False),
'bio': user.get('signature', '')[:100],
'sec_uid': user.get('secUid', '')
}
profile = get_profile('charlidamelio')
for k, v in profile.items():
if k != 'sec_uid':
val = f'{v:,}' if isinstance(v, int) else v
print(f' {k}: {val}')Paso 2: Analizar el rendimiento de publicaciones recientes
Obtenga publicaciones recientes y calcule métricas de participación.
Python
def get_posts(sec_uid):
data = requests.post('https://api.scavio.dev/api/v1/tiktok/user/posts',
headers=TH, json={'sec_user_id': sec_uid}).json()
posts = data.get('videos', data.get('data', {}).get('videos', []))
return [{'desc': p.get('desc', '')[:60],
'plays': p.get('stats', {}).get('playCount', 0),
'likes': p.get('stats', {}).get('diggCount', 0),
'comments': p.get('stats', {}).get('commentCount', 0),
'shares': p.get('stats', {}).get('shareCount', 0),
'created': p.get('createTime', 0)} for p in posts]
def analyze_engagement(posts, followers):
if not posts or not followers:
return {}
total_eng = sum(p['likes'] + p['comments'] + p['shares'] for p in posts)
total_plays = sum(p['plays'] for p in posts)
avg_plays = total_plays / len(posts)
avg_likes = sum(p['likes'] for p in posts) / len(posts)
er = total_eng / total_plays * 100 if total_plays else 0
follower_er = total_eng / (followers * len(posts)) * 100
return {
'avg_plays': int(avg_plays), 'avg_likes': int(avg_likes),
'engagement_rate': round(er, 2), 'follower_er': round(follower_er, 2),
'total_posts_analyzed': len(posts)
}
posts = get_posts(profile['sec_uid'])
metrics = analyze_engagement(posts, profile['followers'])
for k, v in metrics.items():
print(f' {k}: {v:,}' if isinstance(v, int) else f' {k}: {v}')Paso 3: Calcular la frecuencia y los patrones de publicación
Determine con qué frecuencia se publica la cuenta e identifique patrones de sincronización.
Python
from datetime import datetime
def posting_patterns(posts):
if len(posts) < 2:
return {}
timestamps = sorted([p['created'] for p in posts if p['created']])
if not timestamps:
return {}
# Calculate posting frequency
time_span_days = (timestamps[-1] - timestamps[0]) / 86400 if len(timestamps) > 1 else 1
freq = len(posts) / max(time_span_days, 1)
# Day of week distribution
days = [datetime.fromtimestamp(t).strftime('%A') for t in timestamps if t]
day_counts = {}
for d in days:
day_counts[d] = day_counts.get(d, 0) + 1
best_day = max(day_counts, key=day_counts.get) if day_counts else 'Unknown'
return {
'posts_per_day': round(freq, 2),
'posts_per_week': round(freq * 7, 1),
'most_active_day': best_day,
'time_span_days': round(time_span_days, 0)
}
patterns = posting_patterns(posts)
print('Posting patterns:')
for k, v in patterns.items():
print(f' {k}: {v}')Paso 4: Generar informe completo de auditoría de cuentas
Combine todos los análisis en un informe de cuenta completo.
Python
def audit_account(username):
print(f'\n=== TikTok Account Audit: @{username} ===')
profile = get_profile(username)
cost = 0.005
print(f'\nProfile:')
print(f' Followers: {profile["followers"]:,} | Following: {profile["following"]:,}')
print(f' Total likes: {profile["likes"]:,} | Videos: {profile["videos"]}')
print(f' Verified: {profile["verified"]} | Bio: {profile["bio"][:50]}')
posts = get_posts(profile['sec_uid'])
cost += 0.005
metrics = analyze_engagement(posts, profile['followers'])
print(f'\nEngagement ({len(posts)} recent posts):')
print(f' Avg plays: {metrics.get("avg_plays", 0):,}')
print(f' Avg likes: {metrics.get("avg_likes", 0):,}')
print(f' Play-based ER: {metrics.get("engagement_rate", 0)}%')
print(f' Follower-based ER: {metrics.get("follower_er", 0)}%')
patterns = posting_patterns(posts)
print(f'\nPosting:')
print(f' Frequency: {patterns.get("posts_per_week", 0)} posts/week')
print(f' Most active: {patterns.get("most_active_day", "Unknown")}')
# Top performing post
if posts:
top = max(posts, key=lambda p: p['plays'])
print(f'\nTop post: {top["desc"][:50]}... ({top["plays"]:,} plays)')
print(f'\nAudit cost: ${cost:.3f}')
audit_account('charlidamelio')Ejemplo en Python
Python
import os, requests
TH = {'Authorization': f'Bearer {os.environ["SCAVIO_API_KEY"]}', 'Content-Type': 'application/json'}
def audit(username):
p = requests.post('https://api.scavio.dev/api/v1/tiktok/profile',
headers=TH, json={'username': username}).json()
user = p.get('user', p.get('data', {}).get('user', p))
followers = user.get('followerCount', 0)
posts_data = requests.post('https://api.scavio.dev/api/v1/tiktok/user/posts',
headers=TH, json={'sec_user_id': user.get('secUid', '')}).json()
vids = posts_data.get('videos', posts_data.get('data', {}).get('videos', []))[:10]
total_likes = sum(v.get('stats', {}).get('diggCount', 0) for v in vids)
total_plays = sum(v.get('stats', {}).get('playCount', 0) for v in vids)
er = total_likes / total_plays * 100 if total_plays else 0
print(f'@{username}: {followers:,} followers, {er:.2f}% ER, {len(vids)} posts. Cost: $0.010')
audit('charlidamelio')Ejemplo en JavaScript
JavaScript
const TH = { 'Authorization': `Bearer ${process.env.SCAVIO_API_KEY}`, 'Content-Type': 'application/json' };
async function audit(username) {
const p = await fetch('https://api.scavio.dev/api/v1/tiktok/profile', {
method: 'POST', headers: TH, body: JSON.stringify({ username })
}).then(r => r.json());
const user = p.user || p.data?.user || p;
const posts = await fetch('https://api.scavio.dev/api/v1/tiktok/user/posts', {
method: 'POST', headers: TH, body: JSON.stringify({ sec_user_id: user.secUid })
}).then(r => r.json());
const vids = (posts.videos || posts.data?.videos || []).slice(0, 10);
const plays = vids.reduce((s, v) => s + (v.stats?.playCount || 0), 0);
const likes = vids.reduce((s, v) => s + (v.stats?.diggCount || 0), 0);
console.log(`@${username}: ${(user.followerCount||0).toLocaleString()} followers, ${(likes/plays*100).toFixed(2)}% ER`);
}
audit('charlidamelio').catch(console.error);Salida esperada
JSON
=== TikTok Account Audit: @charlidamelio ===
Profile:
Followers: 155,200,000 | Following: 1,234
Total likes: 11,800,000,000 | Videos: 2,456
Verified: True | Bio: dance + vibes
Engagement (10 recent posts):
Avg plays: 8,900,000
Avg likes: 1,200,000
Play-based ER: 14.52%
Follower-based ER: 0.85%
Posting:
Frequency: 4.2 posts/week
Most active: Tuesday
Top post: New dance challenge with... (23,400,000 plays)
Audit cost: $0.010