TikTok API Python Tutorial: Get Video Stats Without Official API Restrictions

pip install requests

import requests

API_KEY = "your_contentstats_api_key"  # Get at contentstats.io
BASE_URL = "https://www.contentstats.io/api/v1"

def track_video(video_url: str) -> dict:
    """Start tracking a TikTok, YouTube, or Instagram video."""
    response = requests.post(
        f"{BASE_URL}/posts/track",
        headers={"x-api-key": API_KEY},
        json={"postLink": video_url}
    )
    response.raise_for_status()
    return response.json()

def get_video_stats(post_id: str) -> dict:
    """Get current stats for a tracked video."""
    response = requests.get(
        f"{BASE_URL}/posts/{post_id}",
        headers={"x-api-key": API_KEY}
    )
    response.raise_for_status()
    return response.json()

# Track a TikTok video
tiktok_url = "https://www.tiktok.com/@username/video/1234567890"
tracked = track_video(tiktok_url)
post_id = tracked["data"]["id"]

print(f"Video tracked. ID: {post_id}")

# Fetch current stats
stats = get_video_stats(post_id)
print(f"Views: {stats['data']['viewCount']}")
print(f"Likes: {stats['data']['likeCount']}")
print(f"Comments: {stats['data']['commentCount']}")
print(f"Shares: {stats['data']['shareCount']}")

import time
from typing import List

def track_multiple_videos(urls: List[str]) -> List[dict]:
    """Track multiple videos and return their IDs."""
    tracked = []
    for url in urls:
        result = track_video(url)
        tracked.append({
            "url": url,
            "post_id": result["data"]["id"]
        })
        time.sleep(0.5)  # Respect rate limits
    return tracked

def get_all_stats(tracked_videos: List[dict]) -> List[dict]:
    """Fetch stats for all tracked videos."""
    results = []
    for video in tracked_videos:
        stats = get_video_stats(video["post_id"])
        results.append({
            "url": video["url"],
            "views": stats["data"]["viewCount"],
            "likes": stats["data"]["likeCount"],
            "comments": stats["data"]["commentCount"],
            "engagement_rate": (
                (stats["data"]["likeCount"] + stats["data"]["commentCount"])
                / max(stats["data"]["viewCount"], 1)
            ) * 100
        })
    return results

# Example usage
urls = [
    "https://www.tiktok.com/@creator1/video/111",
    "https://www.tiktok.com/@creator2/video/222",
    "https://www.youtube.com/watch?v=abc123",  # Also works for YouTube!
]

tracked = track_multiple_videos(urls)
all_stats = get_all_stats(tracked)

for stat in all_stats:
    print(f"URL: {stat['url']}")
    print(f"  Views: {stat['views']:,}")
    print(f"  Engagement Rate: {stat['engagement_rate']:.2f}%")
    print()

import time
from datetime import datetime

def monitor_video(post_id: str, hours: int = 24, interval_minutes: int = 60):
    """Monitor a video's view count over time to detect viral spikes."""
    readings = []
    intervals = (hours * 60) // interval_minutes
    
    for i in range(intervals):
        stats = get_video_stats(post_id)
        reading = {
            "timestamp": datetime.now().isoformat(),
            "views": stats["data"]["viewCount"],
            "likes": stats["data"]["likeCount"]
        }
        readings.append(reading)
        
        # Detect spike: views grew >10x vs previous hour
        if len(readings) >= 2:
            prev_views = readings[-2]["views"]
            curr_views = readings[-1]["views"]
            growth = curr_views - prev_views
            if prev_views > 0 and growth / prev_views > 10:
                print(f"VIRAL SPIKE DETECTED at {reading['timestamp']}")
                print(f"Views jumped from {prev_views:,} to {curr_views:,} in {interval_minutes} min")
        
        print(f"[{reading['timestamp']}] Views: {reading['views']:,}")
        
        if i < intervals - 1:  # Don't sleep after last check
            time.sleep(interval_minutes * 60)
    
    return readings

# Monitor a video for 24 hours, checking every hour
# monitor_video(post_id, hours=24, interval_minutes=60)

import pandas as pd
import requests

API_KEY = "your_contentstats_api_key"

def list_tracked_posts(limit: int = 50) -> pd.DataFrame:
    """Get all tracked videos as a pandas DataFrame."""
    response = requests.get(
        "https://www.contentstats.io/api/v1/posts",
        headers={"x-api-key": API_KEY},
        params={"limit": limit}
    )
    data = response.json()["data"]
    
    records = []
    for post in data:
        records.append({
            "id": post.get("id"),
            "url": post.get("postLink"),
            "platform": post.get("platform"),
            "views": post.get("viewCount", 0),
            "likes": post.get("likeCount", 0),
            "comments": post.get("commentCount", 0),
            "shares": post.get("shareCount", 0),
        })
    
    df = pd.DataFrame(records)
    df["engagement_rate"] = (
        (df["likes"] + df["comments"]) / df["views"].replace(0, 1) * 100
    ).round(2)
    return df

df = list_tracked_posts()
print(df.sort_values("views", ascending=False).head(10))
print(f"\nAverage engagement rate: {df['engagement_rate'].mean():.2f}%")