A YouTube trend detector searches niche keywords via the Scavio API with platform set to youtube, stores view counts daily in SQLite, and identifies rising topics by calculating week-over-week view count growth.
Prerequisites
- Python 3.9+
- Scavio API key
- SQLite (stdlib)
Walkthrough
Step 1: Search YouTube for a keyword
Use platform:youtube to get video listings with view counts for any query.
Python
import requests
API_KEY = "your-scavio-api-key"
def search_youtube(query: str, n: int = 10) -> list:
r = requests.post(
"https://api.scavio.dev/api/v1/search",
json={"query": query, "platform": "youtube", "num_results": n},
headers={"x-api-key": API_KEY},
timeout=15
)
r.raise_for_status()
return r.json().get("organic_results", [])Step 2: Parse view counts from results
Extract total view count across top videos for the keyword.
Python
import re
def parse_views(views_str: str) -> int:
if not views_str:
return 0
s = views_str.upper().replace(",","")
m = re.search(r"([\d.]+)([KMB])?", s)
if not m:
return 0
num = float(m.group(1))
mult = {"K": 1_000, "M": 1_000_000, "B": 1_000_000_000}.get(m.group(2), 1)
return int(num * mult)
def total_views_for_keyword(query: str) -> int:
videos = search_youtube(query, n=5)
return sum(parse_views(v.get("views","")) for v in videos)Step 3: Track and detect trends
Store daily view sums and alert when a keyword's views jump by 50%+ week-over-week.
Python
import sqlite3
from datetime import date, timedelta
NICHE_KEYWORDS = ["vibe coding", "ai agent tools", "local llm setup", "cursor vs copilot", "claude code tutorial"]
def init_db(path="youtube_trends.db"):
conn = sqlite3.connect(path)
conn.execute("CREATE TABLE IF NOT EXISTS trends (date TEXT, keyword TEXT, total_views INTEGER, PRIMARY KEY (date, keyword))")
conn.commit()
return conn
def run_trend_detector():
conn = init_db()
today = str(date.today())
week_ago = str(date.today() - timedelta(days=7))
results = []
for kw in NICHE_KEYWORDS:
views = total_views_for_keyword(kw)
conn.execute("INSERT OR REPLACE INTO trends VALUES (?,?,?)", (today, kw, views))
conn.commit()
prev = conn.execute("SELECT total_views FROM trends WHERE keyword=? AND date=?", (kw, week_ago)).fetchone()
growth = ((views - prev[0]) / prev[0] * 100) if prev and prev[0] > 0 else None
results.append({"keyword": kw, "views": views, "growth_pct": growth})
results.sort(key=lambda x: x.get("growth_pct") or 0, reverse=True)
for r in results:
g = f"+{r['growth_pct']:.0f}%" if r["growth_pct"] else "no prior data"
print(f"{r['keyword']:<35} {r['views']:>10,} views | WoW: {g}")
run_trend_detector()Python Example
Python
import requests
import sqlite3
import re
from datetime import date, timedelta
API_KEY = "your-scavio-api-key"
KEYWORDS = ["vibe coding", "ai agent tools", "local llm setup", "cursor vs copilot", "claude code tutorial"]
def search_youtube(query, n=5):
r = requests.post("https://api.scavio.dev/api/v1/search",
json={"query": query, "platform": "youtube", "num_results": n},
headers={"x-api-key": API_KEY}, timeout=15)
r.raise_for_status()
return r.json().get("organic_results", [])
def parse_views(s):
if not s: return 0
m = re.search(r"([\d.]+)([KMB])?", s.upper().replace(",",""))
if not m: return 0
return int(float(m.group(1)) * {"K":1000,"M":1_000_000,"B":1_000_000_000}.get(m.group(2),1))
def total_views(query):
return sum(parse_views(v.get("views","")) for v in search_youtube(query))
def init_db():
conn = sqlite3.connect("youtube_trends.db")
conn.execute("CREATE TABLE IF NOT EXISTS trends (date TEXT, keyword TEXT, views INTEGER, PRIMARY KEY (date, keyword))")
conn.commit()
return conn
def run():
conn = init_db()
today = str(date.today())
week_ago = str(date.today() - timedelta(days=7))
rows = []
for kw in KEYWORDS:
views = total_views(kw)
conn.execute("INSERT OR REPLACE INTO trends VALUES (?,?,?)", (today, kw, views))
conn.commit()
prev = conn.execute("SELECT views FROM trends WHERE keyword=? AND date=?", (kw, week_ago)).fetchone()
growth = ((views - prev[0]) / prev[0] * 100) if prev and prev[0] else None
rows.append((kw, views, growth))
rows.sort(key=lambda x: x[2] or 0, reverse=True)
print(f"YouTube Trend Report — {today}")
for kw, views, g in rows:
g_str = f"+{g:.0f}%" if g else "no prior"
print(f" {kw:<35} {views:>10,} | {g_str}")
if __name__ == "__main__":
run()JavaScript Example
JavaScript
const API_KEY = 'your-scavio-api-key';
const KEYWORDS = ['vibe coding', 'ai agent tools', 'local llm setup'];
async function searchYoutube(query, n = 5) {
const res = await fetch('https://api.scavio.dev/api/v1/search', {
method: 'POST',
headers: { 'Content-Type': 'application/json', 'x-api-key': API_KEY },
body: JSON.stringify({ query, platform: 'youtube', num_results: n })
});
const data = await res.json();
return data.organic_results ?? [];
}
function parseViews(s) {
if (!s) return 0;
const m = s.toUpperCase().replace(/,/g,'').match(/([\d.]+)([KMB])?/);
if (!m) return 0;
return Math.round(parseFloat(m[1]) * ({K:1e3,M:1e6,B:1e9}[m[2]] ?? 1));
}
for (const kw of KEYWORDS) {
const videos = await searchYoutube(kw);
const total = videos.reduce((s, v) => s + parseViews(v.views), 0);
console.log(`${kw}: ${total.toLocaleString()} total views`);
}Expected Output
JSON
YouTube Trend Report - 2026-05-22
vibe coding 24,892,441 | +187%
ai agent tools 18,441,209 | +94%
cursor vs copilot 12,209,882 | +71%
local llm setup 8,891,022 | +43%
claude code tutorial 4,102,441 | +28%