Daily WSB Sentiment Analysis Pipeline

import requests
import json
import re
from collections import Counter
from datetime import datetime
from pathlib import Path

API_KEY = "your_scavio_api_key"
TICKER_RE = re.compile(r"\b[A-Z]{2,5}\b")
SKIP_WORDS = {"THE","AND","FOR","ARE","BUT","NOT","YOU","ALL","CAN","HAS","HER","WAS","ONE","OUR","OUT","HIS","HOW","ITS","MAY","NEW","NOW","OLD","SEE","WAY","WHO","DID","GET","HIM","LET","SAY","SHE","TOO","USE","WSB","IMO","TBH","YOLO","FOMO","HODL"}

BULLISH = {"bull","moon","buy","calls","long","squeeze","rocket","tendies","gain","pump"}
BEARISH = {"bear","puts","short","crash","dump","sell","tank","loss","drill","rug"}

def scan_subreddit(query: str) -> list[dict]:
    res = requests.post(
        "https://api.scavio.dev/api/v1/search",
        headers={"x-api-key": API_KEY},
        json={"platform": "reddit", "query": query},
        timeout=15,
    )
    res.raise_for_status()
    return res.json().get("organic", [])

def extract_signals(posts: list[dict]) -> dict:
    ticker_counts = Counter()
    ticker_sentiment = {}
    for post in posts:
        text = f"{post.get('title', '')} {post.get('snippet', '')}"
        tickers = [t for t in TICKER_RE.findall(text) if t not in SKIP_WORDS]
        words = set(text.lower().split())
        bull_score = len(words & BULLISH)
        bear_score = len(words & BEARISH)
        sentiment = "bullish" if bull_score > bear_score else "bearish" if bear_score > bull_score else "neutral"
        for t in tickers:
            ticker_counts[t] += 1
            if t not in ticker_sentiment:
                ticker_sentiment[t] = {"bullish": 0, "bearish": 0, "neutral": 0}
            ticker_sentiment[t][sentiment] += 1
    return {"counts": ticker_counts, "sentiment": ticker_sentiment}

def run():
    date = datetime.utcnow().strftime("%Y-%m-%d")
    all_posts = []
    for query in ["wallstreetbets today", "stocks trading today", "options plays today"]:
        all_posts.extend(scan_subreddit(query))

    signals = extract_signals(all_posts)
    top_tickers = signals["counts"].most_common(15)

    feed = {
        "date": date,
        "posts_scanned": len(all_posts),
        "signals": [
            {"ticker": t, "mentions": c, "sentiment": signals["sentiment"].get(t, {})}
            for t, c in top_tickers
        ],
    }

    Path(f"wsb_signals_{date}.json").write_text(json.dumps(feed, indent=2))
    print(f"WSB signal scan {date}: {len(all_posts)} posts, {len(top_tickers)} tickers")
    for t, c in top_tickers[:5]:
        s = signals["sentiment"].get(t, {})
        print(f"  ${t}: {c} mentions (bull:{s.get('bullish',0)} bear:{s.get('bearish',0)})")

if __name__ == "__main__":
    run()

const API_KEY = "your_scavio_api_key";
const SKIP = new Set(["THE","AND","FOR","ARE","BUT","NOT","YOU","ALL","CAN","HAS","WSB","IMO","YOLO","FOMO"]);
const BULL = new Set(["bull","moon","buy","calls","long","squeeze","gain"]);
const BEAR = new Set(["bear","puts","short","crash","dump","sell","loss"]);

async function scanReddit(query) {
  const res = await fetch("https://api.scavio.dev/api/v1/search", {
    method: "POST",
    headers: { "x-api-key": API_KEY, "content-type": "application/json" },
    body: JSON.stringify({ platform: "reddit", query }),
  });
  return (await res.json()).organic ?? [];
}

const posts = [];
for (const q of ["wallstreetbets today", "stocks trading today"]) posts.push(...await scanReddit(q));
const counts = {};
for (const p of posts) {
  const text = `${p.title ?? ""} ${p.snippet ?? ""}`;
  for (const m of text.matchAll(/\b[A-Z]{2,5}\b/g)) {
    if (!SKIP.has(m[0])) counts[m[0]] = (counts[m[0]] ?? 0) + 1;
  }
}
const top = Object.entries(counts).sort((a, b) => b[1] - a[1]).slice(0, 10);
top.forEach(([t, c]) => console.log(`$${t}: ${c} mentions`));