How Pulsebit Detects Crypto Sentiment Shifts in Real Time (Python)

#python #api #datascience #trading

The Problem

Building a news sentiment pipeline from scratch takes weeks. Web scrapers break. NLP models drift. You end up maintaining infrastructure instead of shipping product.

The Solution

The Pulsebit News Sentiment API does the heavy lifting: it ingests thousands of articles per hour, extracts entities, clusters narratives, and returns clean confidence-weighted scores in a single JSON response.

Current Crypto reading (live from the API):

avg_sentiment: -0.42
momentum_24h: +0.21
cluster_count: 3
confidence: 0.91

The Code

import requests

resp = requests.get(
    "https://api.pulsebit.co/news_semantic",
    headers={"X-API-Key": "YOUR_KEY"},
    params={"query": "crypto", "limit": 20},
)
data = resp.json()
print(f"Sentiment: {data['avg_sentiment']:+.3f}")
print(f"Momentum:  {data['momentum_24h']:+.3f}")