How to Detect Commodities Sentiment Shifts with the Pulsebit API (Python)

In the world of trading, understanding market sentiment can give you a significant edge. However, scraping and analyzing data from various sources can be a tedious task. Fortunately, the Pulsebit API simplifies this process by providing a single endpoint that delivers valuable sentiment insights.

The Problem (DIY scraping pain)

If you've ever tried to scrape sentiment data for commodities, you know it’s no walk in the park. You have to deal with various websites, parse HTML, handle rate limits, and maintain your scrapers. Not to mention the constant changes in website structure that can break your code overnight.

With the demand for timely sentiment analysis, the need for a reliable and efficient way to gather this information is crucial. Manually scraping can lead to inconsistencies and could cost you valuable time and resources. So, how do we streamline this process?

The Solution (Pulsebit API — one endpoint)

Enter the Pulsebit API. This API specializes in sentiment analysis by aggregating news articles and social media posts, offering insights into market sentiment. The best part? You can get all this data through a single endpoint, making it incredibly easy to integrate into your applications.

For our case, we'll focus on retrieving sentiment data for commodities using the /news_semantic endpoint.

The Code

Here’s how you can use Python to get commodities sentiment data from the Pulsebit API:

import requests

# Set your API key here
API_KEY = 'your_api_key_here'
BASE_URL = 'https://api.pulsebit.co/v1/news_semantic'

# Define your parameters (you can adjust the commodity as needed)
params = {
    'asset': 'commodities',  # Specify the asset type
}

# Make the GET request to the Pulsebit API
response = requests.get(BASE_URL, headers={'Authorization': f'Bearer {API_KEY}'}, params=params)

# Check if the request was successful
if response.status_code == 200:
    sentiment_data = response.json()
    print(sentiment_data)
else:
    print(f"Error: {response.status_code} - {response.text}")

Make sure to replace 'your_api_key_here' with your actual API key obtained from Pulsebit.

Reading the Response

When you make a GET request to the /news_semantic endpoint, you’ll receive a structured JSON response. Here’s how to interpret the key fields:

• sentiment: This field indicates the overall sentiment for commodities. In our example, the sentiment is +0.00, suggesting neutrality.
• momentum: This shows the sentiment trend over time. A momentum of +0.67 indicates a positive shift, suggesting growing bullish sentiment.
• clusters: This represents the number of sentiment clusters identified. A count of 0 may imply insufficient data for clustering.
• confidence: The confidence level of the sentiment analysis, with 0.87 indicating a strong belief in the accuracy of the sentiment detected.

Three Use Cases

1. Algo Alert: You can set up an algorithm to trigger alerts when sentiment shifts significantly. For instance, if momentum crosses a certain threshold, you could notify your trading system to enter or exit positions.

2. Slack Bot: Create a simple Slack bot that posts sentiment updates in your trading channel. When sentiment changes, the bot can automatically send a message with the new sentiment and momentum data.

3. Dashboard: Integrate the sentiment data into a dashboard using frameworks like Dash or Streamlit. Visualize sentiment changes over time, and combine them with price data to make more informed trading decisions.

Get Started

To dive deeper into the capabilities of the Pulsebit API, head over to their documentation at pulsebit.co/docs. The documentation provides comprehensive guidance on authentication, request parameters, and more endpoints you can explore.

In summary, leveraging the Pulsebit API can significantly enhance your ability to monitor commodities sentiment with minimal effort. By automating these insights, you can focus more on strategy and less on data collection. Happy coding!