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9.6 - Advanced Topics

9.6.1 - Rate Limiting and How to Handle It Programmatically

Overview of Rate Limiting: APIs often restrict the number of requests that can be made in a given time frame to prevent abuse and overuse. This mechanism is known as rate limiting.

Strategies for Managing Rate Limits:

  • Monitor Your Rate Limits: Always check the response headers after making a request to see how many requests you have left:

    response = requests.get('https://api.example.com/data')
    remaining = int(response.headers.get('X-RateLimit-Remaining'))
  • Graceful Handling: Implement logic to handle scenarios when you've hit the rate limit:

    import time
    if remaining == 0:
    reset_time = int(response.headers.get('X-RateLimit-Reset'))
    sleep_time = reset_time - time.time()
    time.sleep(sleep_time) # Sleep until the rate limit is reset.

9.6.2 - Example of Session Persistence with Requests Sessions

Benefits of Using Sessions:

  • Efficiency: Sessions allow you to reuse underlying TCP connections for multiple requests, which can significantly increase the efficiency of your API interactions.
  • Simplicity: Maintain consistent headers and parameters across requests without needing to set them repeatedly.

Using Sessions:

with requests.Session() as session:
session.headers.update({'Authorization': 'Bearer YOUR_API_TOKEN'})
response = session.get('https://api.example.com/user_details')
print(response.text)

9.6.3 - Utilizing Webhooks for Real-Time Data Processing

Introduction to Webhooks: Webhooks provide a powerful method to allow APIs to communicate with your applications in real-time.

Setting Up and Managing Webhooks:

Configure the webhook URL in your API settings to which the API will send POST requests.

from flask import Flask, request
app = Flask(__name__)

@app.route('/webhook', methods=['POST'])
def handle_webhook():
data = request.json
process_webhook_data(data)
return "Acknowledged", 200

def process_webhook_data(data):
print("New data received:", data)
# Additional processing logic here

if __name__ == '__main__':
app.run(port=5000, debug=True)