In the world of software performance and DevOps, having fast, actionable insights into your web service response times is critical. While there are heavy-duty monitoring tools available, sometimes you just want something dead-simple to test how a specific URL is performing —  that’s where perfometrics comes in.

🔍 What is perfometrics?

perfometrics is a minimalistic Python package that lets you measure performance metrics for any HTTP/HTTPS URL , using nothing more than a couple of lines of code.

It’s built on top of pycurl, providing a clean API to track:

• HTTP status code
• DNS resolution time
• TCP connection time
• SSL/TLS handshake time
• Time to First Byte (TTFB)
• Data transfer time
• Total request time

⚙️ Installation

You can install it directly from PyPI:‍

pip install perfometrics

🚀 How to Use It

import perfometrics.curl as pcurl

url = 'https://example.com'
curl_uptime = pcurl.CurlUptime(url)
metrics = curl_uptime.get_metrics()

print('Metrics for', url)
print('HTTP status code:', metrics['status_code'])
print('Time taken for DNS resolution:', metrics['dns_lookup'], 'seconds')
print('Time taken for establishing TCP connection:', metrics['tcp'], 'seconds')
print('Time taken for SSL/TLS handshake:', metrics['ssl_tls'], 'seconds')
print('Time to First Byte (TTFB):', metrics['ttfb'], 'seconds')
print('Time taken for data transfer:', metrics['data_transfer'], 'seconds')
print('Total time taken for request:', metrics['total'], 'seconds')

curl_uptime.close_session()

✅ The result gives you a breakdown of where your time is being spent in the connection process — ideal for debugging latency issues or verifying optimizations.

💡 Use Cases

• DevOps Monitoring : Benchmark your production endpoints periodically
• CI/CD Testing : Run it in your pipelines to ensure APIs respond within acceptable limits
• Data Collection : Log metrics over time and analyze performance trends
• Lightweight Health Checks : Build quick health monitors using this package

📦 What’s Inside

• A single class: CurlUptime
• One method: .get_metrics() returns a dictionary of timing values
• Optional: .close_session() to clean up the curl handler

No need for extra config or YAMLs. Just import and measure.

📁 Source Code & Documentation

• 🔗 GitHub: https://github.com/aliesm-com/perfometrics
• 📦 PyPI: https://pypi.org/project/perfometrics/

🧠 Final Thoughts

If you’re looking for a dead-simple way to collect performance metrics for your URLs in Python, without setting up a full observability stack, give perfometrics a try.

If you like it, I’d appreciate a ⭐ on GitHub, and feel free to submit issues or PRs with ideas!