Python Logs Aren’t Code A Communication Tool
<h1>Your Present & Future Self Will Hate You For Forgetting To Do This Programming Chore</h1>
<p>Nothing will ruin a programming session faster than bad coffee shop WiFi. And on the particular day I’m recounting, as much as I needed the vanilla latte sitting to my left, I really needed that sweet, sweet public broadband because the power was out at home and, more importantly, so was the coffee.</p>
<p>I needed all the caffeine I could get because even though I was deep in our tech stack, in the three hours I was online, I hadn’t written a line of code. Instead, I was doing something you wouldn’t normally associate with technical work: Reading. While some coffee shop patrons were reading novels, magazines and blog posts I was engrossed in my team’s logs.</p>
<h2>How to Use Logging Query Language to Analyze GCP Logs Data in Python</h2>
<h3>How to use Google Cloud’s Logs API and Logging Query Language in Python to obtain real-time data on active GCP…</h3>
<p>medium.com</p>
<p>Reviewing our various processes, I was surprised at the scope and variety of the logs I encountered. Some extensively logged every function execution and every API response.</p>
<p>Others only provided logs to signal the start and end of a script’s execution. After my review I flagged these under-logged products and the team revised logs so the majority of our products are legible and extensively logged.</p>
<p>That exercise and my own experience building data pipelines made me realize that new developers are all too often making the same mistake: You’re treating logs like code when you should be treating them like units of communication.</p>
<p><a href="https://medium.com/pipeline-a-data-engineering-resource/your-logs-arent-code-they-re-a-communication-tool-c87c91d474e5">Click Here</a></p>