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your CI/CD pipeline probably ran malware on march 31st between 00:21 and 03:15 UTC. here's how to check. by Peace_Seeker_1319 in devops

[–]Embarrassed-Rest9104 14 points15 points  (0 children)

This is a nightmare scenario for any CI/CD pipeline. The fact that the malware self-erases after exfiltrating secrets makes it incredibly difficult to audit after the build. If you ran a build in that 3-hour window on March 31, don't just check the logs rotate every credential. A 15-second install is all it took to lose everything.

FAANG Data Engineers — what does your day actually look like, and is it worth it? by Few-Sandwich-7328 in dataengineering

[–]Embarrassed-Rest9104 0 points1 point  (0 children)

As a researcher, I see a massive gap between the clean ETL pipelines we teach in the classroom and the reality of managing proprietary internal tools at that scale. It often feels like FAANG engineers become experts in systems they can't even use once they leave the company

Readability or Modernity by Embarrassed-Rest9104 in learnpython

[–]Embarrassed-Rest9104[S] 0 points1 point  (0 children)

it’s a tough trade-off between the elegance of old Python and modern safety.

Readability or Modernity by Embarrassed-Rest9104 in learnpython

[–]Embarrassed-Rest9104[S] 1 point2 points  (0 children)

That’s a fair point on network latency, but, I still worry that ignoring memory efficiency leads to massive cloud bills and unstable production environments.

Readability or Modernity by Embarrassed-Rest9104 in learnpython

[–]Embarrassed-Rest9104[S] -1 points0 points  (0 children)

You're spot on about Async, it’s a performance lever I usually save for my CS students once they hit a wall with standard scripts.

Regarding Type Hinting, the complexity for beginners usually starts when we move into Protocols and Generics in 3.10+. It's a big jump when you're just learning logic!

I actually used a 10M row benchmark recently to show them how modern execution (like in Polars) compares to Pandas. It’s a great 'lightbulb moment' for why efficiency matters.

python for engineering ? by PriorImprovement8714 in learnpython

[–]Embarrassed-Rest9104 2 points3 points  (0 children)

Your math professor is 100% correct. As a researcher in engineering, I can tell you that Python is no longer optional for engineers but it’s the modern-day calculator.

Whether you go into Civil, Mechanical, or Electrical engineering, you’ll use Python to automate repetitive calculations, analyze sensor data, and run simulations that Excel simply can't handle.

Start with VS Code, learn computational thinking through libraries like NumPy and Pandas and try solving your math homework with a script to see the real power of Python in engineering.

Why does Python feel easy to learn but hard to master? by arjunv70 in learnpython

[–]Embarrassed-Rest9104 0 points1 point  (0 children)

As a researcher who works with Python daily, I can tell you that what you’re feeling is the most common phase in a developer's journey often called the "Hand-holding Hydra".

Python’s syntax is like plain English, which makes the loops and variables very easy. But mastering Python is about the (memory management, vectorized operations, asynchronous programming).

Recently i ran a experiment comparing Pandas v/s Polars on a 10 million row dataset. When you hit those performance bottlenecks, you're forced to learn why the code works the way it does. That’s where the real mastery start.