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Bite-Sized Python News & Updates |
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Hey Pythonista,
By now many of you would have seen or heard about the mass layoffs that took place at Amazon last week.
I've had a few friends impacted in this wave and it hasn't been pretty. I won't even try to soothe you with platitudes about how "it'll get better", because who knows what will happen tomorrow at the whim of tech CEOs?
So, what can we do in this situation? What can we do when we feel like the industry we've devoted years to feels like it's dying?
Here's my take:
Try not to be alarmist or make knee-jerk decisions. Keep a level head and your eye on your goal. E.g.: news about Amazon doesn't have to mean the entire tech industry is falling apart.
Keep up to date and don't let your skills atrophy. Keep learning and stay on top of new technologies, even if it's just situational awareness. This means you'll be ready when opportunity strikes.
Network your butt off. This isn't the time to slink into the shadows and disappear from view. Now is the time to be engaging your network and taking every opportunity to speak with and help others. Be the person that's top of mind when others think of your field (Python, or otherwise).
Force screen-free time every day. Disconnect from the computer at least for a bit every day and get outside. When we're plugged in, the world can seem like a dire place right now. Take a moment to breathe, reset and centre yourself again before diving back in.
[Bonus] Exercise! I know, I know but it's one of the few things I do that makes me feel like I'm literally burning the stress/anxiety off. I don't know how else to put it, but it feels like a healthy way to channel stress into something good!
These are just some of the things that helped me when I went through an Amazon role redundancy in 2024. I think they're still solid tips to get you through any industry uncertainty.
If there's anything we can do to help, you can reach us in our community using the link below.
Finally, if you were impacted by these layoffs, please reach out if you'd like to chat.
Cheers,
Julian
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| Continue the Conversation in our Community
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🐍 Python Tip: Exponential Backoff Decorator |
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Turn network retries into clean, reusable code using a decorator. Example:
@retry(times=3, wait=0.5, factor=2)
def get(url):
...
Great for handling flaky APIs or outages gracefully ⚡
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| See the Full Tip Here
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🐍 Lazy Imports Insight (PEP 810) |
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About 17% of stdlib imports are already deferred manually inside functions for speed.
PEP 810 proposes built-in lazy imports to make this easier and cleaner. Great for startup time ⚡ but beware: errors may surface later.
You can use python -X importtime to profile slow imports, and tools like importlib.util.LazyLoader for experimentation.
Interestingly while posting and discussing this on LinkedIn, Will McGugan jumped in with a cool use of __getattr__ in textual, see here.
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| Learn more about PEP 810
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Pybites Win: Congrats to Kishan Patel! |
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Congrats to Kishan Patel for earning his PyBites Certified Python Developer – Pro (PCPD-P) certification! 💪
As part of our mentorship program, he built three full-stack apps:
Each project was tested, documented, and production-ready, an incredible and well-earned achievement! 🚀
Book us in for a chat when you're ready to take your skills to the next level and build your own apps like Kishan!
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