Hey Pythonista,
Welcome back, happy Monday!
1) Get better at programming by learning how things work
... by Julia Evans. Quote:
> I find that if I can use my newfound understanding to do something concrete like implement a new feature or fix a bug or even just write a test program that demonstrates how the thing works, it feels a LOT more real than if I just read about it. And then it’s much more likely that I’ll be able to use it in practice later.
We often see people focusing a lot on syntax, especially when starting out, but as Julia Evans emphasizes, it's important to understand the inner workings of systems in programming for skill enhancement.
Practicing good coding habits, delving into how underlying systems operate can solve problems more effectively and foster innovation.
For instance, in front-end development, grasping the event loop or HTTP methods can prevent bugs and improve performance.
Similarly, in systems programming, knowing the difference between stack and heap or how virtual memory works can lead to more efficient code.
This approach aligns with the our philosophy of practical, hands-on learning. We encourage exploring the "why" and "how" behind coding challenges, promoting a deeper understanding of programming concepts.
A highly recommended read:
2) What's the difference between == and is in Python?
What is the difference between 'is' and '==' in #Python? 🐍 💡
🔶 `is` checks that 2 arguments refer to the same object.
🔶`==` is used to check that they have the same value.
So given two lists and this assignment:
>>> a = [1, 2, 3]
>>> b = [1, 2, 3]
>>> c = a
We can see the difference here:
>>> a == b # same content
True
>>> a == c # also same content
True
However:
>>> a is c # same object
True
>>> a is b # not the same object
False
a is c, because they point to same list object in memory. 🤯
Usually, `==` is what you want, but there are two cases where I use `is` 📈
- singletons (`None`, `True`, `False`)
- enums
3) Mindset tips from a self-taught security engineer + power lifter
This week, we're proud to feature Jacob Moyers, a friend of Julian's from his AWS Data Centre days. Jacob is here to share his remarkable transition from mechanical engineering to Cyber Security, paralleled with his success in powerlifting.
Jacob’s story is a testament to setting ambitious goals and achieving them with grit and perseverance, offering profound lessons for Python developers.
His journey from novice to expert, in both his career and personal passions, mirrors the path many of you navigate in coding - starting from scratch, facing challenges head-on, and thriving through persistence and continuous learning.
4) Coaching == lasting changes + the compound effect
We received this amazing feedback from one of our clients that we want to celebrate 🎉
> I’m astonished at how far I’ve come in my career after PDM. I went from writing my very first Pull Request in the program to leading (by example) several seasoned engineers in the field of Data Engineering. I now give demos during office hours every week where I provide “bites” of helpful refactoring ideas and showing how we can leverage more of the Standard Library. This is all in no small part due to the lessons I learned through Pybites and the PDM program. What may seem like just little nuggets of info become an invaluable tool set.
5) From the archive
There are many great libraries in Python to produce appealing plots, but have you considered JS?
On the platform and some other tools, we use Chart.js to make some really nice-looking graphs.
Maybe something cool for you too?
We also use it on our platform ... if you're coding there head over to this page:
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Go crush it this week!
Bob & Julian
P.S. Over the years we've accumulated so many resources and ways to grow into a better developer.
Still a bit lost as to what we have to offer as Pybites?
Check out our new resources page:
And feel free to reach out to us directly in our growing Circle community: