#Python tip: Dunder methods aren't just for classes. People often forget that __getattr__ and __dir__ can be defined at the module level. This gives modules dynamic capabilities like lazy loading or context sensitive loads.

#Python factlet: functools.partial() self-flattens. Writing: partial(partial(pow, 2), 5) optimizes to: partial(pow, 2, 5) The result is only one layer deep.

#Python tip: operator.itemgetter() accepts slice objects. >>> from operator import itemgetter >>> chomp_ends = itemgetter(slice(1, -1)) >>> chomp_ends('abcdefgh') 'bcdefg'

asyncio is still really wild in 2025. I haven't actively written asyncio code in a while but now that I have done it for a week agian, I noticed that most problems from when I used it last are still unresolved. Problem 1: asyncio.create_task is a massive footgun because it can

This is 100% true!

#Python musing: From a practical point of view, "infinite" is just a special case of "inconveniently large". There is nothing special about: sum(itertools.count()) as compared to: sum(range(10**20))

Overall, AI Is Making Humans More Stupid AI makes 1% of us smarter and the remaining 99% stupider. The 1% are using AI to learn and do things, and know how to use it effectively. The remaining 99% blindly use AI to copy homework, write emails they don't read, try vibe coding,

For me, the Desmos Graphing Calculator sparks joy. Its API designers are true craftsmen (and women). The tool is approachable for kids, powerful enough for real world use, and completely devoid of cruft/nonsense. It takes discipline to make something this good.

#Python tip: The w in r"\w+" stands for "wrong". False negatives: can't you've Mary's cul-de-sac non-profit False positives: _____ 123 Actual word tokens may include apostrophes and hyphens and may exclude underscores or numbers.

#Python teaching tip: If someone says, "I didn't get topic X, can you go over it again" that means that your approach wasn't successful. Don't say the same words over again. Instead, approach the topic from a completely different angle. Home in on what works.

#Python teaching tool: To demonstrate testing and debugging, I often use this function: def square(n: int) -> int: return sum(n - 2 for i in range(n + 2)) + 4 Tests pass for n=100, n=7, n=1, n=0, n=-1, and n=-2. But fail for n=-5. Tests can't prove the absence of errors.

#Python notes: The Counter in the collections module supports two kinds of arithmetic. The update() and subtract() methods implement normal arithmetic with possible negative numbers in the results. The "+" and "-" implement saturating arithmetic giving non-negative results.

In your experience, are LLMs as vulnerable as humans to be thrown-off by incorrect code comments?

*raises hand* There are dozens of us! DOZENS!!

#Python recipe of the day: relu = functools.partial(max, 0.0) Presto, you have rectified linear unit for a neural net. geeksforgeeks.org/deep-learning/…