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Kinda curious. Have you figured out why the code runs faster on a Mac?
> Framework laptop running Ubuntu Linux 24.04 (Intel Core i5 CPU)
> Mac laptop running macOS Sequoia (M2 CPU)
Earlier quoted context omitted.
I've been writing Python professionally for a couple of decades, and there've only been 2-3 times where its performance actually mattered. When writing a Flask API, the timing usually looks like: process the request for .1ms, make a DB call for 300ms, generate a response for .1ms. Or writing some data science stuff, it might be like: load data from disk or network for 6 seconds, run Numpy on it for 3 hours, write it…
Sure then you get a developer who decides to go with Flask for an embedded product and it's an eye watering slog.
It's slow. Get back to work.
Tangential, but I practically owe my life to this guy. He wrote the flask mega tutorial in what I followed religiously to launch my first website. Then right before launch, in the most critical part of my entire application; piping a fragged file in flask. He answered my stackoverflow question, I put his fix live, and the site went viral. Here's the link for posterity's sake https://stackoverflow.com/a/34391304/41802…
Off-topic, but I absolutely loathe new Flask logo. Old one[0] has this vintage, crafty feel. And the new one[1] looks like it was made by a starving high schooler experimenting with WordArt.
[0] - https://upload.wikimedia.org/wikipedia/commons/3/3c/Flask_lo...
[1] - https://flask.palletsprojects.com/en/stable/_images/flask-na...
Earlier quoted context omitted.
Because in the real world, for code where performance is needed, you run the profiler and either find that the time is spent on I/O, or that the time is spent inside native code.
This might have been your experience, but mine has been very different. In my experience a typical python workload is 50% importing python libraries, 45% slow python wrapper logic and 5% fast native code. I spend a lot of time rewriting the python logic in C++, which makes it 100x faster, so the resulting performance approaches "10% fast native logic, 90% useless python imports".
I hope it doesn't get stuck at 3.14, like TeX. https://www.reddit.com/r/RedditDayOf/comments/7we430/donald_...
You hope it doesn't ? > [Donald Knuth] firmly believes that having an unchanged system that will produce the same output now and in the future is more important than introducing new features This is such a breath of fresh air in a world where everything is considered obsolete after like 3 years. Our industry has a disease, an insatiable hunger for newness over completeness or correctness . There's no reason we can't…
>There's no reason we can't be writing code that lasts 100 years.
There are many reason this is most likely not going to happen. Code despite best effort to achieve separation of concern (in the best case) is a highly contextual piece of work. Even with a simple program with no external library, there is a full compiler/interpreter ecosystem that forms a huge dependency. And hardware platforms they abstract from are also moving target. Change is the only constant, as we say.
>Imagine having this attitude with math: "LOL loser you still use polynomials!? Weren't those invented like thousands of years ago?
Well, that might surprise you, but no, they weren't. At least, they were not dealt with as they are thought and understood today in their contemporary most common presentation. When Babylonians (c. 2000 BCE) solved quadratic equation, they didn't have anything near Descartes algebraic notation connected to geometry, and there is a long series evolution in between, and still to this days.
Mathematicians actually do make a lot of fancy innovative things all the time. Some fundamentals stay stable over millennia, yes. But also some problem stay unsolved for millennia until some outrageous move is done out of the standard.
Tangential, but I practically owe my life to this guy. He wrote the flask mega tutorial in what I followed religiously to launch my first website. Then right before launch, in the most critical part of my entire application; piping a fragged file in flask. He answered my stackoverflow question, I put his fix live, and the site went viral. Here's the link for posterity's sake https://stackoverflow.com/a/34391304/41802…
> flask Off-topic, but I absolutely loathe new Flask logo. Old one[0] has this vintage, crafty feel. And the new one[1] looks like it was made by a starving high schooler experimenting with WordArt. [0] - https://upload.wikimedia.org/wikipedia/commons/3/3c/Flask_lo... [1] - https://flask.palletsprojects.com/en/stable/_images/flask-na...
Here's hoping they make 16 patch versions
I'm thankful they included a compiled language for comparison, because most of the time when I see Python benchmarks, they measure against other versions of Python. But "fast python" is an oxymoron and 3.14 doesn't seem to really change that, which I feel most people expected given the language hasn't fundamentally changed. This isn't a bad thing; I don't think Python has to be or should be the fastest language in th…
It's pretty simple. Nobody wants to do ML R&D in C++. Tensorflow is a C++ library with python bindings. Pytorch has supported a C++ interface for some time now, yet virtually nobody uses C++ for ML R&D. The relationship between Python and C/C++ is the inverse of the usual backend/wrapper cases. C++ is the replaceable part of the equation. It's a means to an end. It's just there because python isn't fast enough. Nobod…
Tangential, but I practically owe my life to this guy. He wrote the flask mega tutorial in what I followed religiously to launch my first website. Then right before launch, in the most critical part of my entire application; piping a fragged file in flask. He answered my stackoverflow question, I put his fix live, and the site went viral. Here's the link for posterity's sake https://stackoverflow.com/a/34391304/41802…
You have made my day, sir. :)
But just now checking out the Mega Flask Tutorial, wow looks pretty awesome.
