But for unioning a bunch of spark dataframes together i think
df = reduce(DataFrame.union, list_of_dfs)
df, *rest = list_of_dfs
for other in rest:
df = df.union(other)
I can't find the motivation to do anything at the moment. But if reddit or facebook get opened up i'll just scroll. It's almost like i've replace doing things with watching other people do things and that somehow makes me less likely to work on my hobbies because i'm not as good or far along.
AI has added to this, almost like, why bother bettering myself when I could probably shit out my idea in a handful of prompts? I need a dopamine fast or something. Might try staring at a wall
I'm after undergraduate level books that have problems in them both practical and theoretical if possible.Ultimately i want to be able to send signals to components like sensors and be able to retrieve the results via code. Think like temperature and humidity sensors, or light sensors, that sort of thing.For background i'm a software developer with a PhD in chemistry, so i'm fairly confident...
Will take a look when i get to my laptop!
The specialty dark roast will have notes of cookies, chocolate, nuts. Lots of brown roasty flavour.
Starbucks tastes bitter. With very little nuance. (Unless you cold brew it, then you can leave most of the bitter behind)
Thanks for sharing!
hell i do this if our tester hasn't managed to go over some aspect of our release. That way i get in writing from the product owner that he has OKd it, and if he sends me a teams message i ask him to email me confirmation.
Sure. Writing C++ that utilises your resources effectively then writing bindings so you can use that in python is great. But with elixir, if I've got 8 cores and 8 processes, those 8 processes run in parallel.
If I want raw cpu speed I can write something in rust, c, cpp or zig and then call it still using elixir semantics.
Not to mention that with Nx you can write elixir code that compiles to run on the GPU. Without writing any bindings.
But python doesn't vertically scale very well. A language like Elixir can grow to fit the size of the box it is on, making use of all the cores, and then without too much additional ceremony scale horizontally aswell with distributed elixir/erlang.
Elixir getting a good story around webdev (phoenix and liveview) and more recently the a good story around ML is going to increase it's adoption, but it's not going to happen overnight. But maybe tomorrows CTOs will take the leap.
It's over training syndrome, caused by too much training without enough rest. The athletes that try to push through struggle to perform as well.
yield from
Instead of
return
If you are going to iterate through some of the resulting thing but not all of it then the generator means you aren't throwing away a bunch of the work that you've done.
It can also be more cache friendly. It doesn't need to allocate a whole new lists worth of memory.
One of the downsides of it being lazy is that if list x is mutated between when you create the generator and when you consume it then those changes are reflected in the generator.
I've done some micro benchmarks and it really depends on what you are doing. Profiling it with cProfile, Pyspy or using %timeit in an Ipython shell will tell you if it makes a difference.
# title
this is the paragraph
is more natural to write than:
<html> <head>...<head/> <body> <h1> title </h1> <p>this is the paragraph</p> </body> </html>
when you're just jotting some thoughts down.
I've also heard good things about 7 programming languages in 7 weeks, as well as crafting interpreters.
The latter 2 I intend to pick up this year
Multiple stages, conversations with team members,tech tests, psychology and aptitude tests. The only reason I turned the offer down is because they took several months to get me a contract and I didn't stop interviewing in that time
When i was a scientist, speed was getting the code written during my break, and if it took all afternoon to run that's fine because i was in the lab anyway.
Even as i moved more into the software engineer direction, and started profiling code more, most of the bottlenecks come from things like "creating objects on every incovation rather than pooling them", "blocking IO", "using a bad algorithm" or "using the wrong datasctructure for the task". problems that exist in every language, though "bad algorithm" or "using the wrong datasctructure" might matter less in a faster language you're still leaving performance on the table.
> "Python is so slow that we have to write any important code in C. And this is somehow a good thing."
The good thing is that python has a very vibrant ecosystem filled with great libraries, so we don't have to write it in C, because somebody else has. We can just benefit from that when the situation calls for it
There has been a lot of competition to make browsers fast. Nowadays there are 3 main JS engines, V8 backed by google, JavaScriptCore backed by apple, and spidermonkey backed by mozilla.
If python had been the language embedded into web browsers, then maybe we would see 3 competing python engines with crazy performance.
The alternative interpreters for python have always been a bit more niche than Cpython, but now that Guido works at microsoft there has been a bit more of a push to make it faster
He dicusses techniques for this. one of which is a "migration" approach, similar to database migrations. Where, for example, you have a version number in your struct. and a function for migrating from an old version to a new version. I don't think he implements it in that video though.
So I'd say from what I know the niche is "batteries included high performance code that can target the gpu"