Explanation: Python is a programming language. Numpy is a library for python that makes it possible to run large computations much faster than in native python. In order to make that possible, it needs to keep its own set of data types that are different from python’s native datatypes, which means you now have two different...
You’re just describing parsing in statically-typed languages, to be honest. Adding all of this stuff to Python is just (poorly) reinventing the wheel.
Python’s a great language for writing small scripts (one of my favorite for the task, in fact), but it’s not really suitable for serious, large scale production usage.
I understand what you’re saying—I’m saying that data validation is precisely the purpose of parsers (or deserialization) in statically-typed languages. Type-checking is data validation, and parsing is the process of turning untyped, unvalidated data into typed, validated data. And, what’s more, is that you can often get this functionality for free without having to write any code other than your type (if the validation is simple enough, anyway). Pydantic exists to solve a problem of Python’s own making and to reproduce what’s standard in statically-typed languages.
In the case of config files, it’s even possible to do this at compile time, depending on the language. Or in other words, you can statically guarantee that a config file exists at a particular location and deserialize it/validate it into a native data structure all without ever running your actual program. At my day job, all of our app’s configuration lives in Dhall files which get imported and validated into our codebase as a compile-time step, meaning that misconfiguration is a compiler error.
Misinformation campaigns increasingly target the cavity-fighting mineral, prompting communities to reverse mandates. Dentists are enraged. Parents are caught in the middle....
I just mean the usual water treatment practices to ensure safe drinking water. At minimum I would expect filtration to be happening since you don’t want particulates floating around in it.
I just found out about this debate and it’s patently absurd. The ISO 80000-2 standard defines ℕ as including 0 and it’s foundational in basically all of mathematics and computer science. Excluding 0 is a fringe position and shouldn’t be taken seriously.
None of this requires anything at the kernel level. It can be done entirely in userland. It is absolutely a violation of standard system security principles.
Sure… That"s what libraries are for. No one hand-rolls that stuff. You can do all of that just fine (and, actually, in a lot less code, mostly because Java is so fucking verbose) without using the nightmare that is Spring.
I know it’s a joke, but just wanted to say that Uranium used for fuel is not something you can actually use for weaponry directly. It requires enrichment to increase the concentration of U-235 to weapons-grade levels.
Generally agree with your points, even though I"m honestly not sure what a union would look like like in practice.
But I just wanted to say that this job is definitely harder than plumbing. I usually do my own plumbing and it’s not really that bad. It’s not my favorite thing to do and can sometimes be a pain in the ass, but it’s way less taxing imo.
Teaching kids is hard as fuck though and good teachers are priceless. Honestly quality caregiving of any sort is massively underrated.
Sure yeah, but like, I work remote and will always work remote (I live in a city with a pretty mediocre tech scene). On top of that, I work in a non-mainstream programming language (Haskell). So it’s hard to envision what I could actually do.
I’m very pro-union btw, it just seems like there are certain things that can sometimes make it more difficult to make happen
It’s got nothing to do with capitalism. It’s fundamentally a matter of people using it for things it’s not actually good at, because ultimately it’s just statistics. The words generated are based on a probability distribution derived from its (huge) training dataset. It has no understanding or knowledge. It’s mimicry.
It’s why it’s incredibly stupid to try using it for the things people are trying to use it for, like as a source of information. It’s a model of language, yet people act like it has actual insight or understanding.
You do not understand how these things actually work. I mean, fair enough, most people don’t. But it’s a bit foolhardy to propose changes to how something works without understanding how it works now.
There is no “database”. That’s a fundamental misunderstanding of the technology. It is entirely impossible to query a model to determine if something is “present” or not (the question doesn’t even make sense in that context).
A model is, to greatly simplify things, a function (like in math) that will compute a response based on the input given. What this computation does is entirely opaque (including to the creators). It’s what we we call a “black box”. In order to create said function, we start from a completely random mapping of inputs to outputs (we’ll call them weights from now on) as well as training data, iteratively feed training data to this function and measure how close its output is to what we expect, adjusting the weights (which are just numbers) based on how close it is. This is a gross simplification of the complexity involved (and doesn’t even touch on the structure of the model’s network itself), but it should give you a good idea.
It’s applied statistics: we’re effectively creating a probability distribution over natural language itself, where we predict the next word based on how frequently we’ve seen words in a particular arrangement. This is old technology (dates back to the 90s) that has hit the mainstream due to increases in computing power (training models is very computationally expensive) and massive increases in the size of dataset used in training.
Source: senior software engineer with a computer science degree and multiple graduate-level courses on natural language processing and deep learning
Btw, I have serious issues with both capitalism itself and machine learning as it is applied by corporations, so don’t take what I’m saying to mean that I’m in any way an apologist for them. But it’s important to direct our criticisms of the system as precisely as possible.
In my experience, your average software developer has absolutely terrible security hygiene. It’s why you see countless instances of private keys copy/pasted into public GitHub repos or the seemingly daily occurrences of massive data breaches.
My undergrad in CS (which I should point out, is still by far the most common major for software engineers) did not require a security course, and I’m fairly confident that this is pretty typical. To be honest, I wouldn’t have trusted any of my CS professors to know the first thing about security. It’s a completely different field and something that generally requires a lot of practical experience. The closest we ever got was an explanation of asymmetric vs. symmetric encryption. There was certainly no discussion of even basic things like how to properly manage secrets or authn best practices.
Everything I know now as a senior software engineer about software security has come from experience on the job. I’ve been very fortunate to work at some places that take it very seriously (including a government contractor writing cybersecurity software for the Department of Defense) and learned a lot there. But a lot of shops don’t have a culture that promotes good security hygiene, and it shows in the litany of insecure software out in the wild today.
1 Is pretty standard in the industry for people with experience. I haven’t actually applied to any jobs myself in a while. Job hunting for me is sifting through the recruiter messages that hit my inbox.
It’s not a terrible name, since it’s derived from the mathematical construct of vectors as n-tuples. In the case of vectors in programming, n relates to the size of the underlying array, and the tuple consists of the elements of the vector.
I’d say it’s definitely worth it. I don’t actually use nixos itself, but I do use nix a lot. I have everything I need for work in a home manager configuration, so I can literally just install nix and load up my config and have all programs and configuration of said programs installed and ready to go (on any UNIX system). I started doing this since changing jobs means a new machine, and I got really tired of all of the inconsistencies between machines when bringing over my dotfiles, and having to install a bunch of packages I use every time I changed jobs.
I do want to make the switch from Arch to nixos on my personal machine eventually too, but I hardly spend any time on computers outside of work these days, unfortunately. But the great thing is that my home manager configuration can pretty easily slide right into a nixos configuration, which is what many people do.
The tooling has improved dramatically since then. There’s now a full-fledged language server (haskell-language-server.readthedocs.io/…/stable/), ghcup (www.haskell.org/ghcup/) is now a thing for installing/managing different versions of GHC/cabal/HLS, there’s now formatters (github.com/tweag/ormolu) and cabal has modernized significantly and supports multi-package projects much more comfortably now. Nix-based Haskell infrastructure is also now pretty nice. There’s even stuff like github.com/srid/haskell-template/…/flake.nix to very quickly get spun up on a new project using Haskell and nix, including vscode, formatter, HLS, and a full development shell with a bunch of useful commands.
Another great modern thing (which powers HLS) is that GHC can now emit .hie files for each file it compiled, which is basically a standardized representation of the AST for that module that can be consumed/manipulated programatically. Lots of tools can use this. One such tool that’s particularly useful is github.com/wz1000/HieDb, which constructs an sqlite database from the information in these files, so you basically can have an index of every symbol definition, reference, export, etc. all readily available to use however you want.
No, you divide work so that the majority of it can be done in isolation and in parallel. Testing components together, if necessary, is done on integration branches as needed (which you don’t rebase, of course). Branches and MRs should be small and short-lived with merges into master happening frequently. Collaboration largely occurs through developers frequently branching off a shared main branch that gets continuously updated.
Trunk-based development is the industry-standard practice at this point, and for good reason. It’s friendlier for CI/CD and devops, allows changes to be tested in isolation before merging, and so on.
Python is great, but stuff like this just drives me up the wall (lemmy.world)
Explanation: Python is a programming language. Numpy is a library for python that makes it possible to run large computations much faster than in native python. In order to make that possible, it needs to keep its own set of data types that are different from python’s native datatypes, which means you now have two different...
50 million rendered polygons vs one spicy 4.2MB boi (lemmy.world)
In some cultures, that is considered an honor Samantha! (sh.itjust.works)
Maybe an injection or pill? (lemmy.world)
Medical freedom vs. public health: Should fluoride be in our drinking water? (www.nbcnews.com)
Misinformation campaigns increasingly target the cavity-fighting mineral, prompting communities to reverse mandates. Dentists are enraged. Parents are caught in the middle....
Zero to hero (mander.xyz)
Enshittification sure is fast (sh.itjust.works)
STOP DOING DEPENDENCY INJECTION (sopuli.xyz)
Why data centers want to have their own nuclear reactors (english.elpais.com)
Google lays off hundreds of 'Core' employees, moves some positions to India and Mexico (www.cnbc.com)
Google is laying off more employees and hiring for their roles outside of the U.S.
ChatGPT provides false information about people, and OpenAI can’t correct it (noyb.eu)
Fake job interviews target developers with new Python backdoor (www.bleepingcomputer.com)
Explain yourselves, comp sci. (mander.xyz)
The Average™ arch user (lemmy.zip)
It must confuse English learners to hear phrases like, "I'm home", instead of "I am at home." We don't say I'm school, or I'm post office.
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Rebase Supremacy (programming.dev)