I fucking hate chained methods. Ok, not all of them. Query things like array.where.first... that stuff is ok.

Specially if it's part of the std lib of a lang, which would be probably written by a very competent coder and under scrutiny.
But if you're not that person, chances are you'll produce VASTLY inferior code.

I'm talking about things like:
expect(n).to.be(x).and.not(y)

And the reason I don't like it is because it's all fine and dandy at first.

But once you get to the corner cases, jesus christ, prepare to read some docpages.

You end up reading their entire fucking docs (which are suboptimal sometimes) trying to figure if this fucking dsl can do what you need.

Then you give up and ask in a github issue. And the dev first condescends you and then tells you that the beautiful eden of code he created doesn't let you do what you want.

The corner cases usually involve nesting or some very specific condition, albeit reasonable.

This kind of design is usually present in testing or validation js libraries. And I hate all of those for it.

If you want a modern js testing lib that doesn't suck ass, check avajs. It's as simple as testing should be.

No magic globals, no chaining, zero config. Fuck globals forced by libs.

But my favorite thing about it that is I can put a breakpoint wherever the fuck I want and the debugger stops right fucking there.

Code is basically lines of statements, that's it, and by overusing chaining, by encouraging the grouping of dozens of statements into one, you are preventing me from controlling these statements on MY code.

As an end dev, I only expect complexity increases to come from the problems themselves rather than from needlessly "beautified" apis.

When people create their own shitty dsl, an image comes to my mind of an incoherent rambling man that likes poetry a lot and creates his own martial art, which looks pretty but will get your ass kicked against the most basic styles of fighting.

I fucking hate esoteric code.

Even if I had to execute a list of functions, I'd rather send them in an array instead of being able to chain them because:
a) tree shaking would spare from all the functions i didn't import
b) that's what fucking arrays are for, to contain several things.

This bad style of coding is a result of how low the barrier to code in higher level langs are.

As a language or library gets easier to use you might think that's a positive thing. But at the same time it breeds laziness.

Js has such a low learning curve that it attacts the wrong kind of devs, the lazy, the uninspired, the medium.com reader, the "i just care about my paycheck" ones.

Someone might think that by bashing bad js devs I'm trying to elevate myself.

That'd be extremely stupid. That's like beating a retarded blind man in a game and then saying "look, I'm way better than this retarded blind man".

I'm not on a risky point of view, just take a stroll down npmjs.com. That place is a landfill. Not really npm's fault, in fact their search algorithm is good.

It's just the community.

Every lang has a ratio of competence. Of competent to incompetent devs.

You have the lang devs and most intelligent lib devs at the top. At the bottom you have the bottom.

Well js has a horrible ratio. I wouldn't be shocked to find out that most js devs still consider using import or await the future.

You could say that js improved a lot, that it was way worse beforr. But I hate chaining now, and i hated back then!

On top of this, you have these blog web companies, sucking the "js tutorial" business tit dry, pumping out the most obscenely unprofessional and bar lowering tutorials you can imagine, further capping the average intelligence of most js devs.

And abusing SEO while they're at it, littering the entire web with copy paste content.

Running a fucking conda environment on windows (an update environment from the previous one that I normally use) gets to be a fucking pain in the fucking ass for no fucking reason.

First: Generate a new conda environment, for FUCKING SHITS AND GIGGLES, DO NOT SPECIFY THE PYTHON VERSION, just to see compatibility, this was an experiment, expected to fail.

Install tensorflow on said environment: It does not fucking work, not detecting cuda, the only requirement? To have the cuda dependencies installed, modified, and inside of the system path, check done, it works on 4 other fucking environments, so why not this one.

Still doesn't work, google around and found some thread on github (the errors) that has a way to fix it, do it that way, fucking magic, shit is fixed.

Very well, tensorflow is installed and detecting cuda, no biggie. HAD TO SWITCH TO PYHTHON 3,8 BECAUSE 3.9 WAS GIVING ISSUES FOR SOME UNKNOWN FUCKING REASON

Ok no problem, done.

Install jupyter lab, for which the first in all other 4 environments it works. Guess what a fuckload of errors upon executing the import of tensorflow. They go on a loop that does not fucking end.

The error: imPoRT eRrOr thE Dll waS noT loAdeD

Ok, fucking which one? who fucking knows.

I FUCKING HATE that the main language for this fucking bullshit is python. I guess the benefits of the repl, I do, but the python repl is fucking HORSESHIT compared to the one you get on: Lisp, Ruby and fucking even NODE in which error messages are still more fucking intelligent than those of fucking bullshit ass Python.

Personally? I am betting on Julia devising a smarter environment, it is a better language already, on a second note: If you are worried about A.I taking your job, don't, it requires a team of fucktards working around common basic system administration tasks to get this bullshit running in the first place.

My dream? Julia or Scala (fuck you) for a primary language in machine learning and AI, in which entire environments, with aaaaaaaaaall of the required dlls and dependencies can be downloaded and installed upon can just fucking run. A single directory structure in which shit just fucking works (reason why I like live environments like Smalltalk, but fuck you on that too) and just run your projects from there, without setting a bunch of bullshit from environment variables, cuda dlls installation phases and what not. Something that JUST FUCKING WORKS.

I.....fucking.....HATE the level of system administration required to run fucking anything nowadays, the reason why we had to create shit like devops jobs, for the sad fuckers that have to figure out environment configurations on a box just to run software.

Fuck me man development turned to shit, this is why go mod, node npm, php composer strict folder structure pipelines were created. Bitch all you want about npm, but if I can create a node_modules setting with all of the required dlls to run a project, even if this bitch weights 2.5GB for a project structure you bet your fucking ass that I would.

"YOU JUST DON'T KNOW WHAT YOU ARE DOING" YES I FUCKING DO and I will get this bullshit fixed, I will get it running just like I did the other 4 environments that I fucking use, for different versions of cuda and python and the dependency circle jerk BULLSHIT that I have to manage. But this "follow the guide and it will work, except when it does not and you are looking into obscure github errors" bullshit just takes away from valuable project time when you have a small dedicated group of developers and no sys admin or devops mastermind to resort to.

I have successfully deployed:
Java
Golang
Clojure
Python
Node
PHP
VB/C# .NET
C++
Rails
Django

Projects, and every single fucking time (save for .net, that shit just fucking works on a dedicated windows IIS server) the shit will not work with x..nT reasons. It fucking obliterates me how fucking annoying this bullshit is. And the reason why the ENTIRE FUCKING FIELD of computer science and software engineering is so fucking flawed.

But we can't all just run to simple windows bs in which we have documentation for everything. We have to spend countless hours on fucking Linux figuring shit out (fuck you also, I have been using Linux since I was 18, I am 30 now) for which graphical drivers for machine learning, cuda and whatTheFuckNot require all sorts of sys admin gymnasts to be used.

Y'all fucked up a long time ago. Smalltalk provided an all in one, easily rollable back to previous images, easily administered interfaces for this fileFuckery bullshit, and even though the JVM and the .NET environments did their best to hold shit down, and even though we had npm packages pulling the universe inside, or gomod compiling shit into one place NOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO we had to do whatever the fuck we wanted to feel l337 and wanted.

Fuck all of you, fuck this field, fuck setting boxes for ML/AI and fuck every single OS in existence

Python is a fucking joke. "Readability" disguised as 150+ magic methods and values. Virtual environments to hide shitty dependency management. Strings that may or may not act as comments. No correlation between package and module names - install Pillow; import PIL. **kwargs instead of options=dict(), because why separate function arguments from arbitrary extra data? And finally, the only way to have tkinter on Windows is to install IDLE, so that some fucktard can stick their shitty app right up yours ...

I got my dirty fingers on this leak of an AMAZING ML model capable of pondering EVERY PARAMETER IN THE UNIVERSE and saying if your business idea needs improvement or is good to go.
BEHOLD THIS 100% PURE PYTHON SOLUTION:

```python
import random

def magic(*args, **kwargs):
if random.random() > 0.5:
return "Good to go!"
else:
return "Requires improvement on value proposition"
```

This LEAK is from a startup that just received 4 BILLION USD IN VENTURE CAPITAL to improve their AI SYSTEMS.
Literally enough money to solve world hunger forever.
Who else is gonna invest in NEW THERANOS ADVANCED A.I. RESEARCH INTERNATIONAL INC?

It seems like Python solutions are always shorter.

python machine learning tutorials:
- import preprocessed dataset in perfect format specially crafted to match the model instead of reading from file like an actual real life would work
- use images data for recurrent neural network and see no problem
- use Conv1D for 2d input data like images
- use two letter variable names that only tutorial creator knows what they mean.
- do 10 data transformation in 1 line with no explanation of what is going on
- just enter these magic words
- okey guys thanks for watching make sure to hit that subscribe button

ehh, the machine learning ecosystem is burning pile of shit let me give you some examples:

- thanks to years of object oriented programming research and most wonderful abstractions we have "loss.backward()" which have no apparent connection to model but it affects the model, good to know
- cannot install the python packages because python must be >= 3.9 and at the same time < 3.9
- runtime error with bullshit cryptic message
- python having no data types but pytorch forces you to specify float32
- lets throw away the module name of a function with these simple tricks:
"import torch.nn.functional as F"
"import torch_geometric.transforms as T"
- tensor.detach().cpu().numpy() ???
- class NeuralNetwork(torch.nn.Module):
def __init__(self):
super(NeuralNetwork, self).__init__() ????
- lets call a function that switches on the tracking of math operations on tensors "model.train()" instead of something more indicative of the function actual effect like "model.set_mode_to_train()"
- what the fuck is ".iloc" ?
- solving environment -/- brings back memories when you could make a breakfast while the computer was turning on
- hey lets choose the slowest, most sloppy and inconsistent language ever created for high performance computing task called "data sCieNcE". but.. but. you can use numpy! I DONT GIVE A SHIT about numpy why don't you motherfuckers create a language that is inherently performant instead of calling some convoluted c++ library that requires 10s of dependencies? Why don't you create a package management system that works without me having to try random bullshit for 3 hours???
- lets set as industry standard a jupyter notebook which is not git compatible and have either 2 second latency of tab completion, no tab completion, no documentation on hover or useless documentation on hover, no way to easily redo the changes, no autosave, no error highlighting and possibility to use variable defined in a cell below in the cell above it
- lets use inconsistent variable names like "read_csv" and "isfile"
- lets pass a boolean variable as a string "true"
- lets contribute to tech enabled authoritarianism and create a face recognition and object detection models that china uses to destroy uyghur minority
- lets create a license plate computer vision system that will help government surveillance everyone, guys what a great idea

I don't want to deal with this bullshit language, bullshit ecosystem and bullshit unethical tech anymore.

Yesterday, my team had a react crash-course workshop.
It was like "you have to import a couple of libs, use 'em in different react elements you pull up and Tadaaaa! Magic is happening and your app works".
This workshop was the pinnacle of "intense".

I understood 60% of the stuff.
My team-mates about 15%.

So react is the front-end technology of choice after our architectural-team. The other teams have to use this the technology for their UIs.
This will be a lot of fun ^^

I've been working on an Emscripten emulation layer for a fledgling startup, and it's just a huge bitch. Seriously, Emscripten is the worst designed project I've ever seen. It embeds constants into a js file that it spits out. It turns out you can't fucking run the wasm that Emscripten emits without these magic constants from the js file.

Additionally, all the wasm imports that emscripten specifies are weirdly cased, with apparently no naming convention. They also use some weird, shitty vararg implementation when it already fucking knows exactly how many arguments are going to get passed to an import.

Also, there are a ton of broken things left over from when emscripten compiled to asm.js that they never bothered to replace with features from wasm. God knows how it even works.

Hi people first as you know my English is not very poor im sorry for that.
I try to make an automat a sprinkle water and a auto light on a interior garden in aquarium.

For that in python i use main thread, a class Water.py extends Threading and Light.py extends Threading

In the __init__.py file i put my main function that get argv for execution. One of my arguments is -v (--verbose)
I want to pass that args to my class instances.

-I don't want to make one parameter in my constructors because I think we don't passe verbose mode in parameter of constructor.

-I use global not working through de import.

Do you have some magic for me :/ ?

The end of today was extremely fun.

Imagine the surprise. I was importing a simple 8 GB big virtual machine into the Proxmox hypervizor.

First issue: It was in the Open Virtualization Format (.ova) for easy import into... most hypervizors... Not Proxmox, however.

But really, not that bad, there are ways around it. Create a blank virtual machine through the UI, scrap the disk you create, then extract the two disk QCOW2 files from the .ova file, which by itself is just a POSIX TAR archive. Then import them through the commandline.

...So I did just that. The larger of the two was about 8 GBs, the other just like... 50 MBs.

The larger imported fine. The smaller?

Color me surprised, when it created a FUCKING. 1. TB. LOGICAL. VOLUME.

...

That it then proceeded to try and fill full of zeros...

Oh yes, it was one of the fancy dynamic storage files that expand as space is needed.

...
Tomorrow, I'll have to try if I can export just the filesystem data into an individual, shrunken down, normal, plain, old disk. None of this fancy black magic shit.

...Also... I don't get why Proxmox doesn't support that... The filesystem was only a few megs big... Ugh.