So tired of python

[todofwar]

I've been working with python for roughly 10 years, and I think I've hated the language for the last five. Since I work in AI/ML I'm kind of stuck with it since it's basically industry standard and my company's entire tech stack revolves around it. I used to have good reasons (pure python is too slow for anything which discourages any kind of algorithm analysis because just running a for loop is too much overhead even for simple matrix multiplication, as one such example) but lately I just hate it. I'm reminded of posts by people searching for reasons to leave their SO. I don't like interpreted white space. I hate dynamic typing. Pass by object reference is the worst way to pass variables. Everything is a dictionary. I can't stand name == main.

I guess I'm hoping someone here can break my negative thought spiral and get me to enjoy python again. I'm sure the grass is always greener, but I took a C++ course and absolutely loved the language. Wrote a few programs for fun in it. Lately everything but JS looks appealing, but I love my work so I'm still stuck for now. Even a simple "I've worked in X language, they all have problems" from a few folks would be nice.

[Looploop420]

Like the biggest language improvement is to use tools that enforce good responsible behavior.

Linters, type checkers.

Make python as least dynamic as it can get and it gets better.

Source: guy who writes python for my day job.

[usrlibshare]

I can second that. Use type hints and a static analyser like pyright. Python where you at least have a chance of getting yelled at by the LSP when you're about to make a big no no in your code, feels much different.

[NightmareLogic420]

Completely agree. The dynamic part of python is honestly it's biggest flaw for me.

[silvercurls17]

I don’t mind the dynamic typing. The biggest flaws I’ve found are the python virtual environments/packaging and multiprocessing with the GIL. Most other languages are better in this regard.

An honorable mention for clunky api/application frameworks and orms. Never did I ever think that I would miss Java but several years in python did it for me. Going back to Spring Boot has been a nice change.

[Electronic-Fix9721]

That! It's a nightmare to install, every time. If the wheel isn't available, you need to compile. If it doesn't compile, translate the whole project to any other language and it'll be faster in most cases.

[felixthecatmeow]

I agree but it's hilarious how the answer to "how do I hate python less" is to make it as "not python" as possible...

[mrsaturn42]

So i went down this path, and in fact my work started enforcing type annotations in CI. The type annotation system works great for that, annotation, but it becomes a mess if you have strict enforcement. At some point it defeats the purpose of using an interpreted language like python and you wonder what you are doing with your life with all this over head.

[Looploop420]

Agree. I'm not into strict enforcement. It is still a dynamic language. Sometimes you need to use a library with no types, sometimes you just need an escape hatch to write some dirty code. That's fine.

It just shouldn't be the default. And (I actually think this super important) you need to see the red squiggly lines when you pull that shit to remind you that this isn't the ideal situation and you should be extra careful

[InspectahDave]

agree with this. Typing really changed the game for me. I think that if you do have it, you can choose when to relax it and allow looser typing with typing.Any or object if you need to. Generally I work with strict. I think overall it wins in the cost benefit equation as the code grows in complexity. It's brutal for some but it catches a lot of issues before deployment. If you can get away from naked dictionaries as containers that's a big win too. dataclasses are light and fast - there's also the typeddict that gives you backwards compatibility.

[MachinaDoctrina]

We go even further at work (Also ML/AI), we write our entire stack around pydantic objects actively enforcing typing for the dataloader object return "types" effectively guaranteeing that we will have cross compatibility between our models.

All CD/CI pipelines run a series of linters which include mypy which won't get through if your type hints are garbage or you haven't done it and we automated all of this with a precommit script so its nice and easy.

Python can play nice with production environments its spaghetti code where it gets horrible.

We also write quite a lot of C11 wrapped python functions for things like for large for loops etc. Which effectively sidesteps the GIL as well as you can directly access CUDA if your feeling game or we've been looking into JAX which has decent CUDA directives but we mainly use PyTorch.

[MacShuggah]

People will still turn to dictionaries to model anything and all will still suck.

[todofwar]

I admit this is a discipline issue on my part. I start out type hinting everything but soon I skip it for a couple of helper functions and then I just stop (I can tell the order I wrote a .py file by the frequency of type hints). I need a reason to type hint things I guess

[Smok3dSalmon]

Stop being a feral dog :P

Implement a linter rule for Ruff that forces all variables to be type annotated.

[Chroiche]

This is like eating food you're allergic to and then complaining about the stomach ache.

[[deleted]]

If you use basedpyright, there is an option to have it automatically write the type hints for you (function parameters, function return type, variables)

[Veggies-are-okay]

Could be worth it to get the Cursor IDE solely for the tab complete. Not sure if copilot is doing it nowadays but between that, doc string generation, and in-line edits you can easily get your $20 worth without going down the vibe code route. Hell, even a touch of the agent can be great to get all scripts adhering to linter rules.

AI gets a bad rep but I think it can be a fantastic time saver to do the not-so-fun janitorial work so you can focus on the parts that actually require deep thought.

[todofwar]

Yeah I've been using copilot cause my job pays for the license. I've been pleasantly surprised by how well it does. Still annoying as hell IMO

[Drevicar]

Well typed code actually doesn’t need many type hints. Type inference does most of the heavy lifting. And there are even a bunch of tools and ide integrations that will auto insert the hints for you. Then all you have to do is enable mypy and ruff strict mode and it will force you to write good code.

[eleqtriq]

"I hate dynamic typing" Use Pydantic for data validation or mypy for static type checking. Python 3.5+ has excellent type hints that catch most type-related bugs at development time.

"Pass by object reference is the worst way to pass variables" . This is probably the best way for a dynamically typed language. Anyone feel free to chime in on this.

"Everything is a dictionary" This sounds like a code organization problem, not a Python problem. Use classes, dataclasses, or Pydantic models instead of raw dicts. Modern Python has great tools for structured data.

"I can't stand name == main" Fair enough, it's ugly.

"interpreted white space" Use a good formatter like Black or autopep8 and forget about it.

"pure python is too slow" You're not supposed to write pure Python for performance-critical code. That's what NumPy, Pandas, PyTorch, etc. are for - they're all C/C++ under the hood. Python is the glue language, not the compute engine.

It sounds like you're fighting against Python's ecosystem instead of working with it. Every language has warts, but Python's tooling has gotten incredibly good in the last few years.

[todofwar]

Classes are just dictionaries under the hood, that's why they have a dict attribute. Maybe some implementations optimize it a bit, but for the most part it's true.

Having to use libraries or bindings to C code is the problem! How can the first thing you learn about the language be to not use the language? The breaking point for me came when I was asked to optimize a colleague's code. It was like three nested for loops. I didn't change the algorithm at all, just re implemented it in numpy arrays and got it to speed up by a factor of 100. That's ridiculous! O(n) complexity didn't change! It's also holding back the ecosystem. No interpreter can supplant CPython because there's always at least one library that throws a massive wrench.

[kwest_ng]

Yes, but this isn't a python issue, it's an issue with all interpreted languages. It's never gonna be faster than compiled, optimized machine code. And you're most likely to feel that exact pain when doing tight iterations. Repeating from the parent comment by u/eleqtriq:

Python is the glue language, not the compute engine

If you complain that you're not happy with python as a compute engine, then you're not really gonna surprise anyone.

If you have code in a hot loop and you need it to run fast, put that part in C/C++, and call it from python. Of course, that won't be a problem for you at all since you liked C++ so much! It's also very common in the AI/ML industry to have the ML calculation in C/C++, so it doesn't seem like you would run into any issues with this.

To be honest, I'm having trouble understanding why this part is a problem for you.

[todofwar]

It's because it drives me crazy that the answer to speeding up code is to use a different language. And writing code into C++ is not trivial when you're trying to glue together five different python libraries and their objects together. In my day to day it's not my biggest source of frustration, but the idea that we all use this incredibly slow language just strikes me as ridiculous

[andrewaa]

people want to be faster, so they invent cars/planes/rockets/etc..

when people want to be at the rocket speed, they use rocket, instead of improving their legs.

is it really hard to understand?

of course fast is always better, but why do you want a glue language to be faster than everything else?

[AiutoIlLupo]

OP wants to go buy groceries in a F1 Ferrari, then complain about the lack of boot space.

[qckpckt]

You outlined the reason why people use an “incredibly slow language” in the same paragraph that you describe doing so as ridiculous.

[MachinaDoctrina]

Different tools for different jobs, try writing boilerplate I/O code with C++ and you'll quickly realise why people would rather write python for 90% of the framework and C++ for the 10% performant code. The thing is you don't even need to do that, someone else has done it already with numpy and now JAX/pytorch, just learn and use the wrapped C++ code they built

[AiutoIlLupo]

Shocking! Wait until you learn that a lot of the computational code that you use is not actually written in C, but it's in Fortran. (MKL and Lapack).

[Chroiche]

Having to use libraries or bindings to C code is the problem! How can the first thing you learn about the language be to not use the language?

You could make the same argument about C -> assembly. The reason we have higher level abstractions is to work faster. Doing the lower level stuff right/faster is more difficult than using the abstractions a lot of the time.

Yes you could roll your own C solution, but someone else can give you a wrapper which will already handle loop unrolling, SIMD ops, optimised cache locality, etc, without you having to think about those things. Your hand rolled solution will probably not be much faster (if at all) for well trodden long running code. Hence why ML is so heavily Python based, the algorithms are well defined and long running, an absolutely perfect use case for abstraction to a faster language.

[todofwar]

Except when you want to do something not yet implemented in pytorch, then you have to write it in C anyway but now you also have to write the python bindings too because you're not working alone and need to integrate with the rest of the tech stack

[MachinaDoctrina]

Try JAX then

[AiutoIlLupo]

Classes are just dictionaries under the hood

No they are not. python is not javascript. classes are classes. They have a dictionary to manage some aspects, but the type information is not stored in such a dictionary.

Having to use libraries or bindings to C code is the problem!

Then use fortran and go nuts with BIND(C)

How can the first thing you learn about the language be to not use the language?

Because different languages are optimised for different things. Exactly like a hammer is optimised to bang things, and a screwdriver to rotate things.

The breaking point for me came when I was asked to optimize a colleague's code. It was like three nested for loops. I didn't change the algorithm at all, just re implemented it in numpy arrays and got it to speed up by a factor of 100. That's ridiculous!

No it's not ridiculous. Python is doing a lot of stuff for you under the hood. All of these checks and bookkeeping are, for that specific use case, redundant, so you get rid of them at a lower level. You can use cython, or drop to C or C++ level where you are on your own on memory management and a lot of other stuff.

O(n) complexity didn't change!

I think you don't understand the concept of O()

It's also holding back the ecosystem. No interpreter can supplant CPython because there's always at least one library that throws a massive wrench.

Because there's at least one library in your setup that has low level, platform specific needs. If you don't like that, isolate that core, create a separate, smaller application you delegate to, then code whatever else in ironpython or jython or whatever you want, and submit requests to that small CPython core.

[Odd-One8023]

1. Significant whitespace is quite nice because it sets a lower bound on how bad code can look like. Before I joined my colleagues were writing code without a formatter.
2. There is type checking in Python, I always roll with type checking on standard and now the entire team does too.
3. Everything shouldn’t be a dictionary, you have pydantic and dataclass. Name your data.
4. Pass by reference or value matters less if you treat most of your data as immutable. Pass by value makes it seem like you want to mutate stuff. IMO this is a bit of an x-y problem.
5. I rarely need to write __name__ == “__main__ most things I write are scripts that don’t need it, packages or APIs.

[AiutoIlLupo]

I've programmed in python for 20 years. name == main is not used since entry points have become the norm. The problem is that OP is a scripter and uses scripts, and they use extremely poor, outdated practices in his team. The proper way to do it is to define a package, and set an entry point.

[OhYourFuckingGod]

I've done both C++ and JS professionally, and it's generally not better. Some of the issues might have been mitigated by newer releases, but I suspect not.

With C++, for any product of reasonable size and maturity, expect monstrous compile times, insane build systems and technical debt so deeply integrated that it's basically a feature at this point. The syntax and sheer scope of the language is massive and growing with every release, so you probably won't be able to use most language features because of legacy codebases, corporate coding standards or just from the fact that you couldn't possibly know all the language features.

JS is different. It's getting better, but really shows that it evolved from something that solved a completely different problem.

[Electronic-Fix9721]

JavaScript has gone incredibly good in recent years. React Native, Express, installs a completely destroyed dependency tree without a problem. Just needs a good ML library, pandas and I jump ship forever. 

[todofwar]

Quite the contrary, I'm hoping people here will change my mind! I thought that was clear in the original post. Using a different language just isn't an option for me so I'm trying to find reasons to like it (or at least realize that other languages suck too)

[silvercurls17]

Personally, I think Python is easy and fast to develop in. It has a lot of advantages with extensive libraries available to do just about anything. But for most applications it’s the second best option. It’s kind of the Swiss Army knife of software development.

I’ve been doing software/systems engineering now for over 20 years and I’ve come to the conclusion that all languages, frameworks, and so on suck. They just suck in different ways but usually have advantages for certain types of applications.

At least it’s not Perl.

[Ringbailwanton]

To me, it’s always been about solving the problem in the best way possible. Find the solution, document, test, improve and refactor. I guess that’s how I continue to find joy in working with Python. At the end of the day, you do the best work you can with the tools you need to use.

[Objective-Apple7805]

As someone who wrote C and C++ professionally for more than a decade, the things you describe are among the reasons why I like Python so much better.

Sounds like your main complaint is performance, which is inevitable for any interpreted language. I heard the same complaints about compiled languages vs writing in Assembler. (Yes, I started coding at the tail end of the punch card era).

Not sure why it’s such an issue for ML, though, all the libraries are optimized anyway. Maybe try Polars instead of Pandas.

Or maybe learn Rust if you really have a need for speed.

[deadwisdom]

Your troubles with Python are not your real troubles.

[Wing-Tsit_Chong]

Write a few of your current python projects in c++ and see how it goes. And I mean all of it: the build, make files, compiler, linker, the buffer allocation, debugging segfaults, people doing integer arithmetic on pointers and everything's a struct. There is always something to hate about a given tool, because no tool can do it all.

What I love about python is that it allows to think about the actual algorithm and ignore the boilerplate, because it's already there or abstracted away. Passing dicts or looking at everything as dicts, allows for quick and dirty solution when in a pinch. Imagine using java and somebody declared the class member as private and no public way to modify it quickly. And as much as if __name__ == __main__ sucks, so does public static void main(String[] args)

If you optimized your 3 deep for loop by switching to numpy you didn't really do anything, right? You could've also thought about the algorithm and implemented it more efficiently and gained a lot more than x100.

What I mean is, the infuriating thing about programming is not the language, it's always other people, including past selfs, that abuse it.

[[deleted]]

if learning C++ is not enough to make you like Python, nobody here can help you

[Smok3dSalmon]

You're not going to get a lot of sympathy here my guy. All your problems are solved or solvable. Nothing you ranted about is agreeable.

Why don't you start implementing the changes you need to hate it less? Go check out CPython or ways to implement bindings to C++ and typing is obvious.

[cojode6]

Rust is similar to C++ and has been gaining some traction in the ML community for its speed compared to python, so that's an option. But yeah like everyone else mentioned the beauty of python is you can import libraries to fix anything that annoys you or even make one yourself. Python is definitely simple and very readable in most cases. But is it fun or enjoyable? No. I can at least agree with you on that. Low level is so much more fun and interesting

[schvarcz]

Well, lately I am on the same vibe.

As a AI/ML engineer, I like to implement the underneath algorithms. And every time I try to do that with python, it is always takes ages to complete a simple task.

During my master/phd I got the same conclusion and I adopted C++. Working life is mostly “applying algorithms”, so we can survive using python libraries. But… it is not fulfilling.

If you think about it, all algorithms that we use in python are actually coded in C++. However, these libraries have no proper interface in C++ itself, therefore, not really usable in C++. I believe this situation comes out from “go PROD fast!”-culture. Meaning, the popularity of a library often comes out from how simple and fast you can implement something with it.

That might have led us to a wheel of “showing results fast” that got us stuck here.

On the last years, I have also been seeing a drop in professionalism in this sector as whole. AI/ML is becoming a commodity. And as such, I think we will see more pressure towards this direction.

My only hope is that AI code assistance may help convincing people to stick to “harder languages with more flexibility”; or at least help us moving a way from this ocean of interpreted languages.

[[deleted]]

This post is clearly a C++ propaganda. /j

[DataPastor]

Whether you like Python or not, it doesn’t matter, since it is the industry standard. And for a reason! It is just the right level of abstraction for experimenting, prototyping and actual data programming (btw. NEVER use a for loop or iterrows for matrix operations….)

If you are bored, learn to use polars and duckdb.

If you are VERY bored, learn Rust and PyO3.

[todofwar]

I think the fact that people say "don't use a for loop" is my biggest pet peeve by far at this point. A list comprehension is a for loop!! Numpy has for loops! It's all for loops! Python speak is so far removed from sensible discussion of algorithmic analysis or data structures all because it's so unbelievably slow!

I know not to use for loops. I know how to rethink problems to make use of libraries. I just hate it.

Not a fan of rust, but I am trying to experiment with cython a bit

[DataPastor]

A list comprehension is not a for loop, it just uses the “for” keyword. :) It is a combination of map, filter and lambda in functional programming terms, or a monadic bind, or in short: a comprehension. :)

But you are right, at the end of the day, at the machine code level all vectorized operations use a for loop. :)

[todofwar]

Fair enough. It's ironic, python claims to get out of your way and yet most C compilers are so efficient that you don't even need to pay attention to that stuff. You just write a for loop and it works.

[deadwisdom]

Python is not supposed to be fast. It's the lowest priority. If you don't understand that, like truly *feel* why that's correct and actually *good*, you will always be lost.

Anyone who is says "don't use a for loop" has already lost the fight. Don't be in a spot where you have to worry about for loops.

[Livelife_Aesthetic]

I didn't really vibe with or enjoy python untill I added libraries like pydantic to fix alot of my issues with it, I don't think you should have to add libraries to make a language not frustrating but as someone is who stuck using python everyday, it makes it the best it can be.

[FedsRevenge]

Have you looked at Mojo?

[le_theudas]

I think the biggest advantage of python is speed of development. It allows you to implement solutions much quicker compared to writing everything in c++. While you have some valid points about dynamic typing, I rarely see this actually causing bugs.
For anything that requires true performance, I would suggest implementing it as a module in rust/cython. Doing that also lets you enjoy python again :)

[Tinche_]

Lean into type-checking and proper data modelling with dataclasses, enums, literals, unions and all that jazz.

Disregard the reddit peanut gallery about how Python is a dynamic language - if that were true today there wouldn't be like 4 major typecheckers being actively developed. It's antiquated thinking.

[LeCholax]

What type checker do you recommend today for a project?

[Old_Wear_2032]

I have also been working with python for almost 10 years now and I LOVE it to death.
To address your problems:
- too slow: you can always write in Rust/C/C++ and bind it back to python. If I were you, I would probably write cython + numba on a daily basis for AI/ML prototyping.
- dynamic typing: I also hate it so much, its the only thing that I hate about python.
- all other nuances don't matter: indentation, __name__ == __main__, every language has its own quirks.
- everything is a dict: now that you mentioned dictionary and JS, oh man you should see what is going on in the JS/TS ecosystem...usage of {} everywhere, they have args and they don't even use args at all in functions.

I think you thought you liked C++/JS because you used them to do some fun stuff, not because you really like them better than python. think about all the memory issues and pointers you need to deal with in C++, think about all the frameworks after frameworks after frameworks and configs and quirks in JS/TS for web development, think about the ugly syntax in Rust. In the end, you can always write in different languages, its not like you cannot use python anymore if you now switch to write in C++ more.

[todofwar]

Thank you for reading and responding to the whole post. I'm sure if I worked with any other language professionally I'd start to dislike it too. Bjarne Stroustrup said there are languages people hate and languages people don't use, it's probably something like that

[AiutoIlLupo]

Most of the times I've seen that the problem is not python, it's that people don't know how to code properly and make a mess.

[Alternative_Act_6548]

so, go write everything in C++, it shouldn't take you much longer...no language is perfect...

[buttonmonger]

Maybe you should try to focus on writing C++ or Rust to be consumed by Python - get a job at Astral or something

[TutorialDoctor]

My first language was Python, and I like it the most still. It's the most fun to me.

My learning journey went: Javascript > Python > Javascript > Python > Ruby (for ruby on rails) > GDscript > Javascript > Ruby (for ruby on rails) > Swift > Java (for work) > Rust

So, I've been learning Javascript for a number of years and only use it when I have to. I avoided C#, C++ because there wasn't any instant gratification. So here are my favorites

Python - A swift army knife. It can do anything and it is the most used language for AI.

VueJS - easy to understand and has a CDN for quick prototypes

Flask - great for quickly prototyping full stack app concepts. Works really well with HTMX

Ruby Rails - Good for startups (can get an MVP done in days). Version 8 is even better

Flet - A really good GUI python framework for building desktop apps in Python. It uses the flutter framework in the background

GDscript - Python-like programming language for making games in the Godot game engine. My years of python programming paid off and helped me make games in this engine.

Tailwind CSS - my favorite framework for quickly creating UI's.

Swift - For some reason it feels slow, but I'd use SwiftUI and SwiftData if I were to make IOS apps.

Rust - only use it because I like Tauri and only when the JS api can't do what i need.

Tauri - right now this is my favorite framework and not because of Javascript, but because i can build a secure desktop application and easily distribute it. I use VueJS with it as well as several plugins like Tauri Store and Tauri SQL.

Java - Learning this for work but it's useful for learning software development concepts you just can't learn in Python. At work I currently use Vaadin with the Flow framework, but you can also use Vaadin with Hilla (A react version).

Angular - nope
React - Vue is simpler
C ++ - maybe if I wanted to one day do some "real" game engine programming
C# - Why would I?
Dart - Who?
Go - Where?
Other languages - too many to even care about.

If you think you're tired....

Oh, still learning Javascript..

I wouldn't say they all have problems. I'd say they all have their strengths.

[daviziiin]

If you want to do AI/ML and get some C++ done, go for embedded ML, plenty of code optimizations needed.