Sure, this is just my experience, but I use Python a lot and use a lot of tools written in Python.
Usually happens to me when I find code for some research paper. Even something that's just three months old can be a real pain to get running
Still, I would think it's rare that package versions of different packages become incompatible?
To be fair to the GP comment, this is how I feel about Ruby software. I am not nearly as practiced at installing and upgrading in that ecosystem so if there was a way to install tools in a way that lets me easily and completely blow them away, I would be happier to use them.
One of the commentors above explained what the problem really is (basically devs doing "pip install whatever" for their dependencies, instead of managing them properly). That's more a problem of bad development practices though, no?
I guess this is mostly about data science code and maybe people who publish software in those communities are just doing very poor packaging, so this idea of a "lock file" that freezes absolutely everything with zero chance for any kind of variation is useful. Certainly the worst packaged code I've ever seen with very brittle links to certain python versions and all that is typically some ML sort of thing, so yeah.
This is all anathema to those of us who know how to package and publish software.
God, I hate Python. Why is it so hard to not break code?
Exactly my case. I had to move back to Debian from Ubuntu, where I had installed Chatterbox without much difficulty, and it was hell. You pretty much need Anaconda. With it, it's a cinch.
>what are open-source voice synth which have been working for you.
I tried a few, although rather superficially. Keeping in mind that my 3090 is on my main (Windows) machine, I was constrained to what I could get running on it without too much hassle. Considering that:
* I tried Parler for a bit, although I became disillusioned when I learned all models have an output length limit, rather than doing something internally to split the input into chunks. What little I tried with it sounded pretty good if it stayed within the 30-second window, otherwise it became increasingly (and interestingly) garbled.
* Higgs was good. I gave it one of Senator Armstrong's lines and made it generate the "mother of all omelettes" one, and it was believable-ish; not as emphatic but pretty good. But it was rather too big and slow and required too much faffing around with the generation settings.
* Chatterbox is what I finally settled with for my application, which is making audiobooks for myself to listen to during my walks and bike rides. It fits in the 3070 I have on the Linux machine and it runs pretty quick, at ~2.7 seconds of audio per second.
These are my notes after many hours of listening to Chatterbox:
* The breathing and pauses sound quite natural, and generally speaking, even with all the flaws I'm about to list, it's pleasing to listen to, provided you have a good sample speaker.
* It you go over the 40-second limit, it handles it somewhat more graciously than Parler (IMO). Instead of generating garbage it just cuts off abruptly. In my experience splitting text at 300-350 characters works fairly well, and keeping paragraphs intact where possible generates best results.
* If the input isn't perfectly punctuated it will guess at the sentence structure to read it with the correct cadence and intonation, but some things can still trip it up. I have one particular text where the writer used commas in many places where a period should have gone, and it just cannot figure out the sentence structure like that.
* The model usually tries to guess emotion from the text content, but it mostly gets it wrong.
* It correctly reads quoted dialogue in the middle of narration, by speaking slightly louder. If the text indicates a woman is speaking the model tries to affect a high pitch, with varying degrees of appropriateness in the given context. Honestly, it'd be better if it kept a consistent pitch. And, perplexingly, no matter how much the surrounding text talks about music, it will read "bass" as "bass", instead of "base".
* Quite often the model inserts weird noises at the beginning and end of a clip which will throw you off until you learn to ignore them. It's worse for short fragments, like chapter titles and the like. Very rarely it inserts what are basically cut-off screams, like imagine a professional voice actor is doing a recording and just before he hit stop someone was murdered inside the booth.
* It basically cannot handle numbers more than two digits long. Even simple stuff like "3:00 AM" it will read as complete nonsense like "threenhundred am".
* It also has problems with words in all caps. It's a tossup if it's going to spell it out, yell it, or something in between. In my particular case, I tried all sorts of things to get it to say "A-unit" (as in a unit with the 'A' designation) properly, but sometimes it still manages to fuck it up and go "ah, ah, ah, ah, ah, ah unit".
* Sometimes it will try to guess the accent it should use based on the grammar. For example, I used a sample from a Lovecraft audiobook, with a British speaker, and the output will sometimes turn Scottish out of nowhere, quite jarringly, if the input uses "ya" for "you" and such.
This is the entire problem. You gonna put that in a lock file or just tell your colleagues to run the same command?
In 2025, the overall developer experience is much better in (1) Rust compared to C++, and (2) Java/DotNet(C#) compared to Python.
I'm talking about type systems/memory safety, IDEs (incl. debuggers & compilers), package management, etc.
Recently, I came back to Python from Java (for a job). Once you take the drug of a virtual machine (Java/DotNet), it is hard to go back to native binaries.
Last, for anyone unfamiliar with this quote, the original is from Winston Churchill:
Many forms of Government have been tried, and will be tried in this world of sin and woe. No one pretends that democracy is perfect or all-wise. Indeed it has been said that democracy is the worst form of Government except for all those other forms that have been tried from time to time.I don't really know why this is, at a high level, and I don't care. All I know is that Python is, for me, with the kinds of things I tend to need to build, the absolute fucking worst. I hope uv gets adopted and drives real change.
My last dance with Python was trying to build Ardupilot, which is not written in Python but does have a build that requires a tool written in Python, for whatever reason. I think I was on my Mac, and I couldn't get this tool from Homebrew. Okay, I'll install it with Pip—but now Pip is showing me this error I've never seen before about "externally managed environments", a concept I have no knowledge of. Okay, I'll try a venv—but even with the venv activated, the Ardupilot makefile can't find the tool in its path. Okay, more googling, I'll try Pipx, as recommended broadly by the internet—I don't remember what was wrong with this approach (probably because whatever pipx does is totally incomprehensible to me) but it didn't work either. Okay, what else? I can do the thing everybody is telling me not to do, passing `--break-system-packages` to plain old Pip. Okay, now the fucking version of the tool is wrong. Back it out and install the right version. Now it's working, but at what cost?
This kind of thing always happens, even if I'm on Linux, which is where I more usually build stuff. I see errors nobody has ever posted about before in the entire history of the internet, according to Google. I run into incomprehensible changes to the already incomprehensible constellation of Python tooling, made for incomprehensible reasons, and by incomprehensible I mean I just don't care about any of it, I don't have time to care, and I shouldn't have to care. Because no other language or build system forces me to care as much, and as consistently, as Python does. And then I don't care again for 6 months, a year, 2 years, until I need to do another Python thing, and whatever I remember by then isn't exactly obsolete but it's still somehow totally fucking useless.
The universe has taught me through experience that this is what Python is, uniquely. I would welcome it teaching me otherwise.