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I personally hate Conda with a firey passion - it does so much weird magic and ends up breaking things in non obvious ways. Python works best when you keep it r

I personally hate Conda with a firey passion - it does so much weird magic and ends up breaking things in non obvious ways. Python works best when you keep it really simple. Just a python -m venv per project, a requirements.txt, and you will basically never have issues.

bobbylarrybobby 4y ago
If it were really that simple, surely all these other solutions wouldn't exist?
- buildbot 4y ago
  Not saying Conda et. al don't solve problems, especially in specific cases, but they also add them in my opinion.
- Spivak 4y ago
  So there's two notions of simple. Simple in the sense that it's actually simple, the software you need can be installed with pip install with precompiled binaries for your platform when necessary it supports Python 3.something+, and all it's dependencies are either >= version or the version is >= x.y <= x+1.0 Then there's simple as in the software is actually incredibly useful but is an absolute nightmare of complicated dependency trees where only specific pinned minor versions work together, you need multiple incompatible compiler toolchains and distro packages, it only works if you have CUDA, precompiled binaries exist for some but not all and if you use the precompiled binaries then it changes the dependency story, if you want jupyter support that's a whole different thing AHHHHHHHHHHHHH In that case some people with more time than sanity said fuck it we'll make it work and conda was born. For me it's a lifesaver when you want to use a piece of software but I wouldn't ever dare deploy production software with it without it being strongly isolated from everything else.
- zzzeek 4y ago
  it really is that simple conda exists because it deals with an entirely different package registry and is a whole distro on its own (I dont know why people need that either, my vague impression is that scence-y types want complete pushbutton installation, typing a command == fail, I guess, I dont know). poetry exists because it does some kind of automated version management thing (as did pipenv), that I'm sure is nice but not something I've ever needed, but the buzz got out and it took over, people who have never typed "virtualenv" use poetry and they have no idea why.
  - teruakohatu 4y ago
    > vague impression is that scence-y types Because often python is only one part of the puzzle, we also need a variety of third party libraries and maybe R as well (along with R packages). And we would rather not have to explain to another researcher how to install it all.
  - squeaky-clean 4y ago
    Conda is very nice for people who just want to write some python and not need to learn about the ecosystem or weird issues like some Visual Studio dependency not being installed to get scipy to compile on Windows or whatever. Like someone coming from R to Python. But aside from that situation I agree with you.
  - pletnes 4y ago
    Before conda, you needed a C and a fortran compiler, a BLAS and LAPACK installation, and various build tools, to install scipy. Scipy is one - 1 - dependency used in science and engineering. The pain used to be massive. Now, we’re complaining about the existence of 2 high quality (not perfect) alternatives, and pip (part of the official python distro) can install tensorflow etc, GPU libs included, with a oneliner.
    - Doxin 4y ago
      These days with wheels there is 0 reason why there can't be binary pip packages for any of those. Definitely used to be a problem though.
  - jayvius 4y ago
    > (I dont know why people need that either, my vague impression is that scence-y types want complete pushbutton installation, typing a command == fail, I guess, I dont know). Essentially, yes, and justifiably so. Try installing science-y Python packages on Windows written in C. When conda was created in 2012 this meant installing Visual Studio 2005 (for Python 2.7) which was hard to find on Microsoft's own website even back then.
    - 4y ago
- schainks 4y ago
  If software were that simple, surely all these other languages wouldn't exist?
  - bobbylarrybobby 4y ago
    Right, software is anything but simple
- crabbone 4y ago
  Any program with real world application solves some problem. That's not the point. The point is in how does it do it. And when it comes to conda... it's like MS Outlook on steroids. I cannot really think about a better way to describe it. It's like a movie that can be so bad that it's actually good.
- hot_gril 4y ago
  Idk, I still have no idea why yarn exists when there's npm.
jstx1 4y ago
With plain venv it’s hard to maintain multiple different Python versions on the same machine; conda makes this much easier. Also on M1/M2 Macs some libraries (especially for ML) are only available through conda-forge.
- buildbot 4y ago
  Is it? I just install different version with brew, and choose which python3.X to create a venv with. The ML packages issue is much more of an issue, but now that the ARM transition is well underway more and more packages work via normal pip.
- zzzeek 4y ago
  I have like seven pythons on my machine, and I use virtualenv all over, there's no issue, what's the issue? I have to type the path of a specific interpreter when i make a virtualenv, is that the problem? I bet that's the problem
- dragonwriter 4y ago
  > With plain venv it’s hard to maintain multiple different Python versions on the same machine Ironically, given the usual software dev experience on Windows vs. Unixy systems, this is not a problem with the standard install on Windows with the py launcher.
  - lmm 4y ago
    It's not ironic at all; traditional Linux package management is actualy really bad. On a Linux system you can basically only have one version of anything installed at the same time.
    - selcuka 4y ago
      I have multiple Python versions on both my Macbook M1 and my Linux laptop, with several dozen venvs. I honestly don't see why others are having so many issues. Probably bad documentation/tutorials.
pbronez 4y ago
Until you want to use anything with a c extension..
- wheelerof4te 4y ago
  Why would you want to use Python with a C extension? If you need performance, just use native code.
  - peterhil 4y ago
    Numpy and Scipy are good reasons. Unfortunately Scipy does not even compile on FreeBSD lately, and I have opened three issues about it against Scipy and Pythran (and the fix was with xsimd). https://github.com/serge-sans-paille/pythran/issues/2070 https://github.com/serge-sans-paille/pythran/issues/2070
  - epgui 4y ago
    > Why would you want to use Python with a C extension? Because if you need performance, you need to use native code.
- buildbot 4y ago
  I use it all the time for things with c extensions?
insane_dreamer 4y ago
I'm the opposite. We have to maintain a lot of different environments for different projects, and with conda things "just work" (esp now with better PyCharm integration). Venv is much more of a hassle.
crabbone 4y ago
I remember when Conda just appeared... I was so high no hopium... well, the word "hopium" didn't exist yet... Anyways. Today I have to help scientists to deal with it. And... I didn't think it was possible to be worse than pip or other Python tools, but they convinced me it is. Conda is the worst Python program of note that I had ever dealt with. It's so spectacularly bad it's breathtaking. You can almost literally take a random piece of its source code and post it to user boards that make fun of bad code. When I have a bad day, I just open its code in a random file, and like that doctor who was happy running around the imaging room exclaiming "I'm so, so, so happy! I'm so unimaginably happy that I'm not this guy! (pointing at an X-ray in his hand)" I'm happy I'm not the author of this program. I would've just died of shame and depression if I was.
lmm 4y ago
> Just a python -m venv per project, a requirements.txt, and you will basically never have issues. As long as you always remember to run exactly the right two commands every time you work on any project and never run the wrong ones, or run project A's commands in project B's terminal. There's no undo BTW, if you ever do that you've permanently screwed up your setup for project B and there's no way to get back to what you had before (your best bet is destroying and recreating project B's venv, but that will probably leave you with different versions of dependencies installed from what you had before). (And as others have said, that doesn't cover multiple versions of Python, or native dependencies. But even if your project is pure python with only pure python dependencies that work on all versions, venv+pip is very easy to mess up and impossible to fix when you do)

bobbylarrybobby 4y ago

If it were really that simple, surely all these other solutions wouldn't exist?

buildbot 4y ago
Not saying Conda et. al don't solve problems, especially in specific cases, but they also add them in my opinion.
Spivak 4y ago
So there's two notions of simple. Simple in the sense that it's actually simple, the software you need can be installed with pip install with precompiled binaries for your platform when necessary it supports Python 3.something+, and all it's dependencies are either >= version or the version is >= x.y <= x+1.0 Then there's simple as in the software is actually incredibly useful but is an absolute nightmare of complicated dependency trees where only specific pinned minor versions work together, you need multiple incompatible compiler toolchains and distro packages, it only works if you have CUDA, precompiled binaries exist for some but not all and if you use the precompiled binaries then it changes the dependency story, if you want jupyter support that's a whole different thing AHHHHHHHHHHHHH In that case some people with more time than sanity said fuck it we'll make it work and conda was born. For me it's a lifesaver when you want to use a piece of software but I wouldn't ever dare deploy production software with it without it being strongly isolated from everything else.
zzzeek 4y ago
it really is that simple conda exists because it deals with an entirely different package registry and is a whole distro on its own (I dont know why people need that either, my vague impression is that scence-y types want complete pushbutton installation, typing a command == fail, I guess, I dont know). poetry exists because it does some kind of automated version management thing (as did pipenv), that I'm sure is nice but not something I've ever needed, but the buzz got out and it took over, people who have never typed "virtualenv" use poetry and they have no idea why.
- teruakohatu 4y ago
  > vague impression is that scence-y types Because often python is only one part of the puzzle, we also need a variety of third party libraries and maybe R as well (along with R packages). And we would rather not have to explain to another researcher how to install it all.
- squeaky-clean 4y ago
  Conda is very nice for people who just want to write some python and not need to learn about the ecosystem or weird issues like some Visual Studio dependency not being installed to get scipy to compile on Windows or whatever. Like someone coming from R to Python. But aside from that situation I agree with you.
- pletnes 4y ago
  Before conda, you needed a C and a fortran compiler, a BLAS and LAPACK installation, and various build tools, to install scipy. Scipy is one - 1 - dependency used in science and engineering. The pain used to be massive. Now, we’re complaining about the existence of 2 high quality (not perfect) alternatives, and pip (part of the official python distro) can install tensorflow etc, GPU libs included, with a oneliner.
  - Doxin 4y ago
    These days with wheels there is 0 reason why there can't be binary pip packages for any of those. Definitely used to be a problem though.
- jayvius 4y ago
  > (I dont know why people need that either, my vague impression is that scence-y types want complete pushbutton installation, typing a command == fail, I guess, I dont know). Essentially, yes, and justifiably so. Try installing science-y Python packages on Windows written in C. When conda was created in 2012 this meant installing Visual Studio 2005 (for Python 2.7) which was hard to find on Microsoft's own website even back then.
  - 4y ago
schainks 4y ago
If software were that simple, surely all these other languages wouldn't exist?
- bobbylarrybobby 4y ago
  Right, software is anything but simple
crabbone 4y ago
Any program with real world application solves some problem. That's not the point. The point is in how does it do it. And when it comes to conda... it's like MS Outlook on steroids. I cannot really think about a better way to describe it. It's like a movie that can be so bad that it's actually good.
hot_gril 4y ago
Idk, I still have no idea why yarn exists when there's npm.

jstx1 4y ago

With plain venv it’s hard to maintain multiple different Python versions on the same machine; conda makes this much easier. Also on M1/M2 Macs some libraries (especially for ML) are only available through conda-forge.

buildbot 4y ago
Is it? I just install different version with brew, and choose which python3.X to create a venv with. The ML packages issue is much more of an issue, but now that the ARM transition is well underway more and more packages work via normal pip.
zzzeek 4y ago
I have like seven pythons on my machine, and I use virtualenv all over, there's no issue, what's the issue? I have to type the path of a specific interpreter when i make a virtualenv, is that the problem? I bet that's the problem
dragonwriter 4y ago
> With plain venv it’s hard to maintain multiple different Python versions on the same machine Ironically, given the usual software dev experience on Windows vs. Unixy systems, this is not a problem with the standard install on Windows with the py launcher.
- lmm 4y ago
  It's not ironic at all; traditional Linux package management is actualy really bad. On a Linux system you can basically only have one version of anything installed at the same time.
  - selcuka 4y ago
    I have multiple Python versions on both my Macbook M1 and my Linux laptop, with several dozen venvs. I honestly don't see why others are having so many issues. Probably bad documentation/tutorials.

pbronez 4y ago

Until you want to use anything with a c extension..

wheelerof4te 4y ago
Why would you want to use Python with a C extension? If you need performance, just use native code.
- peterhil 4y ago
  Numpy and Scipy are good reasons. Unfortunately Scipy does not even compile on FreeBSD lately, and I have opened three issues about it against Scipy and Pythran (and the fix was with xsimd). https://github.com/serge-sans-paille/pythran/issues/2070 https://github.com/serge-sans-paille/pythran/issues/2070
- epgui 4y ago
  > Why would you want to use Python with a C extension? Because if you need performance, you need to use native code.
buildbot 4y ago
I use it all the time for things with c extensions?

insane_dreamer 4y ago

I'm the opposite. We have to maintain a lot of different environments for different projects, and with conda things "just work" (esp now with better PyCharm integration). Venv is much more of a hassle.

crabbone 4y ago

I remember when Conda just appeared... I was so high no hopium... well, the word "hopium" didn't exist yet... Anyways. Today I have to help scientists to deal with it. And... I didn't think it was possible to be worse than pip or other Python tools, but they convinced me it is. Conda is the worst Python program of note that I had ever dealt with. It's so spectacularly bad it's breathtaking. You can almost literally take a random piece of its source code and post it to user boards that make fun of bad code. When I have a bad day, I just open its code in a random file, and like that doctor who was happy running around the imaging room exclaiming "I'm so, so, so happy! I'm so unimaginably happy that I'm not this guy! (pointing at an X-ray in his hand)" I'm happy I'm not the author of this program. I would've just died of shame and depression if I was.

lmm 4y ago

> Just a python -m venv per project, a requirements.txt, and you will basically never have issues. As long as you always remember to run exactly the right two commands every time you work on any project and never run the wrong ones, or run project A's commands in project B's terminal. There's no undo BTW, if you ever do that you've permanently screwed up your setup for project B and there's no way to get back to what you had before (your best bet is destroying and recreating project B's venv, but that will probably leave you with different versions of dependencies installed from what you had before). (And as others have said, that doesn't cover multiple versions of Python, or native dependencies. But even if your project is pure python with only pure python dependencies that work on all versions, venv+pip is very easy to mess up and impossible to fix when you do)