7 ms·

Conda now supports PyPy builds

64 points by bratao 7y ago

bratao 7y ago
Here is a good place to follow the effort of packages Migrations and PyPy support https://conda-forge.org/status/ https://conda-forge.org/status/
prpl 7y ago
Just to be pedantic: This is conda forge, which is very popular but it is not conda. That said, I won’t be entirely surprised if there is a fork in the next 1-3 years, with conda-forge releasing miniforge.
- uranusjr 7y ago
  To be really pedantic, Conda is a package manager, and it doesn’t really make sense to say “Conda supports PyPy” because Conda does not even know how PyPy is different from any other package it installs.
  - pletnes 7y ago
    Technically correct, the best kind of correct! Conda can in fact install pypy from conda-forge, which is close enough for most people.
    - sandGorgon 7y ago
      It's not about installing pypy. It's making sure each package has transitive dependencies that behaves well on pypy. This is a huge effort.
vslira 7y ago
Good news. Pypy is criminally underrated
pottertheotter 7y ago
I'm curious, people who use conda, what's your reason for doing so? When I started using Python I used conda because people told me I would have a really hard time managing packages if I didn't. I used it for quite some time, but kept running into issues. For instance, new versions of packages would be released and it would be forever until they were available in conda. And it seemed every month or two conda itself would have some issue that I'd have to spend a while troubleshooting. Then I discovered pyenv + virtualenv. I can't think of a single issue over the last 18 months. I can easily run any version of Python, virtual environments are way easier to deal with, and PIP has been so much better than conda for packages. Is there something else I'm missing about conda? Or was conda something that was needed and great several years ago, but not so much these days? I'd also love to hear if there's something better than pyenv + virtualenv I should look into.
- chockablock 7y ago
  Managing non-python software and its dependencies, for one thing. I’ve used it to package Qt apps, shell scripts, even JavaScript packages that were intertwined with non-js components (though that was painful).
- RocketSyntax 7y ago
  Agreed. It bothers me that Jupyter ecosystem trends toward it. pip + virtualenv + pyenv + poetry (not pipenv) However, one of the main benefits I remember is that it is not just Python env/package mgmt. Data scientists can pull R packages too.
  - rdtsc 7y ago
    The issue I think is that it is just one thing as opposed to 4 different ones. Now I prefer pip and friends but I remember starting out it was hard to figure out and remember the interplay between all them. Especially with Windows in the mix conda was just much simpler.
- bawana 7y ago
  conda makes cudatoolkit available. That can save a lot of time not having to figure out how to install CUDA and cudnn
deleted 7y ago
[deleted]
dmulholl 7y ago
On the subject of PyPy, I'd never used it until a month or so ago but I've been working on reinforcement learning models for a final year computer engineering project and slow training times were a serious problem until I found I could get a 10x speed boost without changing a line of code simply by switching from the default Python interpreter to PyPy. (Average training time dropped instantly from three minutes per episode to twenty seconds.) I'm seriously impressed by the work the PyPy guys have done.
- Raphaellll 7y ago
  Did you use any library?
  - nyanpasu64 7y ago
    Not parent, but in my experience, PyPy is much faster than CPython on regular scripts, but has slower C API interop (more overhead calling Numpy).
pjmlp 7y ago
Great news! Python needs more JIT love.

64 points by bratao 7y ago

Here is a good place to follow the effort of packages Migrations and PyPy support https://conda-forge.org/status/ https://conda-forge.org/status/

prpl 7y ago

Just to be pedantic: This is conda forge, which is very popular but it is not conda. That said, I won’t be entirely surprised if there is a fork in the next 1-3 years, with conda-forge releasing miniforge.

uranusjr 7y ago
To be really pedantic, Conda is a package manager, and it doesn’t really make sense to say “Conda supports PyPy” because Conda does not even know how PyPy is different from any other package it installs.
- pletnes 7y ago
  Technically correct, the best kind of correct! Conda can in fact install pypy from conda-forge, which is close enough for most people.
  - sandGorgon 7y ago
    It's not about installing pypy. It's making sure each package has transitive dependencies that behaves well on pypy. This is a huge effort.

vslira 7y ago

Good news. Pypy is criminally underrated

pottertheotter 7y ago

I'm curious, people who use conda, what's your reason for doing so? When I started using Python I used conda because people told me I would have a really hard time managing packages if I didn't. I used it for quite some time, but kept running into issues. For instance, new versions of packages would be released and it would be forever until they were available in conda. And it seemed every month or two conda itself would have some issue that I'd have to spend a while troubleshooting. Then I discovered pyenv + virtualenv. I can't think of a single issue over the last 18 months. I can easily run any version of Python, virtual environments are way easier to deal with, and PIP has been so much better than conda for packages. Is there something else I'm missing about conda? Or was conda something that was needed and great several years ago, but not so much these days? I'd also love to hear if there's something better than pyenv + virtualenv I should look into.

chockablock 7y ago
Managing non-python software and its dependencies, for one thing. I’ve used it to package Qt apps, shell scripts, even JavaScript packages that were intertwined with non-js components (though that was painful).
RocketSyntax 7y ago
Agreed. It bothers me that Jupyter ecosystem trends toward it. pip + virtualenv + pyenv + poetry (not pipenv) However, one of the main benefits I remember is that it is not just Python env/package mgmt. Data scientists can pull R packages too.
- rdtsc 7y ago
  The issue I think is that it is just one thing as opposed to 4 different ones. Now I prefer pip and friends but I remember starting out it was hard to figure out and remember the interplay between all them. Especially with Windows in the mix conda was just much simpler.
bawana 7y ago
conda makes cudatoolkit available. That can save a lot of time not having to figure out how to install CUDA and cudnn

deleted 7y ago

[deleted]

dmulholl 7y ago

On the subject of PyPy, I'd never used it until a month or so ago but I've been working on reinforcement learning models for a final year computer engineering project and slow training times were a serious problem until I found I could get a 10x speed boost without changing a line of code simply by switching from the default Python interpreter to PyPy. (Average training time dropped instantly from three minutes per episode to twenty seconds.) I'm seriously impressed by the work the PyPy guys have done.

Raphaellll 7y ago
Did you use any library?
- nyanpasu64 7y ago
  Not parent, but in my experience, PyPy is much faster than CPython on regular scripts, but has slower C API interop (more overhead calling Numpy).

pjmlp 7y ago

Great news! Python needs more JIT love.