3 ms·

Although conda is also getting slower and slower, and now routinely spends 5-20 minutes on dependency resolution even for trivial environments.

by goerz 8y ago

mlthoughts2018 8y ago
This is deeply untrue for conda. Even very complex environments build in less than a minute. I can believe there are corner cases where conda is very slow, but claiming conda takes 5 minutes for trivial environments is flat out wrong. Perhaps it is issues with a firewall, VPN connection or something else, absolutely no chance that is from normally executing conda.
- goerz 8y ago
  Well, I experience it on a daily basis, and I'm not the only one! It's officially an open issue: https://github.com/conda/conda/issues/7239 https://github.com/conda/conda/issues/7239
  - mlthoughts2018 8y ago
    The slowest operation in the linked thread is still taking less than 2 minutes... Edit: correction, there are two examples that take longer, one at 3.5 minutes, one around 8 minutes. I don’t think it changes any takeaways though.
    - goerz 8y ago
      The last one in that thread is 11 minutes. And, I just did `time conda create -n test -y anaconda pytest-cov pytest-xdist coverage sphinx_rtd_theme flake8` on my Macbook, and it clocked in at 36 minutes! Probably, this is affected by also having the condaforge channel active (which I need), but it's definitely not from some network/VPN issues. Everyone I work with has similar problems. So don't tell me there's "absolutely no chance that is from normally executing conda".
      - mlthoughts2018 8y ago
        The same command for me, also running on a Macbook, took just over 5 minutes, using conda 4.5.9. I also repeated inside a Ubuntu docker container with only miniconda installed and got the same. It’s funny to me that you would expect operations involving “conda install anaconda” to be fast though. 11 minutes seems perfectly fast for that and would be comparable to pip or anything else if doing that huge of a set of package installs. That is not at all a “trivial environment” like you said previously.

Although conda is also getting slower and slower, and now routinely spends 5-20 minutes on dependency resolution even for trivial environments.

by goerz 8y ago

Although conda is also getting slower and slower, and now routinely spends 5-20 minutes on dependency resolution even for trivial environments.

mlthoughts2018 8y ago

This is deeply untrue for conda. Even very complex environments build in less than a minute. I can believe there are corner cases where conda is very slow, but claiming conda takes 5 minutes for trivial environments is flat out wrong. Perhaps it is issues with a firewall, VPN connection or something else, absolutely no chance that is from normally executing conda.

goerz 8y ago
Well, I experience it on a daily basis, and I'm not the only one! It's officially an open issue: https://github.com/conda/conda/issues/7239 https://github.com/conda/conda/issues/7239
- mlthoughts2018 8y ago
  The slowest operation in the linked thread is still taking less than 2 minutes... Edit: correction, there are two examples that take longer, one at 3.5 minutes, one around 8 minutes. I don’t think it changes any takeaways though.
  - goerz 8y ago
    The last one in that thread is 11 minutes. And, I just did `time conda create -n test -y anaconda pytest-cov pytest-xdist coverage sphinx_rtd_theme flake8` on my Macbook, and it clocked in at 36 minutes! Probably, this is affected by also having the condaforge channel active (which I need), but it's definitely not from some network/VPN issues. Everyone I work with has similar problems. So don't tell me there's "absolutely no chance that is from normally executing conda".
    - mlthoughts2018 8y ago
      The same command for me, also running on a Macbook, took just over 5 minutes, using conda 4.5.9. I also repeated inside a Ubuntu docker container with only miniconda installed and got the same. It’s funny to me that you would expect operations involving “conda install anaconda” to be fast though. 11 minutes seems perfectly fast for that and would be comparable to pip or anything else if doing that huge of a set of package installs. That is not at all a “trivial environment” like you said previously.