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I've had the opposite experience. I used conda for several years, primarily for data science, but regularly ran into problems with packages not working, updates

I've had the opposite experience. I used conda for several years, primarily for data science, but regularly ran into problems with packages not working, updates for packages bring severely delayed, and issues with conda itself. Switched to pyenv+virtualenv 18 months ago and haven't had a single issue. I believe both of our stories. I just always wonder how this happens that two people have such opposite experiences.

talentedcoin 7y ago
Ha!! Likewise, I believe you 100%. It’s fascinating isn’t it? Just goes to show what a diverse (and frankly wonderful) platform Python is, despite the warts. If you don’t mind my asking, what kind of stuff we’re you working on? Just curious! I have definitely found it’s easy to bork a conda install with updates, enough to make it easier to just wipe it out and start over. I mostly work on financial software and only conda seemed to play nicely with pandas and brokerage APIs. I should probably mention that I do a lot of this is cross-platform and conda seemed to be the only thing that worked without a lot of tweaking on Windows, Mac and Linux consistently. But the Linux experience with pyenv and virtualenv (and pipenv too, for the most part) was great. If I was Linux-only I honestly might never have switched.
poooood 7y ago
We’re you using conda on windows or not windows? (Just curious)
zelphirkalt 7y ago
Default Python's Venv puts reproducibility of environment and scientific computing results at risk, by not creating a file which includes all the checksums recursively. One needs to take extra steps to achieve that. It is possible though.
takluyver 7y ago
Just to note: this kind of difference is part of why it's so difficult to improve packaging. There are lots of different tools, and they all work well for some people in some situations. There's no realistic prospect of persuading them all to use a single tool - but the fragmentation is a big part of what makes packaging so daunting.
BiteCode_dev 7y ago
Because conda and other tools don't mix. If you only use conda, it works. If you start to pip install or use venv, it will break at some point.

talentedcoin 7y ago

Ha!! Likewise, I believe you 100%. It’s fascinating isn’t it? Just goes to show what a diverse (and frankly wonderful) platform Python is, despite the warts. If you don’t mind my asking, what kind of stuff we’re you working on? Just curious! I have definitely found it’s easy to bork a conda install with updates, enough to make it easier to just wipe it out and start over. I mostly work on financial software and only conda seemed to play nicely with pandas and brokerage APIs. I should probably mention that I do a lot of this is cross-platform and conda seemed to be the only thing that worked without a lot of tweaking on Windows, Mac and Linux consistently. But the Linux experience with pyenv and virtualenv (and pipenv too, for the most part) was great. If I was Linux-only I honestly might never have switched.

poooood 7y ago

We’re you using conda on windows or not windows? (Just curious)

zelphirkalt 7y ago

Default Python's Venv puts reproducibility of environment and scientific computing results at risk, by not creating a file which includes all the checksums recursively. One needs to take extra steps to achieve that. It is possible though.

takluyver 7y ago

Just to note: this kind of difference is part of why it's so difficult to improve packaging. There are lots of different tools, and they all work well for some people in some situations. There's no realistic prospect of persuading them all to use a single tool - but the fragmentation is a big part of what makes packaging so daunting.

BiteCode_dev 7y ago

Because conda and other tools don't mix. If you only use conda, it works. If you start to pip install or use venv, it will break at some point.