Comments (6)
pystow only relies on a small number of super popular packages so i'm not super worried about pinning their versions. Also, this sounds like it's catering to end-users who aren't really creating reusable software
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I'm going to close this as pystow is now on conda-forge. I'm not exactly sure what the update instructions are so i will burn that bridge when we need to come to it
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if i can figure this out, sure. I'm traveling tomorrow and will try to get it set up then
(though personally I'm a huge conda hater - it's a massive problem for reproducibility)
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@cthoyt thanks for being willing to take a look!
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@sgbaird I think it's up, https://anaconda.org/conda-forge/pystow. Let me know if you're able to use this in your package now
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@cthoyt I'm still waiting on the conda-forge
devs to merge mine conda-forge/staged-recipes#19864, but I will let you know if I run into any issues with incorporating it. In the meantime, I did a local installation in a fresh conda env and was able to run a few examples from the README and nothing seems incompatible based on the meta.yaml
recipe you uploaded, so I don't think it will pose a problem. I'll keep the reproducibility issue in mind. One of the recommendations from PyScaffold's data science extension template is:
Dependency Management & Reproducibility
- Always keep your abstract (unpinned) dependencies updated in
environment.yml
and eventually
insetup.cfg
if you want to ship and install your package viapip
later on.- Create concrete dependencies as
environment.lock.yml
for the exact reproduction of your
environment with:For multi-OS development, consider usingconda env export -n matbench-genmetrics -f environment.lock.yml
--no-builds
during the export.- Update your current environment with respect to a new
environment.lock.yml
using:conda env update -f environment.lock.yml --prune
I also came across https://github.com/conda-incubator/conda-lock. Do either of these address that issue? I'm sure each comes with its slew of issues.
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Related Issues (20)
- Potential naming conflicts with default pystow home directory name. HOT 8
- Confusing folder configuration HOT 1
- Joining to existing pystow path HOT 1
- Python 3.10 support
- Ensure zip file? HOT 3
- Bug in ensure_open_zip when using API HOT 2
- Variants of ensure functions focused on loading HOT 3
- syncing an upstream gzip file with an expanded local version HOT 4
- Autogenerate README in .data folder HOT 1
- [WINDOWS] TypeError when using `ensure_csv`: "argument of type 'WindowsPath' is not iterable" HOT 1
- loading comma-separated values format defaults to tab separators
- Ensure from figshare
- Best practices for clearing stale files HOT 2
- Need to create a config file before it can be written to using write_config HOT 6
- Get configuration from file corresponding to leading part
- Alignment with platform-specific directories HOT 1
- Feature: Add progress bar during download HOT 2
- Return types for some ensure functions
- Raise error if directory passed as name
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