https://github.com/bast/apptainer-conda
Local Conda environments via Apptainer.
Science Score: 13.0%
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Low similarity (11.6%) to scientific vocabulary
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Repository
Local Conda environments via Apptainer.
Statistics
- Stars: 10
- Watchers: 3
- Forks: 0
- Open Issues: 0
- Releases: 2
Topics
Metadata Files
README.md
Local Conda environments via Apptainer
The nice thing about this approach is that you don't need to install Conda and you don't need to modify your environment/bashrc/settings.
I use it to install dependencies that may be tough to install on a supercomputer or on my NixOS environment.
How to fetch the image:
$ apptainer pull https://github.com/bast/apptainer-conda/releases/download/0.8.0/conda.sif
Usage
- Reads the Conda environment file environment.yml.
- Creates the folder
environment.
Run myscript.py inside the Conda environment defined by environment.yml:
$ ./conda.sif python myscript.py
Open Python shell inside the Conda environment defined by environment.yml:
$ ./conda.sif python
First time you run either of the above commands it will take a bit of time
since it needs to install the dependencies into the environment folder.
However, subsequent runs will start basically immediately since the environment
is then there.
Micromamba and environment files
Under the hood, it uses Micromamba instead of Conda in order to speed up installations but it should not really matter for the functionality.
The one place where I found it to matter is that you have to specify channels
in the environment file.
Instead of this (example taken from conda
documentation):
yaml
name: stats
dependencies:
- numpy
- pandas
You need to do this:
yaml
name: stats
channels:
- defaults
dependencies:
- numpy
- pandas
But I believe that specifying channels explicitly is anyway good practice.
Running on a supercomputer/cluster
On a cluster you might need to bind folders like here:
$ env APPTAINER_BIND="/cluster" ./conda.sif python
To build the image, I have used this wonderful guide as starting point and inspiration.
Owner
- Name: Radovan Bast
- Login: bast
- Kind: user
- Location: Tromsø, Norway
- Company: @uit-no @neicnordic
- Website: https://bast.fr
- Repositories: 181
- Profile: https://github.com/bast
Theoretical chemist turned research software engineer. Leads @coderefinery.
GitHub Events
Total
- Release event: 1
- Delete event: 2
- Push event: 3
- Pull request event: 3
- Fork event: 1
- Create event: 3
Last Year
- Release event: 1
- Delete event: 2
- Push event: 3
- Pull request event: 3
- Fork event: 1
- Create event: 3
Issues and Pull Requests
Last synced: 11 months ago
All Time
- Total issues: 4
- Total pull requests: 7
- Average time to close issues: 10 days
- Average time to close pull requests: 4 minutes
- Total issue authors: 3
- Total pull request authors: 1
- Average comments per issue: 2.75
- Average comments per pull request: 0.0
- Merged pull requests: 7
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 0
- Pull requests: 1
- Average time to close issues: N/A
- Average time to close pull requests: 1 minute
- Issue authors: 0
- Pull request authors: 1
- Average comments per issue: 0
- Average comments per pull request: 0.0
- Merged pull requests: 1
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- bast (2)
- knutfrode (1)
- gauteh (1)
Pull Request Authors
- bast (9)