Anaconda/en: Difference between revisions
Jump to navigation
Jump to search
No edit summary |
(Created page with "For these reasons, we insist that users instead rely on tools like a virtual environment and the binary packages we provide through Python wheels as documented on the Pytho...") |
||
| Line 3: | Line 3: | ||
'''Attention:''' While Conda works well in a desktop environment, it tends to create more problems than it solves on a cluster. For example, Conda very often installs software (compilers, scientific libraries etc.) which is already available on the Compute Canada clusters in the form of modules but with a far from ideal configuration. With the installation of all of this additional software by Conda, you also risk exceeding the quota on the number of files in your home directory. | '''Attention:''' While Conda works well in a desktop environment, it tends to create more problems than it solves on a cluster. For example, Conda very often installs software (compilers, scientific libraries etc.) which is already available on the Compute Canada clusters in the form of modules but with a far from ideal configuration. With the installation of all of this additional software by Conda, you also risk exceeding the quota on the number of files in your home directory. | ||
For these reasons, we insist that users instead rely on tools like a virtual environment and the binary packages we provide through Python wheels as documented on the [[Python]] page or else turn to a container-based solution such as [[Singularity]] and a Docker image. | |||
Revision as of 16:37, 18 February 2020
Attention: While Conda works well in a desktop environment, it tends to create more problems than it solves on a cluster. For example, Conda very often installs software (compilers, scientific libraries etc.) which is already available on the Compute Canada clusters in the form of modules but with a far from ideal configuration. With the installation of all of this additional software by Conda, you also risk exceeding the quota on the number of files in your home directory.
For these reasons, we insist that users instead rely on tools like a virtual environment and the binary packages we provide through Python wheels as documented on the Python page or else turn to a container-based solution such as Singularity and a Docker image.