Going one step further. I would get in the habit of using environment.yml
files to setup your environments. This way you know exactly what you
specified to create the environment you are using for a particular project
and can easily recreate it when necessary.
An example from one of my projects, that uses multiple conda channels and
also has pip dependencies:
https://github.com/ulmo-dev/ulmo/blob/master/py3_conda_environment.yml
Now I can create my env either by typing:
conda env create --file py3_conda_environment.yml (this creates a conda env
called py3-ulmo)
or
conda env create -n myenvname --file py3_conda_environment.yml . (if I want
to override my default env name)
Rules of thumb.
- always try to use conda packages over pip
- if a conda package is not available but the module is pure python, then
pip works fine.
- if package is not pure python then pip installing it may not work reliably
- dharhas
Post by Paul HobsonYes.
For that I would create new environments.
conda create --name=numpy112 python=3.6 numpy=1.12
and
conda create --name=numpy111 python=3.6 numpy=1.11
I don't install anything with pip except as a second-to-last resort (last
resort is building from source code).
On Mon, Jan 22, 2018 at 7:43 AM, Jonathan Rodrigues <
Post by Jonathan RodriguesCool. But let's say that I want to install numpy 1.11.3 and 1.12.1
alongside. Am I able to do that and choose which version I want?
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