Creating new Conda Environment and importing into Jupyter on MacOSX
Creating new Conda Environment
So to start with let me put the documentation page, which is pretty straight forward and you may refer there for further information
So it is a good practice to start with a fresh environment for your fresh project. You can install only the dependencies you need and later export them if you need to share your project in the future or replicate on another machine. And frankly it is pretty easy to do that. Lets assume that you have conda installed on your machine. Then what we need to do is create the environment. You can specify python version like
python=3.4. After creating we can activate the environment and install manually whatever we need.
conda create -n <new_env_name> python source activate <new_env_name> conda install pytorch torchvision -c soumith source deactivate
You can later save the environment and create a new environment using the specs. Or(last line below) you can install the specs into an existing environment.
conda list --explicit > spec-file.txt conda create --name <new_env_name> --file spec-file.txt conda install --name <env_name> --file spec-file.txt
You can also export the environment.yaml
source activate <new_env_name> conda env export > environment.yml source deactivate
If you are working with jupyter notebooks, the easiest way to export your environment into jupyter is installing nb_conda within your environment. It would pull many dependencies, but that’s it. Now, you should see your
source activate <new_env_name> conda install nb_conda source deactivate
To remove an environment.
conda remove --name <new_env_name> --all