Command Environments

A useful list of conda commands
Author

Danilo Toapanta

Published

August 22, 2023

Environments

conda deactivate                  # to desactivate an environment
conda activate <progLab>          # to activate base environment
conda list                        # to see all packages in env
conda env list                    # to see all env
conda create -n <web> python=3.7  # install an environment
conda create -n <example_env>     # to create an env
conda env remove -n <ENV_NAME>    # remove env
conda create --name new_env --clone old_env    # Change name. Clone the old environment to a new environment with the name we want
conda remove --name old_env --all              # Delete the old environment

To make sure that the progLab environment is activated every time (auto) that we start a terminal, we can run the following command (replace bash with zsh if needed):

the following command (replace bash with zsh if needed):

echo 'conda activate progLab' >> ~/.zshrc

Conda

A conda environment is a directory that contains a specific collection of conda packages that you have installed. For example, you may have one environment with NumPy 1.7 and its dependencies, and another environment with NumPy 1.6 for legacy testing.

Anaconda

It gives you all the standard packages used in scientific computing in a convenient package without having to worry about installing them all individually with their dependencies.

In short Conda + Anaconda

Conda is a package manager. It helps you take care of your different packages by handling installing, updating and removing them. Anaconda contains all of the most common packages (tools) a data scientist needs and can be considered the hardware store of data science tools.

conda install anaconda

How to create an environment

Create your new environment, here called “mypython3” but you can call it what you wish:

conda create -n <mypython3> python=3

To activate the environment:

source activate mypython3

To get all the goodies (e.g. Jupyter Notebook, NumPy, matplotlib) you can install Anaconda, which will auto-magically use Python 3.

conda install anaconda

and then our additional install, netcdf4-python

conda install netcdf4

Now you have set-up your Python 3 environment. To start it in a new terminal

source activate mypython3

When you are using that environment your prompt will change and will include (mypython3). To return to using your “base” environment you can de-activate the conda environment with:

source deactivate

How to erase an environment

conda remove --name ml1labs --all

echo $PATH

$PATH (or the search path) is the list of directories that will be searched for anything that you type on the command line

We use sometimes ls or pwd or echo this is because there is a $PATH where this was. This list of pre-designated directories is stored in a special variable called “PATH”

This is a colon-delimited list of all the directories the command line looks in by default for programs on the particular computer.

Example

$ (progLab) datoapanta@Danilos-MacBook-Pro ~ % echo $PATH

/Users/datoapanta/opt/anaconda3/envs/progLab/bin:/Users/datoapanta/opt/anaconda3/condabin:/usr/local/bin:/usr/bin:/bin:/usr/sbin:/sbin:/Library/TeX/texbin:/usr/local/share/dotnet:~/.dotnet/tools:/Library/Frameworks/Mono.framework/Versions/Current/Commands:/Users/datoapanta/.local/bin:/Users/datoapanta/.local/bin

echo $PATH | tr ":" "\n"

/Users/datoapanta/opt/anaconda3/envs/progLab/bin /Users/datoapanta/opt/anaconda3/condabin /usr/local/bin /usr/bin /bin /usr/sbin /sbin /Library/TeX/texbin /usr/local/share/dotnet ~/.dotnet/tools /Library/Frameworks/Mono.framework/Versions/Current/Commands /Users/datoapanta/.local/bin /Users/datoapanta/.local/bin

We can now more clearly see this is a list of directories. All of these places, stored in the variable called “PATH”, are searched whenever we are typing a command in the terminal window.

If the command we are trying to use is present in any of the directories listed in our PATH, we don’t need to point at its specific location in full (its path, lowercase) when we are trying to use it – which is of course nice for things we use often.