managing_python_conda_envs.md

Anaconda / Python Environment Management

##Creating and Managing Anaconda Environments

conda create --name <name> python=<version> # Makes a new conda env 
conda activate my_env # Activates the env, IE uses it, also used to switch envs 
conda deactivate # Deactivates the current env
conda env list # Lists all conda environments 
conda remove --name my_env --all # Deletes an environment
conda info --envs # check the current env and path

Installing Packages

• conda install installs from Anaconda repositories, ensuring package compatibility.
• pip install fetches packages from PyPI, which may have dependency issues with Conda environments.

conda install <name, ie numpy> <name2> # Installs to active conda env
pip install numpy matplotlib scipy # Installs with pip, the conda method is preffered 

Importing and Exporting Conda env from/to a file

conda env export > environment.yml # The > writes the file 
conda env create -f environment.yml # Creates the environment from a file, use --name to name the env

Magic jupyter notebook commands

Run in an empty jupyter-cell, jupyter knows your current active python or conda env and will install a package to that env.

!pip install package_name  # For pip
!conda install package_name -y  # For conda
!which python # Path to check the currently active Python interpreter inside a Jupyter Notebook