conda vs. pip vs. virtualenv — Anaconda Enterprise 4.4 documentation

Anaconda Enterprise: Documentation

# conda vs. pip vs. virtualenv

If you are already familiar with pip or virtualenv, please see our chart comparing `Conda, pip, and virtualenv`.

If you’ve used pip and virtualenv in the past, you can use conda to perform all of the same operations. Pip is a package manager, and Virtualenv is an environment manager. Conda is both.

Task | Conda package and environment manager command | Pip package manager command | Virtualenv environment manager command
--- | --- | --- | ---
Install a package | `conda install $PACKAGE_NAME` | `pip install $PACKAGE_NAME` | X
Update a package | `conda update --name $ENVIRONMENT_NAME $PACKAGE_NAME` | `pip install --upgrade $PACKAGE_NAME` | X
Update package manager | `conda update conda` | Linux/OSX: `pip install -U pip` Win: `python -m pip install -U pip` | X
Uninstall a package | `conda remove --name $ENVIRONMENT_NAME $PACKAGE_NAME` | `pip uninstall $PACKAGE_NAME` | X
Create an environment | `conda create --name $ENVIRONMENT_NAME python` | X | `cd $ENV_BASE_DIR; virtualenv $ENVIRONMENT_NAME`
Activate an environment | `source activate $ENVIRONMENT_NAME` | X | `source $ENV_BASE_DIR/$ENVIRONMENT_NAME/bin/activate`
Deactivate an environment | `source deactivate` | X | `deactivate`
Search available packages | `conda search $SEARCH_TERM` | `pip search $SEARCH_TERM` | X
Install package from specific source | `conda install --channel $URL $PACKAGE_NAME` | `pip install --index-url $URL $PACKAGE_NAME` | X
List installed packages | `conda list --name $ENVIRONMENT_NAME` | `pip list` | X
Create requirements file | `conda list --export` | `pip freeze` | X
List all environments | `conda info --envs` | X | Install virtualenv wrapper, then `lsvirtualenv`
Install other package manager | `conda install pip` | `pip install conda` | X
Install Python | `conda install python=x.x` | X | X
Update Python | `conda update python` * | X | X

- `conda update python` updates to the most recent in the series, so any Python 2.x would update to the latest 2.x, and any Python 3.x to the latest 3.x.