Virtual Environments¶

This guide explains how Pipenv manages virtual environments, including customization options, best practices, and troubleshooting tips.

Understanding Virtual Environments¶

What is a Virtual Environment?¶

A virtual environment is an isolated Python environment that allows you to install packages for a specific project without affecting your system Python installation or other projects. This isolation helps prevent dependency conflicts and ensures reproducible environments.

How Pipenv Uses Virtual Environments¶

Pipenv automatically creates and manages virtual environments for your projects. When you run pipenv install for the first time in a project, Pipenv:

Creates a new virtual environment for your project
Installs the specified packages into that environment
Creates a Pipfile and Pipfile.lock to track dependencies

Virtual Environment Location¶

Default Location¶

By default, Pipenv stores virtual environments in a centralized location:

On Linux/macOS: ~/.local/share/virtualenvs/
On Windows: %USERPROFILE%\.virtualenvs\

The virtual environment name is derived from the project directory name plus a hash of the full path to ensure uniqueness. For example, a project in /home/user/projects/myproject might have a virtual environment named myproject-a1b2c3d4.

Finding Your Virtual Environment¶

To find the path to your project’s virtual environment:

$ pipenv --venv
/home/user/.local/share/virtualenvs/myproject-a1b2c3d4

To find the Python interpreter path:

$ pipenv --py
/home/user/.local/share/virtualenvs/myproject-a1b2c3d4/bin/python

Customizing Virtual Environment Location¶

Project-Local Virtual Environments¶

You can tell Pipenv to create the virtual environment in your project directory by setting the PIPENV_VENV_IN_PROJECT environment variable:

$ export PIPENV_VENV_IN_PROJECT=1
$ pipenv install

This creates a .venv directory in your project, making it easier to find and manage.

Benefits of project-local virtual environments:

Easier to locate and manage
Self-contained project directory
Better for version control (though you should still add .venv to your .gitignore)
Useful for containerized environments

Custom Virtual Environment Directory¶

You can specify a custom location for all virtual environments by setting the WORKON_HOME environment variable:

$ export WORKON_HOME=~/my-virtualenvs
$ pipenv install

This is useful if you want to store all virtual environments in a specific directory.

Custom Virtual Environment Name¶

You can specify a custom name for your virtual environment by setting the PIPENV_CUSTOM_VENV_NAME environment variable:

$ export PIPENV_CUSTOM_VENV_NAME=myproject-env
$ pipenv install

This overrides the default naming scheme and uses your specified name instead.

Managing Virtual Environments¶

Activating the Virtual Environment¶

To activate the virtual environment:

$ pipenv shell

This spawns a new shell with the virtual environment activated. You can exit this shell with exit or Ctrl+D.

Alternatively, you can run commands in the virtual environment without activating it:

$ pipenv run python script.py

Deactivating the Virtual Environment¶

If you’re in a shell created by pipenv shell, you can deactivate the virtual environment by exiting the shell:

$ exit

Removing the Virtual Environment¶

To remove the virtual environment:

$ pipenv --rm

This deletes the virtual environment but leaves your Pipfile and Pipfile.lock intact.

Virtual Environment Naming¶

Default Naming Scheme¶

The default virtual environment name follows this pattern:

{project_name}-{hash}

Where:

{project_name} is the name of your project directory
{hash} is a hash of the full path to your project

For example, a project in /home/user/projects/myproject might have a virtual environment named myproject-a1b2c3d4.

Character Handling¶

Dangerous characters (i.e., $!*@", as well as space, line feed, carriage return, and tab) in the project name are converted to underscores in the virtual environment name.

Moving or Renaming Projects¶

When you move or rename a project directory, Pipenv can no longer find the associated virtual environment because the path hash changes.

Recommended Workflow for Moving/Renaming¶

Remove the virtual environment before moving or renaming:
```
$ pipenv --rm
```
Move or rename your project directory.
Recreate the virtual environment in the new location:
```
$ cd /path/to/new/location
$ pipenv install
```

This ensures that Pipenv creates a new virtual environment with the correct path hash.

Using Different Python Versions¶

Specifying Python Version¶

You can specify which Python version to use when creating a virtual environment:

$ pipenv --python 3.10

This creates a virtual environment using Python 3.10.

Using pyenv with Pipenv¶

If you have pyenv installed, Pipenv can automatically use it to find and install the required Python version:

$ pipenv --python 3.10

If Python 3.10 isn’t installed, Pipenv will prompt you to install it with pyenv.

Using asdf with Pipenv¶

Similarly, if you have asdf installed with the Python plugin, Pipenv can use it to find and install the required Python version.

Advanced Configuration¶

Environment Variables¶

Several environment variables affect how Pipenv manages virtual environments:

Variable	Description	Default
`PIPENV_VENV_IN_PROJECT`	Create virtualenv in project directory	`0` (disabled)
`WORKON_HOME`	Custom directory for virtual environments	Platform-specific
`PIPENV_CUSTOM_VENV_NAME`	Custom name for the virtual environment	None
`PIPENV_PYTHON`	Path to Python executable to use	System default
`PIPENV_IGNORE_VIRTUALENVS`	Ignore active virtual environments	`0` (disabled)

Shell Configuration¶

For the best experience with pipenv shell, ensure your shell configuration only sets environment variables like PATH during login sessions, not during every subshell spawn.

For example, in fish:

if status --is-login
    set -gx PATH /usr/local/bin $PATH
end

In bash or zsh, you might use:

if [[ -z $PIPENV_ACTIVE ]]; then
    export PATH=/usr/local/bin:$PATH
fi

Troubleshooting¶

Virtual Environment Not Found¶

If Pipenv can’t find your virtual environment:

Check if the virtual environment exists:
```
$ pipenv --venv
```
If it doesn’t exist, create it:
```
$ pipenv install
```
If you’ve moved or renamed your project, follow the steps in the “Moving or Renaming Projects” section.

Shell Activation Issues¶

If pipenv shell doesn’t work correctly:

Try compatibility mode (the default):
```
$ pipenv shell
```
If that doesn’t work, try fancy mode:
```
$ pipenv shell --fancy
```
If neither works, use pipenv run instead:
```
$ pipenv run python
```

Python Version Issues¶

If Pipenv uses the wrong Python version:

Specify the Python version explicitly:
```
$ pipenv --python 3.10
```
Check your Pipfile for the required Python version:
```
[requires]
python_version = "3.10"
```
If using pyenv, ensure the required Python version is installed:
```
$ pyenv versions
$ pyenv install 3.10.4
```

Best Practices¶

Version Control¶

Add .venv/ to your .gitignore if using project-local virtual environments
Commit both Pipfile and Pipfile.lock to version control
Don’t commit the virtual environment itself

Project Organization¶

Consider using project-local virtual environments (PIPENV_VENV_IN_PROJECT=1) for better organization
Use a consistent approach across all your projects
Document your virtual environment setup in your project’s README

CI/CD Integration¶

In CI/CD pipelines:

# Example GitHub Actions workflow
steps:
  - uses: actions/checkout@v3
  - uses: actions/setup-python@v4
    with:
      python-version: '3.10'
  - name: Install pipenv
    run: pip install pipenv
  - name: Install dependencies
    run: pipenv install --deploy
  - name: Run tests
    run: pipenv run pytest

Docker Integration¶

When using Pipenv with Docker, consider using project-local virtual environments:

FROM python:3.10-slim

WORKDIR /app

COPY Pipfile Pipfile.lock ./

RUN pip install pipenv && \
    PIPENV_VENV_IN_PROJECT=1 pipenv install --deploy

COPY . .

CMD ["pipenv", "run", "python", "app.py"]

Conclusion¶

Pipenv’s virtual environment management simplifies Python project setup and dependency isolation. By understanding how Pipenv creates and manages virtual environments, you can ensure consistent, reproducible environments for your Python projects.