CLI interface#
virtualenv is primarily a command line application. It modifies the environment variables in a shell to create an isolated Python environment, so you’ll need to have a shell to run it. You can type in virtualenv (name of the application) followed by flags that control its behaviour. All options have sensible defaults, and there’s one required argument: the name/path of the virtual environment to create. The default values for the command line options can be overridden via the Configuration file or Environment Variables . Environment variables takes priority over the configuration file values ( —help will show if a default comes from the environment variable as the help message will end in this case with environment variables or the configuration file). The options that can be passed to virtualenv, along with their default values and a short description are listed below. virtualenv [OPTIONS]
| Named Arguments | ||
| —version | display the version of the virtualenv package and its location, then exit | |
| —with-traceback | False | on failure also display the stacktrace internals of virtualenv |
| —read-only-app-data | False | use app data folder in read-only mode (write operations will fail with error) |
| —app-data | platform specific application data folder | a data folder used as cache by the virtualenv |
| —reset-app-data | False | start with empty app data folder |
| —upgrade-embed-wheels | False | trigger a manual update of the embedded wheels |
| verbosity ⇒ verbosity = verbose — quiet, default INFO, mapping => CRITICAL=0, ERROR=1, WARNING=2, INFO=3, DEBUG=4, NOTSET=5 | ||
| -v , —verbose | 2 | increase verbosity |
| -q , —quiet | 0 | decrease verbosity |
discovery#
| core ⇒ options shared across all discovery | ||
| —discovery | builtin | interpreter discovery method; choice of: builtin |
| -p , —python | the python executable virtualenv is installed into | interpreter based on what to create environment (path/identifier) — by default use the interpreter where the tool is installed — first found wins |
| —try-first-with | [] | try first these interpreters before starting the discovery |
creator#
| core ⇒ options shared across all creator | ||
| —creator | builtin if exist, else venv | create environment via; choice of: cpython3-mac-framework , cpython3-posix , cpython3-win , pypy3-posix , pypy3-win , venv |
| dest | directory to create virtualenv at | |
| —clear | False | remove the destination directory if exist before starting (will overwrite files otherwise) |
| —no-vcs-ignore | False | don’t create VCS ignore directive in the destination directory |
| —system-site-packages | False | give the virtual environment access to the system site-packages dir |
| —symlinks | True | try to use symlinks rather than copies, when symlinks are not the default for the platform |
| —copies , —always-copy | False | try to use copies rather than symlinks, even when symlinks are the default for the platform |
seeder#
| core ⇒ options shared across all seeder | ||
| —seeder | app-data | seed packages install method; choice of: app-data , pip |
| —no-seed , —without-pip | False | do not install seed packages |
| —no-download , —never-download | True | pass to disable download of the latest pip/setuptools/wheel from PyPI |
| —download | False | pass to enable download of the latest pip/setuptools/wheel from PyPI |
| —extra-search-dir | [] | a path containing wheels to extend the internal wheel list (can be set 1+ times) |
| —pip | bundle | version of pip to install as seed: embed, bundle, none or exact version |
| —setuptools | bundle | version of setuptools to install as seed: embed, bundle, none or exact version |
| —wheel | bundle | version of wheel to install as seed: embed, bundle, none or exact version |
| —no-pip | False | do not install pip |
| —no-setuptools | False | do not install setuptools |
| —no-wheel | False | do not install wheel |
| —no-periodic-update | False | disable the periodic (once every 14 days) update of the embedded wheels |
| app-data ⇒ options specific to seeder app-data | ||
| —symlink-app-data | False | symlink the python packages from the app-data folder (requires seed pip>=19.3) |
activators#
| core ⇒ options shared across all activators | ||
| —activators | comma separated list of activators supported | activators to generate — default is all supported; choice of: bash , batch , cshell , fish , nushell , powershell , python |
| —prompt | provides an alternative prompt prefix for this environment (value of . means name of the current working directory) | |
Defaults#
Configuration file#
Unless VIRTUALENV_CONFIG_FILE is set, virtualenv looks for a standard virtualenv.ini configuration file. The exact location depends on the operating system you’re using, as determined by platformdirs application configuration definition. It can be overridden by setting the VIRTUALENV_CONFIG_FILE environment variable. The configuration file location is printed as at the end of the output when —help is passed. The keys of the settings are derived from the command line option (left strip the — characters, and replace — with _ ). Where multiple flags are available first found wins (where order is as it shows up under the —help ). For example, —python would be specified as:
[virtualenv] python = /opt/python-3.8/bin/python
[virtualenv] extra_search_dir = /path/to/dists /path/to/other/dists
Environment Variables#
Default values may be also specified via environment variables. The keys of the settings are derived from the command line option (left strip the — characters, and replace — with _ , finally capitalize the name). Where multiple flags are available first found wins (where order is as it shows up under the —help ). For example, to use a custom Python binary, instead of the one virtualenv is run with, you can set the environment variable VIRTUALENV_PYTHON like:
env VIRTUALENV_PYTHON=/opt/python-3.8/bin/python virtualenv Where the option accepts multiple values, for example for python or extra-search-dir , the values can be separated either by literal newlines or commas. Newlines and commas can not be mixed and if both are present only the newline is used for separating values. Examples for multiple values:
env VIRTUALENV_PYTHON=/opt/python-3.8/bin/python,python3.8 virtualenv env VIRTUALENV_EXTRA_SEARCH_DIR=/path/to/dists\n/path/to/other/dists virtualenv
virtualenv --python=/opt/python-3.8/bin/python --python=python3.8 virtualenv --extra-search-dir=/path/to/dists --extra-search-dir=/path/to/other/dists
12. Virtual Environments and Packages¶
Python applications will often use packages and modules that don’t come as part of the standard library. Applications will sometimes need a specific version of a library, because the application may require that a particular bug has been fixed or the application may be written using an obsolete version of the library’s interface.
This means it may not be possible for one Python installation to meet the requirements of every application. If application A needs version 1.0 of a particular module but application B needs version 2.0, then the requirements are in conflict and installing either version 1.0 or 2.0 will leave one application unable to run.
The solution for this problem is to create a virtual environment , a self-contained directory tree that contains a Python installation for a particular version of Python, plus a number of additional packages.
Different applications can then use different virtual environments. To resolve the earlier example of conflicting requirements, application A can have its own virtual environment with version 1.0 installed while application B has another virtual environment with version 2.0. If application B requires a library be upgraded to version 3.0, this will not affect application A’s environment.
12.2. Creating Virtual Environments¶
The module used to create and manage virtual environments is called venv . venv will usually install the most recent version of Python that you have available. If you have multiple versions of Python on your system, you can select a specific Python version by running python3 or whichever version you want.
To create a virtual environment, decide upon a directory where you want to place it, and run the venv module as a script with the directory path:
python -m venv tutorial-env
This will create the tutorial-env directory if it doesn’t exist, and also create directories inside it containing a copy of the Python interpreter and various supporting files.
A common directory location for a virtual environment is .venv . This name keeps the directory typically hidden in your shell and thus out of the way while giving it a name that explains why the directory exists. It also prevents clashing with .env environment variable definition files that some tooling supports.
Once you’ve created a virtual environment, you may activate it.
tutorial-env\Scripts\activate.bat
source tutorial-env/bin/activate
(This script is written for the bash shell. If you use the csh or fish shells, there are alternate activate.csh and activate.fish scripts you should use instead.)
Activating the virtual environment will change your shell’s prompt to show what virtual environment you’re using, and modify the environment so that running python will get you that particular version and installation of Python. For example:
$ source ~/envs/tutorial-env/bin/activate (tutorial-env) $ python Python 3.5.1 (default, May 6 2016, 10:59:36) . >>> import sys >>> sys.path ['', '/usr/local/lib/python35.zip', . '~/envs/tutorial-env/lib/python3.5/site-packages'] >>>
To deactivate a virtual environment, type:
12.3. Managing Packages with pip¶
You can install, upgrade, and remove packages using a program called pip. By default pip will install packages from the Python Package Index. You can browse the Python Package Index by going to it in your web browser.
pip has a number of subcommands: “install”, “uninstall”, “freeze”, etc. (Consult the Installing Python Modules guide for complete documentation for pip .)
You can install the latest version of a package by specifying a package’s name:
(tutorial-env) $ python -m pip install novas Collecting novas Downloading novas-3.1.1.3.tar.gz (136kB) Installing collected packages: novas Running setup.py install for novas Successfully installed novas-3.1.1.3
You can also install a specific version of a package by giving the package name followed by == and the version number:
(tutorial-env) $ python -m pip install requests==2.6.0 Collecting requests==2.6.0 Using cached requests-2.6.0-py2.py3-none-any.whl Installing collected packages: requests Successfully installed requests-2.6.0
If you re-run this command, pip will notice that the requested version is already installed and do nothing. You can supply a different version number to get that version, or you can run python -m pip install —upgrade to upgrade the package to the latest version:
(tutorial-env) $ python -m pip install --upgrade requests Collecting requests Installing collected packages: requests Found existing installation: requests 2.6.0 Uninstalling requests-2.6.0: Successfully uninstalled requests-2.6.0 Successfully installed requests-2.7.0
python -m pip uninstall followed by one or more package names will remove the packages from the virtual environment.
python -m pip show will display information about a particular package:
(tutorial-env) $ python -m pip show requests --- Metadata-Version: 2.0 Name: requests Version: 2.7.0 Summary: Python HTTP for Humans. Home-page: http://python-requests.org Author: Kenneth Reitz Author-email: me@kennethreitz.com License: Apache 2.0 Location: /Users/akuchling/envs/tutorial-env/lib/python3.4/site-packages Requires:
python -m pip list will display all of the packages installed in the virtual environment:
(tutorial-env) $ python -m pip list novas (3.1.1.3) numpy (1.9.2) pip (7.0.3) requests (2.7.0) setuptools (16.0)
python -m pip freeze will produce a similar list of the installed packages, but the output uses the format that python -m pip install expects. A common convention is to put this list in a requirements.txt file:
(tutorial-env) $ python -m pip freeze > requirements.txt (tutorial-env) $ cat requirements.txt novas==3.1.1.3 numpy==1.9.2 requests==2.7.0
The requirements.txt can then be committed to version control and shipped as part of an application. Users can then install all the necessary packages with install -r :
(tutorial-env) $ python -m pip install -r requirements.txt Collecting novas==3.1.1.3 (from -r requirements.txt (line 1)) . Collecting numpy==1.9.2 (from -r requirements.txt (line 2)) . Collecting requests==2.7.0 (from -r requirements.txt (line 3)) . Installing collected packages: novas, numpy, requests Running setup.py install for novas Successfully installed novas-3.1.1.3 numpy-1.9.2 requests-2.7.0
pip has many more options. Consult the Installing Python Modules guide for complete documentation for pip . When you’ve written a package and want to make it available on the Python Package Index, consult the Distributing Python Modules guide.