Creating and managing virtual environments¶
When it comes to the management of third-party packages, Python has some complications:
By default, every third-party package will be installed to same directory.
Python is unable to differentiate between different versions of the same package installed to that directory
This means:
If you’re working on a project and you make a backwards incompatible change, then other projects that depend on it may be broken until you go through and update them all with the necessary changes.
If you have two projects that depend on different version of the same package then it becomes impossible for both to function simultaneously.
In order to deal with these problems (and others) it’s recommended that you work within a Python virtual environment, which is an isolated environment with its own set of installed system and third-party packages. Because these are maintained separately from both the system installation of Python and other virtual environments we no longer have to worry about the issues mentioned above.
In this tutorial you will:
(pip only) Install a couple of packages that make using virtual environments easier
Create new virtual environments and learn how to delete them
Learn how to activate, deactivate and switch between environments
Learn how to manage packages in a virtual environment
By the end of the tutorial you should have a fully functioning virtual environment ready for installing pydicom.
If you’re using pip as your package manager then continue reading. If you’re using conda then start here
Using pip¶
Install packages¶
First up, we’re going to install a couple of packages that make managing virtual environments a lot easier: virtualenv and virtualenvwrapper:
$ pip install virtualenv virtualenvwrapper
Create new virtual environments¶
To create a new environment run:
$ mkvirtualenv test-env
This should produce output similar to the following:
Using base prefix '/usr/local'
New python executable in /home/user/env/test-env/bin/python3.5
Also creating executable in /home/user/env/test-env/bin/python
Installing setuptools, pip, wheel...done.
virtualenvwrapper.user_scripts creating /home/user/env/test-env/bin/predeactivate
virtualenvwrapper.user_scripts creating /home/user/env/test-env/bin/postdeactivate
virtualenvwrapper.user_scripts creating /home/user/env/test-env/bin/preactivate
virtualenvwrapper.user_scripts creating /home/user/env/test-env/bin/postactivate
virtualenvwrapper.user_scripts creating /home/user/env/test-env/bin/get_env_details
The output includes the location where the new environment will
be created, in this case at /home/user/env/test-env
. By default, new
environments will be created in the location specified by the WORKON_HOME
environmental variable.
After creation, the new environment will be activated and ready to use, as
shown by the (test-env)
before the prompt:
(test-env) $
By default, a new virtual environment will be creating using the version of
Python you get from running the system’s (not the virtual environment’s)
python
command:
$ python --version # system Python
Python 2.7.17
$ mkvirtualenv default-env # environment Python
(default-env) $ python --version
Python 2.7.17
You can use a different version of Python (as long as one’s installed)
by passing the -p path
option, where path
is the path to a Python
executable:
$ mkvirtualenv -p /usr/bin/python3.7 py37-env
(py37-env) $ python --version
Python 3.7.5
Deleting environments¶
Environments can be deleted from the WORKON_HOME
directory by using
rmvirtualenv [env name]
:
(py37-env) $ rmvirtualenv default-env
However environments must be deactivated first:
(py37-env) $ rmvirtualenv py37-env
Removing py37-env...
ERROR: You cannot remove the active environment ('py37-env').
Either switch to another environment, or run 'deactivate'.
Activating and deactivating¶
Environments can be deactivated with the deactivate
command, which will
return you to the system:
(py37-env) $ deactivate
$ python --version
Python 2.7.17
And activated with the workon
command:
$ workon test-env
(test-env) $
You can switch between environments without needing to deactivate them first:
(test-env) $ workon py37-env
(py37-env) $
Managing packages¶
Packages within the environment can be managed normally, just remember to activate the environment first:
(py37-env) $ pip install antigravity
(py37-env) $ pip uninstall antigravity
And given it’s one of the reasons we’re using virtual environments, it’s not surprising that different environments can have different versions of the same package installed:
(py37-env) $ mkvirtualenv old
(old) $ pip install pydicom==1.2
(old) $ python -c "import pydicom; print(pydicom.__version__)"
1.2.0
(old) $ mkvirtualenv current
(current) $ pip install pydicom
(current) $ python -c "import pydicom; print(pydicom.__version__)"
1.4.0
Final steps¶
Let’s clean up the environments we created. First we’ll take a look to see what environments are available, then we’ll delete them all:
(current) $ deactivate
$ lsvirtualenv -b
current
old
py37-env
test-env
$ rmvirtualenv current
$ rmvirtualenv old
$ rmvirtualenv py37-env
$ rmvirtualenv test-env
And finally, let’s create a fresh virtual environment ready for installing pydicom:
$ mkvirtualenv pydicom
(pydicom) $
If you want more information on using the virtualenvwrapper
package, take a
look at the command reference.
If you’re using Python 3.3 or higher you may also be interested in the Python venv module which also allows the creation virtual environments, but without the need for extra packages.
Using conda¶
Create a new virtual environment¶
To create a new virtual environment we use the conda create
command with
the -n [env name]
flag:
$ conda create -n test-env
When asked if you want to proceed, enter y
.
This creates a new environment test-env
in [path/to/conda]/envs/
with
the default version of Python used by the system. To use Python
version X.Y
, you can use the python=X.Y
option:
$ conda create -n py37-env python=3.7
Activating and deactivating environments¶
Environments must be activated before they can be used:
$ conda activate py37-env
(py37-env) $ python --version
Python 3.7.5
(py37-env) $ conda activate test-env
(test-env) $
Deactivating the environment will return you to the previous environment:
(test-env) $ conda deactivate
(py37-env) $
To return to the base conda environment it’s recommended you just use conda
activate
:
(py35-env) $ conda activate
$
You can switch between environments without needing to deactivate them first:
$ conda activate test-env
(test-env) $ conda activate py37-env
(py37-env) $
Deleting environments¶
Environments can be deleted with the conda remove
command:
$ conda remove -n test-env --all
However environments must be deactivate first:
(py37-env) $ conda remove -n py37-env --all
CondaEnvironmentError: cannot remove current environment. deactivate and run conda remove again
Managing installed packages¶
Packages within the environment can be managed normally, just remember to activate the environment first:
(py37-env) $ pip install antigravity
(py37-env) $ pip uninstall antigravity
(py37-env) $ conda install numpy
(py37-env) $ conda uninstall numpy
Different virtual environments can have different versions of the same package installed:
(py37-env) $ conda create -n old && conda activate old
(old) $ pip install pydicom==1.2
(old) $ python -c "import pydicom; print(pydicom.__version__)"
1.2.0
(old) $ conda create -n current && conda activate current
(current) $ pip install pydicom==1.4
(current) $ python -c "import pydicom; print(pydicom.__version__)"
1.4.0
Final steps¶
Let’s clean up the environments we created. First we’ll take a look to see what environments are available, then we’ll delete them all:
(current) $ conda activate
$ conda env list
# conda environments:
#
base * /home/user/conda
current /home/user/conda/envs/current
old /home/user/conda/envs/old
py37-env /home/user/conda/envs/py37-env
$ conda remove -n current --all
$ conda remove -n old --all
$ conda remove -n py37-env --all
And finally, let’s create a fresh virtual environment ready for installing pydicom:
$ conda create -n pydicom
$ conda activate pydicom
(pydicom) $
If you want more information on using virtual environments in conda, take a look at managing conda environments.