Python Virtual Environment
From UABgrid Documentation
Python virtual environment is a method of creating an isolated environment for Python projects. It enables each project to have its own dependencies, regardless of what dependencies every other project has. To read more about Python virtual environments, click here.
Creating a Python Virtual Environment
Load one of the Python modules available on Cheaha in your environment.
[snoopy@c1 ~]$ module avail Python -------------------------- /share/apps/rc/modules/all -------------------------- Python/2.7.10-goolf-1.7.20 Python/2.7.13-intel-2017a Python/2.7.10-intel-2015b Python/2.7.3-foss-2016a Python/2.7.11-foss-2016a Python/2.7.3-goolf-1.7.20 Python/2.7.11-foss-2016b Python/2.7.5-goolf-1.7.20 Python/2.7.11-goolf-1.7.20 Python/2.7.8-intel-2015b Python/2.7.11-intel-2015b Python/2.7.9-goolf-1.7.20 Python/2.7.11-intel-2016a Python/2.7.9-intel-2015b Python/2.7.12-foss-2016a Python/3.2.3-goolf-1.7.20 Python/2.7.12-foss-2016b Python/3.5.1-foss-2016a Python/2.7.12-intel-2015b Python/3.5.1-intel-2016a Python/2.7.12-intel-2016a Python/3.6.1-intel-2017a Python/2.7.13-GCCcore-6.3.0-bare Python/3.6.3-intel-2017a
Once you have loaded Python, we would use virtualenv to create and manage virtual environments.
[snoopy@c1 Python_Environments]$ module load Python/3.6.3-intel-2017a [snoopy@c1 Python_Environments]$ virtualenv test_environment Using base prefix '/share/apps/rc/software/Python/3.6.3-intel-2017a' New python executable in /data/user/snoopy/Python_Environments/test_environment/bin/python Installing setuptools, pip, wheel...done. [snoopy@c1 Python_Environments]$
Activating a Virtual Environment
Once a virtual environment has been created, you need to activate it to be in the virtual environment.
[snoopy@c1 Python_Environments]$ source test_environment/bin/activate (test_environment) [snoopy@c1 Python_Environments]$
Activating the virtual environment will change your shell’s prompt to show what virtual environment you’re using, test_environment in the above case, and modify the environment so that you can install Python packages for that particular environment.
Maintaining a Virtual Environment
After this you can install the packages that you would like for this environment, using pip. pip is a package management system used to install and manage software packages written in Python.
(test_environment) [snoopy@c1 Python_Environments]$ pip install numpy Collecting numpy Downloading numpy-1.14.0-cp36-cp36m-manylinux1_x86_64.whl (17.2MB) 100% |████████████████████████████████| 17.2MB 77kB/s Installing collected packages: numpy Successfully installed numpy-1.14.0 (test_environment) [snoopy@c1 Python_Environments]$ ls test_environment/lib/python3.6/site-packages/ easy_install.py pip-9.0.1.dist-info setuptools-38.4.0.dist-info numpy pkg_resources wheel numpy-1.14.0.dist-info __pycache__ wheel-0.30.0.dist-info pip setuptools (test_environment) [snoopy@c1 Python_Environments]$
You can use this method to install a Python application alongside all the dependencies that it requires.
Deactivating a Virtual Environment
After you are done using the virtual environment, you can use deactivate command to go back to your bash shell environemnt.
(test_environment) [snoopy@c1 Python_Environments]$ deactivate [snoopy@c1 Python_Environments]$
It would change your shell's prompt and remove the name of the virtual environment that you were in.
Sharing a virtual environment
You can use pip freeze to list all the packages in a virtual environment and copy it to a requirement.txt.file
pip freeze > requirements.txt
Now you can create new virtualenv and after activating that virtual environment, install all the packages using the following command.
pip install -r requirements.txt