diff --git a/doc.zih.tu-dresden.de/docs/software/python_virtual_environments.md b/doc.zih.tu-dresden.de/docs/software/python_virtual_environments.md
index 7772f01834147d0ef51c4241add5fdbef041f22e..5ee0c4fd4d2a92bc67d260aa3e7e36f4109beab2 100644
--- a/doc.zih.tu-dresden.de/docs/software/python_virtual_environments.md
+++ b/doc.zih.tu-dresden.de/docs/software/python_virtual_environments.md
@@ -1,50 +1,12 @@
# Python Virtual Environments
-## TODO
-
-Link to this page from other DA/ML topics.
-
-## copied from alpha_centauri.md
-
-??? comment
- copied from `alpha_centauri.md`. Please remove there if this article is finished
-
Virtual environments allow users to install additional python packages and create an isolated
-run-time environment. We recommend using `virtualenv` for this purpose.
-
-```console
-marie@login$ srun --partition=alpha-interactive --nodes=1 --cpus-per-task=1 --gres=gpu:1 --time=01:00:00 --pty bash
-marie@alpha$ mkdir python-environments # please use workspaces
-marie@alpha$ module load modenv/hiera GCC/10.2.0 CUDA/11.1.1 OpenMPI/4.0.5 PyTorch
-Module GCC/10.2.0, CUDA/11.1.1, OpenMPI/4.0.5, PyTorch/1.9.0 and 54 dependencies loaded.
-marie@alpha$ which python
-/sw/installed/Python/3.8.6-GCCcore-10.2.0/bin/python
-marie@alpha$ pip list
-[...]
-marie@alpha$ virtualenv --system-site-packages python-environments/my-torch-env
-created virtual environment CPython3.8.6.final.0-64 in 42960ms
- creator CPython3Posix(dest=~/python-environments/my-torch-env, clear=False, global=True)
- seeder FromAppData(download=False, pip=bundle, setuptools=bundle, wheel=bundle, via=copy, app_data_dir=~/.local/share/virtualenv)
- added seed packages: pip==21.1.3, setuptools==57.2.0, wheel==0.36.2
- activators BashActivator,CShellActivator,FishActivator,PowerShellActivator,PythonActivator,XonshActivator
-marie@alpha$ source python-environments/my-torch-env/bin/activate
-(my-torch-env) marie@alpha$ pip install torchvision
-[...]
-Installing collected packages: torchvision
-Successfully installed torchvision-0.10.0
-[...]
-(my-torch-env) marie@alpha$ python -c "import torchvision; print(torchvision.__version__)"
-0.10.0+cu102
-(my-torch-env) marie@alpha$ deactivate
-```
+run-time environment. We recommend using `virtualenv` for this purpose. In your virtual environment,
+you can use packages from the (Complete List of Modules) or if you didn't find what you need you can
+install required packages with the command: `pip install`. With the command `pip freeze`, you can
+see a list of all installed packages and their versions.
-## copied from python.md
-
-??? comment
- clear up the following. Maybe leave only conda stuff...
-
-There are two methods of how to work with virtual environments on
-ZIH system:
+There are two methods of how to work with virtual environments on ZIH systems:
1. **virtualenv** is a standard Python tool to create isolated Python environments.
It is the preferred interface for
@@ -55,77 +17,99 @@ virtual environments on ZIH system. conda is an open-source package
management system and environment management system from Anaconda. The
conda manager is included in all versions of Anaconda and Miniconda.
-**Note:** Keep in mind that you **cannot** use virtualenv for working
-with the virtual environments previously created with conda tool and
-vice versa! Prefer virtualenv whenever possible.
+!!! warning
+ Keep in mind that you **cannot** use virtualenv for working
+ with the virtual environments previously created with conda tool and
+ vice versa! Prefer virtualenv whenever possible.
+
+## Python virtual environment
+
+This example shows how to start working with **virtualenv** and Python virtual environment (using
+the module system). At first we use an interactive job and create a directory for the virtual
+environment:
+
+```console
+marie@login$ srun -p alpha -N 1 -n 1 -c 7 --mem-per-cpu=5772 --gres=gpu:1 --time=04:00:00 --pty bash #Job submission in ml nodes with 1 gpu on 1 node.
+marie@alpha$ mkdir python-environments #Optional: Create folder. Please use Workspaces!
+```
+
+Now we check available Python modules and load the preferred version:
+
+```console
+marie@alpha$ ml av Python #Check the available modules with Python
+marie@alpha$ module load Python #Load default Python. Example output: Module Python/3.7 4-GCCcore-8.3.0 with 7 dependencies loaded
+marie@alpha$ which python #Check which python are you using
+```
+
+Then create the virtual environment and activate it:
+
+```console
+marie@alpha$ virtualenv --system-site-packages python-environments/envtest #Create virtual environment
+marie@alpha$ source python-environments/envtest/bin/activate #Activate virtual environment. Example output: (envtest) bash-4.2$
+```
-This example shows how to start working
-with **virtualenv** and Python virtual environment (using the module system)
+Now you can work in this isolated environment, without interferring with other tasks running on the
+system. Note that the inscription (env) at the beginning of each line represents that you are in
+the virtual environment. You can deactivate the environment as follows:
-```Bash
-srun -p ml -N 1 -n 1 -c 7 --mem-per-cpu=5772 --gres=gpu:1 --time=04:00:00 --pty bash #Job submission in ml nodes with 1 gpu on 1 node.
+```console
+(envtest) marie@alpha$ deactivate #Leave the virtual environment
+```
-mkdir python-environments # Optional: Create folder. Please use Workspaces!
+## Conda virtual environment
-module load modenv/ml # Changing the environment. Example output: The following have been reloaded with a version change: 1 modenv/scs5 => modenv/ml
-ml av Python #Check the available modules with Python
-module load Python #Load default Python. Example output: Module Python/3.7 4-GCCcore-8.3.0 with 7 dependencies loaded
-which python #Check which python are you using
-virtualenv --system-site-packages python-environments/envtest #Create virtual environment
-source python-environments/envtest/bin/activate #Activate virtual environment. Example output: (envtest) bash-4.2$
-python #Start python
+This example shows how to start working with **conda** and virtual environment (with using module
+system). At first we use an interactive job and create a directory for the conda virtual
+environment:
-from time import gmtime, strftime
-print(strftime("%Y-%m-%d %H:%M:%S", gmtime())) #Example output: 2019-11-18 13:54:16
-deactivate #Leave the virtual environment
+```console
+marie@login$ srun -p ml -N 1 -n 1 -c 7 --mem-per-cpu=5772 --gres=gpu:1 --time=04:00:00 --pty bash #Job submission in ml nodes with 1 gpu on 1 node.
+marie@alpha$ mkdir conda-virtual-environments #create a folder
```
-The [virtualenv](https://virtualenv.pypa.io/en/latest/) Python module (Python 3) provides support
-for creating virtual environments with their own site-directories, optionally isolated from system
-site directories. Each virtual environment has its own Python binary (which matches the version of
-the binary that was used to create this environment) and can have its own independent set of
-installed Python packages in its site directories. This allows you to manage separate package
-installations for different projects. It essentially allows us to create a virtual isolated Python
-installation and install packages into that virtual installation. When you switch projects, you can
-simply create a new virtual environment and not have to worry about breaking the packages installed
-in other environments.
-
-In your virtual environment, you can use packages from the (Complete List of
-Modules) or if you didn't find what you need you can install required packages
-with the command: `pip install`. With the command `pip freeze`, you can see a list of all installed
-packages and their versions.
-
-This example shows how to start working with **conda** and virtual
-environment (with using module system)
-
-```Bash
-srun -p ml -N 1 -n 1 -c 7 --mem-per-cpu=5772 --gres=gpu:1 --time=04:00:00 --pty bash # Job submission in ml nodes with 1 gpu on 1 node.
-
-module load modenv/ml
-mkdir conda-virtual-environments #create a folder
-cd conda-virtual-environments #go to folder
-which python #check which python are you using
-module load PythonAnaconda/3.6 #load Anaconda module
-which python #check which python are you using now
-
-conda create -n conda-testenv python=3.6 #create virtual environment with the name conda-testenv and Python version 3.6
-conda activate conda-testenv #activate conda-testenv virtual environment
-
-conda deactivate #Leave the virtual environment
+Then we load Anaconda, create an environment in our directory and activate the environment:
+
+```console
+marie@alpha$ module load Anaconda3 #load Anaconda module
+marie@alpha$ conda create --prefix conda-virtual-environments/conda-testenv python=3.6 #create virtual environment with Python version 3.6
+marie@alpha$ conda activate conda-virtual-environments/conda-testenv #activate conda-testenv virtual environment
```
-You can control where a conda environment
-lives by providing a path to a target directory when creating the
-environment. For example, the following command will create a new
-environment in a workspace located in `scratch`
+Now you can work in this isolated environment, without interferring with other tasks running on the
+system. Note that the inscription (env) at the beginning of each line represents that you are in
+the virtual environment. You can deactivate the conda environment as follows:
-```Bash
-conda create --prefix /scratch/ws/<name_of_your_workspace>/conda-virtual-environment/<name_of_your_environment>
+```console
+(conda-testenv) marie@alpha$ conda deactivate #Leave the virtual environment
```
-Please pay attention,
-using srun directly on the shell will lead to blocking and launch an
-interactive job. Apart from short test runs, it is **recommended to
-launch your jobs into the background by using Slurm**. For that, you can conveniently put
-the parameters directly into the job file which you can submit using
-`sbatch [options] <job file>.`
+TODO: Link to this page from other DA/ML topics. insert link in alpha centauri
+
+??? example
+ This is an example on alpha partition. The example creates a virtual environment, and installs
+ the package `torchvision` with pip.
+ ```console
+ marie@login$ srun --partition=alpha-interactive -N=1 --gres=gpu:1 --time=01:00:00 --pty bash
+ marie@alpha$ mkdir python-environments # please use workspaces
+ marie@alpha$ module load modenv/hiera GCC/10.2.0 CUDA/11.1.1 OpenMPI/4.0.5 PyTorch
+ Module GCC/10.2.0, CUDA/11.1.1, OpenMPI/4.0.5, PyTorch/1.9.0 and 54 dependencies loaded.
+ marie@alpha$ which python
+ /sw/installed/Python/3.8.6-GCCcore-10.2.0/bin/python
+ marie@alpha$ pip list
+ [...]
+ marie@alpha$ virtualenv --system-site-packages python-environments/my-torch-env
+ created virtual environment CPython3.8.6.final.0-64 in 42960ms
+ creator CPython3Posix(dest=~/python-environments/my-torch-env, clear=False, global=True)
+ seeder FromAppData(download=False, pip=bundle, setuptools=bundle, wheel=bundle, via=copy, app_data_dir=~/.local/share/virtualenv)
+ added seed packages: pip==21.1.3, setuptools==57.2.0, wheel==0.36.2
+ activators BashActivator,CShellActivator,FishActivator,PowerShellActivator,PythonActivator,XonshActivator
+ marie@alpha$ source python-environments/my-torch-env/bin/activate
+ (my-torch-env) marie@alpha$ pip install torchvision
+ [...]
+ Installing collected packages: torchvision
+ Successfully installed torchvision-0.10.0
+ [...]
+ (my-torch-env) marie@alpha$ python -c "import torchvision; print(torchvision.__version__)"
+ 0.10.0+cu102
+ (my-torch-env) marie@alpha$ deactivate
+ ```