We’ve been looking at how to get started using the new vSphere Automation SDKs. In the last couple parts of the series we looked at the SDK for REST, which included Postman REST client samples, as well as some JavaScript samples. This time, we’ll be looking at the vSphere Automation SDK for Python!


There are a handful of ways to install and setup Python on your workstation, I will be walking through a high level configuration for my Mac.

First things first, clone the vSphere Automation SDK for Python from the VMware GitHub repository located here. Cloning the Python SDK repo

After that’s complete, we’ll need to install the Python prerequisites. These include the GNU Complier Collection (GCC), a C compiler, and HomeBrew, a package management system.

GCC can be installed in multiple ways, but I’ve found it’s easiest to obtain it by installing the Xcode Command Line Tools. This can be done with the following command, then following the prompts:

xcode-select --install

XCode Installation

Next, we’ll need to install the package manager, Homebrew. It can be easily downloaded and installed with the following command:

/usr/bin/ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)"

Homebrew Installation

Finally, we’ll install Python in the recommended version of 3.6. It’s worth noting here that Mac OS X comes with a version of Python already installed. However, it is generally an older version (normally, Python 2.7) and is used for some system related tasks. Due to that, it is best not to modify that version or the defaults.

Utilizing our package manager, we’ll install Python 3.6 with the following command:

brew install python3

Python 3.6 Installation

It’s also recommended to isolate your development environments from each other so, we’ll setup a virtual environment and jump into it. We can do that with the following commands:

python3 -m venv SDKDemo source SDKDemo/bin/activate

Creating a virtual development environment

Lastly, we’ll install the SDK requirements. They’re listed within the root of the SDK folder in the file labeled: requirements.txt. After checking out which requirements are necessary, we’ll install those requirements by way of the following command:

pip3 install -r requirements.txt

Requirement Installation

One other item worth mentioning is an IDE. This will make editing, running and debugging the code a lot easier to deal with. I’ll be using PyCharm, which is available here.

Running Sample Setup Script

To really show off the capabilities of the SDK, there’s a sample script which takes an un-configured vSphere environment and performs all of those normal configuration steps. The environment requirements to run the script are as follows:

  • 1 vCenter Server
  • 2 ESXi Hosts
  • 1 NFS Datastore (minimum of 3GB free)

We’ll first need to open up the testbed.py file and populate lines 17 through 29 as follows: Modification of the Testbed File

We’re now ready to set the environment up with the sample script! However, before running the script we should take a look at what it’s doing. The script is available in the SDK directory at: /bin/run_sample.sh

The goal of the script is to do the following actions:

  • Create 2 Datacenters
  • Create a Cluster
  • Create Test Folders for VM Storage
  • Attach the Hosts
  • Create a Distributed Switch
  • Create a Distributed PortGroup
  • Attach the NFS Datastore (if Selected) to the hosts
  • Copy the Photon OS ISO image downloaded from VMware’s bintray server to the Datastore
  • Create directories to add sample ports

One note before running the script, the ISO image being downloaded is roughly 200MB and could take a while depending on your bandwidth. My tests ranged anywhere between 30 seconds and 5 minutes. The sample script can be run with the following command:

./run_sample.sh ../samples/vsphere/vcenter/setup/main.py –sv

Configuring an environment with the main.py file

Create a VM with Defaults

Now that our environment is setup, let’s take a look at adding a VM to this environment. The easiest way is to create a default VM. This action means the API takes care of all the configuration settings based on the Guest OS version. There are some prerequisites that are required for placement such as desired datacenter, VM folder, and datastore. These are all referenced from the testbed.py configuration file we referenced in the first example. Updating the Testbed File for VM Tasks

The VM can then be created with the following command:

./run_sample.sh ../samples/vsphere/vcenter/vm/create/create_default_vm.py –v

Default VM Creation Sample

Notice in the above example how even though we didn’t populate all of the settings, the VM received required items like a CPU, a disk, and so forth. To verify the VM does indeed exist, we can obtain a list of VMs with the following command:

./run_sample.sh ../samples/vsphere/vcenter/vm/list_vms.py –v

List VMs Sample

VM Power Actions

The next logical step after creating a VM is to power it on. There’s a sample within the vm folder named power.py, which shows off all of the power actions. This file references the ‘VM_NAME_DEFAULT’ input from the testbed.py file.

When running the command as is, the VM will be put through the following power states:

  • Obtain current power state
  • Power Off (NOTE: Only if the VM is currently powered on)
  • Power On
  • Suspend the VM
  • Resume the VM
  • Reset the VM

The command can be run with the following:

./run_sample.sh ../samples/vsphere/vcenter/vm/power.py –v

VM Power State Sample


This post shows you how to easily get started with the vSphere Automation SDK for Python. It takes you through the setup of an entire environment, as well as using the individual samples. You can then take whichever is most relevant to you and apply to your environment or, pull parts of this code out and use it to automate or integrate as needed. With our SDK now being open sourced, we are intent on making sure these samples are of a high quality. If you notice areas of improvement, or come up with some new samples, please feel free to raise issues or pull requests on our GitHub repository.