This page describes how to install Workload Automation 2.


Operating System

WA runs on a native Linux install. It was tested with Ubuntu 12.04, but any recent Linux distribution should work. It should run on either 32-bit or 64-bit OS, provided the correct version of Android (see below) was installed. Officially, other environments are not supported. WA has been known to run on Linux Virtual machines and in Cygwin environments, though additional configuration may be required in both cases (known issues include makings sure USB/serial connections are passed to the VM, and wrong python/pip binaries being picked up in Cygwin). WA should work on other Unix-based systems such as BSD or Mac OS X, but it has not been tested in those environments. WA does not run on Windows (though it should be possible to get limited functionality with minimal porting effort).


If you plan to run Workload Automation on Linux devices only, SSH is required, and Android SDK is optional if you wish to run WA on Android devices at a later time. Then follow the steps to install the necessary python packages to set up WA.

However, you would be starting off with a limited number of workloads that will run on Linux devices.

Android SDK

You need to have the Android SDK with at least one platform installed. To install it, download the ADT Bundle from here. Extract it and add <path_to_android_sdk>/sdk/platform-tools and <path_to_android_sdk>/sdk/tools to your PATH. To test that you’ve installed it properly, run adb version. The output should be similar to this:

adb version
Android Debug Bridge version 1.0.31

Once that is working, run

android update sdk

This will open up a dialog box listing available android platforms and corresponding API levels, e.g. Android 4.3 (API 18). For WA, you will need at least API level 18 (i.e. Android 4.3), though installing the latest is usually the best bet.

Optionally (but recommended), you should also set ANDROID_HOME to point to the install location of the SDK (i.e. <path_to_android_sdk>/sdk).


You may need to install 32-bit compatibility libararies for the SDK to work properly. On Ubuntu you need to run:

sudo apt-get install lib32stdc++6 lib32z1


Workload Automation 2 requires Python 2.7 (Python 3 is not supported at the moment).


pip is the recommended package manager for Python. It is not part of standard Python distribution and would need to be installed separately. On Ubuntu and similar distributions, this may be done with APT:

sudo apt-get install python-pip


Some versions of pip (in particluar v1.5.4 which comes with Ubuntu 14.04) are know to set the wrong permissions when installing packages, resulting in WA failing to import them. To avoid this it is recommended that you update pip and setuptools before proceeding with installation:

sudo -H pip install --upgrade pip
sudo -H pip install --upgrade setuptools

If you do run into this issue after already installing some packages, you can resolve it by running

sudo chmod -R a+r /usr/local/lib/python2.7/dist-packagessudo
find /usr/local/lib/python2.7/dist-packages -type d -exec chmod a+x {} \;

(The paths above will work for Ubuntu; they may need to be adjusted for other distros).

Python Packages


pip should automatically download and install missing dependencies, so if you’re using pip, you can skip this section.

Workload Automation 2 depends on the following additional libraries:

  • pexpect
  • docutils
  • pySerial
  • pyYAML
  • python-dateutil

You can install these with pip:

sudo -H pip install pexpect
sudo -H pip install pyserial
sudo -H pip install pyyaml
sudo -H pip install docutils
sudo -H pip install python-dateutil

Some of these may also be available in your distro’s repositories, e.g.

sudo apt-get install python-serial

Distro package versions tend to be older, so pip installation is recommended. However, pip will always download and try to build the source, so in some situations distro binaries may provide an easier fall back. Please also note that distro package names may differ from pip packages.

Optional Python Packages


unlike the mandatory dependencies in the previous section, pip will not install these automatically, so you will have to explicitly install them if/when you need them.

In addition to the mandatory packages listed in the previous sections, some WA functionality (e.g. certain extensions) may have additional dependencies. Since they are not necessary to be able to use most of WA, they are not made mandatory to simplify initial WA installation. If you try to use an extension that has additional, unmet dependencies, WA will tell you before starting the run, and you can install it then. They are listed here for those that would rather install them upfront (e.g. if you’re planning to use WA to an environment that may not always have Internet access).

  • nose
  • pandas
  • PyDAQmx
  • pymongo
  • jinja2


Some packages have C extensions and will require Python development headers to install. You can get those by installing python-dev package in apt on Ubuntu (or the equivalent for your distribution).


Installing the latest released version from PyPI (Python Package Index):

sudo -H pip install wlauto

This will install WA along with its mandatory dependencies. If you would like to install all optional dependencies at the same time, do the following instead:

sudo -H pip install wlauto[all]

Alternatively, you can also install the latest development version from GitHub (you will need git installed for this to work):

git clone workload-automation
sudo -H pip install ./workload-automation

If the above succeeds, try

wa --version

Hopefully, this should output something along the lines of “Workload Automation version $version”.

(Optional) Post Installation

Some WA extensions have additional dependencies that need to be statisfied before they can be used. Not all of these can be provided with WA and so will need to be supplied by the user. They should be placed into ~/.workload_automation/dependencies/<extenion name> so that WA can find them (you may need to create the directory if it doesn’t already exist). You only need to provide the dependencies for workloads you want to use.

Binary Files

Some workloads require native binaries to work. Different binaries will be required for different ABIs. WA may not include the required binary for a workload due to licensing/distribution issues, or may not have a binary compiled for your device’s ABI. In such cases, you will have to supply the missing binaries.

Executable binaries for a workload should be placed inside ~/.workload_automation/dependencies/<extension name>/bin/<ABI> directory. This directory may not already exist, in which case you would have to create it.

Binaries placed in that location will take precidence over any already inclueded with WA. For example, if you have your own drystone binary compiled for arm64, and you want WA to pick it up, you can do the following on WA host machine

mkdir -p ~/.workload_automation/dependencies/dhrystone/bin/arm64/
cp /path/to/your/dhrystone ~/.workload_automation/dependencies/dhrystone/bin/arm64/

APK Files

APKs are applicaton packages used by Android. These are necessary to install an application onto devices that do not have Google Play (e.g. devboards running AOSP). The following is a list of workloads that will need one, including the version(s) for which UI automation has been tested. Automation may also work with other versions (especially if it’s only a minor or revision difference – major version differens are more likely to contain incompatible UI changes) but this has not been tested.

workload package name version code version name
andebench com.eembc.coremark AndEBench v1383a 1383
angrybirds com.rovio.angrybirds Angry Birds 2.1.1 2110
angrybirds_rio com.rovio.angrybirdsrio Angry Birds 1.3.2 1320
anomaly2 com.elevenbitstudios.anomaly2Benchmark A2 Benchmark 1.1 50
antutu com.antutu.ABenchMark AnTuTu Benchmark 5.3 5030000
antutu com.antutu.ABenchMark AnTuTu Benchmark 3.3.2 3322
antutu com.antutu.ABenchMark AnTuTu Benchmark 4.0.3 4000300
benchmarkpi gr.androiddev.BenchmarkPi BenchmarkPi 1.11 5
caffeinemark com.flexycore.caffeinemark CaffeineMark 1.2.4 9
castlebuilder com.ettinentertainment.castlebuilder Castle Builder 1.0 1
castlemaster com.alphacloud.castlemaster Castle Master 1.09 109
cfbench eu.chainfire.cfbench CF-Bench 1.2 7
citadel com.epicgames.EpicCitadel Epic Citadel 1.07 901107
dungeondefenders com.trendy.ddapp Dungeon Defenders 5.34 34
facebook com.facebook.katana Facebook 3.4 258880
geekbench ca.primatelabs.geekbench2 Geekbench 2 2.2.7 202007
geekbench com.primatelabs.geekbench3 Geekbench 3 3.0.0 135
glb_corporate net.kishonti.gfxbench GFXBench 3.0.0 1
glbenchmark com.glbenchmark.glbenchmark25 GLBenchmark 2.5 2.5 4
glbenchmark com.glbenchmark.glbenchmark27 GLBenchmark 2.7 2.7 1
gunbros2 com.glu.gunbros2 GunBros2 1.2.2 122
ironman Iron Man 3 1.3.1 1310
krazykart com.polarbit.sg2.krazyracers Krazy Kart Racing 1.2.7 127
linpack com.greenecomputing.linpackpro Linpack Pro for Android 1.2.9 31
nenamark se.nena.nenamark2 NenaMark2 2.4 5
peacekeeper Chrome 18.0.1025469 1025469
peacekeeper org.mozilla.firefox Firefox 23.0 2013073011
quadrant com.aurorasoftworks.quadrant.ui.professional Quadrant Professional 2.0 2000000
realracing3 Real Racing 3 1.3.5 1305
smartbench com.smartbench.twelve Smartbench 2012 1.0.0 5
sqlite com.redlicense.benchmark.sqlite RL Benchmark 1.3 5
templerun com.imangi.templerun Temple Run 1.0.8 11
thechase com.unity3d.TheChase The Chase 1.0 1
truckerparking3d com.tapinator.truck.parking.bus3d Truck Parking 3D 2.5 7
vellamo com.quicinc.vellamo Vellamo 3.0 3001
vellamo com.quicinc.vellamo Vellamo 2.0.3 2003
videostreaming FREEdi YT Player 2.1.13 79

Gaming Workloads

Some workloads (games, demos, etc) cannot be automated using Android’s UIAutomator framework because they render the entire UI inside a single OpenGL surface. For these, an interaction session needs to be recorded so that it can be played back by WA. These recordings are device-specific, so they would need to be done for each device you’re planning to use. The tool for doing is revent and it is packaged with WA. You can find instructions on how to use it here.

This is the list of workloads that rely on such recordings:


Maintaining Centralized Assets Repository

If there are multiple users within an organization that may need to deploy assets for WA extensions, that organization may wish to maintain a centralized repository of assets that individual WA installs will be able to automatically retrieve asset files from as they are needed. This repository can be any directory on a network filer that mirrors the structure of ~/.workload_automation/dependencies, i.e. has a subdirectories named after the extensions which assets they contain. Individual WA installs can then set remote_assets_path setting in their config to point to the local mount of that location.

(Optional) Uninstalling

If you have installed Workload Automation via pip and wish to remove it, run this command to uninstall it:

sudo -H pip uninstall wlauto


This will not remove any user configuration (e.g. the ~/.workload_automation directory)

(Optional) Upgrading

To upgrade Workload Automation to the latest version via pip, run:

sudo -H pip install --upgrade --no-deps wlauto