A one-click installer for Robot Framework, JupyterLab, Firefox, and Friends
Start the download now for your platform:
... or view the release notes.
You'll want at least 2GB available to install and run RobotLab
- On Windows, double-click the installer
- We recommend:
- don't add RobotLab to your
PATH - don't register RobotLab's python
- don't add RobotLab to your
- We recommend:
- On Linux/MacOSX
bash RobotLab-*.sh- follow the prompts
- don't install into your shell
Remember where you install RobotLab!
We recommend someplace
- short, e.g.
C:\robotlabor/home/myuser/robotlab - with no spaces in the path, e.g.
c:\Robot Lab - not shared on something like Dropbox, or a network drive
During installation, RobotLab will try to create a desktop icon:
Click it to launch the RobotLab server in a console window. It will also attempt to launch the bundled Firefox. The application log will keep running in the background, and sometimes useful information will appear there.
If you don't see an icon, launch a console, e.g. bash on Linux/MacOSX or
cmd.exe on Windows.
| | Linux/MacOSX | Windows
|--|-|
| start a prompt | open your terminal or console application | open cmd.exe from the start menu |
| activate the robotlab environment | type source /path/to/robolab/bin/activate
press ENTER | type c:\path\to\robotlab\Scripts\activate
press ENTER
| start robotlab | type robotlab
press ENTER | type robotlab
press ENTER
If you're still stuck, open an issue. There should be some template information to provide.
# assuming you've already `activate`d
robotlab [.] # basically just jupyterlab
robotlab-tutorial [.] # copy the robotkernel tutorial to this directory
robotlab-examples [.] # " " " examples " " "
robotlab-shortcuts- Delete the installation directory.
- Delete any desktop shortcuts.
- That is all.
While Robot Framework has no dependencies beyond the Python standard library, using it for non-trivial testing or process automation usually requires a fair number of additional Python dependencies, and even some more exotic ones. We wanted to run a workshop for RoboCon 2019 and show interactive editing/running with robotkernel.
The focus of this workshop, running Robot tests and tasks interactively, required the Jupyter stack. To demonstrate some of its more advanced features, some fairly extensive extra libraries from both the Robot Framework and the scientific Python ecosystems were needed, and getting these to install smoothly on every attendee's computers can prove to be... interesting.
To make a three-hour workshop reasonable, we needed a distribution approach that was:
- easy to start, to that we could get to the Good Stuff
- cross-platform, so that everyone could follow along
- self-contained, so that it could be easily removed
- offline-capable, so that we could handle intermittent network access
- hackable by the user, so that we could fix Surprise Features
At our 2019 workshop, graciously hosted by Siili, (whose network was super fast!) our room full of attendees, on three distributions of Linux, two versions of MacOSX and two versions of Windows were all up and running in under 30 minutes. We got through all of the tutorial before lunch!
RobotLab is built with:
- conda, an OS-agnostic package manager
- anaconda-project, a multi-environment manager and command executor
- conda-build, the conda package builder
- constructor, the installer-builder of conda packages
- azure pipelines, a continuous integration provider
Once it has matured, robotkernel will be available from conda-forge, the
community-driven upstream of the Anaconda Distribution, which is also built
with constructor.
So for the RobotLab installers, and supporting examples and tutorials, we need to build a number of dependencies.
JupyterLab's build chain has some negative externalities
for end users, namely an install- or run-time dependency on NodeJS and npmjs.org
when using any labextensions other than the built-in set (e.g. Notebook, Terminal,
Console, Editor, etc.). Because, for the purposes of the workshop, we want to
get to the Good Stuff of running Robot notebooks and not spend a bunch of time
debugging nodejs and webpack, we've added a few choice JupyterLab extensions:
jupyterlab_robotmode: syntax highlighting for Robot Frameworkjupyterlab-jupytext: ipynb/text pairing for your notebook@jupyterlab/toc: a table of contents pane for Markdown headers@jupyter-widgets/jupyterlab-manager: because widgets are always good
All of these are built outside of the conda-build cycle.
This asset, and all our dependencies, are wrapped into a conda package which
exposes some useful commands, which can do most of the things jupyter lab can do,
as well as create desktop shortcuts, and unpack the tutorial content.
robotlab works like jupyter lab, while robotlab-extension works like
jupyter labextension. This isn't a toy installation: with the bundled nodejs,
an intrepid user can still install any of the labextensions that are
compatible with the version robotlab was built with: as of writing, 1.1.x.
All of the dependencies are captured in construct.yaml.in. In addition to required dependencies, a number of extra libraries are included to showcase some of the features of using Robot Framework interactively.
JupyterLibraryfor testing Jupyter clients with robotframeworkSeleniumLibraryfor controlling browsersgeckodriverfor interacting with...firefox, the open source web browser
opencvfor image-driven testingRESTInstancefor testing REST APIs, including swagger
RobotLab includes Mozilla Firefox and geckodriver, with versions that will be
supported for years, not weeks, by a team that is committed to open source
and web standards.
It's pretty easy to get webdriver for Microsoft Edge, but...
- it but can't be redistributed
- it has to match the version of Edge/Explorer exactly
It's also pretty easy to get chromedriver for Google Chrome, but...
- it has to match the version of Chrome exactly
Contributions are welcome! See the [issues][] for outstanding work we've been discussing.
- Get Miniconda
- Install anaconda-project
- Clone this repo
From the command line e.g. bash or cmd.exe or the Anaconda Prompt, run:
anaconda-project run build:lab
anaconda-project run buildanaconda-project run testanaconda-project run lint
anaconda-project run integrity