Robocorp Lab (4.4.13)

Image-based workflow improvements and support for macOS & Ubuntu

• The image-based selector feature now also supports macOS and Linux.
• Added confidence slider, which can used to fine-tune the hits you get for your image.
  • Helps out for example in Windows where the contrast changes when the application is focused vs. unfocused.
• Multi-monitor snipping is still experimental. Feedback is welcome from all platforms.

Keyword explorer documentation formatting

• Keyword explorer now out of beta with improved documentation formatting.
• Improved documentation formatting also visible in the documentation site: see an example

Robot run supports Python robots and output improved

• Support for pure Python robots added.
• More visibility to the output feed coming from the robot run.

Fixes

• Cloud linking now works directly from Lab view: Upload to Robocorp Cloud directs to linking without having to exit your robot.
• Loading a shared robot from robocorp.com/robots while in Lab view notifies you to save and exit the current robot to import the new one.

Known issues

• Opening a robot with a conda.yaml that is not found in the cache takes a minute or two (Conda package loading). Closing the Lab view for the robot does not stop the cache set up, so the user needs to wait for it to complete.
• JupyterLab v2 forces extensions build to happen on target machines, which makes the Lab initialization error-prone. We are pushing JupyterLab v3 upgrade hard to get rid of the issues on startups.
• Miniconda, Chrome web drivers, and temp folder handling are causing file lock states on Windows machines.