Add language support for PSJ (Python Script in Jupiter) and JPL (Jupiter Macro) to Visual Studio Code.
Overview
PSJ (Python Script in Jupiter) is a set of Jupiter’s technologies enable user-customization for automation purpose.
When user executes an operation via Jupiter UI, a respective macro based on Python scripting language will be generated. User can use this macro for the same model, or implement advanced Python scripting for different models/specifications. In addition, a customized Python script language is also available for user to implement necessary UI to interact with end user when needed.
Benefits
CAD designer wants to do simple but repeated analysis using his/her design rule.
CAE engineer wants to automate work, shorten modelling time, reduce workload and improve productivity.
CAE expert with programming background wants to do advanced modelling, which required different software interaction, data read-in/written-out ability.
CAE company with standard workflow wants to make its in-housed CAD-CAE automation system, from concept design to analysis report, through a Worksheet template or customized wizard. The company can build and maintain this system based on its own resource.
Key features
User can operate Jupiter with Python and develop new functions using Jupiter.
The GUI Command Builder makes it easy to create a GUI without any knowledge of Python.
Besides, PSJ also has supporting tools such as “Customized IDE” and “Linkage between GUI and program”
Note
This extension uses TabNine's binaries as a machine learning based autocompleter to provide responsive, reliable, and relevant suggestions.
A note on licensing: this repo includes packaged Tabnine binaries. The MIT license only applies to the source code, not the packaged Tabnine binaries. The binaries are covered by the Tabnine End User License Agreement.
TabNine's local deep learning completion might be enabled by default. It is very CPU-intensive if your device can't handle it. You can check by typing "TabNine::config" in any buffer (your browser should then automatically open to TabNine's config page) and disable Deep TabNine Local (you will lose local deep learning completion).
