Jupyter kernel for the textS and textM languages

Installation

After installing the vre-language package according to the installation guide, run this command to install the kernel:

python -m virtmat.language.kernel.install

To check if the installation has been successful run the command

jupyter kernelspec list

to see all installed Jupyter kernels. The new kernel should appear there under the name texts. Then, after opening a Jupyter Notebook, a new kernel with the name textS/textM should appear in the drop-down menu on the top right. In Jupyter Lab, the kernel appears in the Launcher tab.

Short overview of the implementation

The current implementation is based on the jupyter_client documentation and includes the VMKernel class which is derived from the Kernel class in module ipykernel.kernelbase. It further supports auto-completion (by pressing the tab key) of variable and function names that it knows from previous cells that have already been run. The keywords print and use are always auto-completed, even in the very first cell.

The Kernel class of ipykernel.kernelbase already has an attribute called session. This should not be confused with the Session class in vre-language package. The attribute vmlang_session in the kernel is an object of this Session class.

The VMKernel class has two principal methods, do_execute and do_complete. The do_execute method is the heart of the kernel and handles the messaging protocols. It takes the input (“code”) and creates a textX model from it. Then, the model value (“output”) is passed as value belonging to the key “text” in the dictionary “stream_content” and sent to the “iopub_socket” to show up as printed output in the notebook.

The do_complete method only concerns the auto-completion functionality of the kernel. The kernel is fully functional also without the do_complete method. The method accesses the list self.memory which is initialized to contain “print” and “use”. While cells are executed, the namespace grows, and the names (functions, variables, and imports) are added to self.memory. Messaging again works with dictionaries of very definite structure and naming.