1. workflow tools like zapier or the BPM example. These focus on integration of external systems with minimal code.
2. A better interface than text to a complex model. Think CAD Software.
I built a lowcode UI for pandas called Buckaroo[1], along with a datatable, it works in the jupyter notebook. I wanted to make it quick to visualize and clean dataframes. I built the lowcode UI because I knew the transformations I wanted to apply to a dataframe, and I wanted a faster way to express it then typing code. Specifically I built the lowcode system to enable an expert user to express themselves more quickly, it's not built as training wheels for beginners.
Here is how I built the system:
1. I adapted Peter Norvig's lispy2.py [2] to read JSON, called it JLisp.
2. I built a simple react frontend that emits JSON commands in the format of JLisp.
3. It was very easy to define new lowcode commands, and have the frontend add them to the palette. Each command defines two methods "transform" which manipulates the dataframe, and "transform_to_py" which takes the same arguments but emits python code.
Adoption of my library in general, and the low code UI specifically has been very limited. I'm in the middle of plumbing the lowcode support back in after a refactor of other parts.
I would like to build a whole ecosystem around JLisp and Buckaroo. Specifically I have some "auto-cleaning" functionality that emits JLisp cleaning and normalization commands, these commands can then be editted in the UI (delete, edit parameters). It's easier to emit JLisp than raw python syntax, it's also much easier to make a UI to manipulate it.
Do you have a repo to look at? What usecase did you have in mind when you were building it?
If I were evaluating a low-code backend builder I'd be interested in the examples, and tests. Hopefully the tests would double as examples. For a Workflow type low-code-builder I'd be most interested in the cron functionality.