Ask HN: Problems worth solving with a low-code back end?

• buckaroo

  9 152 9.1 Jupyter Notebook

  Buckaroo - the data wrangling assistant for pandas. Quickly explore dataframes, and run pandas commands via a GUI. Works inside the jupyter notebook.

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.

[1] https://github.com/paddymul/buckaroo

[2] http://norvig.com/lispy2.html

• yeoman

  27 10,052 0.0

  Yeoman - a set of tools for automating development workflow

  

Drag and Drop Visual Programming Language, the click of a button is interpreted as a source of an object stream. Think packet oriented programming, of reactive functional programming, or RxJs, or Node-RED.

To answer your question: you evaluate a low-code builder by the ease with which it can generate entire website applications. And by generate, I mean code generation as well, because you want these programs to emit beautiful code that is indistinguishable from hand made code. For code generation see yeoman, especially AST parsing and that nifty var function: https://yeoman.io/

And of course any one of the 5 above is a good test, but all 5 in harmony are better.

As to non-visual/tui tools, its bash. shells are low code tools take a look:

AT&T Archives: The UNIX Operating System:

• InfluxDB

  www.influxdata.com sponsored

  Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

  

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