buckaroo VS yeoman

I created buckaroo [1] as a better dataframe viewer for jupyter with built in summary stats. It's built to bring a better dataframe experience to people already using pandas/polars. All of it is extensible [2] so that you can customize stats and transformations to your workflow.

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

Great tables has done some really nice work on python/jupyter tables. It looks like they are almost building a "grammar of tables" similar to a grammar of graphics. More projects should write about their philosophy and aims like this.

I have built a different table library for jupyter called buckaroo. My approach has been different. Buckaroo aims to allow you to interactively cycle through different formats and post-processing functions to quickly glean important insights from a table while working interactively. I took the view that I type the same commands over and over to perform rudimentary exploratory data analysis, those commands and insights should be built into a table.

Great tables seems built so that you can manually format a table for presentation.

https://github.com/paddymul/buckaroo

https://youtu.be/GPl6_9n31NE

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

I used Norvig’s lisp2.py to build a low code UI. I modified the interpreter to accept JSON flavored lisp, basically replace parens with brackets. The upside is that it was very very easy to make a react front end that manipulates JSON (JLisp). My thinking was, I need a serialization format for operations from the front end, and a way to interpret them. I could write my own language that no one has heard of, or use lisp, which few have used.

https://github.com/paddymul/buckaroo/blob/main/buckaroo/jlis...

Location: Boston

Remote: Yes

Willing to relocate: Yes

Technologies: talking to users, python, pandas/numpy, jupyter, js/ts

Résumé/CV: https://www.linkedin.com/in/paddymullen/

Email: [email protected]

In my next role, I want a broad mandate to make a meaningful impact within an organization by developing products that address genuine business challenges, with a preference for data related problems.

Recently I built the data table for Jupyter/Pandas that I have wanted for over a decade. The open source Buckaroo (https://github.com/paddymul/buckaroo) data table combines a performant table, summary statistics, and a low code UI to expedite common data analysis tasks.

wanted for over a decade. The open source Buckaroo https://github.com/paddymul/buckaroo data table combines a performant table, summary statistics, and a low code UI to

This morning I added a "Related Projects" [3] Section to the Buckaroo docs. If Buckaroo doesn't solve your problem, look at one of the other linked projects (like Mito).

[1] https://github.com/approximatelabs/sketch

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

[3] https://buckaroo-data.readthedocs.io/en/latest/FAQ.html

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:

Plop js actually allows us to create the structures that we have previously created templates on cli via command. It does this in a very simple way. I can give hygen and yeoman as an alternative to plop js. I plan to write content about these libraries in the future.

You use them to install Yeoman and the VS Code Extension Generator. This generator creates a frame (scaffold) for your extension so you don't have to write everything from scratch. If you elect to build your project using TypeScript (recommended for this blog), it's recommended that you install the TypeScript + Webpack Problem Matcher to make it easier to find and match coding errors.

Nice, reminds me of https://yeoman.io/ which was popular couple years ago

Before we can start building the extension, we need to gather and prepare the necessary tools. In this case, the needed tools are node, git, yeoman and generator-code. For a newcomer like myself, this basic tutorial is perfect. I recommend going through it to learn the fundamentals.

If you wanted something much more advanced for some actual syntax highlighting and not just word highlighting, you can you use the built-in tools to create your own language syntax highlighter. You can define words, expressions, and grammar that gets formatted and colored and more across a specific type of file (you could enable it for .txt files if you really wanted to). You'd want to install Yeoman and the VScode Extension Generator.

Maybe recheck the name ? https://www.npmjs.com/package/yo https://yeoman.io/

If you are wondering about performance cost please take a look here, especially the last comment. https://github.com/yeoman/yeoman/issues/810 . With the advent of http2 and http3 the tcp connection is never reset and in http 3 the browser can always stop and resume the image loading without throwing the current progress away. FB, Google, Shopify, Reddit and many others are all using webp which doesn't support progressive rendering and I am sure at their scale they have at least million site visits with slow network and they are doing fine.