domoritz

I’ve been using refined GitHub for years and multiple times I thought GitHub added a new feature when was refined GitHub. Needless to say, I am really happy about this extension and came to rely on it.

Vega-Lite and Falcon author here. Many people ask for scalable visualizations and I think declarative visualization approaches are really promising since systems can transparently optimize data movement and rendering. I have done some more experiments to scale Vega such as https://github.com/vega/scalable-vega but I think what we need is a system that automatically offloads heavy computations to a backend such as https://github.com/omnisci/jupyterlab-omnisci.

Take a look at https://www.streamlit.io/.

JupyterLab outputs have a mime type. Depending on the mimetype, a different renderer is used. For example, text is shown as plain text and an image is binary with the image type (e.g. png). There is also a mimetype for Vega and Vega-Lite JSON.

What this means for you as a user is that you don't need to install the renderer as it comes with the JL frontend.

Vega-Lite is client side so it's not running in the kernel.

Not yet, although sand dance is built on top of Vega and implements a custom renderer. https://sanddance.js.org

Vega-Lite is built on Vega, which is fully reactive and can do partial updates. In order to use it, you need to update the data via the Vega view api. Check out https://vega.github.io/vega/docs/api/view/#view_data.

One other piece of advice I have it to reduce the number of marks you need to draw with aggregation or sampling. I used this approach in https://github.com/uwdata/falcon to visualize billions of points and interact with them in real time.

Nice. Feel free to send us a pull request to add your Voyager clone to https://vega.github.io/vega-lite/ecosystem.html.

Hi Hacker News! One of the Vega-Lite authors here. I'm excited to see you all here checking out our declarative visualization system.

If you want to learn more about the academic origins, check out the paper: https://idl.cs.washington.edu/papers/vega-lite. Vega-Lite is also available as the default plotting library in JupyterLab.

If you like, also check out Altair (https://github.com/altair-viz/altair), a Python API for generating Vega-Lite and Vega-Lite-API (https://observablehq.com/@uwdata/introduction-to-vega-lite), a JavaScript API to generate Vega-Lite.

Vega-Lite author here. The reason why we integrated the two is that we wanted to provide support for interactions with a fully reactive runtime system (https://idl.cs.washington.edu/papers/reactive-vega-architect...). It's difficult to do that while being agnostic to different implementations of these transformations.

The app looks sleek. Do you plan to also support Gmail's smart compose feature or is that beyond what a native app can support?

Check out Vega/Vega-Lite (https://vega.github.io/) for a fully declarative visualization grammar (including interactions).

D3 started out as an academic project and Vega/Vega-Lite come from the same lab. Also, while Vega does not generate D3 code (Vega is a declarative visualization language and reactive runtime), it uses the D3 libraries internally and is heavily inspired by some of the core principles (e.g. data join).

It’s great if you are on a system where you don’t have root and you want to install some packages.

I just noticed that the home assistant addon has been deprecated: https://github.com/hassio-addons/addon-pi-hole. I hope that it comes back eventually.

Author of uwdata/falcon here. I'm glad to hear you like the tool we've built.

So if it isn't supposed to be officially endorsed, should someone file an issue at https://github.com/pypa/packaging.python.org/issues?

The tools are available. Maybe someone would be willing to make a similar project for other languages.

A tiny fraction but it's important to realize what we personally contribute, and not only blame something outside of our control.

I think you might be able to build one based on this Vega version https://vega.github.io/vega/examples/wind-vectors/

Yes, you can save an Altair chart as an HTML page. See https://altair-viz.github.io/user_guide/saving_charts.html#h.... You can also just get the Vega-Lite JSON form Altair and embed it in a web page with Vega-Embed.

This is something we are painfully aware of and have started to work on. For a start, see Jake's work on https://pypi.org/project/altair-data-server/.

Altair builds on Vega-Lite but if you cannot do something in Vega-Lite, you can do it in Vega.

Performance is a huge concern for us and we are working on some improvements in that area. We will first focus on pushing computation and aggregation down into the Python kernel.

There is an XKCD for almost every situation.

Jake started Altair, a declarative visualization library that is becoming quite popular. Check it out at https://altair-viz.github.io/.

I need this as well. I have a ton of PRs with WIP labels.

The change list is at https://github.com/rollup/rollup/pull/2293

This is a fantastic example of all the important steps you have to go through before you get to the final visualization. Many explanations jump over these instructive details.

Vega-Lite author here. Performance is hugely important for us and is covered y the first three points on our roadmap: https://docs.google.com/document/d/1fscSxSJtfkd1m027r1ONCc7O.... Some improvements will ship with Vega-Lite 3. Others are being worked on as we speak.

Any kind of enforcement would already be a huge benefit over the status quo and make things too annoying for at least half of the attackers.

Hi, one of the Vega-Lite author here. I'm glad you like Vega-Lite and were inspired by our Infovis paper. Vega-Lite is much more mature than when we wrote the Infovis paper so I suggest you to check it out. Compared to Muze, Vega-Lite is embracing full declarativeness.