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Framework: Refactor a few items from "Visualization"
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Dash, hvPlot/Datashader, and Plotly.
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amotl committed Jun 27, 2024
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121 changes: 121 additions & 0 deletions docs/integrate/framework.md
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Original file line number Diff line number Diff line change
Expand Up @@ -31,6 +31,60 @@ infrastructure to framework integrations.
:::::


(dash)=
## Dash

```{div}
:style: "float: right"
[![](https://github.com/crate/crate-clients-tools/assets/453543/8b679c0b-2740-4dcc-88f0-1106aee7fa95){w=180px}](https://dash.plotly.com/)
```

[Dash] is a low-code framework for rapidly building data apps in Python,
based on [Plotly]. Built on top of Plotly.js, React and Flask, Dash ties
modern UI elements like dropdowns, sliders, and graphs, directly to your
analytical Python code.

Dash is a trusted Python framework for building ML & data science web apps. Many
specialized open-source Dash libraries exist that are tailored for building
domain-specific Dash components and applications.

```{div}
:style: "clear: both"
```
:::

![](https://github.com/crate/crate-clients-tools/assets/453543/cc538982-e351-437b-97ec-f1fc6ca34948){h=200px}
![](https://github.com/crate/crate-clients-tools/assets/453543/24908861-f0ad-43f3-b229-b2bfcc61596d){h=200px}

:::{dropdown} **Dash Enterprise**
```{div}
:style: "float: right"
[![](https://github.com/crate/crate-clients-tools/assets/453543/8b679c0b-2740-4dcc-88f0-1106aee7fa95){w=180px}](https://plotly.com/dash/)
```

Dash Enterprise is Plotly’s paid product for building, testing, deploying, managing,
and scaling Dash applications organization-wide, advertised as the Premier Data App
Platform for Python.

When building Dash apps in a business setting, Dash Enterprise supports you to deploy
and scale them, plus integrate them with IT infrastructure such as authentication and
VPC services, in order to deliver faster and more impactful business outcomes on AI
and data science initiatives.

Dash Enterprise enables the rapid development of production-grade data apps within your
business. Python has taken over the world, and traditional BI dashboards no longer
cut it in today’s AI and ML driven world. Production-grade, low-code Python data apps
are needed to visualize the sophisticated data analytics and data pipelines that run
modern businesses.

```{div}
:style: "clear: both"
```
![](https://github.com/crate/crate-clients-tools/assets/453543/161a9b73-25eb-4ec4-aa3e-5fa73757b440){h=200px}
![](https://github.com/crate/crate-clients-tools/assets/453543/d199b9c9-8be0-4ff7-a7b5-835dc122cc6d){h=200px}
:::


(gradio)=
## Gradio

Expand All @@ -52,6 +106,65 @@ machine learning model demo applications, written in Python.
```


(hvplot)=
## hvPlot and Datashader

```{div}
:style: "float: right"
[![](https://hvplot.holoviz.org/_static/logo_horizontal.svg){w=220px}](https://hvplot.holoviz.org/)
[![](https://datashader.org/_static/logo_horizontal.svg){w=220px}](https://datashader.org/)
```

[hvPlot] is a familiar and high-level API for data exploration and visualization.
[Datashader] is a graphics pipeline system for creating meaningful representations of
large datasets quickly and flexibly.

It is used on behalf of the [hvPlot] package, which is based on [HoloViews], from the
family of [HoloViz] packages of the [PyViz] ecosystem.

With Datashader, you can "just plot" large datasets and explore them instantly, with no
parameter tweaking, magic numbers, subsampling, or approximation, up to the resolution
of the display.

[hvPlot] sources its power in the [HoloViz] ecosystem. With [HoloViews], you get the
ability to easily layout and overlay plots, with [Panel], you can get more interactive
control of your plots with widgets, with [DataShader], you can visualize and interactively
explore very large data, and with [GeoViews], you can create geographic plots.

```{div}
:style: "clear: both"
```

![](https://github.com/crate/crate-clients-tools/assets/453543/7f38dff6-04bc-429e-9d31-6beeb9289c4b){h=200px}
![](https://github.com/crate/crate-clients-tools/assets/453543/23561a87-fb4f-4154-9891-1b3068e40579){h=200px}


(plotly)=
## Plotly

```{div}
:style: "float: right"
[![](https://github.com/crate/crate-clients-tools/assets/453543/8b679c0b-2740-4dcc-88f0-1106aee7fa95){w=180px}](https://plotly.com/)
```

[Plotly] Open Source Graphing Libraries make interactive, publication-quality graphs.
Line plots, scatter plots, area charts, bar charts, error bars, box plots, histograms,
heatmaps, subplots, multiple-axes, polar charts, bubble charts, and maps.

The supported programming languages / libraries / frameworks are Python, R, Julia,
JavaScript, ggplot2, F#, MATLAB®, and Dash.

Based on Plotly, [Dash] is a low-code framework for rapidly building data apps in Python.

```{div}
:style: "clear: both"
```

![](https://github.com/crate/crate-clients-tools/assets/453543/380114a8-7984-4966-929b-6e6d52ddd48a){h=200px}
![](https://github.com/crate/crate-clients-tools/assets/453543/f6a99ae7-b730-4587-bd23-499e1be02c92){h=200px}


(streamlit)=
## Streamlit

Expand All @@ -76,6 +189,14 @@ out Python data applications. It provides fast, interactive prototyping, and liv
```


[Dash]: https://plotly.com/dash/
[Datashader]: https://datashader.org/
[Gradio]: https://www.gradio.app/
[HoloViews]: https://www.holoviews.org/
[HoloViz]: https://holoviz.org/
[hvPlot]: https://hvplot.holoviz.org/
[Hugging Face]: https://en.wikipedia.org/wiki/Hugging_Face
[Panel]: https://panel.holoviz.org/
[Plotly]: https://plotly.com/graphing-libraries/
[PyViz]: https://pyviz.org/
[Streamlit]: https://streamlit.io/
122 changes: 2 additions & 120 deletions docs/integrate/visualize.md
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Expand Up @@ -2,7 +2,8 @@
# Visualize data in CrateDB

Dashboard and other data visualization applications and toolkits for
visualizing data stored inside CrateDB.
visualizing data stored inside CrateDB, mostly dashboarding.


::::{card} {material-outlined}`lightbulb;2em` Tutorials
:margin: 0 0 5 5
Expand Down Expand Up @@ -86,59 +87,6 @@ your entire company in few minutes.
![report-creator.png](https://github.com/crate/crate-clients-tools/assets/453543/844a5ffd-0b92-4c77-8cdd-0b5cc5b392b1){h=200px}


## Dash

```{div}
:style: "float: right"
[![](https://github.com/crate/crate-clients-tools/assets/453543/8b679c0b-2740-4dcc-88f0-1106aee7fa95){w=180px}](https://dash.plotly.com/)
```

[Dash] is a low-code framework for rapidly building data apps in Python,
based on [Plotly]. Built on top of Plotly.js, React and Flask, Dash ties
modern UI elements like dropdowns, sliders, and graphs, directly to your
analytical Python code.

Dash is a trusted Python framework for building ML & data science web apps. Many
specialized open-source Dash libraries exist that are tailored for building
domain-specific Dash components and applications.

```{div}
:style: "clear: both"
```
:::

![](https://github.com/crate/crate-clients-tools/assets/453543/cc538982-e351-437b-97ec-f1fc6ca34948){h=200px}
![](https://github.com/crate/crate-clients-tools/assets/453543/24908861-f0ad-43f3-b229-b2bfcc61596d){h=200px}

:::{dropdown} **Dash Enterprise**
```{div}
:style: "float: right"
[![](https://github.com/crate/crate-clients-tools/assets/453543/8b679c0b-2740-4dcc-88f0-1106aee7fa95){w=180px}](https://plotly.com/dash/)
```

Dash Enterprise is Plotly’s paid product for building, testing, deploying, managing,
and scaling Dash applications organization-wide, advertised as the Premier Data App
Platform for Python.

When building Dash apps in a business setting, Dash Enterprise supports you to deploy
and scale them, plus integrate them with IT infrastructure such as authentication and
VPC services, in order to deliver faster and more impactful business outcomes on AI
and data science initiatives.

Dash Enterprise enables the rapid development of production-grade data apps within your
business. Python has taken over the world, and traditional BI dashboards no longer
cut it in today’s AI and ML driven world. Production-grade, low-code Python data apps
are needed to visualize the sophisticated data analytics and data pipelines that run
modern businesses.

```{div}
:style: "clear: both"
```
![](https://github.com/crate/crate-clients-tools/assets/453543/161a9b73-25eb-4ec4-aa3e-5fa73757b440){h=200px}
![](https://github.com/crate/crate-clients-tools/assets/453543/d199b9c9-8be0-4ff7-a7b5-835dc122cc6d){h=200px}
:::


## Explo

```{div}
Expand Down Expand Up @@ -208,39 +156,6 @@ Get Grafana fully managed with [Grafana Cloud].
:::


## hvPlot and Datashader

```{div}
:style: "float: right"
[![](https://hvplot.holoviz.org/_static/logo_horizontal.svg){w=220px}](https://hvplot.holoviz.org/)
[![](https://datashader.org/_static/logo_horizontal.svg){w=220px}](https://datashader.org/)
```

[hvPlot] is a familiar and high-level API for data exploration and visualization.
[Datashader] is a graphics pipeline system for creating meaningful representations of
large datasets quickly and flexibly.

It is used on behalf of the [hvPlot] package, which is based on [HoloViews], from the
family of [HoloViz] packages of the [PyViz] ecosystem.

With Datashader, you can "just plot" large datasets and explore them instantly, with no
parameter tweaking, magic numbers, subsampling, or approximation, up to the resolution
of the display.

[hvPlot] sources its power in the [HoloViz] ecosystem. With [HoloViews], you get the
ability to easily layout and overlay plots, with [Panel], you can get more interactive
control of your plots with widgets, with [DataShader], you can visualize and interactively
explore very large data, and with [GeoViews], you can create geographic plots.

```{div}
:style: "clear: both"
```

![](https://github.com/crate/crate-clients-tools/assets/453543/7f38dff6-04bc-429e-9d31-6beeb9289c4b){h=200px}
![](https://github.com/crate/crate-clients-tools/assets/453543/23561a87-fb4f-4154-9891-1b3068e40579){h=200px}


## Metabase

```{div}
Expand Down Expand Up @@ -285,51 +200,18 @@ with none of the work or hidden costs that come with self-hosting.
:::


## Plotly

```{div}
:style: "float: right"
[![](https://github.com/crate/crate-clients-tools/assets/453543/8b679c0b-2740-4dcc-88f0-1106aee7fa95){w=180px}](https://plotly.com/)
```

[Plotly] Open Source Graphing Libraries make interactive, publication-quality graphs.
Line plots, scatter plots, area charts, bar charts, error bars, box plots, histograms,
heatmaps, subplots, multiple-axes, polar charts, bubble charts, and maps.

The supported programming languages / libraries / frameworks are Python, R, Julia,
JavaScript, ggplot2, F#, MATLAB®, and Dash.

Based on Plotly, [Dash] is a low-code framework for rapidly building data apps in Python.

```{div}
:style: "clear: both"
```

![](https://github.com/crate/crate-clients-tools/assets/453543/380114a8-7984-4966-929b-6e6d52ddd48a){h=200px}
![](https://github.com/crate/crate-clients-tools/assets/453543/f6a99ae7-b730-4587-bd23-499e1be02c92){h=200px}



[Apache Superset]: https://superset.apache.org/
[Cluvio]: https://www.cluvio.com/
[CrateDB and Grafana]: https://cratedb.com/integrations/cratedb-and-grafana
[CrateDB and Superset]: https://cratedb.com/integrations/cratedb-and-apache-superset
[CrateDB and Metabase]: https://cratedb.com/integrations/cratedb-and-metabase
[Dash]: https://plotly.com/dash/
[Datashader]: https://datashader.org/
[Explo]: https://www.explo.co/
[Explo Explore]: https://www.explo.co/products/explore
[GeoViews]: https://geoviews.org/
[Grafana Cloud]: https://grafana.com/grafana/
[Grafana Labs]: https://grafana.com/about/team/
[Grafana OSS]: https://grafana.com/oss/grafana/
[HoloViews]: https://www.holoviews.org/
[HoloViz]: https://holoviz.org/
[hvPlot]: https://hvplot.holoviz.org/
[Metabase]: https://www.metabase.com/
[Metabase Cloud]: https://www.metabase.com/cloud/
[Panel]: https://panel.holoviz.org/
[Plotly]: https://plotly.com/graphing-libraries/
[Preset]: https://preset.io/
[Preset Cloud]: https://preset.io/product/
[PyViz]: https://pyviz.org/

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