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2 changes: 1 addition & 1 deletion doc/getting_started/core_concepts.md
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Expand Up @@ -6,7 +6,7 @@ Now, let's explain the core concepts of Panel.

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Lower down in the page it says this:

  • If you're unsure, starting in a notebook is recommended as you familiarize yourself with Panel. However, you can switch between them at any time.

Suggested additional sentence: Hosted Notebook environements like https://ananconda.cloud and others are available for a quick start (or something similar).

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@MarcSkovMadsen MarcSkovMadsen Mar 3, 2024 •
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Maybe. Can you explain why this is important?

If this should be included. It could be included in different places: Installation, core_concepts, its own guide(s) similar to the Deployment guides. What would be the best place to include this?

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I think it's important (or at least relevant) because people might not be aware that this is an alternative to setting up and installing Jupyter from the ground up. That step can add al ot of friction for certain users in my view.

Hosted Notebooks allow them to skip that initially, and get to a working Panel example quickly, with as little friction as possible.

They can then always to choose to use the created .ipynb Notebook files in other (local) environments later.

## Development Flow

As you gear up to develop your Panel application, you'll encounter a couple of initial decisions to make regarding **API** and **environment**:
As you gear up to develop your Panel application, you'll encounter a couple of initial decisions to make regarding **approach** and **environment**:

1. **Programming Approach:** Will you opt for a Python *function-based* approach or a *class-based* approach?
- The function-based approach is recommended for new and basic users. It utilizes `pn.bind`, as you've already experienced while [building a simple app](build_app.md).
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30 changes: 18 additions & 12 deletions doc/index.md
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Expand Up @@ -14,7 +14,7 @@ sd_hide_title: true

# Overview

<h2 style="margin-top: 0.3em;">The powerful data exploration & web app framework for Python</h2>
<h2 style="margin-top: 0.3em;">The Powerful Data Exploration & Web App Framework for Python</h2>

::::{grid} 2 4 4 4

Expand Down Expand Up @@ -46,7 +46,7 @@ alt: Portfolio Optimizer App

```{image} https://assets.holoviz.org/panel/gallery/vtk_slicer.png
---
alt: VTK 3D Slicer App
alt: MRI Slicer App
---
```
:::
Expand All @@ -57,34 +57,40 @@ alt: VTK 3D Slicer App

```{image} https://assets.holoviz.org/panel/gallery/streaming_videostream.png
---
alt: scikit-image Videostream App
alt: Videostream App
---
```
:::

::::

Panel is an [open-source](https://github.com/holoviz/panel/blob/main/LICENSE.txt) Python library that lets you **easily build powerful tools, dashboards and complex applications entirely in Python**. It has a batteries-included philosophy, putting the PyData ecosystem, powerful data tables and much more at your fingertips. High-level reactive APIs and lower-level callback based APIs ensure you can quickly build exploratory applications, but you aren't limited if you build complex, multi-page apps with rich interactivity. Panel is a member of the [HoloViz](https://holoviz.org/) ecosystem, your gateway into a connected ecosystem of data exploration tools.
Panel is an [open-source](https://github.com/holoviz/panel/blob/main/LICENSE.txt) Python library designed to streamline the **development of robust tools, dashboards, and complex applications entirely within Python**. With a comprehensive philosophy, Panel integrates seamlessly with the PyData ecosystem, offering powerful, interactive data tables, visualizations, and much more, to unlock, visualize, share, and collaborate on your data for efficient workflows.

Its feature set includes high-level reactive APIs and lower-level callback-based APIs, enabling rapid development of exploratory applications and facilitating the creation of intricate, multi-page applications with extensive interactivity.

Panel is a proud member of the [HoloViz](https://holoviz.org/) ecosystem, providing a gateway to a cohesive suite of data exploration tools.

```{notebook} panel ../examples/homepage.ipynb
:disable_interactivity_warning: True
```

<br/>

Panel makes it simple to:

- Develop in your favorite **editor or notebook** environment
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  • Develop in your favorite editor or notebook environment and seamlessly publish the result to the web.

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Okay maybe add this part "seamlessly publish the result to the web." when there is clear documentation on how to do that :-)

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I'm in doubt:

  • Should "seamlessly publish the result to the web" be included?
  • If yes. Should it be a separate bullet point?

Could you elaborate on why this is important to add to an already long list of items?

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I think the ability to do that is important, and even fundamental for many use cases.

Publishing a development project as a webpage directly from your environment or Notebook without cumbersome deployment / conversion etc. etc. is (in my opinion) an important box to check for many users.

Together with the ability to then quickly iterate your development and immediately see the results in the webpage.

So there is a Notebook or other environment level where you can develop with other developers, and at the same time you have a (selective, constrained, polished) app that you serve from that environment to users.

So it enables an almost instant develop <-> web loop. Do others not also emphasize this? Like Gradio, etc.? Or the framework that mainly uses Plotly (is that Streamlit or another one?). I think it is an important part in many development cycles.

I think that part is pretty essential as a selling point, but would be good, but I don't know the user base well enough. Maybe others can chime in that have a good feel for the (potential) user base? @jbednar, any thoughts?

Conversely: are there also many cases where people do NOT need this in their project? So they stay entirely in a local environment / Notebook, and never need to pubish to a webpage?

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Does it align with the roadmap? doc/about/roadmap.md

- Combine the **PyData tools and plotting libraries** that you know and love
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  • Seamlessly publish your app to the web from a Notebook environment.

- **Iterate quickly** to develop data tools, dashboards and complex apps
- **Iterate quickly** to develop data tools, dashboards, and complex apps
- **Collaborate** across skill levels and tool preferences
- Add **advanced bi-directional communication** to your data apps
- Create interactive **big data** applications with **crossfiltering**
- Create **high performing**, **streaming** data applications
- Create **high-performing**, **streaming** data applications
- Create data apps that **can run entirely in the browser**
- Create **polished, performant, secure and production-ready web applications**
- Create **polished, performant, secure, and production-ready web applications**

---

Enjoying Panel? Show your support with a [Github star](https://github.com/holoviz/panel) — it’s a simple click that means the world to us and helps others discover it too! ⭐️
Enjoying Panel? Show your support with a [GitHub star](https://github.com/holoviz/panel) — it’s a simple click that means the world to us and helps others discover it too! ⭐️

## Learn Panel

Expand All @@ -102,7 +108,7 @@ The getting started guide will get you set up with Panel and provide a basic ove
:link: tutorials/index
:link-type: doc

Through guided steps and activities the tutorials will help you acquire the skills and knowledge to use Panel.
Through guided steps and activities, the tutorials will help you acquire the skills and knowledge to use Panel.
:::

:::{grid-item-card} {octicon}`telescope;2.5em;sd-mr-1` Explanation
Expand Down Expand Up @@ -130,19 +136,19 @@ The Component Gallery showcases Panel's components and their essential reference
:link: how_to/index
:link-type: doc

How-to guides provide step by step recipes for solving essential problems and tasks that arise during your work.
How-to guides provide step-by-step recipes for solving essential problems and tasks that arise during your work.
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How-to guides provide step-by-step recipes for solving essential problems and tasks you encounter on a daily basis.

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@MarcSkovMadsen MarcSkovMadsen Mar 3, 2024 •
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I would argue that a lot of the recipes are for solving tasks that arise for many people (not all) sometimes during their work.

For example advanced deployment or finetuning of the server is not something every one does and not daily.

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I see your point. So maybe something like ... that arise when analyzing, visualizing and publishing data in a broad range of scenario's? Basically stating the main challenges Panel can help solve?

:::

:::{grid-item-card} {octicon}`book;2.5em;sd-mr-1` API Reference
:link: api/index
:link-type: doc

The Panel API Reference Manual furnishes an extensive guide covering Panels methods and parameters.
The Panel API Reference Manual provides an extensive guide covering Panel's methods and parameters.
:::

::::

For usage questions or technical assistance, please head over to [Discourse](https://discourse.holoviz.org/) or our [Discord server](https://discord.gg/muhupDZM). If you have any [issues](https://github.com/holoviz/panel/issues), [feature requests](https://github.com/holoviz/panel/issues) or wish to [contribute](https://github.com/holoviz/panel/blob/main/CONTRIBUTING.MD), you can visit our [GitHub site](https://github.com/holoviz/panel).
For usage questions or technical assistance, please head over to [Discourse](https://discourse.holoviz.org/) or our [Discord server](https://discord.gg/muhupDZM). If you have any [issues](https://github.com/holoviz/panel/issues), [feature requests](https://github.com/holoviz/panel/issues), or wish to [contribute](https://github.com/holoviz/panel/blob/main/CONTRIBUTING.MD), you can visit our [GitHub site](https://github.com/holoviz/panel).

## Sponsors

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