How to change theme of plotly dash dashboard python tutorial

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okay, let's dive into changing themes in plotly dash dashboards. this is a crucial aspect of creating visually appealing and user-friendly applications. we'll cover various approaches, from simple css overrides to leveraging dash bootstrap components (dbc) and more advanced theming techniques.

**understanding the basics: dash and styling**

before we get into specific methods, let's quickly recap the core concepts:

* **dash:** dash is a python framework for building web applications, especially analytical dashboards. it uses react.js under the hood for the frontend but allows you to define the ui using python.
* **components:** dash applications are built using reusable ui elements called "components." these components are things like buttons, dropdowns, graphs, text, tables, etc. plotly provides the `dash_html_components` (html) and `dash_core_components` (dcc) libraries for this.
* **styling:** dash components accept a `style` property. this is a python dictionary that maps css properties (in camelcase) to values. you can apply styling directly to components:



* **css (cascading style sheets):** css is the language used to define the visual presentation of html elements. it's the foundation of web design. you can use css to change colors, fonts, layouts, and much more.

**methods for changing themes in dash**

here's a breakdown of several methods for theming your dash applications, ordered roughly from simplest to most advanced:

1. **inline styling (good for quick changes)**

* **description:** the most basic approach is to apply css directly to components using the `style` property.
* **pros:** quick and easy for small tweaks.
* **cons:** can become cumbersome and difficult to maintain for larger applications. not easily reusable.
* **example:**



2. **external stylesheets (css files)**

* **description:** store your css rules in separate `.css` files and link them to your dash app.
* **pros:** improved organization, reusabili ...

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