Add css for DatePicker component

.pre-commit-config.yaml

@@ -45,7 +45,7 @@ repos:
         args: [--autofix]
 
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.8.1
+    rev: v0.8.6
     hooks:
       - id: ruff
         args: [--fix]
@@ -85,7 +85,7 @@ repos:
         args: ["--fix"]
 
   - repo: https://github.com/executablebooks/mdformat
-    rev: 0.7.18
+    rev: 0.7.21
     hooks:
       - id: mdformat
         args:

CODEOWNERS

@@ -1,2 +1,3 @@
 * @Joseph-Perkins @antonymilne @huong-li-nguyen @maxschulz-COL @lingyielia
 docs/ @stichbury @Joseph-Perkins @antonymilne @huong-li-nguyen @maxschulz-COL
+*.css @huong-li-nguyen @nadijagraca

README.md

@@ -1,118 +1,126 @@
-<br/><br/>
+<br><br>
+
+<div align="center">
 
-<p align="center">
 <picture>
   <source media="(prefers-color-scheme: dark)" srcset="https://raw.githubusercontent.com/mckinsey/vizro/main/.github/images/Vizro_Github_Banner_Dark_Mode.png">
   <source media="(prefers-color-scheme: light)" srcset="https://raw.githubusercontent.com/mckinsey/vizro/main/.github/images/Vizro_Github_Banner_Light_Mode.png">
   <img alt="Vizro logo" src="https://raw.githubusercontent.com/mckinsey/vizro/main/.github/images/Vizro_Github_Banner_Dark_Mode.png" width="250">
 </picture>
-</p>
-<br/><br/>
 
-<div align="center" markdown="1">
+#### Vizro is a low-code toolkit for building high-quality data visualization apps
 
 [![Python version](https://img.shields.io/badge/python-3.9%20%7C%203.10%20%7C%203.11%20%7C%203.12%20%7C%203.13-blue.svg)](https://pypi.org/project/vizro/) [![PyPI version](https://badge.fury.io/py/vizro.svg)](https://badge.fury.io/py/vizro) [![License](https://img.shields.io/badge/license-Apache%202.0-blue.svg)](https://github.com/mckinsey/vizro/blob/main/LICENSE.md) [![Documentation](https://readthedocs.org/projects/vizro/badge/?version=stable)](https://vizro.readthedocs.io/) [![OpenSSF Best Practices](https://www.bestpractices.dev/projects/7858/badge)](https://www.bestpractices.dev/projects/7858)
 
+[Documentation](https://vizro.readthedocs.io/en/stable/) | [Get Started](https://vizro.readthedocs.io/en/stable/pages/tutorials/first_dashboard/) | [Vizro examples gallery](http://vizro.mckinsey.com/)
+
+<img src="https://raw.githubusercontent.com/mckinsey/vizro/main/.github/images/vizro_spash_teaser.gif" width="600"/>
+<br>
+<br>
+<img src="https://raw.githubusercontent.com/mckinsey/vizro/main/.github/images/logo_watermarks.svg" width="300">
 </div>
 
-<div align="center" markdown="1">
+## What is Vizro?
+
+Vizro is an open-source Python-based toolkit.
+
+Use it to build beautiful and powerful data visualization apps quickly and easily, without needing advanced engineering or visual design expertise.
 
-<a href="https://vizro.readthedocs.io/en/stable/" target="_blank">Documentation </a> | <a href="https://vizro.readthedocs.io/en/stable/pages/tutorials/first_dashboard/" target="_blank">Get Started </a> | <a href="http://vizro.mckinsey.com/" target="_blank">Vizro examples gallery</a>
+Then customize and deploy your app to production at scale.
 
+<div align="center">
+<img src="https://raw.githubusercontent.com/mckinsey/vizro/main/.github/images/code_dashboard.png" width="100%"/>
+Use a few lines of simple low-code configuration, with in-built visual design best practices, to assemble high-quality
+multi-page prototypes.
 </div>
+<br>
 
----
+The benefits of the Vizro toolkit include:
 
-<p align="center">
-<img src="https://raw.githubusercontent.com/mckinsey/vizro/main/.github/images/vizro_spash_teaser.gif" width="600"/>
-</p>
-
-<p align="center">
-<font size="+2">
-<b>
-Visual Intelligence. Beautifully Engineered
-</b>
-</font>
-</p>
-
-<p align="center">
-<font size="+1">
-Vizro is a toolkit for creating modular data visualization applications
-</font>
-</p>
-
-<p align="center">
-<img src="https://raw.githubusercontent.com/mckinsey/vizro/main/.github/images/tech_logos.png" width="300"/>
-</p>
+<div align="center">
+<img src="https://raw.githubusercontent.com/mckinsey/vizro/main/.github/images/infographic.svg" width="800"/>
+</div>
+<br>
 
-## What is Vizro?
+Visit our ["How-to guides"](https://vizro.readthedocs.io/en/stable/pages/user-guides/install/) for a more detailed explanation of Vizro features.
+
+## Why use Vizro?
+
+Vizro helps you to build data visualization apps that are:
+
+**Quick and easy**
 
-<p align="left">
-<font size="+1">
-Rapidly self-serve the assembly of customized dashboards in minutes - without the need for advanced coding or design experience - to create flexible and scalable, Python-enabled data visualization applications.
-</font>
-</p>
+Build apps in minutes. Use a few lines of simple configuration (via Pydantic models, JSON, YAML, or Python dictionaries) in place of thousands of lines of code.
 
-<p align="center">
-<img src="https://raw.githubusercontent.com/mckinsey/vizro/main/.github/images/code_dashboard.png" width="1300"/>
-</p>
+**Beautiful and powerful**
 
-Use a few lines of simple configuration to create complex dashboards, which are automatically assembled using libraries such as [**Plotly**](https://github.com/plotly/plotly.py) and [**Dash**](https://github.com/plotly/dash), with inbuilt coding and design best practices.
+Build high-quality multi-page apps without needing advanced engineering or visual design expertise. Use powerful features of production-grade BI tools, with in-built visual design best practices.
 
-Define high-level categories within the configuration, including:
+**Flexible**
 
-- **Components:** create charts, tables, input/output interfaces, and more.
-- **Controls**: create filters, parameter inputs, and custom action controllers.
-- **Pages, layouts and navigation**: create multiple pages, with customizable layouts and flexible navigation across them.
-- **Actions and interactions**: create interactions between charts, and use pre-defined or customized actions (such as exporting).
+Benefit from the capabilities and flexibility of open-source packages. Use the trusted dependencies of Plotly, Dash, and Pydantic.
 
-Configuration can be written in multiple formats including **Pydantic models**, **JSON**, **YAML** or **Python dictionaries** for added flexibility of implementation.
+**Customizable**
 
-Optional high-code extensions enable almost infinite customization in a modular way, combining the best of low-code and high-code - for flexible and scalable, Python enabled data visualization applications.
+Almost infinite control for advanced users. Use Python, JavaScript, HTML and CSS code extensions.
+
+**Scalable**
+
+Rapidly prototype and deploy to production. Use the in-built production-grade capabilities of Plotly, Dash and Pydantic.
 
 Visit ["Why should I use Vizro?"](https://vizro.readthedocs.io/en/stable/pages/explanation/faq/#why-should-i-use-vizro) for a more detailed explanation of Vizro use cases.
 
-## What is Vizro-AI?
+## When to use Vizro?
+
+Use Vizro when you need to combine the speed and ease of low-code Python tools, with production capabilities of JavaScript and BI tools, and the freedom of open source:
 
-Vizro-AI is a separate package and extends Vizro to enable the use of natural language queries to build Plotly charts and Vizro dashboards. With Vizro-AI you can effortlessly create interactive charts and comprehensive dashboards by simply describing your needs in plain English, or any other language.
+- Have an app that looks beautiful and professional by default.
+- Enjoy the simplicity of low-code, plus the option to customize with code almost infinitely.
+- Rapidly create prototypes which are production-ready and easy to deploy at scale.
 
-<p align="center">
-<img src="./vizro-ai/docs/assets/readme/readme_animation.gif" alt="Gif to show vizro-ai", width="525" height="296">
-</p>
+## How to use Vizro?
 
-See the [Vizro-AI documentation](https://vizro.readthedocs.io/projects/vizro-ai/) for more details.
+## [Vizro framework](https://vizro.readthedocs.io/en/stable/)
 
-## Key benefits of Vizro
+**Low-code framework for building dashboards.**
 
-<br/>
+The Vizro framework underpins the entire Vizro toolkit. It is a Python package (called `vizro`).
 
-<p align="center">
-<img src="https://raw.githubusercontent.com/mckinsey/vizro/main/.github/images/value_prop_icons.png" width="900"/>
-</p>
+Visit the [documentation](https://vizro.readthedocs.io/en/stable/) for more details.
 
-<br/>
+## [Vizro visual vocabulary](https://vizro-demo-visual-vocabulary.hf.space/)
 
-## Vizro examples gallery
+**Chart examples.**
 
-You can see Vizro in action by clicking on the following image or by visiting [the examples gallery at vizro.mckinsey.com](https://vizro.mckinsey.com).
+The visual vocabulary helps you to decide which chart type to use for your requirements, and offers sample code to create these charts with Plotly or embed them into a Vizro dashboard.
 
-<a href="http://vizro.mckinsey.com/">
-<img src="https://raw.githubusercontent.com/mckinsey/vizro/main/.github/images/vizro_examples_gallery.png" width="550">
+Visit the [visual vocabulary](https://vizro-demo-visual-vocabulary.hf.space/) to search for charts or get inspiration.
+
+<a href="https://vizro-demo-visual-vocabulary.hf.space/">
+<img src="https://raw.githubusercontent.com/mckinsey/vizro/main/.github/images/toolkit_visual_vocabulary.png" width="600">
 </a>
 
-## Visual vocabulary
+## [Vizro examples gallery](https://vizro.mckinsey.com/)
+
+**Dashboard examples.**
+
+The dashboard examples gallery enables you to explore Vizro in action by viewing interactive example apps. You can copy the code to use as a template or starter for your next dashboard.
 
-Our visual vocabulary dashboard helps you to select and create various types of charts. It helps you decide when to use each chart type, and offers sample Python code to create these charts with [Plotly](https://plotly.com/python/) and embed them into a Vizro dashboard.
+Visit the [dashboard examples gallery](https://vizro.mckinsey.com/) to see the dashboards in action.
 
-<a href="https://vizro-demo-visual-vocabulary.hf.space">
-<img src="https://raw.githubusercontent.com/mckinsey/vizro/main/.github/images/visual_vocabulary.png" width="550">
+<a href="https://vizro.mckinsey.com/">
+<img src="https://raw.githubusercontent.com/mckinsey/vizro/main/.github/images/toolkit_dashboard_examples.png" width="600">
 </a>
 
-## Dashboard screenshots
+## [Vizro-AI](https://vizro.readthedocs.io/projects/vizro-ai/)
 
-<p align="center">
-<img src="https://raw.githubusercontent.com/mckinsey/vizro/main/.github/images/dashboard_examples.png" width="1300"/>
-</p>
+**Use LLMs to generate charts and dashboards.**
+
+Vizro-AI is a separate package (called `vizro_ai`) that extends Vizro to incorporate LLMs. Use it to build interactive Vizro charts and dashboards, by simply describing what you need in plain English or other languages.
+
+Visit the [Vizro-AI documentation](https://vizro.readthedocs.io/projects/vizro-ai/) for more details.
+
+<img width="600" src="https://raw.githubusercontent.com/mckinsey/vizro/main/.github/images/toolkit_vizro_ai.gif">
 
 ## Installation and first steps
 
@@ -124,10 +132,6 @@ See the [installation guide](https://vizro.readthedocs.io/en/stable/pages/user-g
 
 The [get started documentation](https://vizro.readthedocs.io/en/stable/pages/tutorials/first-dashboard/) explains how to create your first dashboard.
 
-## Get hands on
-
-See the [how-to guides](https://vizro.readthedocs.io/en/stable/pages/user-guides/install/) for step-by-step instructions on the key Vizro features.
-
 ## Packages
 
 This repository is a monorepo containing the following packages:
@@ -139,18 +143,18 @@ This repository is a monorepo containing the following packages:
 
 ## Community and development
 
-We encourage you to ask and answer technical questions via the [GitHub Issues](https://github.com/mckinsey/vizro/issues). This is also the place where you can submit bug reports or request new features.
+We encourage you to ask and discuss any technical questions via the [GitHub Issues](https://github.com/mckinsey/vizro/issues). This is also the place where you can submit bug reports or request new features.
 
 ## Want to contribute to Vizro?
 
-The [contributing guide](https://vizro.readthedocs.io/en/stable/pages/explanation/contributing/) explain how you can contribute to Vizro.
+The [contributing guide](https://vizro.readthedocs.io/en/stable/pages/explanation/contributing/) explains how you can contribute to Vizro.
 
-You can also view current and former [contributors](https://vizro.readthedocs.io/en/stable/pages/explanation/authors/).
+You can also view current and former contributors [here](https://vizro.readthedocs.io/en/stable/pages/explanation/authors/).
 
 ## Want to report a security vulnerability?
 
 See our [security policy](https://github.com/mckinsey/vizro/security/policy).
 
 ## License
 
-`vizro` is distributed under the terms of the [Apache License 2.0](https://www.apache.org/licenses/LICENSE-2.0)
+`vizro` is distributed under the terms of the [Apache License 2.0](https://www.apache.org/licenses/LICENSE-2.0).

pyproject.toml

@@ -6,6 +6,7 @@ authors = [
   {name = "Vizro Team"}
 ]
 description = "Vizro is a package to facilitate visual analytics."
+dynamic = ["version"]
 name = "vizro"
 
 [tool.bandit]
@@ -14,7 +15,7 @@ exclude_dirs = ["tests"]
 [tool.codespell]
 builtin = "clear,rare,en-GB_to_en-US"
 ignore-words-list = "grey,ned,sav,Thur"
-skip = "*.min.css.map,*.min.css,.vale/*, *assets/*"
+skip = "*.min.css.map,*.min.css,.vale/*, *assets/*,.github/*"
 
 [tool.mypy]
 # strict checks : strict = true

vizro-ai/CHANGELOG.md

@@ -11,6 +11,18 @@ See the fragment files in the [changelog.d directory](https://github.com/mckinse
 
 <!-- scriv-insert-here -->
 
+<a id='changelog-0.3.3'></a>
+
+# 0.3.3 — 2025-01-16
+
+## Changed
+
+- Pinned the Vizro upper bound to prepare for Pydantic V2 migration. ([#923](https://github.com/mckinsey/vizro/pull/923))
+
+## Fixed
+
+- Fixed the "Model name could not be retrieved" error when using VizroAI with AWS Bedrock. ([#953](https://github.com/mckinsey/vizro/pull/953))
+
 <a id='changelog-0.3.2'></a>
 
 # 0.3.2 — 2024-11-08