dash README

The project's README from github.com/plotly/dash. As one markdown file: README.md.

Dash

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Dash is the most downloaded, trusted Python framework for building ML & data science web apps.

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. Read our tutorial (proudly crafted ❤️ with Dash itself).

Maintained by Plotly

Dash App Examples

Dash App Description
Sample Dash App Here’s a simple example of a Dash App that ties a Dropdown to a Plotly Graph. As the user selects a value in the Dropdown, the application code dynamically exports data from Google Finance into a Pandas DataFrame. This app was written in just 43 lines of code (view the source).
Crossfiltering Dash App Dash app code is declarative and reactive, which makes it easy to build complex apps that contain many interactive elements. Here’s an example with 5 inputs, 3 outputs, and cross filtering. This app was composed in just 160 lines of code, all of which were Python.
Dash App with Mapbox map showing walmart store openings Dash uses Plotly.js for charting. About 50 chart types are supported, including maps.
Financial report Dash isn't just for dashboards. You have full control over the look and feel of your applications. Here's a Dash App that's styled to look like a PDF report.

To learn more about Dash, read the extensive announcement letter or jump in with the user guide.

Dash OSS & Dash Enterprise

With Dash Open Source, Dash apps run on your local laptop or workstation, but cannot be easily accessed by others in your organization.

Scale up with Dash Enterprise when your Dash app is ready for department or company-wide consumption. Or, launch your initiative with Dash Enterprise from the start to unlock developer productivity gains and hands-on acceleration from Plotly's team.

ML Ops Features: A one-stop shop for ML Ops: Horizontally scalable hosting, deployment, and authentication for your Dash apps. No IT or DevOps required.

Low-Code Features: Low-code Dash app capabilities that supercharge developer productivity.

Enterprise AI Features: Everything that your data science team needs to rapidly deliver AI/ML research and business initiatives.

See https://plotly.com/contact-us/ to get in touch.

Dash Enterprise

dash (plotly/dash)

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Dash
这是什么?Dash 是一个开源的 Python 框架,用于构建机器学习和数据科学 Web 应用:交互式仪表盘和数据应用,下拉框、滑块和图表都直接接入你的 Python 分析代码,完全不需要写 JavaScript。
Dash 是一个框架还是绘图库?它基于什么构建?它是一个框架,不只是一个绘图库。应用完全用 Python 编写,由 Flask 提供服务,浏览器端则用 React 和 Plotly.js 渲染。
我怎样才能跑起第一个应用?用 pip install dash 从 PyPI 安装,然后照着官方教程做——文档承诺 5 分钟内就能做出第一个能运行的应用。dash.gallery 展示区还提供了很多示例应用的完整 Python 和 R 源代码。
用它开发需要会 JavaScript 或 React 吗?不需要。React、Plotly.js 和 Flask 都在底层运行,但你完全不用直接碰它们:布局、交互和图表全部用 Python 定义。
框架本身免费,那给团队共享应用时有什么限制?开源的 Dash 应用只能跑在你自己的笔记本电脑或工作站上,组织里的其他人不容易访问。要服务整个部门或公司——托管、扩容、身份认证——就是付费产品 Dash Enterprise 所增加的功能。
Dash 能渲染哪些图表?Dash 使用 Plotly.js 绘图:支持大约 50 种图表类型,包括地图。
Dash 只能做仪表盘吗?不是——Dash 不只用于仪表盘。你可以完全掌控应用的外观和风格;README 里展示了一个模仿 PDF 报告样式的应用。
做一个交互式应用大概要写多少代码?README 里的示例把一个下拉框绑定到 Plotly 图表,数据从 Google Finance 拉取到 Pandas DataFrame,只有 43 行。一个带 5 个输入、3 个输出并支持 crossfiltering 的更大应用也只要 160 行——全部是 Python,声明式、响应式。
付费的 Dash Enterprise 比免费版多了什么?运维和扩展能力:点几下就能部署应用、在 Kubernetes 上横向扩展、无代码配置身份认证(LDAP、AD、PKI、Okta、SAML、OpenID Connect、OAuth、SSO)、用于后台计算的 Job Queue、无需写 CSS 的 Design Kit、以链接或 PDF 形式分享快照、无需 IFrames 即可嵌入,以及现成的 AI/ML 应用模板。
What are similar projects?plotly.py, plotly.js, pygwalker, gradio, pyecharts, marimo, mlcourse.ai, perspective
Which topics is it in?charting, plotly, dash, bioinformatics, dashboards, gui-framework, flask, jupyter, interactive, analytics, finance, data-visualization
Creator
plotly
Size
224.2 MB
Stars
24.5K
Updated
CommitOct 15Releasev4.4.1Jul 21
Age
11y
Commits · 90 Days