Dash without the annoying bits. Main goals of this fork are (1) to enable Python to write state data to arbitrary component props, not just ones defined by a specific component; and (2) support React-style functional property values by binding unary functional expressions to the global application state, executing them whenever the property is accessed.
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 ❤️ by Dash itself.
Dash Docs on Heroku (for corporate network that cannot access plot.ly)
|Here’s a simple example of a Dash App that ties a Dropdown to a D3.js 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).|
|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 uses Plotly.js for charting. Over 35 chart types are supported, including maps.|
|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.|
Contact and Support
For companies with software budgets, Plotly offers
- Dash Deployment Server speeds your time-to-delivery while providing the right resources, security, and scalability you need to deliver production-quality apps
- Snapshot Engine seamlessly links your analytics and reporting workflows together, giving you a fast way to generate interactive reports of just the data you need
See https://plot.ly/dash/support for ways to get in touch.
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