![]() Dash is simple enough that you can bind a user interface around your Python code in an afternoon. Through these two abstractions - Python components and reactive functional decorators - Dash abstracts away all of the technologies and protocols that are required to build an interactive web-based application. Built in a few hundred lines of Python code. Selecting drugs in the dropdown highlights their position in the chart and appends their symbol in the table below. Hovering over points displays a description of the drug. The application code filters data in a Pandas DataFrame based off of the currently selected point.Ī Dash App for drug discovery. Dash expects that your function will return a new property of some element in the UI, whether that’s a new graph,a new table, or a new text element.įor example, here’s a simple Dash application that updates a text box as you interact with the Graph element. ![]() Your Python function can do anything that it wants with this input new value: It could filter a Pandas DataFrame, make a SQL query, run a simulation, perform a calculation, or start an experiment. when you select an item in the dropdown or drag a slider), Dash’s decorator provides your Python code with the new value of the input. 'figure'), ) def your_data_analysis_function(new_slider_value): new_figure = your_compute_figure_function(new_slider_value) return new_figure Simple.Īn example of a simple Dash Slider componentĭash provides a simple reactive decorator for binding your custom data analysis code to your Dash user interface. This app was written in just 43 lines of code ( view the source). As the user selects a value in the Dropdown, the application code dynamically exports data from Google Finance into a Pandas DataFrame. Here’s a 43-line example of a Dash App that ties a Dropdown to a D3.js Plotly Graph. Those who use Python for data analysis, data exploration, visualization, modelling, instrument control, and reporting will find immediate use for Dash.ĭash makes it dead-simple to build a GUI around your data analysis code. You’ll find a getting started guide here and the Dash code on GitHub here.ĭash is a user interface library for creating analytical web applications. Dash can be downloaded today from Python’s package manager with pip install dash - it’s entirely open-source and MIT licensed. Today, we’re excited to announce the first public release of Dash that is both enterprise-ready and a first-class member of Plotly’s open-source tools. We used feedback from private trials at banks, labs, and data science teams to guide the product forward. We kept this prototype online, but subsequent work on Dash occurred behind closed doors. ![]() Dash started as a public proof-of-concept on GitHub 2 years ago. □ Introducing Dash □ Create Reactive Web Apps in pure Pythonĭash is a Open Source Python library for creating reactive, Web-based applications. ![]()
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