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Dash

319
408
+ 1
63
Streamlit

320
401
+ 1
12
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Dash vs Streamlit: What are the differences?

Key Differences Between Dash and Streamlit

Dash and Streamlit are both popular frameworks for building interactive web applications with Python. While they share some similarities, there are several key differences between the two.

  1. Development Approach: Dash follows a declarative approach to building applications, where the layout and components are defined using Python code. This makes it flexible and allows for more customization. On the other hand, Streamlit follows an imperative approach, where the application is created by writing scripts that are executed sequentially. This makes it easier and quicker to create applications but offers less flexibility.

  2. Design and Styling: Dash allows for more advanced design and styling options. With Dash, developers can fully customize the appearance of their applications using CSS and HTML. Streamlit, on the other hand, has a simpler and more streamlined design approach, with limited options for customization.

  3. Data Sharing and Collaboration: Dash provides a built-in mechanism for sharing and deploying applications, called Dash Enterprise. It allows for easy deployment to the web with automatic scaling and offers collaboration features like version control. Streamlit, on the other hand, is primarily focused on local development, although it does allow for sharing applications via Streamlit Sharing, which is a free hosting service.

  4. Performance: Dash applications tend to be faster and more efficient compared to Streamlit applications. This is because Dash leverages React.js for rendering the user interface, which enables efficient updates and responsive behavior. Streamlit, on the other hand, uses the Python ecosystem for rendering, which can be slower in some cases.

  5. Data Visualization: Dash provides a wide range of interactive data visualization options through its integration with Plotly. This allows for the creation of sophisticated charts, graphs, and other visualizations. Streamlit also supports data visualization but is more focused on providing simple and quick visualization options.

  6. Community and Ecosystem: Dash has a larger and more mature community compared to Streamlit. This means there are more resources, tutorials, and community support available for Dash users. Streamlit, on the other hand, is a newer framework and is rapidly growing in popularity, but its community and ecosystem are not as extensive as Dash's.

In summary, Dash and Streamlit have different approaches to development, design, data sharing, performance, data visualization, and community support. The choice between the two frameworks depends on the specific requirements of the project and the preferences of the developer.

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Pros of Dash
Pros of Streamlit
  • 17
    Dozens of API docs and Cheat-Sheets
  • 12
    Great for offline use
  • 8
    Works with Alfred
  • 8
    Excellent documentation
  • 8
    Quick API search
  • 5
    Fast
  • 3
    Good integration with Xcode and AppCode
  • 2
    Great for mobile dev work
  • 11
    Fast development
  • 1
    Fast development and apprenticeship

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What is Dash?

Dash is an API Documentation Browser and Code Snippet Manager. Dash stores snippets of code and instantly searches offline documentation sets for 150+ APIs. You can even generate your own docsets or request docsets to be included.

What is Streamlit?

It is the app framework specifically for Machine Learning and Data Science teams. You can rapidly build the tools you need. Build apps in a dozen lines of Python with a simple API.

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What companies use Dash?
What companies use Streamlit?
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What tools integrate with Dash?
What tools integrate with Streamlit?
    No integrations found

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    What are some alternatives to Dash and Streamlit?
    Shiny
    It is an open source R package that provides an elegant and powerful web framework for building web applications using R. It helps you turn your analyses into interactive web applications without requiring HTML, CSS, or JavaScript knowledge.
    Plotly.js
    It is a standalone Javascript data visualization library, and it also powers the Python and R modules named plotly in those respective ecosystems (referred to as Plotly.py and Plotly.R). It can be used to produce dozens of chart types and visualizations, including statistical charts, 3D graphs, scientific charts, SVG and tile maps, financial charts and more.
    Git
    Git is a free and open source distributed version control system designed to handle everything from small to very large projects with speed and efficiency.
    GitHub
    GitHub is the best place to share code with friends, co-workers, classmates, and complete strangers. Over three million people use GitHub to build amazing things together.
    Visual Studio Code
    Build and debug modern web and cloud applications. Code is free and available on your favorite platform - Linux, Mac OSX, and Windows.
    See all alternatives