Streamlit vs Gradio: The Ultimate Showdown for Python Dashboards

Python has become a cornerstone in the world of data science, machine learning, and web applications. With an ever-growing ecosystem of libraries, developers now have a plethora of tools to create interactive dashboards and applications. Among these, Streamlit and Gradio stand out as two powerful contenders. This article dives deep into the "Streamlit vs Gradio" debate to help you decide which one suits your needs.

What Are Streamlit and Gradio?

Streamlit

‍

Streamlit is an open-source Python library that allows developers to build interactive, data-driven web applications. It’s designed with simplicity in mind, enabling developers to create dashboards with just a few lines of code. Its declarative approach and native support for Python make it ideal for data scientists and analysts who may not have extensive web development experience.

Key Features:

• Reactive components for real-time interactivity.
• Easy integration with Python libraries like Pandas, NumPy, and Matplotlib.
• Built-in theming and customization.
• Streamlit Cloud for deploying apps effortlessly.

Gradio

‍

Gradio focuses on building interfaces for machine learning models and data science applications. It excels in creating user-friendly UIs for interacting with AI models, making it popular among ML researchers and practitioners.

Key Features:

• Pre-built components for ML tasks (e.g., image uploaders, sliders, text inputs).
• Integration with TensorFlow, PyTorch, and Hugging Face.
• Shareable links for showcasing apps without external hosting.
• Accessibility for non-developers to test ML models.

Use Cases: When to Choose Streamlit vs Gradio

Use Streamlit If:

1. You need to create general-purpose dashboards or visualizations.
2. Your project heavily relies on Python data analysis tools.
3. Customizability and theming are critical.
4. You want scalability for enterprise-level apps.

Use Gradio If:

1. You are building interfaces for machine learning models.
2. Simplicity and pre-built components are more important than flexibility.
3. You want a quick way to share your AI model demos.

Conclusion

The choice between Streamlit and Gradio ultimately boils down to your project’s specific needs:

• Choose Streamlit for flexible and scalable dashboards.
• Choose Gradio for quick, interactive ML model interfaces.

Both tools excel in making Python dashboards accessible, allowing developers to focus more on innovation and less on boilerplate code. Explore their features to see which aligns best with your workflow, and take advantage of the thriving open-source communities supporting these tools.

Last word

While Streamlit and Gradio excel in Python-specific dashboards, UI Bakery can be a great complementary tool, especially for scenarios requiring low-code solutions and backend integrations.

How UI Bakery Fits In

• No-Code/Low-Code Development: UI Bakery is perfect for building full-stack dashboards and admin panels without diving deep into coding.
• Backend Integration: It connects seamlessly with APIs, databases, and other services, which can be helpful for embedding or complementing ML dashboards built with Streamlit or Gradio.
• Custom UI Design: Unlike Streamlit and Gradio, which are more predefined in layout and structure, UI Bakery allows for customized, pixel-perfect UIs for a polished look.
• Team Collaboration: UI Bakery is designed for teams, offering role-based permissions and collaborative workflows that go beyond the individual developer's needs.

Use Case Example

Imagine you’re building a machine learning dashboard with Gradio to interact with your model:

• Use Gradio for the model interaction interface.
• Use UI Bakery to create a management dashboard for data collection, user access control, or analytics that supports your ML app.

Similarly, if you’re using Streamlit for a data visualization dashboard:

• Use UI Bakery to handle user authentication, create admin panels, or provide additional non-Python-based components for advanced business needs.

Key Advantages of Using UI Bakery Alongside Streamlit or Gradio

1. Speed: UI Bakery accelerates building enterprise-ready dashboards.
2. Flexibility: It can integrate with Python apps via REST APIs, GraphQL, or other data sources.
3. Scalability: UI Bakery apps are production-ready and can complement the prototypes built with Python tools.

In essence, UI Bakery can serve as the frontend builder or backend orchestrator, bridging gaps that Streamlit or Gradio might leave in enterprise-grade applications.