Customizing Streamlit Apps by rendering HTML

It is impossible to overlook the usefulness and usability of apps in today’s fast-paced world! Apps keep us engaged the whole day & their significance can be listed in all A-Z categories. 

To build a web app programmers typically use Python web frameworks such as Django and Flask, which are considered the gold standard. But the steep learning curve, technical barriers, and the time investment in implementing these steps act as major hurdles. 

Low-code solutions such as Streamlit have lowered such barriers and enabled data enthusiasts to easily convert machine learning models into interactive web apps. 

Streamlit makes the job of Machine Learning engineers so much easier without the need for a Web development team. The app development can now be done in a faster & more efficient way! This open-source app framework uses the Python language & helps to create web apps for data science & machine learning within a concise time period.  

Streamlit imports the HTML file as a component and displays it in the app. If the programmer’s goal is to create a Streamlit Component solely to display HTML code or render a chart from a Python visualization library, Streamlit incorporates two methods that simplify this process: components.html() and components.iframe(). 

Users can view and operate app features with ease. Now with Streamlit, building apps are as simple as writing Python scripts. Streamlit also enables the user-specific customization of modules using effortless API integration.

 WORKFLOW OF STREAMLIT APPS


Streamlit Apps
 WORKFLOW OF STREAMLIT

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