DEV Community πŸ‘©β€πŸ’»πŸ‘¨β€πŸ’»

Josue Luzardo Gebrim
Josue Luzardo Gebrim

Posted on

Streamlit: The fastest way to create and share data applications!

Transform data scripts into shareable web applications in minutes, all in Python, and for free with no front-end experience required.

image.png

Installation:

It is necessary to have Python 3.6 or higher, and the installation will be done via PIP:

pip install streamlit
streamlit hello
Enter fullscreen mode Exit fullscreen mode

Right after that, it is necessary to configure some environment variables, depending on the operating system you are using:

Streamlit is compatible with many libraries and frameworks such as Keras, Scikit learn, Altair, bokeh, Latex, plotly, OpenCV, Vega-Lite, PyTorch, NumPy, seaborn, Deck.GL Tensorflow, matplotlib, pandas, and many others

Components:

With the popularization of Streamlit, several components appeared with the most diverse functionalities, such as:

image.png

HiPlot

A lightweight interactive visualization tool to help AI researchers discover correlations and patterns in high-dimensional data using parallel plots and other graphical ways of representing information.

pip install hiplot

Gallery:

There are many examples of its use and configurations of different apps; thinking about demonstrating its usability by the community, a gallery was created with several demonstrations of its use.

https://www.streamlit.io/gallery

Happy example :)

This demo project below allows you to browse the entire Udacity autonomous car dataset and perform inference in real-time using the YOLO object detection network.

image.png

Deploy Apps:

One of its great differentials is the possibility of deploying apps in a very automated way using GitOps, that is, through continuous integration, the developer, from a given push on a branch in a code repository like GitHub, triggers an automation that does to deploy the app.

https://docs.streamlit.io/en/stable/deploy_streamlit_app.html#

https://towardsdatascience.com/deploying-your-machine-learning-apps-in-2021-a3471c049507

This framework is straightforward and easy to use, the deployment of new apps is very intuitive. As a negative point, I missed a more visible layer of security, and I think I will have to implement an interface between the user and the apps to ensure more security….

References:

https://www.streamlit.io/

https://towardsdatascience.com/diabetes-prediction-application-using-streamlit-fed6120124a5

https://towardsdatascience.com/image-processing-using-streamlit-d650fb0ccf8

Buy Me A Coffee

Follow me on Medium :)

Top comments (0)

Stop sifting through your feed.

Find the content you want to see.

Change your feed algorithm by adjusting your experience level and give weights to the tags you follow.