Transform data scripts into shareable web applications in minutes, all in Python, and for free with no front-end experience required.
Installation:
It is necessary to have Python 3.6 or higher, and the installation will be done via PIP:
pip install streamlit
streamlit hello
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:
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.
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:
Streamlit 101: o básico para colocar seu projeto no ar | by Rafael K | Medium
Rafael K ・ ・
rknagao.Medium
Build and Deploy Full Web applications Quickly with Python | by Abdishakur | Spatial Data Science | Medium
Abdishakur ・ ・
Medium
https://towardsdatascience.com/diabetes-prediction-application-using-streamlit-fed6120124a5
https://towardsdatascience.com/image-processing-using-streamlit-d650fb0ccf8
Follow me on Medium :)
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