Streamlit is an open-source app framework for Machine Learning and Data Science teams to create beautiful web apps in minutes.
- IDE
- Python 3.x
App is deployed on Streamlit Cloud and accessed via link
Step 01: Create a python virtual environment and activate
python -m venv venv_streamlit
.\venv_streamlit\Scripts\activateStep 02: Install python Packages
pip install streamlitStep 03: Develop a python script - main.py
In this guide, you're going to use Streamlit's core features to create an interactive app; exploring a public Uber dataset for pickups and drop-offs in New York City. When you're finished, you'll know how to fetch and cache data, draw charts, plot information on a map, and use interactive widgets, like a slider, to filter results.
https://docs.streamlit.io/library/get-started/create-an-app
Step 04: Run Streamlit app
streamlit run main.pyStep 05: Export python dependency
pip freeze > requirements.txtStep 06: Commit your code to github
Never commit your virtual environment.
Generate requirements.txt file using pip freeze > requirements.txt and install on the target machine by pip install -r requirements.txt.
Step 07: Deploy on Streamlit Cloud