Introduction to Streamlit

Everything you need to know about streamlit

Streamlit is an open-source Python library that makes it easy to build beautiful custom web-apps for machine learning and data science.

Data scientists are in charge of leading the data science process to a solution, invention, and model. They create a product, which they must share with their stakeholders at the conclusion of the process in order to receive feedback or contribute. Stakeholders can be customers, colleagues, or anyone else, anyone located in another city or perhaps another country.

It is important to publish the model on the internet in order to share it. The most crucial step is to deploy the model; otherwise, you won’t be able to construct a good model and complete the data science process. You should, however, convey this effort to others in an attractive manner.

You can construct your own dynamic environment with Streamlit, A web app with powerful content for your colleagues or customers to whom you want to demonstrate your work. You can collect values from users and adjust the outcome in real-time based on their inputs. Streamlit is an indispensable tool for bringing your concept to the internet. Installing and creating a web app with Streamlit is a breeze.

Installing the Streamlit

You just need to type pip install streamlit into your terminal and it is ready to use. (If you don’t have pip, install pip first.)

pip install streamlit

During the installation phase of streamlit library, one must be conscious of a few basic concepts some times streamlit and python versions do not support each other so there will be an error while installation. To cope with the problem mentioned going for the python 3.0.6 version which perfectly complements the updated streamlit version.

Create your first app

Imports:

import streamlit as st
import pandas as pd
import numpy as np

write some text to display

st.title("Hello world")

Now its time to launch our first web app using streamlit by just typing streamlit run and name of the file

streamlit run