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A Beginners Guide To Streamlit
  • Difficulty Level : Basic
  • Last Updated : 26 Nov, 2020

The trend of Data Science and Analytics is increasing day by day. From the data science pipeline, one of the most important steps is model deployment. We have a lot of options in python for deploying our model. Some popular frameworks are Flask and Django. But the issue with using these frameworks is that we should have some knowledge of HTML, CSS, and JavaScript. Keeping these prerequisites in mind, Adrien Treuille, Thiago Teixeira, and Amanda Kelly created “Streamlit”. Now using streamlit you can deploy any machine learning model and any python project with ease and without worrying about the frontend. Streamlit is very user-friendly.

In this article, we will learn some important functions of streamlit, create a python project, and deploy the project on a local web server.

Let’s install streamlit. Type the following command in the command prompt.

pip install streamlit

Once Streamlit is installed successfully, run the given python code and if you do not get an error, then streamlit is successfully installed and you can now work with streamlit.

How to run Streamlit file?

Open command prompt or Anaconda shell and type



streamlit run filename.py

Run Streamlit file

Here my filename is ‘sample.py’. Open the local URL in the web browser.

 

Understanding the Streamlit basic functions

1.  Title:

Python3




# import module
import streamlit as st
  
# Title
st.title("Hello GeeksForGeeks !!!")

Output:

Title

2. Header and Subheader:

Python




# Header
st.header("This is a header"
  
# Subheader
st.subheader("This is a subheader")

Output:



Header/Subheader

3. Text:

Python3




# Text
st.text("Hello GeeksForGeeks!!!")

Output:

Text

4. Markdown:

Python3




# Markdown
st.markdown("### This is a markdown")

Output:

Markdown

5.  Success, Info, Warning, Error, Exception:

Python3




# success
st.success("Success")
  
# success
st.info("Information")
  
# success
st.warning("Warning")
  
# success
st.error("Error")

Output:

Success, Info, Warning and Error

6.  Write:



Using write function, we can also display code in coding format. This is not possible using st.text(”).

Python3




# Write text
st.write("Text with write")
  
# Writing python inbuilt function range()
st.write(range(10))

Output:

write() function

7. Display Images:

Python3




# Diaplay Images
  
# import Image from pillow to open images
from PIL import Image
img = Image.open("streamlit.png")
  
# display image using streamlit
# width is used to set the width of an image
st.image(img, width=200)

Output:

Display image using streamlit

8. Checkbox:

A checkbox returns a boolean value. When the box is checked, it returns a True value else returns a False value.

Python3




# checkbox
# check if the checkbox is checked
# title of the checkbox is 'Show/Hide'
if st.checkbox("Show/Hide"):
    
  # dispaly the text if the checkbox returns True value
  st.text("Showing the widget")

Output:

Checkbox is not checked

The text is displayed when the box is checked

9. Radio Button:

Python3




# radio button
# first argument is the title of the radio button
# second argument is the options for the ratio button
status = st.radio("Select Gender: ", ('Male', 'Female'))
  
# conditional statement to print 
# Male if male is selected else print female
# show the result using the success function
if (status == 'Male'):
    st.success("Male")
else:
    st.success("Female")

Output:

Success shows Male when male option is selected

Success shows Female when Female option is selected

10. Selection Box:

You can select any one option from the select box.

Python3




# Selection box
  
# first argument takes the titleof the selectionbox
# second argument takes options
hobby = st.selectbox("Hobbies: ",
                     ['Dancing', 'Reading', 'Sports'])
  
# print the selected hobby
st.write("Your hobby is: ", hobby)

Output:

Selectbox showing options to select from

Selected option is printed

11. Multi-Selectbox:

The multi-select box returns the output in the form of a list. You can select multiple options.

Python3




# multi select box
  
# first argument takes the box title
# second argument takes the options to show
hobbies = st.multiselect("Hobbies: ",
                         ['Dancing', 'Reading', 'Sports'])
  
# write the selected options
st.write("You selected", len(hobbies), 'hobbies')

Output:

Multi-SelectBox

 

Selected 2 options

12. Button:

st.button() returns a boolean value. It returns a True value when clicked else returns False.

Python3




# Create a simple button that does nothing
st.button("Click me for no reason")
  
# Create a button, that when clicked, shows a text
if(st.button("About")):
    st.text("Welcome To GeeksForGeeks!!!")

Output:

Click the first button

Click the About button

13. Text Input:

Python3




# Text Input
  
# save the input text in the variable 'name'
# first argument shows the title of the text input box
# second argument displays a default text inside the text input area
name = st.text_input("Enter Your name", "Type Here ...")
  
# display the name when the submit button is clicked
# .title() is used to get the input text string 
if(st.button('Submit')):
    result = name.title()
    st.success(result)

Output:

Text Input

 

Display success message when the Submit button is clicked

14.  Slider:

Python3




# slider
  
# first argument takes the title of the slider
# second argument takes thr starting of the slider
# last argument takes the end number
level = st.slider("Select the level", 1, 5)
  
# print the level
# format() is used to print value 
# of a variable at a specific position
st.text('Selected: {}'.format(level))

Output:

Slider

Mini Project:

Let us recollect everything that we learn above and create a BMI Calculator web app.

The formula of BMI Index when weight is in Kgs and height is in meters is:

bmi = weight/height^2

Python3




# import the streamlit library
import streamlit as st
  
# give a title to our app
st.title('Welcome to BMI Calculator')
  
# TAKE WEIGHT INPUT in kgs
weight = st.number_input("Enter your weight (in kgs)")
  
# TAKE HEIGHT INPUT
# radio button to choose height format
status = st.radio('Select your height format: ',
                  ('cms', 'meters', 'feet'))
  
# compare status value
if(status == 'cms'):
    # take height input in centimeters
    height = st.number_input('Centimeters')
      
    try:
        bmi = weight / ((height/100)**2)
    except:
        st.text("Enter some value of height")
          
elif(status == 'meters'):
    # take height input in meters
    height = st.number_input('Meters')
      
    try:
        bmi = weight / (height ** 2)
    except:
        st.text("Enter some value of height")
          
else:
    # take height input in feet
    height = st.number_input('Feet')
      
    # 1 meter = 3.28
    try:
        bmi = weight / (((height/3.28))**2)
    except:
        st.text("Enter some value of height")
  
# check if the button is pressed or not
if(st.button('Calculate BMI')):
      
    # print the BMI INDEX
    st.text("Your BMI Index is {}.".format(bmi))
      
    # give the interpretation of BMI index
    if(bmi < 16):
        st.error("You are Extremely Underweight")
    elif(bmi >= 16 and bmi < 18.5):
        st.warning("You are Underweight")
    elif(bmi >= 18.5 and bmi < 25):
        st.success("Healthy")        
    elif(bmi >= 25 and bmi < 30):
        st.warning("Overweight")
    elif(bmi >= 30):
        st.error("Extremely Overweight")

Output:

Calculate BMI Indec, Scenario 1

Height in Meters:

Calculate BMI Indec, Scenario 2

Height in Feet:

Calculate BMI Indec, Scenario 3

Conclusion

This way we can use streamlit to deploy our projects without having any knowledge of HTML, CSS, or JavaScript. 

Note: Streamlit is still under development and the team is bringing new concepts.

 Attention geek! Strengthen your foundations with the Python Programming Foundation Course and learn the basics.  

To begin with, your interview preparations Enhance your Data Structures concepts with the Python DS Course. And to begin with your Machine Learning Journey, join the Machine Learning – Basic Level Course

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