Streamlit
1 Introduction to Streamlit
1.1 What is Streamlit?
1.2 Why use Streamlit?
1.3 Setting up the environment
1.4 Creating your first Streamlit app
2 Basic Components
2.1 Text elements
2.1 1 Displaying text
2.1 2 Formatting text
2.2 Data display elements
2.2 1 Displaying data frames
2.2 2 Displaying tables
2.3 Input widgets
2.3 1 Text input
2.3 2 Number input
2.3 3 Date input
2.3 4 Dropdown selection
2.3 5 Slider
2.3 6 Checkbox
2.3 7 Radio buttons
2.3 8 Buttons
3 Advanced Components
3.1 Interactive widgets
3.1 1 Multiselect
3.1 2 File uploader
3.1 3 Color picker
3.2 Media elements
3.2 1 Displaying images
3.2 2 Displaying videos
3.2 3 Displaying audio
3.3 Chart elements
3.3 1 Line chart
3.3 2 Bar chart
3.3 3 Area chart
3.3 4 Scatter chart
3.3 5 Map chart
4 Layout and Styling
4.1 Layout components
4.1 1 Columns
4.1 2 Tabs
4.1 3 Expander
4.2 Styling elements
4.2 1 Custom CSS
4.2 2 Theming
4.2 3 Adding custom fonts
5 State Management
5.1 Session state
5.1 1 Managing state across reruns
5.1 2 Persisting state
5.2 Caching
5.2 1 Caching functions
5.2 2 Caching data
6 Deployment
6.1 Deploying to Streamlit Sharing
6.1 1 Setting up Streamlit Sharing
6.1 2 Deploying your app
6.2 Deploying to other platforms
6.2 1 Deploying to Heroku
6.2 2 Deploying to AWS
6.2 3 Deploying to Google Cloud
7 Best Practices
7.1 Writing clean and maintainable code
7.2 Optimizing performance
7.3 Handling errors and exceptions
7.4 Version control with Git
8 Advanced Topics
8.1 Integrating with other libraries
8.1 1 Integrating with Pandas
8.1 2 Integrating with Plotly
8.1 3 Integrating with TensorFlow
8.2 Building complex apps
8.2 1 Creating multi-page apps
8.2 2 Handling authentication
8.2 3 Building interactive dashboards
8.3 Custom components
8.3 1 Creating custom widgets
8.3 2 Extending Streamlit with custom components
9 Case Studies
9.1 Building a data exploration app
9.2 Building a machine learning model deployment app
9.3 Building a real-time data visualization app
2 3 1 Text Input Explained

3 1 Text Input Explained

Key Concepts

Text input in Streamlit allows users to enter text data interactively. The primary function for this is st.text_input(). This function creates a text box where users can type in their input, which can then be processed by your Streamlit app.

Explanation

1. st.text_input()

st.text_input() is used to create a single-line text input field. Users can type any text into this field, and the input is returned as a string. This function takes several parameters, including a label to describe the input field and an optional default value.

2. Label

The label parameter in st.text_input() is a string that describes the purpose of the text input field. This label is displayed next to the text box, helping users understand what kind of input is expected.

3. Default Value

The default value parameter allows you to specify a string that will be pre-filled in the text input field when the app is first loaded. This can be useful for providing hints or default options to the user.

Examples

Example 1: Basic Text Input

import streamlit as st

st.title("Basic Text Input Example")

user_input = st.text_input("Enter your name")
st.write(f"Hello, {user_input}!")
    

Example 2: Text Input with Default Value

import streamlit as st

st.title("Text Input with Default Value")

default_text = "Type something here"
user_input = st.text_input("Enter some text", default_text)
st.write(f"You entered: {user_input}")
    

Analogies

Think of st.text_input() as a digital form field where users can type in their responses. The label is like a prompt or question that guides the user on what to enter, while the default value is like a pre-filled suggestion that the user can either accept or modify.

Conclusion

Understanding and using st.text_input() effectively can greatly enhance the interactivity of your Streamlit app. By providing clear labels and useful default values, you can guide users to enter the right kind of data, making your app more user-friendly and efficient.