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
6 Deployment Explained

Deployment Explained

Key Concepts

Deployment

Deployment is the process of making a Streamlit application available to users. This involves uploading your application code to a hosting service and configuring it to run continuously.

Example:

streamlit run app.py
    

Hosting Services

Hosting services provide the infrastructure to host and run Streamlit apps. Popular options include Heroku, AWS, Google Cloud, and Streamlit's own sharing platform.

Example:

# Deploying to Heroku
heroku create
git push heroku main
    

Continuous Integration/Continuous Deployment (CI/CD)

CI/CD are automated processes to build, test, and deploy applications. Tools like GitHub Actions, GitLab CI, and Travis CI can be used to set up CI/CD pipelines for Streamlit apps.

Example:

# GitHub Actions workflow
name: Deploy Streamlit App
on: [push]
jobs:
  deploy:
    runs-on: ubuntu-latest
    steps:
    - uses: actions/checkout@v2
    - name: Set up Python
      uses: actions/setup-python@v2
      with:
        python-version: '3.8'
    - name: Install dependencies
      run: |
        python -m pip install --upgrade pip
        pip install -r requirements.txt
    - name: Deploy to Heroku
      run: |
        heroku login
        heroku create
        git push heroku main
    

Environment Variables

Environment variables are used to securely store sensitive information like API keys and passwords. These variables can be set in the hosting service or in the CI/CD pipeline.

Example:

# Setting environment variables in Heroku
heroku config:set API_KEY=your_api_key
    

Scaling

Scaling involves managing the increase in resources required to handle more users. This can be done by adding more instances, using load balancers, or optimizing the application code.

Example:

# Scaling on Heroku
heroku ps:scale web=2
    

Analogies

Think of deployment as opening a store for your business. Hosting services are like the building where your store is located. CI/CD is like having a team that continuously improves and updates your store. Environment variables are like the safe where you keep your valuable items. Scaling is like expanding your store to accommodate more customers.

By mastering deployment in Streamlit, you can make your applications accessible to users, ensure they run smoothly, and handle increased traffic efficiently.