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 1 2 Deploying Your App Explained

1 2 Deploying Your App Explained

Key Concepts

Deployment

Deployment is the process of making your Streamlit app accessible to users over the internet. This involves uploading your app's code and dependencies to a hosting service and configuring the necessary settings to ensure it runs smoothly.

Hosting Services

Hosting services provide the infrastructure to host and run your Streamlit app. Popular options include Streamlit Sharing, Heroku, AWS, Google Cloud, and Azure. Each service has its own setup process and pricing model.

Example: Deploying to Streamlit Sharing

1. Create a GitHub repository for your Streamlit app.
2. Push your app code to the repository.
3. Sign up for Streamlit Sharing.
4. Connect your GitHub repository to Streamlit Sharing.
5. Deploy your app by selecting the repository and branch.
    

Environment Setup

Preparing your development environment for deployment involves ensuring that all dependencies and configurations are correctly set up. This includes creating a requirements.txt file to list all Python dependencies and setting up environment variables if needed.

Example: Creating a requirements.txt

streamlit
pandas
numpy
    

Version Control

Using tools like Git to manage and track changes in your codebase is essential for deployment. Git allows you to version your code, collaborate with others, and easily deploy updates.

Example: Initializing a Git Repository

git init
git add .
git commit -m "Initial commit"
git remote add origin https://github.com/yourusername/yourrepository.git
git push -u origin main
    

Continuous Integration/Continuous Deployment (CI/CD)

CI/CD automates the deployment process, ensuring that your app is automatically built, tested, and deployed whenever changes are pushed to your version control system. Popular CI/CD tools include GitHub Actions, GitLab CI, and Travis CI.

Example: GitHub Actions CI/CD

name: Deploy Streamlit App

on:
  push:
    branches:
      - main

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 Streamlit Sharing
      run: |
        # Add deployment commands here
    

Analogies

Think of deployment as building and launching a spaceship. Hosting services are like the launch pads, environment setup is like preparing the spaceship for launch, version control is like tracking the spaceship's design changes, and CI/CD is like automating the launch sequence. Each step ensures that the spaceship (your app) is ready for its mission (deployment).

By mastering the deployment process in Streamlit, you can make your applications accessible to users worldwide, ensuring they can benefit from your data-driven insights and interactive tools.