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 2 2 Deploying to AWS Explained

2 2 Deploying to AWS Explained

Key Concepts

AWS (Amazon Web Services)

Amazon Web Services (AWS) is a comprehensive cloud computing platform provided by Amazon. It offers a wide range of services that can be used to host and manage applications, including Streamlit apps.

EC2 (Elastic Compute Cloud)

EC2 is a web service that provides resizable compute capacity in the cloud. It allows you to launch virtual servers (instances) to run your applications. For deploying a Streamlit app, you can use an EC2 instance to host your app.

IAM (Identity and Access Management)

IAM is a service that helps you manage access to AWS services and resources securely. You can create and manage AWS users and groups, and use permissions to allow and deny their access to AWS resources.

S3 (Simple Storage Service)

S3 is a scalable object storage service. It can be used to store and retrieve any amount of data, making it useful for storing static files or backups related to your Streamlit app.

Deployment Process

The deployment process to AWS involves several steps:

  1. Create an AWS account and set up IAM roles.
  2. Launch an EC2 instance and configure it.
  3. Install necessary software and dependencies on the EC2 instance.
  4. Upload your Streamlit app code to the EC2 instance.
  5. Run your Streamlit app on the EC2 instance.
  6. Configure security groups and access settings.

Examples

Example 1: Launching an EC2 Instance

# Sign in to the AWS Management Console
# Navigate to the EC2 Dashboard
# Click "Launch Instance"
# Choose an Amazon Machine Image (AMI)
# Select an instance type
# Configure instance details
# Add storage
# Configure security group
# Review and launch the instance
    

Example 2: Installing Dependencies on EC2

# Connect to your EC2 instance using SSH
ssh -i your-key.pem ec2-user@your-instance-ip

# Update the package list
sudo yum update -y

# Install Python and pip
sudo yum install python3 -y
sudo yum install python3-pip -y

# Install Streamlit
pip3 install streamlit
    

Example 3: Running a Streamlit App on EC2

# Upload your Streamlit app code to the EC2 instance
scp -i your-key.pem your-app.py ec2-user@your-instance-ip:/home/ec2-user

# Run the Streamlit app
streamlit run your-app.py
    

Analogies

Think of AWS as a vast warehouse where you can store and manage your goods (data and applications). EC2 is like a storage unit within this warehouse where you can place your items (applications). IAM is like a security system that controls who can access your storage unit. S3 is like a shelf where you can store additional items (files) securely.

By mastering the deployment process to AWS, you can leverage the power of cloud computing to host and manage your Streamlit applications efficiently.