Gan, Jimmy
6c0d5a4e63
- Flask-based mold cost calculation application - PostgreSQL database with SQLAlchemy ORM - Docker/Podman containerization - Comprehensive documentation in docs/ - Clean, organized codebase without obsolete files - Production-ready deployment configuration - Enhanced pytest configuration with coverage reporting - Master/Development branch structure
47 lines
1.5 KiB
Bash
Executable File
47 lines
1.5 KiB
Bash
Executable File
#!/bin/bash
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# A universal deployment script that can be run from a local machine or directly on the server.
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#
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# - When run locally, it will SSH to the server and execute the deployment.
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# - When run on the server, it will execute the deployment directly.
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set -e
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# --- Configuration ---
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REMOTE_USER="jimmyg"
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REMOTE_HOST="server1"
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REMOTE_DIR="/home/jimmyg/mold_cost_online_tool"
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SERVER_HOSTNAME="server1" # The hostname of the production server
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# --- Deployment Logic ---
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deploy_commands() {
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echo ">>> [1/4] Navigating to the application directory..."
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cd "$REMOTE_DIR"
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echo ">>> [2/4] Pulling latest changes from Git..."
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git pull
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echo ">>> [3/4] Building new container image with the latest code..."
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podman-compose build
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echo ">>> [4/4] Restarting services with the updated image..."
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podman-compose down
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podman-compose up -d
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echo ""
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echo "✅ Deployment finished successfully on $REMOTE_HOST!"
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}
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# --- Execution ---
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# Get the hostname of the machine this script is running on
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current_hostname=$(hostname)
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if [ "$current_hostname" == "$SERVER_HOSTNAME" ]; then
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echo "🚀 Running deployment script directly on the server ($current_hostname)..."
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deploy_commands
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else
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echo "🚀 Running deployment script from local machine ($current_hostname)..."
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echo "Connecting to $REMOTE_USER@$REMOTE_HOST..."
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# Using 'bash -s' allows us to execute the function on the remote server.
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# We pass the function definition and then call it.
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ssh "$REMOTE_USER@$REMOTE_HOST" "$(declare -f deploy_commands); deploy_commands"
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fi |