Workbench Deploy Tool Design

Goal

Build a Python desktop tool that helps deploy separated Spring Boot + Vue projects. The user selects one folder, then the tool detects backend, frontend, SQL files, required local environments, configurable deployment settings, and deployment command steps.

Interface

Use a workbench layout:

Left navigation for Project, Environment, Database, Deployment, Logs.
Top action bar with folder selection, scan, environment check, and deploy actions.
Main dashboard cards for backend, frontend, SQL, and environment status.
Configuration fields for backend port, frontend build directory, MySQL connection, and deployment output directory.
Log panel for command output and status messages.

Architecture

Use Python standard library only for the first version. Keep business logic outside the GUI:

deploy_tool/scanner.py detects Spring Boot, Vue, and SQL files.
deploy_tool/environment.py checks commands such as Java, Maven, Gradle, Node, npm, Vue CLI, and MySQL.
deploy_tool/deployer.py builds deployment steps and can run shell commands with streamed output.
deploy_tool/gui.py implements the tkinter/ttk workbench.
main.py starts the application.

Behavior

The scanner walks the selected folder and recognizes:

Spring Boot backend by pom.xml, build.gradle, src/main/java, and Spring Boot dependency text.
Vue frontend by package.json containing Vue dependencies or scripts plus common Vue config files.
SQL files by .sql extension.

Environment checks run non-destructive version commands and report installed/missing states.

Deployment starts with a dry, visible command plan. The first version focuses on local build/import/start orchestration and clear logs rather than remote server provisioning.

Testing

Use unittest from the standard library. Tests cover scanner detection, environment command handling with injected runners, and deployment plan generation.

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