running-commands

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description: Details best practices specific to Python and FastAPI implementations, including recommendations for asynchronous operations, API design, code quality, and performance improvements. globs: *.py alwaysApply: false

Running Commands

Follow these guidelines when running commands in this project:

pip Commands

• all pip commands should be prefixed with uv to ensure we are properly accessing our dependencies

Environment Variables

• Always prefix commands with doppler run when access to environment variables is required
• Example: doppler run python app/main.py instead of python app/main.py
• For development, use: doppler run --config dev [command]
• For production, use: doppler run --config prod [command]

Dependency Management

• Use uv for all Python dependency management
• Use task uv:venv to create a virtual environment
• Use source .venv/bin/activate to activate the virual environment
• Use task uv:install to install dependencies from pyproject.toml
• Use task uv:sync to sync dependencies with lockfile
• Use task uv:lock to update the project's lockfile (uv.lock)
• Use task uv:update-deps to update dependencies
• Use task uv:export-reqs to export requirements.txt

Task Runner

• Prefer using the task runner for common operations instead of direct commands
• Use task --list to see all available tasks
• Use namespaced tasks for specific operations:
  • task docker:* for Docker operations
  • task doppler:* for Doppler operations
  • task uv:* for UV operations
• Common tasks:
  • task install - Install project dependencies
  • task lint - Run linters
  • task format - Run formatters
  • task test - Run tests
  • task docker:build - Build the Docker image
  • task docker:up - Start the project with docker-compose
  • task doppler:setup - Setup Doppler

Development Workflow

1. Set up Doppler: task doppler:setup
2. Install dependencies: task uv:install
3. Run the application: doppler run python app/main.py or use the appropriate task