python-response-time

A Pythonic, DevOps-friendly HTTP benchmarking tool leveraging Pydantic v2 for robust configuration, Loguru for structured logging, and a modern, testable workflow.

Features

• Configurable HTTP benchmarking via environment variables or .env file (Pydantic v2 + pydantic-settings)
• Structured logging with Loguru (console and file, colorized, with rotation)
• Pre-flight DevOps checks: auto-formatting, linting, and test coverage in one command
• Modern Python packaging: pyproject.toml-based, ready for CI/CD
• Type-safe, validated settings: all config is validated at startup
• Tested and type-checked: includes pytest-based tests for all config
• CLI entrypoints for both benchmarking and checks

Quickstart

# Install with all dev dependencies
uv pip install -e '.[build]'

# Run the HTTP benchmark
uv run python-response-time

# Run all pre-flight DevOps checks (format, lint, test)
uv run checks

Configuration

All settings are managed with Pydantic v2 and can be set via environment variables or a .env file:

Variable	Type	Default	Description
TARGET_URL	str	https://httpbin.org/get	Target endpoint for benchmarking
NUM_REQUESTS	int	10	Total number of requests
CONNECT_TIMEOUT	float	1.0	Connection timeout in seconds
READ_TIMEOUT	float	3.0	Request timeout in seconds
REQUEST_DELAY	float	0.1	Delay between requests in seconds
LOG_LEVEL	str	INFO	Log level (DEBUG, INFO, WARNING, ERROR, CRITICAL)
VERIFY_SSL	bool	True	Whether to verify SSL certificates

Example .env:

TARGET_URL=https://example.com/api
NUM_REQUESTS=100
CONNECT_TIMEOUT=2.0
READ_TIMEOUT=5.0
REQUEST_DELAY=0.5
LOG_LEVEL=DEBUG
VERIFY_SSL=False

DevOps & Pythonic Practices

• Pre-flight checks: One command (uv run checks) runs ruff, isort, black, and pytest with coverage.
• Strict config validation: Pydantic v2 ensures all settings are valid before running.
• Logging: Loguru provides both human-friendly console logs and persistent file logs with rotation and compression.
• Modern packaging: Uses pyproject.toml for dependencies, scripts, and tool config.
• CI/CD ready: Semantic release and coverage tools are pre-configured.
• Type annotations: All code is type-annotated for clarity and safety.

tests/

Architecture

Graceful Shutdown & Signal Handling

• Signal handling is modular: the signal handler function is defined at module scope and can be reused or tested independently.
• register_signals simply registers this handler for SIGINT/SIGTERM, and the handler itself is not nested or dynamically created.
• This makes the shutdown logic more testable, maintainable, and explicit.

Project Structure

src/python_response_time/
    main.py         # Benchmark runner, entry point, signal registration
    pre_flight.py   # DevOps checks
    core/
        config.py   # Pydantic v2 settings
        logging.py  # Loguru setup
        startup.py  # Signal handler and registration logic
tests/
    test_basic.py   # Pytest-based config tests

CI/CD Pipeline

• Linting, testing, and Docker image build are triggered on every push and pull request.
• The pipeline is not affected by the signal handler refactor; no changes are required for this architectural update.
• See .github/workflows/ci-cd.yaml for details.

License

MIT