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spakky-logging

Spakky Framework를 위한 구조화 로깅 시스템입니다. Context-local log binding, formatter 설정, AOP 기반 메서드 호출 로깅, PostProcessor 기반 자동 설정을 제공합니다.

설치

pip install spakky-logging

빠른 시작

1. 플러그인 자동 등록

spakky-loggingload_plugins()를 통해 자동으로 로드됩니다.

app = SpakkyApplication(ApplicationContext()).load_plugins().scan(my_app).start()

2. @logged로 메서드 표시

from spakky.plugins.logging import logged

class UserService:
    @logged()
    async def create_user(self, name: str, password: str) -> User:
        ...

3. 설정(선택)

LoggingConfig로 기본값을 override합니다.

LoggingConfig@Configuration Pod로 로드되며, pydantic-settings를 통해 SPAKKY_LOGGING__* 환경변수를 읽습니다.

export SPAKKY_LOGGING__LEVEL=10
export SPAKKY_LOGGING__FORMAT=json
export SPAKKY_LOGGING__MASK_KEYS='["password", "token", "secret"]'
export SPAKKY_LOGGING__SLOW_THRESHOLD_MS=500

4. LogContext 전파

모든 log record에 자동 포함될 contextual key-value pair를 바인딩합니다.

from spakky.plugins.logging import LogContext

LogContext.bind(request_id="req-123", user_id="u-456")

with LogContext.scope(trace_id="t-789"):
    # 이 block 안의 모든 log는 trace_id를 포함
    ...

주요 기능

기능 설명
@logged() annotation AOP 기반 method call/result/error 자동 logging
LogContext contextvars 기반 structured context 전파
ContextInjectingFilter 모든 LogRecord에 LogContext value 주입
SpakkyTextFormatter pipe로 구분된 text format
SpakkyJsonFormatter line당 JSON object 하나
SpakkyPrettyFormatter 개발용 ANSI color multi-column format
LoggingConfig 중앙 logging configuration용 @Configuration pod
LoggingSetupPostProcessor application start 시 root logger 자동 설정
민감 데이터 masking log output에서 password, token, secret 등을 masking
느린 호출 감지 method 실행 시간이 threshold를 넘으면 warning 출력
결과 truncation 긴 return value를 log output에서 잘라냄

개발 검증

패키지 단위 검증은 해당 패키지 디렉토리에서 실행합니다.

uv run ruff format .
uv run ruff check .
uv run pyrefly check
uv run pytest

pytest는 각 패키지 pyproject.toml의 coverage 설정을 사용합니다.

라이선스

MIT License

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