A Variable Monitoring Logger with C-Engine
Project description
vmlog
Python 프로그램 실행 중 변수의 값 변화를 자동으로 감지하고 기록하는 모니터링 라이브러리
1. Overview
대규모 시스템이나 복잡한 알고리즘을 디버깅할 때 변수의 상태 변화를 확인하는 것은 필수적입니다. 그러나 일반적인 디버깅 방식은 다음과 같은 한계를 가집니다:
- 코드 오염: 임시로 작성한 출력문(
print)이 비즈니스 로직과 섞여 가독성을 해치고, 제거 누락 시 프로덕션 환경에 악영향을 줍니다. - 실행 흐름 방해: 대화형 디버거(PDB, IDE 디버거)는 루프나 고빈도 함수 내에서 실행을 멈추기 때문에 전체적인 시스템의 런타임 흐름을 유기적으로 관찰하기 어렵습니다.
vmlog는 이러한 문제를 해결하기 위해 런타임 오버헤드를 최소화한 백그라운드 실시간 변수 추적 아키텍처를 제공합니다. 사용자는 소스 코드 오염 없이 변수의 변경 여부를 자동으로 감지하고, 프로그램이 종료되는 시점에 수집된 모든 이력을 안전하게 디스크에 저장할 수 있습니다.
2. Features
- 무결성 및 투명성 (Zero-Invasive): 최초 등록 이후 별도의 로그 매크로나 로깅 함수를 반복 호출할 필요가 없습니다. Python 고유의 실행 문법과 흐름을 100% 유지하며 백그라운드에서 추적합니다.
- C Extension 기반 고성능 엔진: 파이썬 레벨에서 매 라인마다 거대한 객체를 비교하는 비효율을 극복하기 위해, 가변/불변 객체 판별 및 메모리 참조·크기 비교 연산을 C 확장 모듈(
vmlog_engine)로 처리하여 런타임 오버헤드를 극소화했습니다. - 지연 쓰기 기반 I/O 최적화: 변수가 바뀔 때마다 디스크에 접근하는 대신, 스레드-세이프한 메모리 버퍼(
HistoryBuffer)에 로그를 적재한 후 최종 시점에 일괄 파일로 출력하여 디스크 I/O 병목을 방지합니다. - 안전한 프로세스 생명주기 연동: 프로그램이 정상 종료되거나 예기치 못한 예외로 중단되더라도, 내부
atexit런타임 훅이 자동으로 트리거되어 유실 없이 파일 생성을 보장합니다. - 지능적 스코프 해석 (Scope Resolution): 실행 프레임 분석기를 통해 동일한 이름의 로컬 변수와 글로벌 변수가 충돌하거나, 로컬 변수가 글로벌 변수를 가리는(Shadowing) 현상을 정확히 해석합니다.
3. Installation
vmlog는 고성능 변수 비교를 위해 C 확장 모듈 컴파일이 필요합니다. 아래 명령어를 통해 환경에 맞게 설치할 수 있습니다.
개발자 모드 설치 (추천)
소스 코드를 수정하거나 테스트 슈트를 직접 구동하려는 경우, C 확장 모듈 빌드를 포함하여 편집 가능한 모드로 설치합니다:
pip install -e .
일반 패키지 설치
빌드 후 현재 환경에 고정 설치하려는 경우
pip install .
C 확장 모듈 직접 빌드
python setup.py build_ext --inplace
요구 사항
- Python 3.11 이상
- C 컴파일러 (GCC, Clang, MSVC 등)
4. Usage
기본 사용법 (단일 변수 추적)
vmlog.logger 함수에 추적하고자 하는 변수의 이름을 문자열로 전달합니다.
import vmlog
# 1. 추적 대상 변수 생성
target_list = [100, 200]
# 2. 감시 장치 등록 (이 시점에 'init' 이벤트가 기록됩니다)
vmlog.logger("target_list")
# 3. 변수 조작 (인플레이스 변경 및 재할당 모두 자동 감지)
target_list.append(300)
# 4. 변수 삭제 감지
del target_list
# 추가적인 라인이 실행되거나 프로그램이 종료될 때 상기 변경점들이 자동으로 기록됩니다.
고급 사용법
vmlog.VMlog 클래스를 인스턴스화하여 여러 개의 로컬/글로벌 변수를 동시에 모니터링하고 저장 파일명을 직접 지정할 수 있습니다.
import vmlog
# 커스텀 로그 파일명을 지정하여 모니터 인스턴스 생성
monitor = vmlog.VMlog(fileName="analytics_dump.jsonl")
user_score = 10
active_items = ["potion", "shield"]
# 복수의 변수를 하나의 모니터에 등록
monitor.logger("user_score")
monitor.logger("active_items")
# 값 업데이트 진행
user_score += 55
active_items.append("sword")
vmlog.logger("변수명") 또는 VMlog 인스턴스의 .logger() 메서드로 등록된 변수는 별도 조작 없이 생명주기 동안 자동으로 추적됩니다.
기존 Python 문법과 런타임 실행 흐름을 100% 유지합니다.
5. 로그 형식
로그는 JSON Lines(.jsonl) 형식으로 저장됩니다.
하나의 JSON 객체는 하나의 변수 변경 이력을 의미합니다.
{"name": "target", "data": [1, 2, 3], "event": "init", "domain": "LOCAL", "line": 3}
{"name": "target", "data": [1, 2, 3, 4], "event": "updated", "domain": "LOCAL", "line": 5}
{"name": "target", "data": "String Assignment", "event": "updated", "domain": "LOCAL", "line": 6}
{"name": "target", "data": null, "event": "deleted", "domain": "LOCAL", "line": 7}
| 필드 | 타입 | 설명 |
|---|---|---|
name |
string | 추적 중인 변수명 |
data |
any | null | 변경 시점의 변수 값 (deleted 이벤트는 null) |
event |
string | init / updated / deleted |
domain |
string | 변수 스코프: LOCAL / GLOBAL |
line |
int | null | 변경이 감지된 소스 코드 라인 번호 |
이 형식은 대용량 로그 처리와 스트리밍 파싱에 적합합니다.
6. Architecture
Python tracer를 통해 실행 흐름을 관찰하고, 변수 변경 여부 판단은 C 엔진에 위임하여 성능을 유지합니다.
sequenceDiagram
autonumber
participant U as User Code (사용자)
participant V as vmlog (Python 라이브러리)
participant S as Python Subsystem (sys.settrace)
participant C as C Engine (vmlog_engine.c)
participant B as History Buffer (메모리 버퍼)
participant F as JSONL File (디스크 저장)
Note over U, S: [1. 초기화 및 감시 장치 등록]
U->>V: vmlog.logger("변수명") 호출
V->>V: ScopeResolver를 통해 최초 스코프(LOCAL/GLOBAL) 및 주소 분석
V->>B: 최초 상태 적재 {event: "init", data: 현재값}
V->>S: sys.settrace(TraceDispatcher) 글로벌 등록
V->>S: atexit.register(_finalSave) 프로세스 훅 등록
V-->>U: 감시 준비 완료 및 실행 재개
Note over U, C: [2. 라인 실행 및 실시간 변수 변경 검사]
loop 사용자 코드 실행 단계
U->>U: 코드 순차 실행 (예: 객체 변형, 재할당 등)
S->>V: 다음 행 실행 신호 전달 (f_trace 인터셉트)
V->>C: check_variable(프레임, 이전참조, 이전스냅샷, 스코프, 변수명) 호출
alt C 엔진 검사 결과: 주소 변경 혹은 내부 값 변경 (Return True)
C-->>V: 변수 변경 확인 신호 리턴
V->>B: {event: "updated", data: 신규값, line: f_lineno} 적재
V->>V: VariableTracker 내부 스냅샷 및 참조 주소 갱신
else C 엔진 검사 결과: 변경 없음 (Return False)
C-->>V: 상태 유지 신호 리턴 (아무 작업 안 함 - 성능 보존)
else C 엔진 검사 결과: 변수 scope 내 부재 (Return None)
C-->>V: 변수 소멸 신호 리턴
V->>B: {event: "deleted", data: null, line: f_lineno} 적재
V->>V: 해당 변수 트래커 비활성화
end
end
Note over U, F: [3. 프로세스 종료 및 자동 플러시]
U->>S: 스크립트 실행 완료 혹은 인터럽트 발생 (종료)
S->>V: atexit 트리거 발동
V->>V: sys.settrace(None) 추적 해제 및 무한루프 방지
V->>F: FileWriter를 호출하여 Buffer 내의 수집 이력을 JSONL로 일괄 생성
7. File Structure
.
├── .gitignore
├── LICENSE # MIT LICENSE
├── README.md
├── pyproject.toml
├── setup.py
├── tests/
│ ├── test.py # 테스트 러너 (unittest discover)
│ ├── test_logger.py # 공개 API(vml.logger) 통합 테스트
│ ├── test_vml_behavior.py # 변수 추적 동작 시나리오 테스트
│ ├── test_vml_components.py # 내부 컴포넌트 단위 테스트
│ ├── test_vml_edge_cases.py # 엣지 케이스 및 경계 조건 테스트
│ ├── test_vml_engine.py # C Extension 엔진 단위 테스트
│ └── test_vml_process_lifecycle.py # atexit 기반 프로세스 생명주기 테스트
└── src/
└── vmlog/ # VML Package
├── __init__.py # 공개 API 노출 (VML, logger, vml_engine)
├── vmlog.py # VML 메인 클래스 및 logger() 진입점
├── FileWriter.py # JSONL 파일 I/O
├── HistoryBuffer.py # 메모리 버퍼 관리 (domain, line 포함)
├── ScopeResolver.py # 변수 스코프(LOCAL/GLOBAL) 탐색
├── TraceDispatcher.py # 시스템 Trace 이벤트 라우팅 및 추적 관리
├── VariableTracker.py # 개별 변수 상태 추적 및 스냅샷 관리
└── vmlog_engine.c # C Extension 변수 비교 엔진
8. Test
python tests/test.py
unittest discover 기반으로 tests/ 디렉토리의 모든 test_*.py 파일을 자동으로 수집하여 실행합니다.
test_final_save_is_idempotent (test_vml_components.TestVMLComponents) ... ok
test_file_writer_writes_json_lines (test_vml_components.TestVMLComponents) ... ok
test_history_buffer_clear (test_vml_components.TestVMLComponents) ... ok
test_history_buffer_returns_deepcopy (test_vml_components.TestVMLComponents) ... ok
test_scope_resolver_finds_global_variable (test_vml_components.TestVMLComponents) ... ok
test_scope_resolver_finds_local_variable_first (test_vml_components.TestVMLComponents) ... ok
test_scope_resolver_returns_not_found (test_vml_components.TestVMLComponents) ... ok
test_vml_records_deleted_event (test_vml_components.TestVMLComponents) ... ok
test_dispatcher_stop_prevents_further_tracking (test_vml_edge_cases.TestVMLEdgeCases) ... ok
test_local_variable_has_priority_over_global_name_collision (test_vml_edge_cases.TestVMLEdgeCases) ... ok
test_no_duplicate_update_when_value_does_not_change (test_vml_edge_cases.TestVMLEdgeCases) ... ok
test_tracks_common_scalar_and_tuple_reassignments (test_vml_edge_cases.TestVMLEdgeCases) ... ok
test_tracks_nested_mutable_object_change (test_vml_edge_cases.TestVMLEdgeCases) ... ok
test_unicode_data_is_written_without_corruption (test_vml_edge_cases.TestVMLEdgeCases) ... ok
test_returns_false_when_value_does_not_change (test_vml_engine.TestVMLEngine) ... ok
test_returns_none_when_variable_does_not_exist (test_vml_engine.TestVMLEngine) ... ok
test_returns_true_when_mutable_data_changes (test_vml_engine.TestVMLEngine) ... ok
test_returns_true_when_reference_changes (test_vml_engine.TestVMLEngine) ... ok
test_atexit_saves_log_without_manual_final_save (test_vml_process_lifecycle.TestVMLProcessLifecycle) ... ok
test_atexit_saves_multiple_variables_from_single_monitor (test_vml_process_lifecycle.TestVMLProcessLifecycle) ... ok
test_process_log_uses_jsonl_schema_after_exit (test_vml_process_lifecycle.TestVMLProcessLifecycle) ... ok
test_return_event_captures_last_change_inside_function (test_vml_process_lifecycle.TestVMLProcessLifecycle) ... ok
...
----------------------------------------------------------------------
Ran N tests in X.XXXs
OK
License
MIT © sdkurjnk
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