1. sqlalchemy CRUD 예제 실습

2. callcenter 프로젝트 제작중

project/CALLCENTER_APP/.idea/.gitignore

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+# 디폴트 무시된 파일
+/shelf/
+/workspace.xml
+# 에디터 기반 HTTP 클라이언트 요청
+/httpRequests/
+# 쿼리 파일을 포함한 무시된 디폴트 폴더
+/queries/
+# Datasource local storage ignored files
+/dataSources/
+/dataSources.local.xml

project/CALLCENTER_APP/.idea/CALLCENTER_APP.iml

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+<?xml version="1.0" encoding="UTF-8"?>
+<module type="PYTHON_MODULE" version="4">
+  <component name="NewModuleRootManager">
+    <content url="file://$MODULE_DIR$">
+      <sourceFolder url="file://$MODULE_DIR$" isTestSource="false" />
+      <excludeFolder url="file://$MODULE_DIR$/.venv" />
+    </content>
+    <orderEntry type="jdk" jdkName="~/Source/project/CALLCENTER_APP/.venv" jdkType="Python SDK" />
+    <orderEntry type="sourceFolder" forTests="false" />
+  </component>
+  <component name="PackageRequirementsSettings" />
+  <component name="PyDocumentationSettings" />
+  <component name="ReSTService" />
+  <component name="TestRunnerService" />
+</module>

project/CALLCENTER_APP/.idea/dataSources.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="DataSourceManagerImpl" format="xml" multifile-model="true">
+    <data-source source="LOCAL" name="callcenter" uuid="91805924-e27b-4e0d-8c54-ca806a60bde7">
+      <driver-ref>sqlite.xerial</driver-ref>
+      <synchronize>true</synchronize>
+      <jdbc-driver>org.sqlite.JDBC</jdbc-driver>
+      <jdbc-url>jdbc:sqlite:$PROJECT_DIR$/db/callcenter.db</jdbc-url>
+      <working-dir>$ProjectFileDir$</working-dir>
+    </data-source>
+  </component>
+</project>

project/CALLCENTER_APP/.idea/inspectionProfiles/profiles_settings.xml

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+<component name="InspectionProjectProfileManager">
+  <settings>
+    <option name="USE_PROJECT_PROFILE" value="false" />
+    <version value="1.0" />
+  </settings>
+</component>

project/CALLCENTER_APP/.idea/modules.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ProjectModuleManager">
+    <modules>
+      <module fileurl="file://$PROJECT_DIR$/.idea/CALLCENTER_APP.iml" filepath="$PROJECT_DIR$/.idea/CALLCENTER_APP.iml" />
+    </modules>
+  </component>
+</project>

project/CALLCENTER_APP/.idea/pyLspTools.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="PyToolsState">
+    <option name="tools">
+      <map>
+        <entry key="black">
+          <value>
+            <ToolEntry />
+          </value>
+        </entry>
+        <entry key="pyrefly">
+          <value>
+            <ToolEntry />
+          </value>
+        </entry>
+        <entry key="pyright">
+          <value>
+            <ToolEntry />
+          </value>
+        </entry>
+        <entry key="ruff">
+          <value>
+            <ToolEntry />
+          </value>
+        </entry>
+        <entry key="ty">
+          <value>
+            <ToolEntry />
+          </value>
+        </entry>
+      </map>
+    </option>
+  </component>
+</project>

project/CALLCENTER_APP/.idea/vcs.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="VcsDirectoryMappings">
+    <mapping directory="$PROJECT_DIR$/../.." vcs="Git" />
+  </component>
+</project>

project/CALLCENTER_APP/backend/ai/embedding.py

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+from langchain_ibm import WatsonxEmbeddings
+from backend.config.settings import settings
+
+watson_embedding = WatsonxEmbeddings(
+    model_id="ibm/granite-embedding-278m-multilingual",
+    url=f"{settings.watsonx_url}",
+    api_key=f"{settings.watsonx_api_key}",
+    project_id=f"{settings.watsonx_project_id}",
+)

project/CALLCENTER_APP/backend/ai/llm.py

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+from langchain_ibm import ChatWatsonx
+from backend.config.settings import settings
+from langchain_openai import ChatOpenAI
+
+watson_llm = ChatWatsonx(
+    model_id="ibm/granite-4-h-small",
+    url=f"{settings.watsonx_url}",
+    api_key=f"{settings.watsonx_api_key}",
+    project_id=f"{settings.watsonx_project_id}",
+    max_tokens=2000,
+)
+
+hugging_llm = ChatOpenAI(
+    base_url="https://router.huggingface.co/v1",
+    api_key=f"{settings.hf_token}",
+    model_name="Qwen/Qwen3-8B:nscale",
+)

project/CALLCENTER_APP/backend/config/settings.py

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+from pydantic import Field
+from pydantic_settings import BaseSettings, SettingsConfigDict
+
+class Settings(BaseSettings):
+    model_config = SettingsConfigDict(env_file="backend/.env", extra="ignore")
+    # 사용할 모델
+    watsonx_api_key: str = Field(alias="WATSONX_API_KEY")
+    watsonx_project_id: str = Field(alias="WATSONX_PROJECT_ID")
+    watsonx_url: str = Field(alias="WATSONX_URL")
+    hf_token: str = Field(alias="HF_TOKEN")
+
+settings = Settings()

project/CALLCENTER_APP/backend/main.py

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+from fastapi import FastAPI
+from starlette.staticfiles import StaticFiles
+from contextlib import asynccontextmanager
+
+from backend.repository.db_init import Base, SessionLocal, engine
+from backend.routers.call_router import router as call_router
+from backend.repository.seed import seed_customers
+
+@asynccontextmanager
+async def lifespan(app: FastAPI):
+    print("서버 시작")
+
+    # Base 에 등록된 모든 모델에 테이블 자동 생성
+    Base.metadata.create_all(bind=engine)
+    print("[DB] 테이블 생성 완료 (또는 이미 존재)")
+
+    db = SessionLocal()
+    try:
+        # 기본 user 데이터 삽입
+        seed_customers(db)
+    finally:
+        db.close()
+
+    yield
+    print("서버 종료")
+
+# app = FastAPI()
+app = FastAPI(title="상담 LLM", version="1.0", lifespan=lifespan)
+
+# static 폴더 지정
+app.mount("/static", StaticFiles(directory="backend/static"), name="static")
+
+# 라우터 등록
+app.include_router(call_router)

project/CALLCENTER_APP/backend/prompts/all_prompt.py

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+# 요약 프롬프트 생성
+SUMMARY_SYSTEM_PROMPT = """
+당신은 콜센터 상담 기록 분석 전문가입니다.
+
+다음 항목을 추출하세요.
+
+1. summary
+    - 상담 내용을 한 문장으로 요약
+
+2. keywords
+    - 상담 내용에서 중요한 키워드 3~5개 추출
+
+3. category
+    - 상담 유형
+    - 예: 장애신고, 기술지원, 요금문의, 해지문의, 서비스변경
+    
+4. sentiment
+    - 상담 내용의 감정 분석 결과 = 예: 긍정(positive), 부정(negative), 중립(neutral) 중 하나
+
+5. action_items:
+    - 상담 후 필요한 후속 조치
+
+6. customer_issue
+    - 고객이 겪은 문제
+
+7. resolution
+    - 상담사가 제공한 해결 방법
+"""

project/CALLCENTER_APP/backend/repository/db_init.py

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+from sqlalchemy import create_engine
+from sqlalchemy.orm import DeclarativeBase, sessionmaker
+from pathlib import Path
+
+Path("db").mkdir(parents=True, exist_ok=True)
+
+# echo sql 구문 출력시키는
+engine = create_engine('sqlite:///db/callcenter.db', echo=True)
+
+# 세션 팩토리 생성
+SessionLocal = sessionmaker(bind=engine, autoflush=False, autocommit=False)
+
+# Base = declarative_Base()
+class Base(DeclarativeBase):
+    pass
+
+# session 을 다른 모듈에서 사용할 수 있도록 제공
+def get_db():
+    db = SessionLocal()
+    try:
+        yield db
+    finally:
+        db.close()

project/CALLCENTER_APP/backend/repository/models.py

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+from backend.repository.db_init import Base
+from sqlalchemy.orm import Mapped, mapped_column
+from sqlalchemy import DateTime, func, String, ForeignKey
+from datetime import datetime
+
+class Customer(Base):
+    __tablename__ = 'customers'
+
+    customer_id:Mapped[int] = mapped_column(primary_key=True, autoincrement=True)
+    name:Mapped[str] = mapped_column(String(50), nullable=False)
+    phone:Mapped[str] = mapped_column(String(20), nullable=False)
+
+    def __str__(self):
+        return f"<Customer id={self.customer_id} name={self.name} phone = {self.phone}]"
+
+
+# 상담기록 저장
+class CallHistory(Base):
+    __tablename__ = 'call_history'
+
+    call_id:Mapped[int] = mapped_column(primary_key=True, autoincrement=True)
+    customer_id:Mapped[int] = mapped_column(ForeignKey('customers.customer_id'), nullable=False)
+    transcript:Mapped[str]
+    summary:Mapped[str]
+    category:Mapped[str] = mapped_column(String(50))
+    sentiment:Mapped[str] = mapped_column(String(20))
+    customer_issue:Mapped[str]
+    resolution:Mapped[str]
+    # created_at:Mapped[datetime] = mapped_column(server_default=func.now(), nullable=False)
+    created_at:Mapped[datetime] = mapped_column(default=datetime.now, nullable=False)

project/CALLCENTER_APP/backend/repository/seed.py

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+# 강제로 회원가입
+from sqlalchemy.orm import Session
+from backend.repository.db_init import SessionLocal
+from backend.repository.models import Customer
+
+db = SessionLocal()
+
+DEFAULT_CUSTOMERS = [
+    Customer(name="홍길동", phone="010-1234-5678"),
+    Customer(name="최철수", phone="010-4321-8765"),
+    Customer(name="박영희", phone="010-5678-1234"),
+]
+
+def seed_customers(db: Session):
+    """
+    customer 테이블에 기본(연습용) 회원 데이터 삽입
+    (중복 실행 방지 : 이미 데이터가 있으면 건너뜀)
+    """
+
+    existing = db.query(Customer).first()
+    if existing:
+        print("[Seed] customer 테이블에 이미 데이터가 있습니다.")
+        return
+
+    db.add_all(DEFAULT_CUSTOMERS)
+    db.commit()
+    db.close()
+    print(f"[Seed] 기본 회원 {len(DEFAULT_CUSTOMERS)}명 생성 완료")

project/CALLCENTER_APP/backend/routers/call_router.py

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+from fastapi import APIRouter, Depends
+from backend.schemas.summary_schema import SummaryRequest, CallSummary, CallRequest
+from backend.services.call_service import summary_call, create_call_history
+from sqlalchemy.orm import Session
+from backend.repository.db_init import get_db
+
+
+router = APIRouter(prefix="/api/calls", tags=["Summary"])
+
+# 요약 라우터
+@router.post("", response_model=CallSummary)
+def generate_summary(req:SummaryRequest):
+    return summary_call(req.transcript)
+
+@router.post("/save", response_model=CallSummary)
+# @router.post("/save", response_model=CallRequest)
+def create_call(req: CallRequest, db:Session = Depends(get_db)):
+    return create_call_history(req, db)

project/CALLCENTER_APP/backend/schemas/summary_schema.py

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+from pydantic import BaseModel
+
+class SummaryRequest(BaseModel):
+    transcript: str
+
+class CallSummary(BaseModel):
+    summary: str
+    keywords: list[str]
+    category: str
+    sentiment: str
+    action_items: list[str]
+    customer_issue: str
+    resolution: str
+
+# 상담 요청 시 사용할 타입
+class CallRequest(BaseModel):
+    customer_id: int
+    transcript: str
+
+# 상담 요약 저장 시 사용할 타입
+class CallCreate(BaseModel):
+    customer_id: int
+    transcript: str
+    summary: str
+    category: str
+    sentiment: str
+    customer_issue: str
+    resolution: str

project/CALLCENTER_APP/backend/scripts/build_vector_db.py

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+from langchain_community.vectorstores import Chroma
+from backend.ai.embedding import watson_embedding
+from langchain_core.documents import Document
+from langchain_text_splitters import RecursiveCharacterTextSplitter
+from pathlib import Path
+
+def main():
+    # data 폴더 안의 파일을 읽은 후
+    data_dir = Path("data")
+
+    documents = []
+
+    # Document 객체 생성
+    for file_path in data_dir.glob("*.txt"):
+        content = file_path.read_text(encoding="utf-8")
+        documents.append(Document(page_content=content, metadata={"source": str(file_path.name)}))
+
+    # 분할
+    splitter = RecursiveCharacterTextSplitter(chunk_size=300, chunk_overlap=30)
+    splite_docs = splitter.split_documents(documents)
+
+    # 인덱스 설정(벡터 db) ./vectordb
+    Chroma.from_documents(documents = splite_docs, embedding=watson_embedding, persist_directory="./vectordb")
+
+if __name__ == "__main__":
+    main()

project/CALLCENTER_APP/backend/services/call_service.py

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+from backend.ai.llm import hugging_llm
+from langchain_core.prompts import ChatPromptTemplate
+from backend.prompts.all_prompt import SUMMARY_SYSTEM_PROMPT
+from backend.repository.models import CallHistory
+from backend.schemas.summary_schema import CallSummary, CallCreate
+from sqlalchemy.orm import Session
+
+from backend.schemas.summary_schema import CallRequest
+
+# LLM transcript 요약 시키기
+def summary_call(transcript: str):
+
+    summary_prompt = ChatPromptTemplate.from_messages(
+        [
+            ("system", SUMMARY_SYSTEM_PROMPT),
+            ("human", "상담내용\n{transcript}"),
+        ]
+    )
+
+    structured_llm = hugging_llm.with_structured_output(CallSummary)
+    summary_chain = summary_prompt | structured_llm
+
+    result = summary_chain.invoke({"transcript" : transcript})
+    return result
+
+def save_call_history(db, data):
+    """상담 저장"""
+    history = CallHistory(
+        customer_id = data.customer_id,
+        transcript = data.transcript,
+        summary = data.summary,
+        category = data.category,
+        sentiment = data.sentiment,
+        customer_issue = data.customer_issue,
+        resolution = data.resolution
+    )
+
+    db.add(history)
+    db.commit()
+    db.refresh(history)
+
+    return history
+
+def evaluate_call():
+    """상담  평가"""
+
+    pass
+
+def save_call_evaluation():
+    """상담 평가 내용 저장"""
+
+    pass
+
+def create_call_history(req: CallRequest, db:Session):
+    # 요약
+    # CallSummary
+    summary = summary_call(req.transcript)
+    print("summary",summary)
+    # 데이터베이스 저장용 객체
+    call_data = CallCreate(
+        customer_id = req.customer_id,
+        transcript = req.transcript,
+        summary = summary.summary,
+        category = summary.category,
+        sentiment = summary.sentiment,
+        customer_issue = summary.customer_issue,
+        resolution = summary.resolution
+    )
+
+    return save_call_history(db = db, data = call_data)
+
+

project/CALLCENTER_APP/data/faq.txt

@@ -0,0 +1,15 @@
+Q. 비밀번호를 재설정하려면?
+
+A. 고객 포털의 비밀번호 찾기 메뉴를 이용하세요.
+
+Q. 서비스 장애가 발생하면?
+
+A. 홈페이지 또는 앱에서 장애 공지를 확인하세요.
+
+Q. 요금제를 변경하려면?
+
+A. 고객 포털 > 내 요금제 메뉴에서 변경 가능합니다.
+
+Q. 데이터 사용량은 어디서 확인하나요?
+
+A. 고객 포털 > 데이터 사용량 메뉴에서 확인 가능합니다.

project/CALLCENTER_APP/data/transcript.txt

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+상담사: 안녕하세요. 고객센터입니다. 무엇을 도와드릴까요?\n고객: 몇 시간 전부터 인터넷 속도가 너무 느려서 답답합니다.\n상담사: 고객 확인을 위해 성함을 알려주시겠습니까?\n고객: 네, 홍길동입니다.\n상담사: 감사합니다. 본인 확인을 위해 PIN 번호도 알려주시겠습니까?\n고객: 지금은 PIN 번호를 가지고 있지 않습니다.\n상담사: 괜찮습니다. 우선 제가 회선 상태를 확인하고 조정해보겠습니다. 잠시만 기다려 주세요.\n(잠시 후)\n상담사: 회선 설정을 일부 조정했습니다. 현재 인터넷 속도를 다시 확인해보시겠습니까?\n고객: 잠시만요... 네, 훨씬 빨라졌네요.\n상담사: 다행입니다. 상담 종료 후 설문조사가 발송될 예정입니다. 설문은 인터넷 서비스 품질이 아니라 상담 서비스에 대한 평가입니다.\n고객: 네, 알겠습니다.\n상담사: 이용해 주셔서 감사합니다. 좋은 하루 보내세요.\n고객: 감사합니다.
+
+----
+
+상담사: 안녕하세요. 인터넷 서비스 고객센터입니다. 성함과 PIN 번호를 알려주시겠습니까?\n고객: 홍길동이고 PIN은 1234입니다.\n상담사: 감사합니다. 어떤 문제로 연락주셨나요?\n고객: 어제부터 인터넷 속도가 너무 느립니다.\n상담사: 불편을 드려 죄송합니다. 연결 상태를 확인해보겠습니다.\n(확인 중)\n상담사: 현재 고객님 지역의 회선 장애가 의심됩니다. 관련 부서에 장애 내용을 접수하겠습니다.\n고객: 네, 빨리 해결되면 좋겠네요.\n상담사: 최대한 신속히 처리하겠습니다. 신고해 주셔서 감사합니다.

project/CALLCENTER_APP/data/transcript1.txt

@@ -0,0 +1,27 @@
+상담사: 안녕하세요. 고객센터입니다. 무엇을 도와드릴까요?
+
+고객: 몇 시간 전부터 인터넷 속도가 너무 느려서 답답합니다.
+
+상담사: 고객 확인을 위해 성함을 알려주시겠습니까?
+
+고객: 네, 홍길동입니다.
+
+상담사: 감사합니다. 본인 확인을 위해 PIN 번호도 알려주시겠습니까?
+
+고객: 지금은 PIN 번호를 가지고 있지 않습니다.
+
+상담사: 괜찮습니다. 우선 제가 회선 상태를 확인하고 조정해보겠습니다. 잠시만 기다려 주세요.
+
+(잠시 후)
+
+상담사: 회선 설정을 일부 조정했습니다. 현재 인터넷 속도를 다시 확인해보시겠습니까?
+
+고객: 잠시만요... 네, 훨씬 빨라졌네요.
+
+상담사: 다행입니다. 상담 종료 후 설문조사가 발송될 예정입니다. 설문은 인터넷 서비스 품질이 아니라 상담 서비스에 대한 평가입니다.
+
+고객: 네, 알겠습니다.
+
+상담사: 이용해 주셔서 감사합니다. 좋은 하루 보내세요.
+
+고객: 감사합니다.

project/CALLCENTER_APP/data/transcript2.txt

@@ -0,0 +1,17 @@
+상담사: 안녕하세요. 인터넷 서비스 고객센터입니다. 성함과 PIN 번호를 알려주시겠습니까?
+
+고객: 홍길동이고 PIN은 1234입니다.
+
+상담사: 감사합니다. 어떤 문제로 연락주셨나요?
+
+고객: 어제부터 인터넷 속도가 너무 느립니다.
+
+상담사: 불편을 드려 죄송합니다. 연결 상태를 확인해보겠습니다.
+
+(확인 중)
+
+상담사: 현재 고객님 지역의 회선 장애가 의심됩니다. 관련 부서에 장애 내용을 접수하겠습니다.
+
+고객: 네, 빨리 해결되면 좋겠네요.
+
+상담사: 최대한 신속히 처리하겠습니다. 신고해 주셔서 감사합니다.

project/CALLCENTER_APP/data/transcript3.txt

@@ -0,0 +1,29 @@
+상담사: 안녕하세요. 무엇을 도와드릴까요?
+
+고객: 어제부터 인터넷이 계속 끊어집니다.
+
+상담사: 공유기를 재부팅해 보셨나요?
+
+고객: 네. 이미 해봤는데 똑같습니다.
+
+상담사: 현재 공유기 상태 표시등은 어떻게 되어 있나요?
+
+고객: 전원등은 켜져 있고 인터넷 표시등은 깜빡입니다.
+
+상담사: 공유기 케이블 연결 상태를 확인해 주시겠습니까?
+
+고객: 네. 확인했는데 이상 없습니다.
+
+상담사: 그렇다면 공유기 초기화를 진행해보겠습니다. 초기화 방법을 알고 계신가요?
+
+고객: 아니요.
+
+상담사: 공유기 뒷면의 리셋 버튼을 10~15초 정도 눌러주세요.
+
+고객: 네. 지금 재시작 중입니다.
+
+(몇 분 후)
+
+고객: 이제 정상적으로 작동하는 것 같습니다.
+
+상담사: 다행입니다. 다른 문제가 있으시면 언제든 연락 주세요.

project/CALLCENTER_APP/data/transcript4.txt

@@ -0,0 +1,21 @@
+상담사: 안녕하세요. 고객센터입니다. 성함과 PIN 번호를 확인하겠습니다.
+
+고객: 홍길동이며 PIN은 1234입니다.
+
+상담사: 감사합니다. 어떤 문제가 있으신가요?
+
+고객: 인터넷이 느리고 가끔 끊깁니다.
+
+상담사: 불편을 드려 죄송합니다. 연결 상태를 확인하겠습니다.
+
+(잠시 후)
+
+상담사: 회선에 일시적인 문제가 있었으며 현재 초기화 처리를 완료했습니다. 다시 확인해보시겠습니까?
+
+고객: 네. 정상적으로 작동합니다.
+
+상담사: 다행입니다. 상담 후 설문조사가 발송될 예정이며 상담 서비스에 대한 평가입니다.
+
+고객: 알겠습니다.
+
+상담사: 감사합니다. 좋은 하루 보내세요.

project/CREDIT_APP/.idea/dataSources.xml

@@ -15,5 +15,12 @@
       <jdbc-url>jdbc:sqlite:$PROJECT_DIR$/db/users.db</jdbc-url>
       <working-dir>$ProjectFileDir$</working-dir>
     </data-source>
+    <data-source source="LOCAL" name="demo" uuid="fab7f51e-43ea-4d26-b7f0-6be132dd06fb">
+      <driver-ref>sqlite.xerial</driver-ref>
+      <synchronize>true</synchronize>
+      <jdbc-driver>org.sqlite.JDBC</jdbc-driver>
+      <jdbc-url>jdbc:sqlite:$PROJECT_DIR$/db/demo.db</jdbc-url>
+      <working-dir>$ProjectFileDir$</working-dir>
+    </data-source>
   </component>
 </project>

project/CREDIT_APP/.idea/db-forest-config.xml

@@ -5,6 +5,7 @@
 	----------------------------------------
 	1:0:d34d9830-06d9-4e92-bd10-84567e5a4809
 	2:0:2d5d9d87-b30f-47d4-9d9d-61542cb64ea0
+	3:0:fab7f51e-43ea-4d26-b7f0-6be132dd06fb
 		.</data>
   </component>
 </project>

project/CREDIT_APP/sql.ipynb

@@ -17,29 +17,19 @@
    "metadata": {
     "collapsed": true,
     "ExecuteTime": {
-     "end_time": "2026-06-16T08:48:53.375278031Z",
+     "end_time": "2026-06-17T03:03:17.531519156Z",
-     "start_time": "2026-06-16T08:48:51.509377417Z"
+     "start_time": "2026-06-17T03:03:17.519312421Z"
     }
    },
-   "source": "!pip install sqlalchemy",
+   "source": "# !pip install sqlalchemy",
-   "outputs": [
+   "outputs": [],
-    {
+   "execution_count": 36
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Requirement already satisfied: sqlalchemy in ./.venv/lib/python3.12/site-packages (2.0.51)\n",
-      "Requirement already satisfied: greenlet>=1 in ./.venv/lib/python3.12/site-packages (from sqlalchemy) (3.5.1)\n",
-      "Requirement already satisfied: typing-extensions>=4.6.0 in ./.venv/lib/python3.12/site-packages (from sqlalchemy) (4.15.0)\n"
-     ]
-    }
-   ],
-   "execution_count": 1
   },
   {
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2026-06-16T08:57:27.860045705Z",
+     "end_time": "2026-06-17T03:03:17.555640871Z",
-     "start_time": "2026-06-16T08:57:27.561065535Z"
+     "start_time": "2026-06-17T03:03:17.532414273Z"
     }
    },
    "cell_type": "code",
@@ -49,13 +39,19 @@
     "from sqlalchemy import Column, Integer, String, create_engine\n",
     "from sqlalchemy.orm import declarative_base, sessionmaker\n",
     "\n",
+    "# 1.x 버전 코드\n",
     "# 데이터베이스 연결\n",
-    "engine = create_engine('sqlite:///db/users.db')\n",
+    "# 애플리케이션 당 하나만 만들어 사용\n",
+    "# echo=True : 실행 SQL 을 콘솔에 추력\n",
+    "engine = create_engine('sqlite:///db/users.db', echo=True)\n",
     "# engine = create_engine('sqlite:///users.db')\n",
     "\n",
     "# 모든 모델 크래스의 부모 클래스가 될 Base 객체 생성\n",
     "Base = declarative_base()\n",
+    "\n",
+    "# 데이터베이스랑 관련있는 클래스 : 모델 클래스\n",
     "class User(Base):\n",
+    "    # 테이블 이름 지정\n",
     "    __tablename__ = 'users'\n",
     "\n",
     "    id = Column(Integer, primary_key=True)\n",
@@ -65,20 +61,749 @@
     "    def __str__(self):\n",
     "        return f\"<User(name='{self.name}', email='{self.email}')>\"\n",
     "\n",
-    "# 테이블 생성\n",
+    "# 테이블 생성 ( 없는 경우만 새로 생성됨 )\n",
     "Base.metadata.create_all(engine)"
    ],
    "id": "7a41f863de1efd48",
-   "outputs": [],
+   "outputs": [
-   "execution_count": 2
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2026-06-17 12:03:17,542 INFO sqlalchemy.engine.Engine BEGIN (implicit)\n",
+      "2026-06-17 12:03:17,543 INFO sqlalchemy.engine.Engine PRAGMA main.table_info(\"users\")\n",
+      "2026-06-17 12:03:17,545 INFO sqlalchemy.engine.Engine [raw sql] ()\n",
+      "2026-06-17 12:03:17,548 INFO sqlalchemy.engine.Engine COMMIT\n"
+     ]
+    }
+   ],
+   "execution_count": 37
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2026-06-17T03:03:17.576534965Z",
+     "start_time": "2026-06-17T03:03:17.557316858Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "# 모든 테이블 삭제\n",
+    "Base.metadata.drop_all(engine)"
+   ],
+   "id": "28ae00aa8564cd68",
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2026-06-17 12:03:17,561 INFO sqlalchemy.engine.Engine BEGIN (implicit)\n",
+      "2026-06-17 12:03:17,563 INFO sqlalchemy.engine.Engine PRAGMA main.table_info(\"users\")\n",
+      "2026-06-17 12:03:17,563 INFO sqlalchemy.engine.Engine [raw sql] ()\n",
+      "2026-06-17 12:03:17,565 INFO sqlalchemy.engine.Engine \n",
+      "DROP TABLE users\n",
+      "2026-06-17 12:03:17,566 INFO sqlalchemy.engine.Engine [no key 0.00051s] ()\n",
+      "2026-06-17 12:03:17,571 INFO sqlalchemy.engine.Engine COMMIT\n"
+     ]
+    }
+   ],
+   "execution_count": 38
   },
   {
    "metadata": {},
+   "cell_type": "markdown",
+   "source": "#### text() : 원시 SQL 실행",
+   "id": "d4b2b34ebf185234"
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2026-06-17T03:03:17.599302675Z",
+     "start_time": "2026-06-17T03:03:17.577699609Z"
+    }
+   },
    "cell_type": "code",
+   "source": [
+    "from sqlalchemy import text\n",
+    "\n",
+    "engine = create_engine('sqlite:///db/demo.db', echo=True)\n",
+    "with engine.connect() as conn:\n",
+    "    conn.execute(text(\"\"\"\n",
+    "    CREATE TABLE IF NOT EXISTS users (\n",
+    "    id INTEGER PRIMARY KEY AUTOINCREMENT,\n",
+    "    name TEXT NOT NULL,\n",
+    "    age INTEGER\n",
+    "    )\n",
+    "    \"\"\"\n",
+    "    ))\n",
+    "\n",
+    "    conn.commit()\n",
+    "    # 삽입\n",
+    "    conn.execute(text(\"\"\"\n",
+    "    INSERT INTO users (name, age) VALUES (:name, :age)\"\"\"),\n",
+    "    [{\"name\" : \"Alice\", \"age\" : 23}, {\"name\":\"Bob\", \"age\" : 24}])\n",
+    "\n",
+    "    conn.commit()\n",
+    "\n",
+    "    # 조회\n",
+    "    result = conn.execute(text(\"\"\"\n",
+    "    SELECT * FROM users\n",
+    "    \"\"\"))\n",
+    "\n",
+    "    for row in result:\n",
+    "        print(row.id, row.name, row.age)"
+   ],
+   "id": "de1ebcd8f162fd42",
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2026-06-17 12:03:17,581 INFO sqlalchemy.engine.Engine BEGIN (implicit)\n",
+      "2026-06-17 12:03:17,581 INFO sqlalchemy.engine.Engine \n",
+      "    CREATE TABLE IF NOT EXISTS users (\n",
+      "    id INTEGER PRIMARY KEY AUTOINCREMENT,\n",
+      "    name TEXT NOT NULL,\n",
+      "    age INTEGER\n",
+      "    )\n",
+      "    \n",
+      "2026-06-17 12:03:17,582 INFO sqlalchemy.engine.Engine [generated in 0.00126s] ()\n",
+      "2026-06-17 12:03:17,583 INFO sqlalchemy.engine.Engine COMMIT\n",
+      "2026-06-17 12:03:17,584 INFO sqlalchemy.engine.Engine BEGIN (implicit)\n",
+      "2026-06-17 12:03:17,585 INFO sqlalchemy.engine.Engine \n",
+      "    INSERT INTO users (name, age) VALUES (?, ?)\n",
+      "2026-06-17 12:03:17,585 INFO sqlalchemy.engine.Engine [generated in 0.00116s] [('Alice', 23), ('Bob', 24)]\n",
+      "2026-06-17 12:03:17,586 INFO sqlalchemy.engine.Engine COMMIT\n",
+      "2026-06-17 12:03:17,591 INFO sqlalchemy.engine.Engine BEGIN (implicit)\n",
+      "2026-06-17 12:03:17,593 INFO sqlalchemy.engine.Engine \n",
+      "    SELECT * FROM users\n",
+      "    \n",
+      "2026-06-17 12:03:17,593 INFO sqlalchemy.engine.Engine [generated in 0.00211s] ()\n",
+      "1 Alice 23\n",
+      "2 Bob 24\n",
+      "3 Alice 23\n",
+      "4 Bob 24\n",
+      "5 Alice 23\n",
+      "6 Bob 24\n",
+      "2026-06-17 12:03:17,595 INFO sqlalchemy.engine.Engine ROLLBACK\n"
+     ]
+    }
+   ],
+   "execution_count": 39
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2026-06-17T03:03:17.624396207Z",
+     "start_time": "2026-06-17T03:03:17.600052176Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "# 2.x 버전 코드\n",
+    "from sqlalchemy.orm import DeclarativeBase, Mapped, mapped_column\n",
+    "from sqlalchemy import DateTime, func\n",
+    "from datetime import datetime\n",
+    "\n",
+    "\n",
+    "engine = create_engine('sqlite:///db/users.db', echo=True)\n",
+    "# engine = create_engine('sqlite:///users.db')\n",
+    "\n",
+    "# 모든 모델 크래스의 부모 클래스가 될 Base 객체 생성\n",
+    "class Base(DeclarativeBase):\n",
+    "    pass\n",
+    "\n",
+    "# 데이터베이스랑 관련있는 클래스 : 모델 클래스\n",
+    "class User(Base):\n",
+    "    # 테이블 이름 지정\n",
+    "    __tablename__ = 'users'\n",
+    "\n",
+    "    # 컬럽 타입 지정 : 티입힌트(파이썬 데이터 타입) 사용\n",
+    "    id:Mapped[int] = mapped_column(primary_key=True, autoincrement=True)\n",
+    "    name:Mapped[str]\n",
+    "    email:Mapped[str] = mapped_column(unique=True)\n",
+    "    age:Mapped[int]\n",
+    "    created_at:Mapped[datetime] = mapped_column(DateTime, server_default=func.now())\n",
+    "\n",
+    "    def __str__(self):\n",
+    "        return f\"<User(name='{self.name}', email='{self.email}')>\"\n",
+    "\n",
+    "# 테이블 생성 ( 없는 경우만 새로 생성됨 )\n",
+    "# create_all() : IF NOT EXISTS\n",
+    "Base.metadata.create_all(engine)"
+   ],
+   "id": "d7eb9178f27499a7",
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2026-06-17 12:03:17,606 INFO sqlalchemy.engine.Engine BEGIN (implicit)\n",
+      "2026-06-17 12:03:17,607 INFO sqlalchemy.engine.Engine PRAGMA main.table_info(\"users\")\n",
+      "2026-06-17 12:03:17,609 INFO sqlalchemy.engine.Engine [raw sql] ()\n",
+      "2026-06-17 12:03:17,610 INFO sqlalchemy.engine.Engine PRAGMA temp.table_info(\"users\")\n",
+      "2026-06-17 12:03:17,610 INFO sqlalchemy.engine.Engine [raw sql] ()\n",
+      "2026-06-17 12:03:17,612 INFO sqlalchemy.engine.Engine \n",
+      "CREATE TABLE users (\n",
+      "\tid INTEGER NOT NULL, \n",
+      "\tname VARCHAR NOT NULL, \n",
+      "\temail VARCHAR NOT NULL, \n",
+      "\tage INTEGER NOT NULL, \n",
+      "\tcreated_at DATETIME DEFAULT CURRENT_TIMESTAMP NOT NULL, \n",
+      "\tPRIMARY KEY (id), \n",
+      "\tUNIQUE (email)\n",
+      ")\n",
+      "\n",
+      "\n",
+      "2026-06-17 12:03:17,613 INFO sqlalchemy.engine.Engine [no key 0.00171s] ()\n",
+      "2026-06-17 12:03:17,618 INFO sqlalchemy.engine.Engine COMMIT\n"
+     ]
+    }
+   ],
+   "execution_count": 40
+  },
+  {
+   "metadata": {},
+   "cell_type": "markdown",
+   "source": [
+    "#### 세션\n",
+    "- 데이터베이스 연동\n",
+    "- 변경사항 추적하고 트랜잭션 관리\n",
+    "- sessionmaker 팩토리 사용"
+   ],
+   "id": "de5e7ee1adb4cee6"
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2026-06-17T03:03:17.633680827Z",
+     "start_time": "2026-06-17T03:03:17.625430327Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "# 세션 팩토리 생성\n",
+    "Session = sessionmaker(bind=engine, autoflush=False, autocommit=False)\n",
+    "# 세션 객체 생성\n",
+    "session = Session()"
+   ],
+   "id": "140093069c78dd21",
    "outputs": [],
-   "execution_count": null,
+   "execution_count": 41
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2026-06-17T03:03:17.647449353Z",
+     "start_time": "2026-06-17T03:03:17.637405010Z"
+    }
+   },
+   "cell_type": "code",
+   "source": "session.close()",
+   "id": "c9f8fdb361307ea",
+   "outputs": [],
+   "execution_count": 42
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2026-06-17T03:03:17.667693242Z",
+     "start_time": "2026-06-17T03:03:17.648384205Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "# insert\n",
+    "# session.add() / session.add_all() / session.commit()\n",
+    "\n",
+    "session = Session()\n",
+    "# 사용자 생성\n",
+    "new_User = User(name=\"Alice\", email=\"alice@example.com\", age=23)\n",
+    "session.add(new_User)\n",
+    "session.commit()\n",
+    "session.close()"
+   ],
+   "id": "8c0f8f2c60597d73",
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2026-06-17 12:03:17,651 INFO sqlalchemy.engine.Engine BEGIN (implicit)\n",
+      "2026-06-17 12:03:17,654 INFO sqlalchemy.engine.Engine INSERT INTO users (name, email, age) VALUES (?, ?, ?) RETURNING id, created_at\n",
+      "2026-06-17 12:03:17,655 INFO sqlalchemy.engine.Engine [generated in 0.00099s] ('Alice', 'alice@example.com', 23)\n",
+      "2026-06-17 12:03:17,658 INFO sqlalchemy.engine.Engine COMMIT\n"
+     ]
+    }
+   ],
+   "execution_count": 43
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2026-06-17T03:03:17.691852173Z",
+     "start_time": "2026-06-17T03:03:17.669654096Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "with Session() as session:\n",
+    "    session.add_all(\n",
+    "        [\n",
+    "            User(name=\"Bob\", email=\"bob@example.com\", age=25),\n",
+    "            User(name=\"Charlie\", email=\"charlie@example.com\", age=30),\n",
+    "        ]\n",
+    "    )\n",
+    "    session.commit()"
+   ],
+   "id": "2c91d42f265ded17",
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2026-06-17 12:03:17,672 INFO sqlalchemy.engine.Engine BEGIN (implicit)\n",
+      "2026-06-17 12:03:17,674 INFO sqlalchemy.engine.Engine INSERT INTO users (name, email, age) VALUES (?, ?, ?) RETURNING id, created_at\n",
+      "2026-06-17 12:03:17,675 INFO sqlalchemy.engine.Engine [generated in 0.00009s (insertmanyvalues) 1/2 (ordered; batch not supported)] ('Bob', 'bob@example.com', 25)\n",
+      "2026-06-17 12:03:17,676 INFO sqlalchemy.engine.Engine INSERT INTO users (name, email, age) VALUES (?, ?, ?) RETURNING id, created_at\n",
+      "2026-06-17 12:03:17,676 INFO sqlalchemy.engine.Engine [insertmanyvalues 2/2 (ordered; batch not supported)] ('Charlie', 'charlie@example.com', 30)\n",
+      "2026-06-17 12:03:17,678 INFO sqlalchemy.engine.Engine COMMIT\n"
+     ]
+    }
+   ],
+   "execution_count": 44
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2026-06-17T03:03:17.733033419Z",
+     "start_time": "2026-06-17T03:03:17.693025923Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "from sqlalchemy import select\n",
+    "\n",
+    "with Session() as session:\n",
+    "    # id 를 사용해 조회\n",
+    "    user = session.get(User, 1)\n",
+    "    print(\"--- 단일 사용자 ---\")\n",
+    "    print(user)\n",
+    "\n",
+    "    print(\"--- 모든 사용자 ---\")\n",
+    "    all_users = session.query(User).all()\n",
+    "    for user in all_users:\n",
+    "        print(user)\n",
+    "\n",
+    "    stmt = select(User)\n",
+    "    all_users = session.scalars(stmt)\n",
+    "    for user in all_users:\n",
+    "        print(user)\n",
+    "\n",
+    "    print(\"--- where ---\")\n",
+    "    alice = session.query(User).filter_by(name = \"Alice\").first()\n",
+    "    print(f\"찾은 사용자 {alice}\")\n",
+    "\n",
+    "    stmt = select(User).where(User.age >= 30)\n",
+    "    find_users = session.scalars(stmt).all()\n",
+    "    for user in find_users:\n",
+    "        print(user)\n",
+    "\n",
+    "    stmt = select(User).where(User.email.like('%ali%'))\n",
+    "    find_users = session.scalars(stmt).all()\n",
+    "    for user in find_users:\n",
+    "        print(user)\n",
+    "\n",
+    "    stmt = select(User).order_by(User.id.desc()).limit(2)\n",
+    "    find_users = session.scalars(stmt).all()\n",
+    "    for user in find_users:\n",
+    "        print(user)\n",
+    "\n",
+    "    # 집계 함수\n",
+    "    count = session.scalar(select(func.count()).select_from(User))\n",
+    "    print(count)"
+   ],
+   "id": "b0ce2cc0ee9d68ed",
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2026-06-17 12:03:17,698 INFO sqlalchemy.engine.Engine BEGIN (implicit)\n",
+      "2026-06-17 12:03:17,704 INFO sqlalchemy.engine.Engine SELECT users.id AS users_id, users.name AS users_name, users.email AS users_email, users.age AS users_age, users.created_at AS users_created_at \n",
+      "FROM users \n",
+      "WHERE users.id = ?\n",
+      "2026-06-17 12:03:17,704 INFO sqlalchemy.engine.Engine [generated in 0.00082s] (1,)\n",
+      "--- 단일 사용자 ---\n",
+      "<User(name='Alice', email='alice@example.com')>\n",
+      "--- 모든 사용자 ---\n",
+      "2026-06-17 12:03:17,706 INFO sqlalchemy.engine.Engine SELECT users.id AS users_id, users.name AS users_name, users.email AS users_email, users.age AS users_age, users.created_at AS users_created_at \n",
+      "FROM users\n",
+      "2026-06-17 12:03:17,707 INFO sqlalchemy.engine.Engine [generated in 0.00096s] ()\n",
+      "<User(name='Alice', email='alice@example.com')>\n",
+      "<User(name='Bob', email='bob@example.com')>\n",
+      "<User(name='Charlie', email='charlie@example.com')>\n",
+      "2026-06-17 12:03:17,710 INFO sqlalchemy.engine.Engine SELECT users.id, users.name, users.email, users.age, users.created_at \n",
+      "FROM users\n",
+      "2026-06-17 12:03:17,711 INFO sqlalchemy.engine.Engine [generated in 0.00100s] ()\n",
+      "<User(name='Alice', email='alice@example.com')>\n",
+      "<User(name='Bob', email='bob@example.com')>\n",
+      "<User(name='Charlie', email='charlie@example.com')>\n",
+      "--- where ---\n",
+      "2026-06-17 12:03:17,713 INFO sqlalchemy.engine.Engine SELECT users.id AS users_id, users.name AS users_name, users.email AS users_email, users.age AS users_age, users.created_at AS users_created_at \n",
+      "FROM users \n",
+      "WHERE users.name = ?\n",
+      " LIMIT ? OFFSET ?\n",
+      "2026-06-17 12:03:17,714 INFO sqlalchemy.engine.Engine [generated in 0.00058s] ('Alice', 1, 0)\n",
+      "찾은 사용자 <User(name='Alice', email='alice@example.com')>\n",
+      "2026-06-17 12:03:17,718 INFO sqlalchemy.engine.Engine SELECT users.id, users.name, users.email, users.age, users.created_at \n",
+      "FROM users \n",
+      "WHERE users.age >= ?\n",
+      "2026-06-17 12:03:17,719 INFO sqlalchemy.engine.Engine [generated in 0.00090s] (30,)\n",
+      "<User(name='Charlie', email='charlie@example.com')>\n",
+      "2026-06-17 12:03:17,720 INFO sqlalchemy.engine.Engine SELECT users.id, users.name, users.email, users.age, users.created_at \n",
+      "FROM users \n",
+      "WHERE users.email LIKE ?\n",
+      "2026-06-17 12:03:17,721 INFO sqlalchemy.engine.Engine [generated in 0.00080s] ('%ali%',)\n",
+      "<User(name='Alice', email='alice@example.com')>\n",
+      "2026-06-17 12:03:17,723 INFO sqlalchemy.engine.Engine SELECT users.id, users.name, users.email, users.age, users.created_at \n",
+      "FROM users ORDER BY users.id DESC\n",
+      " LIMIT ? OFFSET ?\n",
+      "2026-06-17 12:03:17,724 INFO sqlalchemy.engine.Engine [generated in 0.00092s] (2, 0)\n",
+      "<User(name='Charlie', email='charlie@example.com')>\n",
+      "<User(name='Bob', email='bob@example.com')>\n",
+      "2026-06-17 12:03:17,727 INFO sqlalchemy.engine.Engine SELECT count(*) AS count_1 \n",
+      "FROM users\n",
+      "2026-06-17 12:03:17,728 INFO sqlalchemy.engine.Engine [generated in 0.00053s] ()\n",
+      "3\n",
+      "2026-06-17 12:03:17,728 INFO sqlalchemy.engine.Engine ROLLBACK\n"
+     ]
+    }
+   ],
+   "execution_count": 45
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2026-06-17T03:03:17.756463366Z",
+     "start_time": "2026-06-17T03:03:17.734005295Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "with Session() as session:\n",
+    "    alice = session.query(User).filter_by(name = \"Alice\").first()\n",
+    "    alice.email = \"alice.new@example.com\"\n",
+    "    session.commit()\n",
+    "\n",
+    "    print(f\"수정된 사용자 {session.query(User).filter_by(name='Alice').first()}\")"
+   ],
+   "id": "93f58b5307abd93f",
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2026-06-17 12:03:17,737 INFO sqlalchemy.engine.Engine BEGIN (implicit)\n",
+      "2026-06-17 12:03:17,739 INFO sqlalchemy.engine.Engine SELECT users.id AS users_id, users.name AS users_name, users.email AS users_email, users.age AS users_age, users.created_at AS users_created_at \n",
+      "FROM users \n",
+      "WHERE users.name = ?\n",
+      " LIMIT ? OFFSET ?\n",
+      "2026-06-17 12:03:17,740 INFO sqlalchemy.engine.Engine [cached since 0.02646s ago] ('Alice', 1, 0)\n",
+      "2026-06-17 12:03:17,741 INFO sqlalchemy.engine.Engine UPDATE users SET email=? WHERE users.id = ?\n",
+      "2026-06-17 12:03:17,742 INFO sqlalchemy.engine.Engine [generated in 0.00075s] ('alice.new@example.com', 1)\n",
+      "2026-06-17 12:03:17,743 INFO sqlalchemy.engine.Engine COMMIT\n",
+      "2026-06-17 12:03:17,747 INFO sqlalchemy.engine.Engine BEGIN (implicit)\n",
+      "2026-06-17 12:03:17,749 INFO sqlalchemy.engine.Engine SELECT users.id AS users_id, users.name AS users_name, users.email AS users_email, users.age AS users_age, users.created_at AS users_created_at \n",
+      "FROM users \n",
+      "WHERE users.name = ?\n",
+      " LIMIT ? OFFSET ?\n",
+      "2026-06-17 12:03:17,749 INFO sqlalchemy.engine.Engine [cached since 0.03613s ago] ('Alice', 1, 0)\n",
+      "수정된 사용자 <User(name='Alice', email='alice.new@example.com')>\n",
+      "2026-06-17 12:03:17,751 INFO sqlalchemy.engine.Engine ROLLBACK\n"
+     ]
+    }
+   ],
+   "execution_count": 46
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2026-06-17T03:03:17.785689642Z",
+     "start_time": "2026-06-17T03:03:17.757935816Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "from sqlalchemy import update\n",
+    "\n",
+    "with Session() as session:\n",
+    "    user = session.get(User, 1)\n",
+    "    if user:\n",
+    "        user.age = 40\n",
+    "        session.commit()\n",
+    "\n",
+    "    # 일괄 업데이트\n",
+    "    stmt = update(User).where(User.age <= 30).values(age=20)\n",
+    "    session.execute(stmt)\n",
+    "    session.commit()"
+   ],
+   "id": "1f333d8d8bcfbf54",
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2026-06-17 12:03:17,761 INFO sqlalchemy.engine.Engine BEGIN (implicit)\n",
+      "2026-06-17 12:03:17,762 INFO sqlalchemy.engine.Engine SELECT users.id AS users_id, users.name AS users_name, users.email AS users_email, users.age AS users_age, users.created_at AS users_created_at \n",
+      "FROM users \n",
+      "WHERE users.id = ?\n",
+      "2026-06-17 12:03:17,763 INFO sqlalchemy.engine.Engine [cached since 0.0592s ago] (1,)\n",
+      "2026-06-17 12:03:17,764 INFO sqlalchemy.engine.Engine UPDATE users SET age=? WHERE users.id = ?\n",
+      "2026-06-17 12:03:17,766 INFO sqlalchemy.engine.Engine [generated in 0.00217s] (40, 1)\n",
+      "2026-06-17 12:03:17,769 INFO sqlalchemy.engine.Engine COMMIT\n",
+      "2026-06-17 12:03:17,773 INFO sqlalchemy.engine.Engine BEGIN (implicit)\n",
+      "2026-06-17 12:03:17,775 INFO sqlalchemy.engine.Engine UPDATE users SET age=? WHERE users.age <= ?\n",
+      "2026-06-17 12:03:17,776 INFO sqlalchemy.engine.Engine [generated in 0.00108s] (20, 30)\n",
+      "2026-06-17 12:03:17,777 INFO sqlalchemy.engine.Engine COMMIT\n"
+     ]
+    }
+   ],
+   "execution_count": 47
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2026-06-17T03:03:17.805168757Z",
+     "start_time": "2026-06-17T03:03:17.787206837Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "with Session() as session:\n",
+    "    bob = session.query(User).filter_by(name=\"Bob\").first()\n",
+    "    session.delete(bob)\n",
+    "    session.commit()\n"
+   ],
+   "id": "f6c6f87020eb7927",
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2026-06-17 12:03:17,790 INFO sqlalchemy.engine.Engine BEGIN (implicit)\n",
+      "2026-06-17 12:03:17,791 INFO sqlalchemy.engine.Engine SELECT users.id AS users_id, users.name AS users_name, users.email AS users_email, users.age AS users_age, users.created_at AS users_created_at \n",
+      "FROM users \n",
+      "WHERE users.name = ?\n",
+      " LIMIT ? OFFSET ?\n",
+      "2026-06-17 12:03:17,793 INFO sqlalchemy.engine.Engine [cached since 0.07924s ago] ('Bob', 1, 0)\n",
+      "2026-06-17 12:03:17,794 INFO sqlalchemy.engine.Engine DELETE FROM users WHERE users.id = ?\n",
+      "2026-06-17 12:03:17,795 INFO sqlalchemy.engine.Engine [generated in 0.00093s] (2,)\n",
+      "2026-06-17 12:03:17,797 INFO sqlalchemy.engine.Engine COMMIT\n"
+     ]
+    }
+   ],
+   "execution_count": 48
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2026-06-17T03:03:17.824210114Z",
+     "start_time": "2026-06-17T03:03:17.807206458Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "from sqlalchemy import delete\n",
+    "\n",
+    "# delete from 테이블명 where id = 1\n",
+    "with Session() as session:\n",
+    "    stmt = delete(User).where(User.id == 1)\n",
+    "    session.execute(stmt)\n",
+    "    session.commit()"
+   ],
+   "id": "b35c028d86f48e31",
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2026-06-17 12:03:17,810 INFO sqlalchemy.engine.Engine BEGIN (implicit)\n",
+      "2026-06-17 12:03:17,811 INFO sqlalchemy.engine.Engine DELETE FROM users WHERE users.id = ?\n",
+      "2026-06-17 12:03:17,812 INFO sqlalchemy.engine.Engine [generated in 0.00074s] (1,)\n",
+      "2026-06-17 12:03:17,813 INFO sqlalchemy.engine.Engine COMMIT\n"
+     ]
+    }
+   ],
+   "execution_count": 49
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2026-06-17T03:03:17.834127797Z",
+     "start_time": "2026-06-17T03:03:17.824909859Z"
+    }
+   },
+   "cell_type": "code",
+   "source": "Base.metadata.clear()",
+   "id": "9da5d9421e56853f",
+   "outputs": [],
+   "execution_count": 50
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2026-06-17T03:03:17.863676311Z",
+     "start_time": "2026-06-17T03:03:17.834932678Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "from sqlalchemy.orm import relationship\n",
+    "from sqlalchemy import ForeignKey\n",
+    "\n",
+    "# 관계(외래키)\n",
+    "# 1:N, N:1, M:N\n",
+    "# 게시글 하나 : 댓글 여러개\n",
+    "\n",
+    "class Post(Base):\n",
+    "    __tablename__ = 'posts'\n",
+    "\n",
+    "    id : Mapped[int] = mapped_column(primary_key=True, autoincrement=True)\n",
+    "    title:Mapped[str] = mapped_column(String(200))\n",
+    "    content:Mapped[str]\n",
+    "    # 역참조\n",
+    "    comments: Mapped[list['Comment']] = relationship('Comment', back_populates='post', cascade='all, delete-orphan')\n",
+    "\n",
+    "# FOREIGN KEY (post_id) REFERENCES posts(id);\n",
+    "class Comment(Base):\n",
+    "    __tablename__ = 'comments'\n",
+    "\n",
+    "    id : Mapped[int] = mapped_column(primary_key=True, autoincrement=True)\n",
+    "    content:Mapped[str]\n",
+    "    # 어느 게시글의 댓글인가?\n",
+    "    post_id:Mapped[int] = mapped_column(ForeignKey(\"posts.id\"))\n",
+    "    # 역참조\n",
+    "    post:Mapped['Post'] = relationship('Post', back_populates='comments')\n"
+   ],
+   "id": "cc7b55c5bf90b92b",
+   "outputs": [],
+   "execution_count": 51
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2026-06-17T03:03:17.884050919Z",
+     "start_time": "2026-06-17T03:03:17.864744917Z"
+    }
+   },
+   "cell_type": "code",
+   "source": "Base.metadata.create_all(engine)",
+   "id": "50e66cc696cfdd21",
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2026-06-17 12:03:17,868 INFO sqlalchemy.engine.Engine BEGIN (implicit)\n",
+      "2026-06-17 12:03:17,872 INFO sqlalchemy.engine.Engine PRAGMA main.table_info(\"posts\")\n",
+      "2026-06-17 12:03:17,873 INFO sqlalchemy.engine.Engine [raw sql] ()\n",
+      "2026-06-17 12:03:17,873 INFO sqlalchemy.engine.Engine PRAGMA main.table_info(\"comments\")\n",
+      "2026-06-17 12:03:17,874 INFO sqlalchemy.engine.Engine [raw sql] ()\n",
+      "2026-06-17 12:03:17,876 INFO sqlalchemy.engine.Engine COMMIT\n"
+     ]
+    }
+   ],
+   "execution_count": 52
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2026-06-17T03:03:17.932695111Z",
+     "start_time": "2026-06-17T03:03:17.885317745Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "with Session() as session:\n",
+    "    post = Post(title=\"LLM 입문\", content=\"LLM이란 무엇인가?\")\n",
+    "    post.comments = [\n",
+    "        Comment(content=\"LLM은 언어 모델의 일종입니다.\"),\n",
+    "        Comment(content=\"좋아요\"),\n",
+    "\n",
+    "    ]\n",
+    "\n",
+    "    session.add(post)\n",
+    "    session.commit()\n",
+    "\n",
+    "    # 역참조 이용\n",
+    "    p = session.get(Post, 1)\n",
+    "    for c in p.comments:\n",
+    "        print(c.content)"
+   ],
+   "id": "7400ebdad0575a44",
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2026-06-17 12:03:17,897 INFO sqlalchemy.engine.Engine BEGIN (implicit)\n",
+      "2026-06-17 12:03:17,902 INFO sqlalchemy.engine.Engine INSERT INTO posts (title, content) VALUES (?, ?)\n",
+      "2026-06-17 12:03:17,903 INFO sqlalchemy.engine.Engine [generated in 0.00105s] ('LLM 입문', 'LLM이란 무엇인가?')\n",
+      "2026-06-17 12:03:17,904 INFO sqlalchemy.engine.Engine INSERT INTO comments (content, post_id) VALUES (?, ?) RETURNING id\n",
+      "2026-06-17 12:03:17,906 INFO sqlalchemy.engine.Engine [generated in 0.00008s (insertmanyvalues) 1/2 (ordered; batch not supported)] ('LLM은 언어 모델의 일종입니다.', 2)\n",
+      "2026-06-17 12:03:17,906 INFO sqlalchemy.engine.Engine INSERT INTO comments (content, post_id) VALUES (?, ?) RETURNING id\n",
+      "2026-06-17 12:03:17,907 INFO sqlalchemy.engine.Engine [insertmanyvalues 2/2 (ordered; batch not supported)] ('좋아요', 2)\n",
+      "2026-06-17 12:03:17,908 INFO sqlalchemy.engine.Engine COMMIT\n",
+      "2026-06-17 12:03:17,918 INFO sqlalchemy.engine.Engine BEGIN (implicit)\n",
+      "2026-06-17 12:03:17,920 INFO sqlalchemy.engine.Engine SELECT posts.id AS posts_id, posts.title AS posts_title, posts.content AS posts_content \n",
+      "FROM posts \n",
+      "WHERE posts.id = ?\n",
+      "2026-06-17 12:03:17,920 INFO sqlalchemy.engine.Engine [generated in 0.00071s] (1,)\n",
+      "2026-06-17 12:03:17,923 INFO sqlalchemy.engine.Engine SELECT comments.id AS comments_id, comments.content AS comments_content, comments.post_id AS comments_post_id \n",
+      "FROM comments \n",
+      "WHERE ? = comments.post_id\n",
+      "2026-06-17 12:03:17,924 INFO sqlalchemy.engine.Engine [generated in 0.00067s] (1,)\n",
+      "LLM은 언어 모델의 일종입니다.\n",
+      "좋아요\n",
+      "2026-06-17 12:03:17,925 INFO sqlalchemy.engine.Engine ROLLBACK\n"
+     ]
+    }
+   ],
+   "execution_count": 53
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2026-06-17T03:03:17.950832461Z",
+     "start_time": "2026-06-17T03:03:17.933917669Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "# 💡 이 셀을 실행해야 'Session'이라는 이름이 메모리에 등록됩니다!\n",
+    "from sqlalchemy import create_engine\n",
+    "from sqlalchemy.orm import sessionmaker\n",
+    "\n",
+    "engine = create_engine(\"sqlite:///users.db\") # 본인의 engine 설정 코드\n",
+    "Session = sessionmaker(bind=engine)"
+   ],
+   "id": "7d17932707f7f879",
+   "outputs": [],
+   "execution_count": 54
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2026-06-17T03:03:17.968159853Z",
+     "start_time": "2026-06-17T03:03:17.952470603Z"
+    }
+   },
+   "cell_type": "code",
    "source": "",
-   "id": "de1ebcd8f162fd42"
+   "id": "48795cdb32be042b",
+   "outputs": [],
+   "execution_count": 54
   }
  ],
  "metadata": {