좋아요. 아래는 앞서 이야기한 has-a (조합형) 구조를 기반으로 한 완성된 설계 코드예요.
Behavior 계층과 Storage 조립, 그리고 Memory/Pandas 백엔드 두 가지 예시를 모두 포함합니다.

---

🧩 구조 개요

storage/
 ├── behaviors/
 │    ├── base.py          # 추상 Protocol 정의
 │    ├── memory_impl.py   # in-memory 구현
 │    └── pandas_impl.py   # pandas 기반 구현
 ├── storage.py            # Storage 조합 클래스
 └── factory.py            # backend 선택 팩토리

---

📘 1. behaviors/base.py

from typing import Protocol, Any, List


class SearchBehavior(Protocol):
    def search(self, query: Any) -> List[Any]: ...


class AddBehavior(Protocol):
    def add(self, item: Any) -> None: ...


class DeleteBehavior(Protocol):
    def delete(self, key: Any) -> None: ...


class UpdateBehavior(Protocol):
    def update(self, key: Any, value: Any) -> None: ...


class CountBehavior(Protocol):
    def count(self) -> int: ...

---

📗 2. behaviors/memory_impl.py

from typing import Any, List

# --- In-Memory Behavior 구현 ---
class MemorySearch:
    def __init__(self, store: list):
        self.store = store

    def search(self, predicate) -> List[Any]:
        """predicate는 lambda x: 조건 함수"""
        return [item for item in self.store if predicate(item)]


class MemoryAdd:
    def __init__(self, store: list):
        self.store = store

    def add(self, item: Any) -> None:
        self.store.append(item)


class MemoryDelete:
    def __init__(self, store: list):
        self.store = store

    def delete(self, key: Any) -> None:
        self.store[:] = [i for i in self.store if i.get("id") != key]


class MemoryUpdate:
    def __init__(self, store: list):
        self.store = store

    def update(self, key: Any, value: Any) -> None:
        for item in self.store:
            if item.get("id") == key:
                item.update(value)


class MemoryCount:
    def __init__(self, store: list):
        self.store = store

    def count(self) -> int:
        return len(self.store)

---

📙 3. behaviors/pandas_impl.py

import pandas as pd
from typing import Any, List

# --- Pandas Behavior 구현 ---
class PandasSearch:
    def __init__(self, df: pd.DataFrame):
        self.df = df

    def search(self, query: str) -> pd.DataFrame:
        """query는 pandas query 문법 문자열"""
        return self.df.query(query).copy()


class PandasAdd:
    def __init__(self, df: pd.DataFrame):
        self.df = df

    def add(self, item: dict) -> None:
        self.df.loc[len(self.df)] = item


class PandasDelete:
    def __init__(self, df: pd.DataFrame):
        self.df = df

    def delete(self, key: Any) -> None:
        self.df.drop(self.df[self.df["id"] == key].index, inplace=True)
        self.df.reset_index(drop=True, inplace=True)


class PandasUpdate:
    def __init__(self, df: pd.DataFrame):
        self.df = df

    def update(self, key: Any, value: dict) -> None:
        idx = self.df[self.df["id"] == key].index
        for k, v in value.items():
            self.df.loc[idx, k] = v


class PandasCount:
    def __init__(self, df: pd.DataFrame):
        self.df = df

    def count(self) -> int:
        return len(self.df)

---

📘 4. storage.py (조합형 Storage)

from typing import Optional
from .behaviors.base import (
    SearchBehavior, AddBehavior, DeleteBehavior, UpdateBehavior, CountBehavior
)


class Storage:
    """조합형 Storage: 개별 Behavior 객체를 소유(has-a)"""
    def __init__(
        self,
        *,
        searcher: Optional[SearchBehavior] = None,
        adder: Optional[AddBehavior] = None,
        deleter: Optional[DeleteBehavior] = None,
        updater: Optional[UpdateBehavior] = None,
        counter: Optional[CountBehavior] = None,
    ):
        self._searcher = searcher
        self._adder = adder
        self._deleter = deleter
        self._updater = updater
        self._counter = counter

    # 단순 위임 메서드들
    def search(self, query): return self._searcher.search(query)
    def add(self, item): return self._adder.add(item)
    def delete(self, key): return self._deleter.delete(key)
    def update(self, key, value): return self._updater.update(key, value)
    def count(self): return self._counter.count()

---

📕 5. factory.py (Storage 생성 팩토리)

import pandas as pd
from .storage import Storage
from .behaviors.memory_impl import (
    MemorySearch, MemoryAdd, MemoryDelete, MemoryUpdate, MemoryCount,
)
from .behaviors.pandas_impl import (
    PandasSearch, PandasAdd, PandasDelete, PandasUpdate, PandasCount,
)


class StorageFactory:
    """백엔드별 Storage 조립기"""

    @staticmethod
    def memory_backend() -> Storage:
        data_store = []
        return Storage(
            searcher=MemorySearch(data_store),
            adder=MemoryAdd(data_store),
            deleter=MemoryDelete(data_store),
            updater=MemoryUpdate(data_store),
            counter=MemoryCount(data_store),
        )

    @staticmethod
    def pandas_backend(columns=None) -> Storage:
        df = pd.DataFrame(columns=columns or ["id", "name", "age"])
        return Storage(
            searcher=PandasSearch(df),
            adder=PandasAdd(df),
            deleter=PandasDelete(df),
            updater=PandasUpdate(df),
            counter=PandasCount(df),
        )

---

🚀 6. 사용 예시

from storage.factory import StorageFactory

# --- In-memory backend ---
memory_storage = StorageFactory.memory_backend()
memory_storage.add({"id": 1, "name": "Alice", "age": 29})
memory_storage.add({"id": 2, "name": "Bob", "age": 32})

print(memory_storage.count())  # 2
print(memory_storage.search(lambda x: x["age"] > 30))
memory_storage.update(1, {"name": "Alicia"})
memory_storage.delete(2)

# --- Pandas backend ---
pandas_storage = StorageFactory.pandas_backend()
pandas_storage.add({"id": 1, "name": "Jane", "age": 24})
pandas_storage.add({"id": 2, "name": "Tom", "age": 35})
print(pandas_storage.search("age >= 30"))
print(pandas_storage.count())  # 2

---

✅ 구조적 특징 요약

항목	설명
조합형 설계	Storage가 Behavior 객체를 “소유(has-a)” 하며 모든 동작을 위임
백엔드 분리	Memory/Pandas 등 다양한 backend 교체 가능
테스트 용이성	Behavior 단위로 독립 테스트 가능
확장성	새로운 backend(예: SQLite, Redis) 추가 시 factory만 확장
유연성	필요 시 Behavior 조합을 달리해 hybrid storage 구성 가능

---

원하신다면 이 설계를 기반으로

• ✅ FilterBehavior 추가 (WHERE 절 파서)
• ✅ TransactionBehavior (commit/rollback)
• ✅ StorageAdapter (FastAPI나 CLI용 어댑터)

등의 확장 버전도 바로 이어서 설계해드릴 수 있어요.
원하시나요?