القائمة
DI/SOA decision tree with full code examples for Python architecture decisions
يُحدَّد Prompt الذي يراجع المصدر أولًا بشكل افتراضي. يمكنك التبديل إلى أمر مباشر أو تنزيل نسخة محلية.
اقرأ SKILL.md وأي ملفات مرافقة يعرضها SkillsMP قبل أن تقرر التثبيت.
استنادا إلى تصنيف SOC المهني
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
يتجاوز الأمر المباشر Prompt المخصّص للمراجعة. افحص المصدر قبل تشغيله.
npx skills add https://github.com/bobmatnyc/claude-mpm-agents --skill python-di-soa-patternsيبقى الأمر في سطر واحد. مرّر أفقيًا لمراجعته كاملًا قبل النسخ.
تفضّل نسخة محلية؟ نزّل الملفات المتاحة حاليًا لدى SkillsMP.
عرض SKILL.md
Production-readiness process checklist covering the code-production pipeline — research, architecture, implementation, tests, critic review, and security gates
Severity-tagged code review rubric (CRITICAL/HIGH/MEDIUM/LOW) used by the code-critic agent to produce APPROVE/WARN/BLOCK verdicts with evidence-backed findings
Audit whether a test suite actually detects regressions (not just whether it runs) by introducing small code mutations and measuring how many your tests catch. Advisory and on-demand — not a blocking CI gate.
| name | python-di-soa-patterns |
| description | DI/SOA decision tree with full code examples for Python architecture decisions |
| version | 1.0.0 |
| category | toolchain |
| author | Claude MPM Team |
| license | MIT |
| progressive_disclosure | {"entry_point":{"summary":"Decision tree and code examples for choosing between DI/SOA and lightweight script patterns in Python","when_to_use":"When deciding on architecture patterns for a new Python project or module","quick_start":"Use the decision tree to determine if DI/SOA or lightweight patterns fit your use case"}} |
| context_limit | 700 |
| tags | ["python","architecture","dependency-injection","service-oriented","design-patterns","decision-tree"] |
| requires_tools | [] |
Benefits: Testability (mock dependencies), maintainability (clear separation), extensibility (swap implementations)
Benefits: Less boilerplate, faster development, easier to understand
Is this a long-lived service or multi-step process?
YES -> Use DI/SOA (testability, maintainability matter)
NO |
Does it need mock testing or swappable dependencies?
YES -> Use DI/SOA (dependency injection enables testing)
NO |
Is it a one-off script or simple automation?
YES -> Skip DI/SOA (keep it simple, minimize boilerplate)
NO |
Will it grow in complexity over time?
YES -> Use DI/SOA (invest in architecture upfront)
NO -> Skip DI/SOA (don't over-engineer)
Lightweight Script Pattern:
# Simple CSV processing script - NO DI needed
import pandas as pd
from pathlib import Path
def process_sales_data() -> :
df = pd.read_csv(input_path)
df[] = df[] * df[]
summary = df.groupby().agg({
: ,
:
}).reset_index()
summary.to_csv(output_path, index=)
()
__name__ == :
process_sales_data(
Path(),
Path()
)
Same Task with Unnecessary DI/SOA (Over-Engineering):
# DON'T DO THIS for simple scripts!
from abc import ABC, abstractmethod
from dataclasses import dataclass
import pandas as pd
from pathlib import Path
class IDataReader(ABC):
@abstractmethod
def read(self, path: Path) -> pd.DataFrame: ...
class IDataWriter(ABC):
@abstractmethod
def write(self, df: pd.DataFrame, path: Path) -> None: ...
class CSVReader(IDataReader):
def read(self, path: Path) -> pd.DataFrame:
return pd.read_csv(path)
class CSVWriter(IDataWriter):
def write(self, df: pd.DataFrame, path: Path) -> None:
df.to_csv(path, index=False)
@dataclass
class SalesProcessor:
reader: IDataReader
writer: IDataWriter
def process(self, input_path: Path, output_path: Path) -> None:
df = self.reader.read(input_path)
df['total'] = df['quantity'] * df['price']
summary = df.groupby('category').agg({
'total': 'sum',
'quantity': 'sum'
}).reset_index()
self.writer.write(summary, output_path)
# Too much boilerplate for a simple script!
if __name__ == "__main__":
processor = SalesProcessor(
reader=CSVReader(),
writer=CSVWriter()
)
processor.process(
Path("data/sales.csv"),
Path("data/summary.csv")
)
Key Principle: Use DI/SOA when you need testability, maintainability, or extensibility. For simple scripts, direct calls and minimal abstraction are perfectly fine.