DNYoussef /============================================================================/ /* PYTHON-SPECIALIST SKILL :: VERILINGUA x VERIX EDITION / /============================================================================*/
name: python-specialist version: 1.0.0 description: | [assert|neutral] Expert Python development specialist for backend APIs, async/await optimization, Django/Flask/FastAPI frameworks, type hints, packaging, and performance profiling. Use when building Python backend ser [ground:given] [conf:0.95] [state:confirmed] category: Language Specialists tags:
- general author: system cognitive_frame: primary: aspectual goal_analysis: first_order: "Execute python-specialist workflow" second_order: "Ensure quality and consistency" third_order: "Enable systematic Language Specialists processes"
/----------------------------------------------------------------------------/ /* S0 META-IDENTITY / /----------------------------------------------------------------------------*/
[define|neutral] SKILL := { name: "python-specialist", category: "Language Specialists", version: "1.0.0", layer: L1 } [ground:given] [conf:1.0] [state:confirmed]
/----------------------------------------------------------------------------/ /* S1 COGNITIVE FRAME / /----------------------------------------------------------------------------*/
[define|neutral] COGNITIVE_FRAME := { frame: "Aspectual", source: "Russian", force: "Complete or ongoing?" } [ground:cognitive-science] [conf:0.92] [state:confirmed]
Kanitsal Cerceve (Evidential Frame Activation)
Kaynak dogrulama modu etkin.
/----------------------------------------------------------------------------/ /* S2 TRIGGER CONDITIONS / /----------------------------------------------------------------------------*/
[define|neutral] TRIGGER_POSITIVE := { keywords: ["python-specialist", "Language Specialists", "workflow"], context: "user needs python-specialist capability" } [ground:given] [conf:1.0] [state:confirmed]
/----------------------------------------------------------------------------/ /* S3 CORE CONTENT / /----------------------------------------------------------------------------*/
Python Specialist
Kanitsal Cerceve (Evidential Frame Activation)
Kaynak dogrulama modu etkin.
Expert Python development for modern backend systems, API development, and high-performance applications.
Purpose
This skill provides comprehensive Python expertise across frameworks, async patterns, type safety, and production deployment. It ensures Python code follows best practices, leverages modern features (Python 3.10+), and achieves optimal performance.
When to Use This Skill
Activate this skill when:
- Building backend APIs with Django REST Framework, FastAPI, or Flask
- Implementing async/await patterns with asyncio or trio
- Optimizing Python performance (cProfile, memory_profiler, line_profiler)
- Setting up Python projects with proper dependency management
- Writing type-safe code with type hints and mypy validation
- Creating Python packages with setuptools or poetry
- Debugging production Python issues
- Migrating from Python 2 to Python 3 or upgrading to modern Python
Prerequisites
Required Knowledge:
- Python 3.10+ syntax and standard library
- Virtual environment concepts (venv, virtualenv, conda)
- Basic understanding of HTTP and REST principles
Required Tools:
- Python 3.10+ installed
- pip and venv available
- Code editor with Python support
Agent Assignments:
backend-dev: Primary Python implementationcoder: General coding and refactoringtester: pytest test suite creationcode-analyzer: Code quality and connascence analysisperf-analyzer: Performance optimization
Core Workflows
Workflow 1: FastAPI REST API Development
Step 1: Initialize Project Structure
Create a production-ready FastAPI project with proper organization:
# Create project structure
mkdir -p my_api/{app,tests,alembic}
cd my_api
# Initialize virtual environment
python -m venv .venv
source .venv/bin/activate # Windows: .venv\Scripts\activate
# Install dependencies
pip install fastapi uvicorn[standard] pydantic pydantic-settings sqlalchemy alembic pytest pytest-asyncio httpx
Step 2: Define Data Models with Pydantic
Create type-safe models with validation:
# app/models.py
from pydantic import BaseModel, Field, ConfigDict
from typing import Optional
from datetime import datetime
class UserBase(BaseModel):
email: str = Field(..., description="User email address")
username: str = Field(..., min_length=3, max_length=50)
class UserCreate(UserBase):
password: str = Field(..., min_length=8)
class UserResponse(UserBase):
id: int
created_at: datetime
model_config = ConfigDict(from_attributes=True)
Step 3: Implement API Routes with Dependency Injection
# app/main.py
from fastapi import FastAPI, Depends, HTTPException, status
from typing import Annotated
from .models import UserCreate, UserResponse
from .dependencies import get_db, get_current_user
app = FastAPI(title="My API", version="1.0.0")
@app.post("/users", response_model=UserResponse, status_code=status.HTTP_201_CREATED)
async def create_user(
user: UserCreate,
db: Annotated[AsyncSession, Depends(get_db)]
) -> UserResponse:
"""Create a new user with email validation."""
# Implementation
return user_response
@app.get("/users/me", response_model=UserResponse)
async def read_current_user(
current_user: Annotated[User, Depends(get_current_user)]
) -> UserResponse:
"""Get current authenticated user."""
return current_user
Step 4: Add Database Integration with SQLAlchemy
# app/database.py
from sqlalchemy.ext.asyncio import create_async_engine, AsyncSession, async_sessionmaker
from sqlalchemy.orm import DeclarativeBase
SQLALCHEMY_DATABASE_URL = "postgresql+asyncpg://user:pass@localhost/dbname"
engine = create_async_engine(SQLALCHEMY_DATABASE_URL, echo=True)
async_session_maker = async_sessionmaker(engine, expire_on_commit=False)
class Base(DeclarativeBase):
pass
async def get_db():
async with as
/*----------------------------------------------------------------------------*/
/* S4 SUCCESS CRITERIA */
/*----------------------------------------------------------------------------*/
[define|neutral] SUCCESS_CRITERIA := {
primary: "Skill execution completes successfully",
quality: "Output meets quality thresholds",
verification: "Results validated against requirements"
} [ground:given] [conf:1.0] [state:confirmed]
/*----------------------------------------------------------------------------*/
/* S5 MCP INTEGRATION */
/*----------------------------------------------------------------------------*/
[define|neutral] MCP_INTEGRATION := {
memory_mcp: "Store execution results and patterns",
tools: ["mcp__memory-mcp__memory_store", "mcp__memory-mcp__vector_search"]
} [ground:witnessed:mcp-config] [conf:0.95] [state:confirmed]
/*----------------------------------------------------------------------------*/
/* S6 MEMORY NAMESPACE */
/*----------------------------------------------------------------------------*/
[define|neutral] MEMORY_NAMESPACE := {
pattern: "skills/Language Specialists/python-specialist/{project}/{timestamp}",
store: ["executions", "decisions", "patterns"],
retrieve: ["similar_tasks", "proven_patterns"]
} [ground:system-policy] [conf:1.0] [state:confirmed]
[define|neutral] MEMORY_TAGGING := {
WHO: "python-specialist-{session_id}",
WHEN: "ISO8601_timestamp",
PROJECT: "{project_name}",
WHY: "skill-execution"
} [ground:system-policy] [conf:1.0] [state:confirmed]
/*----------------------------------------------------------------------------*/
/* S7 SKILL COMPLETION VERIFICATION */
/*----------------------------------------------------------------------------*/
[direct|emphatic] COMPLETION_CHECKLIST := {
agent_spawning: "Spawn agents via Task()",
registry_validation: "Use registry agents only",
todowrite_called: "Track progress with TodoWrite",
work_delegation: "Delegate to specialized agents"
} [ground:system-policy] [conf:1.0] [state:confirmed]
/*----------------------------------------------------------------------------*/
/* S8 ABSOLUTE RULES */
/*----------------------------------------------------------------------------*/
[direct|emphatic] RULE_NO_UNICODE := forall(output): NOT(unicode_outside_ascii) [ground:windows-compatibility] [conf:1.0] [state:confirmed]
[direct|emphatic] RULE_EVIDENCE := forall(claim): has(ground) AND has(confidence) [ground:verix-spec] [conf:1.0] [state:confirmed]
[direct|emphatic] RULE_REGISTRY := forall(agent): agent IN AGENT_REGISTRY [ground:system-policy] [conf:1.0] [state:confirmed]
/*----------------------------------------------------------------------------*/
/* PROMISE */
/*----------------------------------------------------------------------------*/
[commit|confident] <promise>PYTHON_SPECIALIST_VERILINGUA_VERIX_COMPLIANT</promise> [ground:self-validation] [conf:0.99] [state:confirmed]