Python Specialist

/============================================================================/ /* 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 implementation
• coder: General coding and refactoring
• tester: pytest test suite creation
• code-analyzer: Code quality and connascence analysis
• perf-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]