⚡ Live Playground: AI Dev Tool: Managing AI Coding Costs

```python
# AI Dev Tool: FastAPI Postgres Analytics Booster
# =============================================
# A high-performance, production-ready boilerplate for building fast and scalable analytics services
# using FastAPI, Postgres, and advanced optimization techniques.

import os
import uvicorn
from fastapi import FastAPI, Depends
from fastapi.responses import JSONResponse
from fastapi.requests import Request
from pydantic import BaseModel
from typing import List, Optional
from psycopg2 import connect, Error
from psycopg2.extras import DictCursor
import numpy as np

# Define the Postgres connection settings
POSTGRES_HOST = os.environ.get("POSTGRES_HOST", "localhost")
POSTGRES_PORT = os.environ.get("POSTGRES_PORT", 5432)
POSTGRES_DB = os.environ.get("POSTGRES_DB", "analytics")
POSTGRES_USER = os.environ.get("POSTGRES_USER", "postgres")
POSTGRES_PASSWORD = os.environ.get("POSTGRES_PASSWORD", "postgres")

# Define the FastAPI app
app = FastAPI()

# Define a Pydantic model for the analytics data
class AnalyticsData(BaseModel):
    id: int
    timestamp: str
    value: float

# Define a function to connect to Postgres
def connect
⚡ Live Code Sandbox: AI Dev Tool: Managing AI Coding Costs
