import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns

sns.set_theme(style='whitegrid', palette='deep', context='talk')
plt.rcParams.update({

import numpy as np

embeddings = np.array([
    [0.9, 0.1, 0.2],
    [0.1, 0.8, 0.3],
    [0.7, 0.2, 0.4],

import numpy as np

features = np.array([
    [120.0, 3.0, 10.0],
    [90.0, 5.0, 7.0],
    [150.0, 2.0, 14.0],

import pandas as pd

df = pd.read_csv('traffic.csv', parse_dates=['timestamp'])
df['timestamp'] = pd.to_datetime(df['timestamp'], utc=True)
df = df.set_index('timestamp').sort_index()

import pandas as pd

customers = pd.read_parquet('customers.parquet')
orders = pd.read_parquet('orders.parquet')

assert customers['customer_id'].is_unique, 'customer table must be unique by customer_id'

import pandas as pd

df = pd.read_parquet('events.parquet')
df['event_date'] = pd.to_datetime(df['event_date'])
df['month'] = df['event_date'].dt.to_period('M').astype(str)

import pandas as pd

df = pd.read_csv('customers.csv')

df.columns = df.columns.str.strip().str.lower().str.replace(' ', '_', regex=False)

import pandas as pd

df = pd.read_csv(
    'orders.csv',
    parse_dates=['created_at'],
    dtype={

#!/usr/bin/env bash
set -euo pipefail

# ==========================================================
# Production Incident Response Runbook
# ==========================================================

// k6 Load Test Configuration
// Run: k6 run load-test.js --env BASE_URL=https://api.example.com

import http from 'k6/http';
import { check, sleep, group } from 'k6';
import { Rate, Trend, Counter } from 'k6/metrics';

#!/usr/bin/env bash
set -euo pipefail

# Container Registry Management & Image Lifecycle

# ============================================

# AWS Lambda Function with API Gateway trigger

# === Lambda function ===
resource "aws_lambda_function" "api_handler" {
  function_name = "${var.project}-api-handler"
  description   = "API request handler for ${var.project}"