from kubiya_workflow_sdk import Workflow, Step

# Create a workflow that uses multiple technologies
workflow = Workflow(
    name="multi-tech-pipeline",
    runner="kubiya-hosted"
)

# Data extraction with Python
workflow.add_step(Step(
    name="extract-data",
    image="python:3.11",
    packages=["requests", "pandas"],
    code="""
    import requests
    import pandas as pd
    
    # Extract data from API
    response = requests.get('https://api.example.com/data')
    df = pd.DataFrame(response.json())
    df.to_csv('extracted_data.csv')
    """
))

# Analysis with R
workflow.add_step(Step(
    name="statistical-analysis",
    image="r-base:latest",
    code="""
    library(tidyverse)
    
    # Perform statistical analysis
    data <- read.csv('extracted_data.csv')
    analysis <- summary(lm(y ~ x, data))
    write.csv(analysis$coefficients, 'analysis_results.csv')
    """
))

# Visualization with Node.js
workflow.add_step(Step(
    name="create-dashboard",
    image="node:20",
    packages=["d3", "express"],
    code="""
    const express = require('express');
    const d3 = require('d3');
    
    // Create interactive dashboard
    const app = express();
    // Build visualization from analysis results
    """
))