/** @jsxImportSource https://esm.sh/react@18.2.0 */ import { createRoot } from "https://esm.sh/react-dom@18.2.0/client"; import React, { useEffect, useState } from "https://esm.sh/react@18.2.0"; import { blob } from "https://esm.town/v/std/blob"; import { OpenAI } from "https://esm.town/v/std/openai"; // Operational Data Science Tool Report Generator async function generateDataScienceToolReport() { const openai = new OpenAI(); // Comprehensive Data Science and Database Tool Categories const dataScienceToolCategories = [ { category: "Programming Languages", tools: [ { name: "Python", strengths: [ "Most popular data science language", "Extensive libraries (NumPy, Pandas, SciPy)", "Machine learning support", "Data visualization capabilities", ], popularLibraries: [ "NumPy", "Pandas", "Scikit-learn", "TensorFlow", "PyTorch", ], useCases: [ "Machine Learning", "Data Analysis", "Scientific Computing", "Artificial Intelligence", ], operationalReadiness: { learningCurve: "Moderate", communitySupport: "Excellent", industrialAdoption: "High", }, }, // ... (other programming languages remain the same) ], }, // ... (other categories remain the same) ]; // Advanced Operational Analysis async function generateOperationalInsights(category: string) { const operationalCompletion = await openai.chat.completions.create({ model: "gpt-4o-mini", messages: [ { role: "system", content: "You are an expert operational technology strategist. Provide deep insights into the operational readiness and implementation strategies for data science tools.", }, { role: "user", content: `Analyze the operational landscape for ${category}. Provide strategic insights into: 1. Implementation challenges 2. Scalability considerations 3. Enterprise integration potential 4. Cost-effectiveness 5. Performance optimization strategies`, }, ], max_tokens: 400, }); return operationalCompletion.choices[0].message.content || "No operational insights generated"; } // Comprehensive Operational Analysis const operationalTechReport = await Promise.all( dataScienceToolCategories.map(async (category) => ({ ...category, operationalInsights: await generateOperationalInsights(category.category), })), ); // Generate Detailed Operational Report const fullOperationalReport = { reportTitle: "Operational Data Science and Technology Landscape", generatedAt: new Date().toISOString(), technologiesAnalyzed: operationalTechReport, operationalKeyTakeaways: [ "Strategic tool selection criteria", "Enterprise integration frameworks", "Performance and scalability metrics", "Total cost of ownership analysis", ], implementationStrategies: [ "Phased technology adoption", "Continuous skill development", "Cross-functional team alignment", "Agile technology integration", ], }; // Advanced Export and Analysis Methods async function exportOperationalReportToJSON() { const reportKey = `operational_report_${Date.now()}`; await blob.setJSON(reportKey, fullOperationalReport); return reportKey; } async function generateComprehensiveOperationalAnalysis() { const analysis = { totalToolsCovered: dataScienceToolCategories.reduce((total, category) => total + category.tools.length, 0), categoriesCovered: dataScienceToolCategories.map(cat => cat.category), operationalReadinessScores: dataScienceToolCategories.flatMap(category => category.tools.map(tool => ({ name: tool.name, readinessScore: calculateOperationalReadinessScore(tool), })) ), }; return analysis; } function calculateOperationalReadinessScore(tool) { const scoreMap = { learningCurve: { "Low": 3, "Moderate": 2, "High": 1, }, communitySupport: { "Poor": 1, "Good": 2, "Excellent": 3, }, industrialAdoption: { "Low": 1, "Medium": 2, "High": 3, }, }; if (!tool.operationalReadiness) return 0; const learningCurveScore = scoreMap.learningCurve[tool.operationalReadiness.learningCurve] || 0; const communitySupportScore = scoreMap.communitySupport[tool.operationalReadiness.communitySupport] || 0; const industrialAdoptionScore = scoreMap.industrialAdoption[tool.operationalReadiness.industrialAdoption] || 0; return (learningCurveScore + communitySupportScore + industrialAdoptionScore) / 3 * 100; } return { fullOperationalReport, exportOperationalReportToJSON, generateComprehensiveOperationalAnalysis, }; } // React-based Operational Dashboard function OperationalToolDashboard() { const [report, setReport] = useState(null); const [analysis, setAnalysis] = useState(null); const [loading, setLoading] = useState(true); useEffect(() => { async function fetchOperationalReport() { try { const reportGenerator = await generateDataScienceToolReport(); const generatedReport = reportGenerator.fullOperationalReport; const comprehensiveAnalysis = await reportGenerator.generateComprehensiveOperationalAnalysis(); setReport(generatedReport); setAnalysis(comprehensiveAnalysis); setLoading(false); } catch (error) { console.error("Failed to generate operational report:", error); setLoading(false); } } fetchOperationalReport(); }, []); if (loading) { return

Generating Operational Report...

; } return (

{report.reportTitle}

Generated: {report.generatedAt}

Operational Key Takeaways

{takeaway}

Implementation Strategies

{strategy}

Operational Readiness Analysis

{analysis && (

Total Tools Analyzed: {analysis.totalToolsCovered}

Operational Readiness Scores

{analysis.operationalReadinessScores.map((score, index) => ( ))}

Tool	Readiness Score
{score.name}	{score.readinessScore.toFixed(2)}%

)}

); } // Server-side Handler export default async function server(request: Request) { return new Response( ` Operational Data Science Tool Report

`, { headers: { "content-type": "text/html" }, }, ); } // Client-side Rendering function client() { createRoot(document.getElementById("root")).render(); } if (typeof document !== "undefined") { client(); } const css = ` body { font-family: 'Arial', sans-serif; line-height: 1.6; max-width: 800px; margin: 0 auto; padding: 20px; background-color: #f4f4f4; } h1, h2 { color: #333; } table { width: 100%; border-collapse: collapse; margin-top: 15px; } th, td { border: 1px solid #ddd; padding: 8px; text-align: left; } th { background-color: #f2f2f2; } `;

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