serpapi-core-workflow-a

# SerpApi Core Workflow A: Google Search ## Overview Extract structured data from Google Search: organic results, answer boxes, knowledge graph, related questions (PAA), local pack, ads, and shopping results. Each search costs 1 API credit. ## Instructions ### Step 1: Full Google Search with All Components ```python import serpapi, os client = serpapi.Client(api_key=os.environ["SERPAPI_API_KEY"]) result = client.search( engine="google", q="best project management tools", location="New York, New York", hl="en", gl="us", num=10, ) # 1. Organic Results for r in result.get("organic_results", []): print(f"{r['position']}. {r['title']}") print(f" URL: {r['link']}") print(f" Snippet: {r.get('snippet', 'N/A')}") # Rich snippets: sitelinks, rating, date if "rich_snippet" in r: print(f" Rating: {r['rich_snippet'].get('top', {}).get('rating')}") # 2. Answer Box if ab := result.get("answer_box"): print(f"\nAnswer Box ({ab.get('type', 'unknown')}):") print(f" {ab.get('answer') or ab.get('snippet') or ab.get('title')}") # 3. Knowledge Graph if kg := result.get("knowledge_graph"): print(f"\nKnowledge Graph: {kg['title']}") print(f" Type: {kg.get('type')}") print(f" Description: {kg.get('description', 'N/A')[:100]}") # 4. People Also Ask for paa in result.get("related_questions", []): print(f"\nPAA: {paa['question']}") print(f" Answer: {paa.get('snippet', 'N/A')[:100]}") # 5. Related Searches fo...