feat: align with scrapegraph-py v2 API surface from PR #82

- Pass output_schema to extract() so Pydantic schemas are forwarded to the v2 API
- Use context manager pattern (with Client(...) as client) for proper resource cleanup
- Simplify examples to match the v2 SDK style from scrapegraph-py
- Remove unused sgai_logger import (v2 client handles its own logging)

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

Author: VinciGit00

examples/markdownify/markdownify_scrapegraphai.py

@@ -1,33 +1,20 @@
 """
-Example script demonstrating the scrape functionality (v2 API - replaces markdownify)
+Scrape a webpage as clean markdown using scrapegraph-py v2 API.
+Replaces the old markdownify() call with scrape().
 """
 
 import json
 import os
+
 from dotenv import load_dotenv
 from scrapegraph_py import Client
-from scrapegraph_py.logger import sgai_logger
-
-def main():
-    # Load environment variables
-    load_dotenv()
 
-    # Set up logging
-    sgai_logger.set_logging(level="INFO")
+load_dotenv()
 
-    # Initialize the client
-    api_key = os.getenv("SCRAPEGRAPH_API_KEY")
-    if not api_key:
-        raise ValueError("SCRAPEGRAPH_API_KEY environment variable not found")
-    sgai_client = Client(api_key=api_key)
+api_key = os.getenv("SCRAPEGRAPH_API_KEY")
+if not api_key:
+    raise ValueError("SCRAPEGRAPH_API_KEY environment variable not found")
 
-    # Scrape a website as markdown (v2 API - replaces markdownify)
-    print("Scraping website as Markdown")
-    print("-" * 50)
-    response = sgai_client.scrape(
-        url="https://example.com"
-    )
+with Client(api_key=api_key) as client:
+    response = client.scrape(url="https://example.com")
     print(json.dumps(response, indent=2))
-
-if __name__ == "__main__":
-    main()

examples/search_graph/scrapegraphai/searchscraper_scrapegraphai.py

@@ -1,43 +1,20 @@
 """
-Example implementation of search-based scraping using Scrapegraph AI v2 API.
-This example demonstrates how to use the search endpoint to extract information from the web.
+Search the web and extract AI-structured results using scrapegraph-py v2 API.
+Replaces the old searchscraper() call with search().
 """
 
 import json
 import os
+
 from dotenv import load_dotenv
 from scrapegraph_py import Client
-from scrapegraph_py.logger import sgai_logger
-
-def main():
-    # Load environment variables
-    load_dotenv()
-
-    # Get API key
-    api_key = os.getenv("SCRAPEGRAPH_API_KEY")
-    if not api_key:
-        raise ValueError("SCRAPEGRAPH_API_KEY not found in environment variables")
-
-    # Configure logging
-    sgai_logger.set_logging(level="INFO")
-
-    # Initialize client
-    sgai_client = Client(api_key=api_key)
-
-    try:
-        # Search request (v2 API - replaces searchscraper)
-        print("\nSearching for information...")
 
-        search_response = sgai_client.search(
-            query="Extract webpage information"
-        )
-        print(json.dumps(search_response, indent=2))
+load_dotenv()
 
-    except Exception as e:
-        print(f"\nError occurred: {str(e)}")
-    finally:
-        # Always close the client
-        sgai_client.close()
+api_key = os.getenv("SCRAPEGRAPH_API_KEY")
+if not api_key:
+    raise ValueError("SCRAPEGRAPH_API_KEY not found in environment variables")
 
-if __name__ == "__main__":
-    main()
+with Client(api_key=api_key) as client:
+    response = client.search(query="Extract webpage information")
+    print(json.dumps(response, indent=2))

examples/smart_scraper_graph/scrapegraphai/smartscraper_scrapegraphai.py

@@ -1,43 +1,23 @@
 """
-Example implementation using scrapegraph-py v2 client directly.
+Extract structured data from a webpage using scrapegraph-py v2 API.
+Replaces the old smartscraper() call with extract().
 """
 
 import json
 import os
+
 from dotenv import load_dotenv
 from scrapegraph_py import Client
-from scrapegraph_py.logger import sgai_logger
-
-def main():
-    # Load environment variables from .env file
-    load_dotenv()
-
-    # Get API key from environment variables
-    api_key = os.getenv("SCRAPEGRAPH_API_KEY")
-    if not api_key:
-        raise ValueError("SCRAPEGRAPH_API_KEY not found in environment variables")
-
-    # Set up logging
-    sgai_logger.set_logging(level="INFO")
-
-    # Initialize the client with API key from environment
-    sgai_client = Client(api_key=api_key)
-
-    try:
-        # Extract request (v2 API - replaces smartscraper)
-        response = sgai_client.extract(
-            url="https://scrapegraphai.com",
-            prompt="Extract the founders' informations"
-        )
 
-        # Print the response
-        print(json.dumps(response, indent=2))
+load_dotenv()
 
-    except Exception as e:
-        print(f"Error occurred: {str(e)}")
-    finally:
-        # Always close the client
-        sgai_client.close()
+api_key = os.getenv("SCRAPEGRAPH_API_KEY")
+if not api_key:
+    raise ValueError("SCRAPEGRAPH_API_KEY not found in environment variables")
 
-if __name__ == "__main__":
-    main()
+with Client(api_key=api_key) as client:
+    response = client.extract(
+        url="https://scrapegraphai.com",
+        prompt="Extract the founders' informations",
+    )
+    print(json.dumps(response, indent=2))

scrapegraphai/graphs/smart_scraper_graph.py

@@ -79,30 +79,23 @@ def _create_graph(self) -> BaseGraph:
         if self.llm_model == "scrapegraphai/smart-scraper":
             try:
                 from scrapegraph_py import Client
-                from scrapegraph_py.logger import sgai_logger
             except ImportError:
                 raise ImportError(
                     "scrapegraph_py is not installed. Please install it using 'pip install scrapegraph-py'."
                 )
 
-            sgai_logger.set_logging(level="INFO")
-
-            # Initialize the client with explicit API key
-            sgai_client = Client(api_key=self.config.get("api_key"))
-
-            # Extract request (v2 API)
-            response = sgai_client.extract(
-                url=self.source,
-                prompt=self.prompt,
-            )
-
-            # Use logging instead of print for better production practices
-            if "id" in response:
-                logger.info(f"Request ID: {response['id']}")
-            if "data" in response:
-                logger.info(f"Result: {response['data']}")
+            with Client(api_key=self.config.get("api_key")) as sgai_client:
+                # Extract request (v2 API)
+                response = sgai_client.extract(
+                    url=self.source,
+                    prompt=self.prompt,
+                    output_schema=self.schema,
+                )
 
-            sgai_client.close()
+                if "id" in response:
+                    logger.info(f"Request ID: {response['id']}")
+                if "data" in response:
+                    logger.info(f"Result: {response['data']}")
 
             return response