Fix critical schema transformation bugs and improve logging

[Mirza-Samad-Ahmed-Baig]

Problem

The codebase had several critical issues that could cause runtime failures and poor production practices:

1. Schema Transformation Bugs: The transform_schema function in scrapegraphai/utils/schema_trasform.py was vulnerable to KeyError exceptions when processing malformed or incomplete Pydantic schemas, lacking proper error handling for missing keys.

2. Poor Logging Practices: The SmartScraperGraph class used print() statements instead of proper logging, which is inappropriate for production environments and headless execution.

3. Typos: Documentation contained typos that reduced code quality ("trasfrom" instead of "transforms").

Solution

• Added comprehensive error handling to prevent KeyError exceptions in schema processing
• Implemented proper logging using Python's logging module instead of print statements
• Added fallback values for malformed array items and missing schema references
• Improved input validation with proper error messages for invalid schemas

Changes Made

1. scrapegraphai/utils/schema_trasform.py:

   • Fixed typo in docstring: "trasfrom" → "transforms"
   • Added null checks for items, $defs, and reference keys
   • Added fallback values for missing references and malformed arrays
   • Added validation for required schema structure with descriptive error messages

2. scrapegraphai/graphs/smart_scraper_graph.py:

   • Replaced print() statements with proper logger.info() and logger.warning()
   • Added response structure validation before logging
   • Imported and configured logging module

3. scrapegraphai/utils/__init__.py:

   • Added documentation comment noting the filename typo for future reference

Impact

• ✅ Prevents runtime crashes from malformed schema processing
• ✅ Improves production readiness with proper logging practices
• ✅ Better error handling with graceful fallbacks
• ✅ Enhanced debugging with structured logging instead of print statements
• ✅ Maintains backward compatibility while fixing critical bugs

Type of Change

• Bug fix (non-breaking change which fixes an issue)
• Code quality improvement
• New feature (non-breaking change which adds functionality)
• Breaking change (fix or feature that would cause existing functionality to not work as expected)