Update src/analyzer/code_analyzer.py

[CrazyDubya]

No description provided.

[Copilot]

Pull Request Overview

This PR implements performance improvements to the code analyzer through expression type inference caching and adds better tuple unpacking support. The changes aim to reduce redundant type inference computations and handle more complex assignment patterns.

• Adds expression type caching to avoid redundant type inference work
• Improves tuple unpacking assignment handling with nested tuple support
• Refactors expression type inference methods for better maintainability

Reviewed Changes

Copilot reviewed 4 out of 4 changed files in this pull request and generated 4 comments.

File	Description
src/converter/code_generator.py	Adds type checking to handle both dict and object inputs for analysis results
src/analyzer/code_analyzer_fixed.py	Implements comprehensive caching system and refactors type inference logic
src/analyzer/code_analyzer.py	Adds basic caching and tuple unpacking support with debug logging improvements
docs/ComprehensiveCodeAnalysisReport.md	New documentation file providing detailed project structure analysis

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[Copilot]

Using type(node) in cacheable_node_types is less efficient than isinstance(node, cacheable_node_types). Consider changing to isinstance(node, tuple(cacheable_node_types)) for better performance and consistency with the pattern used in code_analyzer_fixed.py.

Suggested change

	cache_key = id(node) if type(node) in cacheable_node_types else None
	cache_key = id(node) if isinstance(node, tuple(cacheable_node_types)) else None

[Copilot]

The cacheable node types are inconsistent between the two analyzer files. In code_analyzer.py it's a set with different ordering, while here it's a tuple. Consider standardizing the cacheable types and their representation across both files.

Suggested change

	# Define cacheable node types
	cacheable_node_types = (ast.Constant, ast.Name, ast.List, ast.Dict, ast.Tuple, ast.Set)
	# Define cacheable node types (standardized as a set, matching code_analyzer.py)
	cacheable_node_types = {ast.Constant, ast.Name, ast.List, ast.Dict, ast.Tuple, ast.Set}

[Copilot]

The self.logger attribute is referenced but there's no logger initialization visible in the __init__ method of this class. This will likely cause an AttributeError at runtime.

[Copilot]

This code assumes self.type_info[func_name] is a dictionary, but earlier in the codebase self.type_info values can be strings. This will cause an AttributeError when calling .get() on a string value.

Suggested change

	return_type = self.type_info[func_name].get('return_type', 'std::tuple<int, int>')
	if isinstance(self.type_info[func_name], dict):
	return_type = self.type_info[func_name].get('return_type', 'std::tuple<int, int>')
	else:
	return_type = 'std::tuple<int, int>'