handle subclass

[lucemia]

Yes, you can determine class inheritance relationships using the Abstract Syntax Tree (AST) in Python, even with "cold analysis" (i.e., without executing the code). This involves parsing the Python source code into an AST and inspecting the structure of the AST to find and analyze class definitions and their respective parent classes.

Here’s a step-by-step explanation on how to achieve this:

1. Parsing the Source Code

First, you'll need to parse the source code into an AST using Python's ast module. This gives you access to all syntactic elements of the code as tree nodes.

2. Visiting Class Definitions

You can use the ast.NodeVisitor or ast.NodeTransformer classes to traverse the AST. By implementing the visit_ClassDef method, you can inspect each class definition encountered during the traversal.

3. Analyzing Inheritance

The ClassDef node in the AST contains an attribute named bases which lists the base classes from which a class inherits. This list can be inspected to determine the inheritance structure of each class.

Example Code

Here’s a simple example demonstrating how to extract class inheritance information from Python source code:

import ast

class InheritanceVisitor(ast.NodeVisitor):
    def visit_ClassDef(self, node):
        # Get the name of the class
        class_name = node.name
        # Extract the names of base classes
        base_classes = [base.id for base in node.bases if isinstance(base, ast.Name)]
        print(f"Class: {class_name}, Inherits from: {base_classes}")
        # Continue visiting child nodes
        self.generic_visit(node)

# Example Python code as a string
source_code = """
class Base:
    pass

class Derived(Base):
    pass
"""

# Parse the source code into an AST
parsed_ast = ast.parse(source_code)

# Create an instance of the visitor and use it to traverse the AST
visitor = InheritanceVisitor()
visitor.visit(parsed_ast)

Output

This code will output:

Class: Base, Inherits from: []
Class: Derived, Inherits from: ['Base']

Limitations and Considerations

• Simple Names: The example handles simple inheritance cases where base classes are directly named. If inheritance involves more complex expressions (like function calls or attribute accesses), you would need to enhance the visitor to handle these cases.
• External Modules: If the inheritance involves classes from external modules, you won't get those class names directly from the AST. You might need to resolve these names using additional context or metadata.
• Metaclasses and Other Advanced Features: Handling Python's more advanced features like metaclasses might require more sophisticated analysis.

Conclusion

Using AST for "cold analysis" of class inheritance in Python is entirely feasible and can be quite powerful for static analysis tools, code quality checkers, or even automated refactoring tools. This method allows you to analyze Python code without running it, ensuring safety and isolation from side effects.