feat(checker): add structural subtyping rule for dataframes

midas/checker/registry.py

@@ -8,8 +8,10 @@ from midas.checker.types import (
     AliasType,
     AppliedType,
     BaseType,
+    ColumnType,
     ComplexType,
     ConstraintType,
+    DataFrameType,
     ExtensionType,
     Function,
     GenericType,
@@ -157,6 +159,24 @@ class TypesRegistry:
                         return False
                 return True
 
+            case (DataFrameType(columns=columns1), DataFrameType(columns=columns2)):
+                # TODO: check order?
+                by_name1: dict[str, DataFrameType.Column] = {
+                    col.name: col for col in columns1 if col.name is not None
+                }
+                for col2 in columns2:
+                    if col2.name not in by_name1:
+                        return False
+                    if not self.is_subtype(by_name1[col2.name].type, col2.type):
+                        return False
+                return True
+
+            case (ColumnType(type=inner1), ColumnType(type=inner2)):
+                # TODO: invariant, replace ColumnType with simple GenericType
+                if not self.are_equivalent(inner1, inner2):
+                    return False
+                return True
+
             case (Function(), Function()):
                 return self.is_func_subtype(type1, type2)
 
@@ -187,6 +207,9 @@ class TypesRegistry:
 
         return False
 
+    def are_equivalent(self, type1: Type, type2: Type) -> bool:
+        return self.is_subtype(type1, type2) and self.is_subtype(type2, type1)
+
     # TODO: verify the logic in here
     def is_func_subtype(self, func1: Function, func2: Function) -> bool:
         """Check whether a function is a subtype of another