feat(checker): add add/mean/groupby on columns

midas/checker/frames/column_methods.py

@@ -1,13 +1,23 @@
 from __future__ import annotations
 
+import ast
 from dataclasses import dataclass
-from typing import TYPE_CHECKING
+from typing import TYPE_CHECKING, Optional
 
 import midas.ast.python as p
 from midas.ast.location import Location
-from midas.checker.frames.utils import MethodRegistry
+from midas.checker.dispatcher import CallResult
+from midas.checker.frames.utils import MethodRegistry, method
 from midas.checker.types import (
+    ColumnGroupBy,
     ColumnType,
+    Function,
+    GenericType,
+    TopType,
+    Type,
+    TypeVar,
+    UnknownType,
+    unfold_type,
 )
 
 if TYPE_CHECKING:
@@ -24,4 +34,183 @@ class Call:
     keywords: dict[str, TypedExpr]
 
 
-class ColumnMethodRegistry(MethodRegistry[Call]): ...
+class ColumnMethodRegistry(MethodRegistry[Call]):
+    @method("add", "__add__")
+    def add(self, call: Call) -> Type:
+        # TODO: support add with scalar
+        # TODO: check operation exists on inner column types
+
+        column2: Optional[ColumnType] = None
+
+        col_type1: Type = call.column.type
+        new_column: Type = ColumnType(type=UnknownType())
+        if len(call.positional) != 0:
+            other: Type = call.positional[0][1]
+            unfolded_other: Type = unfold_type(other)
+            if isinstance(unfolded_other, ColumnType):
+                column2 = unfolded_other
+                col_type2: Type = column2.type
+                if self.types.are_equivalent(col_type2, col_type1):
+                    new_column = ColumnType(type=col_type1)
+
+        # Build signature with new column type and generic operand
+        param_type: TypeVar = TypeVar(name="T", bound=None)
+        signature = GenericType(
+            name="add",
+            params=[param_type],
+            body=Function(
+                args=[
+                    Function.Argument(
+                        pos=0,
+                        name="other",
+                        type=ColumnType(type=param_type),
+                        required=True,
+                    ),
+                ],
+                returns=new_column,
+            ),
+        )
+
+        # Map arguments and compute result type
+        result: CallResult = self.dispatcher.get_result(
+            location=call.location,
+            callee=signature,
+            positional=call.positional,
+            keywords=call.keywords,
+        )
+        if result.is_valid:
+            self._assert_same_length(
+                call.call_expr, call.column_expr, call.positional[0][0]
+            )
+
+        return result.result
+
+    @method()
+    def mean(self, call: Call) -> Type:
+        signature = Function(
+            kw_args=[
+                Function.Argument(
+                    pos=0,
+                    name="axis",
+                    type=TopType(),
+                    required=False,
+                )
+            ],
+            returns=ColumnType(type=TopType()),
+        )
+
+        result: CallResult = self.dispatcher.get_result(
+            location=call.location,
+            callee=signature,
+            positional=call.positional,
+            keywords=call.keywords,
+        )
+        return result.result
+
+    @method()
+    def groupby(self, call: Call) -> Type:
+        bool_: Type = self.types.get_type("bool")
+        function: Function = Function(
+            args=[
+                Function.Argument(
+                    pos=0,
+                    name="by",
+                    type=TopType(),
+                    required=False,
+                ),
+                Function.Argument(
+                    pos=1,
+                    name="level",
+                    type=TopType(),
+                    required=False,
+                ),
+            ],
+            kw_args=[
+                Function.Argument(
+                    pos=2,
+                    name="as_index",
+                    type=bool_,
+                    required=False,
+                ),
+                Function.Argument(
+                    pos=3,
+                    name="sort",
+                    type=bool_,
+                    required=False,
+                ),
+                Function.Argument(
+                    pos=4,
+                    name="group_keys",
+                    type=bool_,
+                    required=False,
+                ),
+                Function.Argument(
+                    pos=5,
+                    name="observed",
+                    type=bool_,
+                    required=False,
+                ),
+                Function.Argument(
+                    pos=6,
+                    name="dropna",
+                    type=bool_,
+                    required=False,
+                ),
+            ],
+            returns=ColumnGroupBy(column=call.column),
+        )
+
+        result: CallResult = self.dispatcher.get_result(
+            location=call.location,
+            callee=function,
+            positional=call.positional,
+            keywords=call.keywords,
+        )
+        return result.result
+
+    def _assert_same_length(self, call_expr: p.Expr, column1: p.Expr, column2: p.Expr):
+        func_name: str = "__midas_column_same_length__"
+        self.assertions.define(
+            func_name,
+            ast.FunctionDef(
+                name=func_name,
+                args=ast.arguments(
+                    posonlyargs=[],
+                    args=[
+                        ast.arg(arg="column1"),
+                        ast.arg(arg="column2"),
+                    ],
+                    kwonlyargs=[],
+                    defaults=[],
+                    kw_defaults=[],
+                ),
+                body=[
+                    ast.Return(
+                        value=ast.Compare(
+                            left=ast.Attribute(
+                                value=ast.Name(id="column1"),
+                                attr="size",
+                            ),
+                            ops=[ast.Eq()],
+                            comparators=[
+                                ast.Attribute(
+                                    value=ast.Name(id="column2"),
+                                    attr="size",
+                                )
+                            ],
+                        )
+                    )
+                ],
+                decorator_list=[],
+            ),
+        )
+        self.assertions.add(
+            bound_expr=call_expr,
+            inputs=[column1, column2],
+            builder=lambda c1, c2: ast.Call(
+                func=ast.Name(id=func_name),
+                args=[c1, c2],
+                keywords=[],
+            ),
+            message="Columns must have the same length",
+        )