Merge pull request 'Frame / columns in manual' (#28) from feat/frame-columns-in-manual into main

Reviewed-on: #28

docs/manual.typ

@@ -198,10 +198,26 @@ python3 build/midas/script.py
 In this chapter, you will find a complete reference for the Midas definition language.
 
 A `*.midas` file contains a number of statements, which can be:
+- *`alias`* statements (see @alias-stmt): to define a new type alias
 - *`type`* statements (see @type-stmt): to define a new type
 - *`extend`* statements (see @extend-stmt): to define member of a type
 - *`predicate`* statements (see @predicate-stmt): to define named predicates that can be used in constraint types
 
+== Alias Statement <alias-stmt>
+
+An *`alias`* statement lets you define a new type alias. It requires a unique name and base type.
+
+While a `type` statement (see @type-stmt) allows generic definitions, aliases are purely a for givin an alternative name to a type.
+
+#figure(
+  ```midas
+  alias MyType = float
+  ```,
+  caption: [Simple `alias` statement declaring a new type "`MyType`" equivalent to `float`],
+) <midas-simple-alias>
+
+This statement defines a new type called `MyType` which is equivalent to `float`. `MyType` and `float` can be used interchangeably.
+
 == Type Statement <type-stmt>
 
 A *`type`* statement lets you define a new type. It requires a unique name and base type.
@@ -212,7 +228,7 @@ The simplest form of a *`type`* statement is:
   type MyType = float
   ```,
   caption: [Simple `type` statement declaring a new type "`MyType`" as a subtype of `float`],
-) <midas-simple-alias>
+) <midas-simple-type>
 
 This statement defines a new type called `MyType` which is a subtype of `float`. `MyType` is a `float` but a `float` is not necessarily `MyType`.
 
@@ -291,8 +307,7 @@ To better refine a generic type, you can also bound type parameters using the fo
   caption: [Generic container type definition with a bound],
 )
 
-This can be read as "`Container` is a generic type which takes one type parameter `T` that must be a subtype of `float`".
-
+This can be read as "`Container` is a generic type which takes one type parameter `T` that must be a subtype of `float`".\
 You can use a generic type, i.e. instantiate it, by using a similar syntax with concrete type as arguments:
 
 #figure(
@@ -318,6 +333,46 @@ The _body_ of a generic type, i.e. the right-hand side of the definition, can co
   caption: [Type parameters in a generic type's body],
 )
 
+=== `Column` / `Frame` types
+
+To provide useful type-checking for data engineers, Midas offers two special types: `Column` and `Frame`.
+Their goal is to help type check Pandas' `Series` and `DataFrame` respectively.
+
+==== `Column`
+
+The `Column` type is a generic type used to represent a `pandas.Series` object.
+You can use it like any other generic type and it will provide type checking for some common methods and attributes offered by Pandas.
+
+#figure(
+  ```midas
+  type Temperature = float
+  alias Temperatures = Column[Temperature]
+  ```,
+  caption: [Simple column type definition],
+)
+
+==== `Frame` <frame-type>
+
+The `Frame` type is a super-powered generic type used to represent a `pandas.DataFrame` object.
+In place of type arguments, `Frame` accepts a schema, i.e. a series of column definitions.
+@simple-frame show how you can define a simple frame type with 3 columns:
+- `name`: a column of `Name` values
+- `age`: a column of `int` values
+- `height`: a column of `float where _ >= 0` values
+
+Notice that you don't need to specify `Column` types.
+
+#figure(
+  ```midas
+  type Name = str where len(_) != 0
+  alias Data = Frame[
+    name: Name,
+    age: int,
+    height: float where _ >= 0
+  ]
+  ```,
+) <simple-frame>
+
 #pagebreak()
 
 == Extend Statement <extend-stmt>
@@ -503,6 +558,7 @@ A simple annotation declaration, without assigning a value, is enough to declare
 )
 
 Because unpacking is not supported, assigning to multiple values is also not handled by the type checker.
+For more information about type annotations, see @type-annotations
 
 == Arithmetic
 
@@ -578,7 +634,7 @@ Conditional statements are checked relatively strictly by Midas. The test expres
 
 Simple forms of `for` loops can be used, that is using a single variable and iterating over an object implementing the `__getitem__` method. Like above in @if-else, leaking variables from inside the loop is ignored.
 
-The `for`-`else` statements are not supported. `while` loops are also not not supported.
+`for`-`else` statements are not supported. `while` loops are also not supported.
 
 == Functions
 
@@ -686,6 +742,35 @@ There may be some cases where the cost of checking a value at runtime is simply
 
 If the value passed to `cast` or `unsafe_cast` is a literal (e.g. an integer, a string, a list of literals, etc.), the assertion is evaluated _at compile-time_ and no runtime assertion is generated.
 
+== Annotations / Type Hints <type-annotations>
+
+Vanilla Python already lets you use type hints to specify the type of variables and function parameters.
+
+Midas use them to type check your code. Additionally, it allows you to use a special syntax to define a `Frame` types directly in these annotations.
+
+Because these annotations are not interpretable by Python, your integrated type checker might complain loudly about them being invalid.
+A workaround is to silence it by adding a type comment at the end of the line, as shown in @silence-errors.
+
+#figure(
+  ```python
+  var: Frame[name: str, age: float]  # type: ignore # noqa: F821
+  ```,
+  caption: [MyPy's and Pylance's complaints about custom type annotation can be silenced with type comments],
+) <silence-errors>
+
+=== Frame type annotation
+
+The syntax is similar to how you can define frame types in the Midas language (see @frame-type). The only difference is that types can only be name references; you cannot inline constraint types.
+
+The example of @python-frame-type shows how you can annotate a dataframe with some columns directly in Python.
+
+#figure(
+  ```python
+  df: Frame[name: Name, age: float, height: Length[Meter]] = ...
+  ```,
+  caption: [Frame type annotation in Python],
+) <python-frame-type>
+
 = Commands <commands>
 
 #TODO

docs/midas.sublime-syntax

@@ -37,6 +37,9 @@ contexts:
       pop: true
 
   keywords:
+    - match: \balias\b
+      scope: keyword.declaration.midas
+      push: alias-stmt
     - match: \btype\b
       scope: keyword.declaration.midas
       push: type-stmt
@@ -47,6 +50,15 @@ contexts:
       scope: keyword.declaration.midas
       push: predicate-stmt
 
+  alias-stmt:
+    - match: "{{identifier}}"
+      scope: entity.name.type
+    - match: "="
+      scope: keyword.operator.equal.midas
+      push: type-expr
+    - match: $
+      pop: true
+
   type-stmt:
     - match: "{{identifier}}"
       scope: entity.name.type
@@ -67,6 +79,13 @@ contexts:
     - match: \b(where)\b
       scope: keyword.other.midas
       set: constraint
+    - match: "Frame"
+      scope: entity.name.type
+      push:
+        - match: \[
+          push: frame-schema
+        - match: $
+          pop: true
     - match: "{{identifier}}"
       scope: entity.name.type
     - match: $
@@ -178,3 +197,15 @@ contexts:
 
     - match: '\)'
       pop: true
+
+  frame-schema:
+    - include: frame-column
+    - match: \]
+      # scope: punctuation.section.block.end
+      pop: true
+
+  frame-column:
+    - match: "{{identifier}}"
+      scope: variable.other.member
+    - match: ":"
+      push: type-expr

midas/checker/builtins.py

@@ -14,10 +14,11 @@ if TYPE_CHECKING:
     from midas.checker.registry import TypesRegistry
 
 
+# Hard-coded subtype relationships between builtin types
+# Circular dependencies and diamond inheritance MUST be avoided
 BUILTIN_SUBTYPES: dict[str, set[str]] = {
     "object": {"float", "list", "dict", "str", "bytes", "tuple"},
     "float": {"int"},
-    "int": {"bool"},
 }
 
 

midas/checker/frames/column_groupby_methods.py

@@ -7,7 +7,7 @@ import midas.ast.python as p
 from midas.ast.location import Location
 from midas.checker.dispatcher import CallResult
 from midas.checker.frames.utils import MethodRegistry, method
-from midas.checker.types import ColumnGroupBy, Function, Type
+from midas.checker.types import ColumnGroupBy, ColumnType, Function, TopType, Type
 
 if TYPE_CHECKING:
     from midas.checker.python import TypedExpr
@@ -22,39 +22,52 @@ class Call:
     positional: list[TypedExpr]
     keywords: dict[str, TypedExpr]
 
+    @property
+    def subject(self) -> TypedExpr:
+        return (self.groupby_expr, self.groupby)
+
 
 class ColumnGroupByMethodRegistry(MethodRegistry[Call]):
-    @method()
-    def mean(self, call: Call) -> Type:
-        bool_ = self.types.get_type("bool")
+    NAMED_ARGS: dict[str, str] = {
+        "numeric_only": "bool",
+        "skipna": "bool",
+        "engine": "str",
+        "engine_kwargs": "dict",
+    }
+
+    def _aggregate(
+        self,
+        call: Call,
+        args: list[str | tuple[str, str, bool]] = [],
+        *,
+        preserve_inner_type: bool = False,
+    ) -> Type:
+        real_args: list[Function.Argument] = []
+        for i, arg in enumerate(args):
+            match arg:
+                case str() as name:
+                    arg = Function.Argument(
+                        pos=i,
+                        name=name,
+                        type=self.types.get_type(self.NAMED_ARGS[name]),
+                        required=False,
+                    )
+                case (name, type, required):
+                    arg = Function.Argument(
+                        pos=i,
+                        name=name,
+                        type=self.types.get_type(type),
+                        required=required,
+                    )
+            real_args.append(arg)
+
         signature = Function(
-            args=[
-                Function.Argument(
-                    pos=0,
-                    name="numeric_only",
-                    type=bool_,
-                    required=False,
-                ),
-                Function.Argument(
-                    pos=1,
-                    name="skipna",
-                    type=bool_,
-                    required=False,
-                ),
-                Function.Argument(
-                    pos=2,
-                    name="engine",
-                    type=self.types.get_type("str"),
-                    required=False,
-                ),
-                Function.Argument(
-                    pos=3,
-                    name="engine_kwargs",
-                    type=self.types.get_type("dict"),
-                    required=False,
-                ),
-            ],
-            returns=call.groupby.column,
+            args=real_args,
+            returns=(
+                call.groupby.column
+                if preserve_inner_type
+                else ColumnType(type=TopType())
+            ),
         )
 
         result: CallResult = self.dispatcher.get_result(
@@ -64,3 +77,127 @@ class ColumnGroupByMethodRegistry(MethodRegistry[Call]):
             keywords=call.keywords,
         )
         return result.result
+
+    @method()
+    def kurt(self, call: Call) -> Type:
+        return self._aggregate(
+            call,
+            ["skipna", "numeric_only"],
+        )
+
+    @method()
+    def max(self, call: Call) -> Type:
+        return self._aggregate(
+            call,
+            [
+                "numeric_only",
+                (
+                    "min_count",
+                    "int",
+                    False,
+                ),
+                "skipna",
+                "engine",
+                "engine_kwargs",
+            ],
+            preserve_inner_type=True,
+        )
+
+    @method()
+    def mean(self, call: Call) -> Type:
+        return self._aggregate(
+            call,
+            ["numeric_only", "skipna", "engine", "engine_kwargs"],
+        )
+
+    @method()
+    def median(self, call: Call) -> Type:
+        return self._aggregate(
+            call,
+            ["numeric_only", "skipna"],
+            preserve_inner_type=True,
+        )
+
+    @method()
+    def min(self, call: Call) -> Type:
+        return self._aggregate(
+            call,
+            [
+                "numeric_only",
+                (
+                    "min_count",
+                    "int",
+                    False,
+                ),
+                "skipna",
+                "engine",
+                "engine_kwargs",
+            ],
+            preserve_inner_type=True,
+        )
+
+    @method()
+    def prod(self, call: Call) -> Type:
+        return self._aggregate(
+            call,
+            [
+                "numeric_only",
+                (
+                    "min_count",
+                    "int",
+                    False,
+                ),
+                "skipna",
+            ],
+        )
+
+    @method()
+    def std(self, call: Call) -> Type:
+        return self._aggregate(
+            call,
+            [
+                (
+                    "ddof",
+                    "int",
+                    False,
+                ),
+                "engine",
+                "engine_kwargs",
+                "numeric_only",
+                "skipna",
+            ],
+        )
+
+    @method()
+    def sum(self, call: Call) -> Type:
+        return self._aggregate(
+            call,
+            [
+                "numeric_only",
+                (
+                    "min_count",
+                    "int",
+                    False,
+                ),
+                "skipna",
+                "engine",
+                "engine_kwargs",
+            ],
+        )
+
+    @method()
+    def var(self, call: Call) -> Type:
+        return self._aggregate(
+            call,
+            [
+                (
+                    "var",
+                    "int",
+                    False,
+                ),
+                "engine",
+                "engine_kwargs",
+                "numeric_only",
+                "skipna",
+            ],
+        )

midas/checker/frames/column_manager.py

@@ -1,12 +1,13 @@
 from __future__ import annotations
 
-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.column_groupby_methods import Call as GroupByCall
 from midas.checker.frames.column_groupby_methods import ColumnGroupByMethodRegistry
 from midas.checker.frames.column_methods import Call, ColumnMethodRegistry
+from midas.checker.registry import TypesRegistry
 from midas.checker.types import ColumnGroupBy, ColumnType, Type
 
 if TYPE_CHECKING:
@@ -60,3 +61,18 @@ class ColumnManager:
             keywords=keywords,
         )
         return self.groupby_method_resolver.call(method, call)
+
+    def get_attribute(self, column: ColumnType, name: str) -> Optional[Type]:
+        types: TypesRegistry = self.typer.types
+        match name:
+            case "ndim" | "size":
+                return types.get_type("int")
+
+            case "shape":
+                return types.tuple_of("int")
+
+            case "T":
+                return column
+
+            case _:
+                return None

midas/checker/frames/column_methods.py

@@ -33,6 +33,10 @@ class Call:
     positional: list[TypedExpr]
     keywords: dict[str, TypedExpr]
 
+    @property
+    def subject(self) -> TypedExpr:
+        return (self.column_expr, self.column)
+
 
 class ColumnMethodRegistry(MethodRegistry[Call]):
     def _element_binary_op(self, call: Call, method: str) -> ColumnType:
@@ -69,8 +73,7 @@ class ColumnMethodRegistry(MethodRegistry[Call]):
                 new_column = ColumnType(type=new_inner_type)
         return new_column
 
-    @method("add", "__add__")
-    def add(self, call: Call) -> Type:
+    def _element_wise(self, call: Call, method: str) -> Type:
         # TODO: support add with scalar
 
         # Build signature with new column type and generic operand
@@ -87,7 +90,7 @@ class ColumnMethodRegistry(MethodRegistry[Call]):
                         required=True,
                     ),
                 ],
-                returns=self._element_binary_op(call, "__add__"),
+                returns=self._element_binary_op(call, method),
             ),
         )
 
@@ -105,8 +108,65 @@ class ColumnMethodRegistry(MethodRegistry[Call]):
 
         return result.result
 
-    @method()
-    def mean(self, call: Call) -> Type:
+    @method("add", "__add__")
+    def add(self, call: Call) -> Type:
+        return self._element_wise(call, "__add__")
+
+    @method("sub", "__sub__")
+    def sub(self, call: Call) -> Type:
+        return self._element_wise(call, "__sub__")
+
+    @method("mul", "__mul__")
+    def mul(self, call: Call) -> Type:
+        return self._element_wise(call, "__mul__")
+
+    @method("div", "truediv", "__truediv__")
+    def truediv(self, call: Call) -> Type:
+        return self._element_wise(call, "__truediv__")
+
+    @method("floordiv", "__floordiv__")
+    def floordiv(self, call: Call) -> Type:
+        return self._element_wise(call, "__floordiv__")
+
+    @method("mod", "__mod__")
+    def mod(self, call: Call) -> Type:
+        return self._element_wise(call, "__mod__")
+
+    @method("pow", "__pow__")
+    def pow(self, call: Call) -> Type:
+        return self._element_wise(call, "__pow__")
+
+    @method("lt", "__lt__")
+    def lt(self, call: Call) -> Type:
+        return self._element_wise(call, "__lt__")
+
+    @method("gt", "__gt__")
+    def gt(self, call: Call) -> Type:
+        return self._element_wise(call, "__gt__")
+
+    @method("le", "__le__")
+    def le(self, call: Call) -> Type:
+        return self._element_wise(call, "__le__")
+
+    @method("ge", "__ge__")
+    def ge(self, call: Call) -> Type:
+        return self._element_wise(call, "__ge__")
+
+    @method("ne", "__ne__")
+    def ne(self, call: Call) -> Type:
+        return self._element_wise(call, "__ne__")
+
+    @method("eq", "__eq__")
+    def eq(self, call: Call) -> Type:
+        return self._element_wise(call, "__eq__")
+
+    def _aggregate(
+        self,
+        call: Call,
+        kwargs: list[Function.Argument] = [],
+        *,
+        preserve_inner_type: bool = False,
+    ) -> Type:
         signature = Function(
             kw_args=[
                 Function.Argument(
@@ -114,9 +174,114 @@ class ColumnMethodRegistry(MethodRegistry[Call]):
                     name="axis",
                     type=TopType(),
                     required=False,
+                ),
+                *kwargs,
+            ],
+            returns=call.column if preserve_inner_type else ColumnType(type=TopType()),
+        )
+
+        result: CallResult = self.dispatcher.get_result(
+            location=call.location,
+            callee=signature,
+            positional=call.positional,
+            keywords=call.keywords,
+        )
+        return result.result
+
+    @method("kurtosis", "kurt")
+    def kurtosis(self, call: Call) -> Type:
+        return self._aggregate(call)
+
+    @method()
+    def max(self, call: Call) -> Type:
+        return self._aggregate(call, preserve_inner_type=True)
+
+    @method()
+    def mean(self, call: Call) -> Type:
+        return self._aggregate(call)
+
+    @method()
+    def median(self, call: Call) -> Type:
+        return self._aggregate(call, preserve_inner_type=True)
+
+    @method()
+    def min(self, call: Call) -> Type:
+        return self._aggregate(call, preserve_inner_type=True)
+
+    @method()
+    def mode(self, call: Call) -> Type:
+        return self._aggregate(call, preserve_inner_type=True)
+
+    @method("product", "prod")
+    def product(self, call: Call) -> Type:
+        return self._aggregate(call)
+
+    @method()
+    def std(self, call: Call) -> Type:
+        return self._aggregate(
+            call,
+            [
+                Function.Argument(
+                    pos=1,
+                    name="ddof",
+                    type=self.types.get_type("int"),
+                    required=False,
                 )
             ],
-            returns=ColumnType(type=TopType()),
+        )
+
+    @method()
+    def sum(self, call: Call) -> Type:
+        return self._aggregate(call)
+
+    @method()
+    def var(self, call: Call) -> Type:
+        return self._aggregate(
+            call,
+            [
+                Function.Argument(
+                    pos=1,
+                    name="var",
+                    type=self.types.get_type("int"),
+                    required=False,
+                )
+            ],
+        )
+
+    @method()
+    def head(self, call: Call) -> Type:
+        signature = Function(
+            args=[
+                Function.Argument(
+                    pos=0,
+                    name="n",
+                    type=self.types.get_type("int"),
+                    required=False,
+                ),
+            ],
+            returns=call.column,
+        )
+
+        result: CallResult = self.dispatcher.get_result(
+            location=call.location,
+            callee=signature,
+            positional=call.positional,
+            keywords=call.keywords,
+        )
+        return result.result
+
+    @method()
+    def tail(self, call: Call) -> Type:
+        signature = Function(
+            args=[
+                Function.Argument(
+                    pos=0,
+                    name="n",
+                    type=self.types.get_type("int"),
+                    required=False,
+                ),
+            ],
+            returns=call.column,
         )
 
         result: CallResult = self.dispatcher.get_result(
@@ -190,6 +355,21 @@ class ColumnMethodRegistry(MethodRegistry[Call]):
 
     def _assert_same_length(self, call_expr: p.Expr, column1: p.Expr, column2: p.Expr):
         func_name: str = "__midas_column_same_length__"
+
+        # Efficiently compute length
+        # https://stackoverflow.com/a/15943975/11109181
+        def len_of_col(col: ast.expr) -> ast.expr:
+            return ast.Call(
+                func=ast.Name(id="len"),
+                args=[
+                    ast.Attribute(
+                        value=col,
+                        attr="index",
+                    )
+                ],
+                keywords=[],
+            )
+
         self.assertions.define(
             func_name,
             ast.FunctionDef(
@@ -207,16 +387,10 @@ class ColumnMethodRegistry(MethodRegistry[Call]):
                 body=[
                     ast.Return(
                         value=ast.Compare(
-                            left=ast.Attribute(
-                                value=ast.Name(id="column1"),
-                                attr="size",
-                            ),
+                            left=len_of_col(ast.Name(id="column1")),
                             ops=[ast.Eq()],
                             comparators=[
-                                ast.Attribute(
-                                    value=ast.Name(id="column2"),
-                                    attr="size",
-                                )
+                                len_of_col(ast.Name(id="column2")),
                             ],
                         )
                     )

midas/checker/frames/frame_groupby_methods.py

@@ -5,9 +5,15 @@ from typing import TYPE_CHECKING
 
 import midas.ast.python as p
 from midas.ast.location import Location
-from midas.checker.dispatcher import CallResult
 from midas.checker.frames.utils import MethodRegistry, method
-from midas.checker.types import FrameGroupBy, Function, Type
+from midas.checker.types import (
+    ColumnGroupBy,
+    ColumnType,
+    DataFrameType,
+    FrameGroupBy,
+    Type,
+    UnknownType,
+)
 
 if TYPE_CHECKING:
     from midas.checker.python import TypedExpr
@@ -22,45 +28,76 @@ class Call:
     positional: list[TypedExpr]
     keywords: dict[str, TypedExpr]
 
+    @property
+    def subject(self) -> TypedExpr:
+        return (self.groupby_expr, self.groupby)
+
 
 class FrameGroupByMethodRegistry(MethodRegistry[Call]):
+    NAMED_ARGS: dict[str, str] = {
+        "numeric_only": "bool",
+        "skipna": "bool",
+        "engine": "str",
+        "engine_kwargs": "dict",
+    }
+
+    def _aggregate(self, call: Call, method: str) -> Type:
+        new_columns: list[DataFrameType.Column] = []
+
+        for column in call.groupby.frame.columns:
+            column_groupby: ColumnGroupBy = ColumnGroupBy(column=column.type)
+            result_type: Type = self.typer.call_method(
+                location=call.location,
+                call_expr=call.call_expr,
+                obj=(call.groupby_expr, column_groupby),
+                method_name=method,
+                positional=call.positional,
+                keywords=call.keywords,
+            )
+            if not isinstance(result_type, ColumnType):
+                result_type = ColumnType(type=UnknownType())
+            new_columns.append(
+                DataFrameType.Column(
+                    index=column.index,
+                    name=column.name,
+                    type=result_type,
+                )
+            )
+
+        return DataFrameType(columns=new_columns)
+
+    @method()
+    def kurt(self, call: Call) -> Type:
+        return self._aggregate(call, "kurt")
+
+    @method()
+    def max(self, call: Call) -> Type:
+        return self._aggregate(call, "max")
+
     @method()
     def mean(self, call: Call) -> Type:
-        bool_ = self.types.get_type("bool")
-        signature = Function(
-            args=[
-                Function.Argument(
-                    pos=0,
-                    name="numeric_only",
-                    type=bool_,
-                    required=False,
-                ),
-                Function.Argument(
-                    pos=1,
-                    name="skipna",
-                    type=bool_,
-                    required=False,
-                ),
-                Function.Argument(
-                    pos=2,
-                    name="engine",
-                    type=self.types.get_type("str"),
-                    required=False,
-                ),
-                Function.Argument(
-                    pos=3,
-                    name="engine_kwargs",
-                    type=self.types.get_type("dict"),
-                    required=False,
-                ),
-            ],
-            returns=call.groupby.frame,
-        )
+        return self._aggregate(call, "mean")
 
-        result: CallResult = self.dispatcher.get_result(
-            location=call.location,
-            callee=signature,
-            positional=call.positional,
-            keywords=call.keywords,
-        )
-        return result.result
+    @method()
+    def median(self, call: Call) -> Type:
+        return self._aggregate(call, "median")
+
+    @method()
+    def min(self, call: Call) -> Type:
+        return self._aggregate(call, "min")
+
+    @method()
+    def prod(self, call: Call) -> Type:
+        return self._aggregate(call, "prod")
+
+    @method()
+    def std(self, call: Call) -> Type:
+        return self._aggregate(call, "std")
+
+    @method()
+    def sum(self, call: Call) -> Type:
+        return self._aggregate(call, "sum")
+
+    @method()
+    def var(self, call: Call) -> Type:
+        return self._aggregate(call, "var")

midas/checker/frames/frame_manager.py

@@ -7,6 +7,7 @@ from midas.ast.location import Location
 from midas.checker.frames.frame_groupby_methods import Call as GroupByCall
 from midas.checker.frames.frame_groupby_methods import FrameGroupByMethodRegistry
 from midas.checker.frames.frame_methods import Call, FrameMethodRegistry
+from midas.checker.registry import TypesRegistry
 from midas.checker.reporter import FileReporter
 from midas.checker.types import (
     ColumnGroupBy,
@@ -240,3 +241,15 @@ class FrameManager:
             keywords=keywords,
         )
         return self.groupby_method_resolver.call(method, call)
+
+    def get_attribute(self, frame: DataFrameType, name: str) -> Optional[Type]:
+        types: TypesRegistry = self.typer.types
+        match name:
+            case "ndim" | "size":
+                return types.get_type("int")
+
+            case "shape":
+                return types.tuple_of("int", "int")
+
+            case _:
+                return None

midas/checker/frames/frame_methods.py

@@ -33,6 +33,10 @@ class Call:
     positional: list[TypedExpr]
     keywords: dict[str, TypedExpr]
 
+    @property
+    def subject(self) -> TypedExpr:
+        return (self.frame_expr, self.frame)
+
 
 class FrameMethodRegistry(MethodRegistry[Call]):
     def _get_method_result(
@@ -142,10 +146,8 @@ class FrameMethodRegistry(MethodRegistry[Call]):
 
         return DataFrameType(columns=new_columns)
 
-    @method("add", "__add__")
-    def add(self, call: Call) -> Type:
-        # TODO: support add with scalar, sequence, Series, dict
-
+    def _element_wise(self, call: Call, method: str) -> Type:
+        # TODO: support scalar, sequence, Series, dict operand
         # Build signature with new schema and generic operand
         signature = Function(
             args=[
@@ -156,7 +158,7 @@ class FrameMethodRegistry(MethodRegistry[Call]):
                     required=True,
                 ),
             ],
-            returns=self._element_binary_op(call, "__add__"),
+            returns=self._element_binary_op(call, method),
         )
 
         # Map arguments and compute result type
@@ -173,8 +175,59 @@ class FrameMethodRegistry(MethodRegistry[Call]):
 
         return result.result
 
-    @method()
-    def mean(self, call: Call) -> Type:
+    @method("add", "__add__")
+    def add(self, call: Call) -> Type:
+        return self._element_wise(call, "__add__")
+
+    @method("sub", "__sub__")
+    def sub(self, call: Call) -> Type:
+        return self._element_wise(call, "__sub__")
+
+    @method("mul", "__mul__")
+    def mul(self, call: Call) -> Type:
+        return self._element_wise(call, "__mul__")
+
+    @method("div", "truediv", "__truediv__")
+    def truediv(self, call: Call) -> Type:
+        return self._element_wise(call, "__truediv__")
+
+    @method("floordiv", "__floordiv__")
+    def floordiv(self, call: Call) -> Type:
+        return self._element_wise(call, "__floordiv__")
+
+    @method("mod", "__mod__")
+    def mod(self, call: Call) -> Type:
+        return self._element_wise(call, "__mod__")
+
+    @method("pow", "__pow__")
+    def pow(self, call: Call) -> Type:
+        return self._element_wise(call, "__pow__")
+
+    @method("lt", "__lt__")
+    def lt(self, call: Call) -> Type:
+        return self._element_wise(call, "__lt__")
+
+    @method("gt", "__gt__")
+    def gt(self, call: Call) -> Type:
+        return self._element_wise(call, "__gt__")
+
+    @method("le", "__le__")
+    def le(self, call: Call) -> Type:
+        return self._element_wise(call, "__le__")
+
+    @method("ge", "__ge__")
+    def ge(self, call: Call) -> Type:
+        return self._element_wise(call, "__ge__")
+
+    @method("ne", "__ne__")
+    def ne(self, call: Call) -> Type:
+        return self._element_wise(call, "__ne__")
+
+    @method("eq", "__eq__")
+    def eq(self, call: Call) -> Type:
+        return self._element_wise(call, "__eq__")
+
+    def _aggregate(self, call: Call, kwargs: list[Function.Argument] = []) -> Type:
         with_axis = Function(
             kw_args=[
                 Function.Argument(
@@ -182,7 +235,8 @@ class FrameMethodRegistry(MethodRegistry[Call]):
                     name="axis",
                     type=self.types.get_type("int"),
                     required=False,
-                )
+                ),
+                *kwargs,
             ],
             returns=ColumnType(type=TopType()),
         )
@@ -193,7 +247,8 @@ class FrameMethodRegistry(MethodRegistry[Call]):
                     name="axis",
                     type=self.types.get_type("None"),
                     required=True,
-                )
+                ),
+                *kwargs,
             ],
             returns=TopType(),
         )
@@ -212,6 +267,110 @@ class FrameMethodRegistry(MethodRegistry[Call]):
         )
         return result.result
 
+    @method("kurtosis", "kurt")
+    def kurtosis(self, call: Call) -> Type:
+        return self._aggregate(call)
+
+    @method()
+    def max(self, call: Call) -> Type:
+        return self._aggregate(call)
+
+    @method()
+    def mean(self, call: Call) -> Type:
+        return self._aggregate(call)
+
+    @method()
+    def median(self, call: Call) -> Type:
+        return self._aggregate(call)
+
+    @method()
+    def min(self, call: Call) -> Type:
+        return self._aggregate(call)
+
+    @method()
+    def mode(self, call: Call) -> Type:
+        return self._aggregate(call)
+
+    @method("product", "prod")
+    def product(self, call: Call) -> Type:
+        return self._aggregate(call)
+
+    @method()
+    def std(self, call: Call) -> Type:
+        return self._aggregate(
+            call,
+            [
+                Function.Argument(
+                    pos=1,
+                    name="ddof",
+                    type=self.types.get_type("int"),
+                    required=False,
+                )
+            ],
+        )
+
+    @method()
+    def sum(self, call: Call) -> Type:
+        return self._aggregate(call)
+
+    @method()
+    def var(self, call: Call) -> Type:
+        return self._aggregate(
+            call,
+            [
+                Function.Argument(
+                    pos=1,
+                    name="var",
+                    type=self.types.get_type("int"),
+                    required=False,
+                )
+            ],
+        )
+
+    @method()
+    def head(self, call: Call) -> Type:
+        signature = Function(
+            args=[
+                Function.Argument(
+                    pos=0,
+                    name="n",
+                    type=self.types.get_type("int"),
+                    required=False,
+                ),
+            ],
+            returns=call.frame,
+        )
+
+        result: CallResult = self.dispatcher.get_result(
+            location=call.location,
+            callee=signature,
+            positional=call.positional,
+            keywords=call.keywords,
+        )
+        return result.result
+
+    @method()
+    def tail(self, call: Call) -> Type:
+        signature = Function(
+            args=[
+                Function.Argument(
+                    pos=0,
+                    name="n",
+                    type=self.types.get_type("int"),
+                    required=False,
+                ),
+            ],
+            returns=call.frame,
+        )
+
+        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")
@@ -275,6 +434,21 @@ class FrameMethodRegistry(MethodRegistry[Call]):
 
     def _assert_same_length(self, call_expr: p.Expr, frame1: p.Expr, frame2: p.Expr):
         func_name: str = "__midas_frame_same_length__"
+
+        # Efficiently compute length
+        # https://stackoverflow.com/a/15943975/11109181
+        def len_of_df(df: ast.expr) -> ast.expr:
+            return ast.Call(
+                func=ast.Name(id="len"),
+                args=[
+                    ast.Attribute(
+                        value=df,
+                        attr="index",
+                    )
+                ],
+                keywords=[],
+            )
+
         self.assertions.define(
             func_name,
             ast.FunctionDef(
@@ -292,17 +466,9 @@ class FrameMethodRegistry(MethodRegistry[Call]):
                 body=[
                     ast.Return(
                         value=ast.Compare(
-                            left=ast.Attribute(
-                                value=ast.Name(id="frame1"),
-                                attr="size",
-                            ),
+                            left=len_of_df(ast.Name(id="frame1")),
                             ops=[ast.Eq()],
-                            comparators=[
-                                ast.Attribute(
-                                    value=ast.Name(id="frame2"),
-                                    attr="size",
-                                )
-                            ],
+                            comparators=[len_of_df(ast.Name(id="frame2"))],
                         )
                     )
                 ],

midas/checker/frames/utils.py

@@ -20,7 +20,7 @@ from midas.checker.types import Type, UnknownType
 from midas.generator.collector import AssertionCollector
 
 if TYPE_CHECKING:
-    from midas.checker.python import PythonTyper
+    from midas.checker.python import PythonTyper, TypedExpr
 
 
 class _MethodRegistryMeta(type):
@@ -41,12 +41,18 @@ class _MethodRegistryMeta(type):
         return new_class
 
 
-class HasLocation(Protocol):
+class MethodCall(Protocol):
     @property
     def location(self) -> Location: ...
 
+    @property
+    def call_expr(self) -> p.Expr: ...
 
-T = TypeVar("T", bound=HasLocation)
+    @property
+    def subject(self) -> TypedExpr: ...
+
+
+T = TypeVar("T", bound=MethodCall)
 
 
 class MethodRegistry(Generic[T], metaclass=_MethodRegistryMeta):
@@ -72,7 +78,9 @@ class MethodRegistry(Generic[T], metaclass=_MethodRegistryMeta):
     def call(self, method: str, call: T) -> Type:
         func: Optional[Callable[[Self, T], Type]] = self._methods.get(method)
         if func is None:
-            self.reporter.warning(call.location, f"Unknown method {method}")
+            self.reporter.warning(
+                call.location, f"Unknown method {method} on {call.subject[1]}"
+            )
             return UnknownType()
         return func(self, call)
 

midas/checker/preamble.py

@@ -108,8 +108,8 @@ class Preamble(Environment):
             ],
         )
 
-    def _list_of(self, item_type: Type) -> Type:
-        return self._types.apply_generic(self._types.get_type("list"), [item_type])
+    def _list_of(self, item_type: str | Type) -> Type:
+        return self._types.list_of(item_type)
 
     def _def_type_constructor(
         self, name: str, py_function: Optional[Callable[..., Any]] = None

midas/checker/python.py

@@ -222,7 +222,7 @@ class PythonTyper(
         method_name: str,
         positional: list[TypedExpr],
         keywords: dict[str, TypedExpr],
-    ) -> Optional[Type]:
+    ) -> Type:
         unfolded: Type = unfold_type(obj[1])
         match unfolded:
             case DataFrameType():
@@ -580,9 +580,8 @@ class PythonTyper(
         right: TypedExpr,
         method: str,
     ) -> Type:
-        result: Optional[Type]
         try:
-            result = self.call_method(
+            return self.call_method(
                 location=location,
                 call_expr=expr,
                 obj=left,
@@ -597,8 +596,6 @@ class PythonTyper(
             )
             return UnknownType()
 
-        return result or UnknownType()
-
     def visit_unary_expr(self, expr: p.UnaryExpr) -> Type:
         method: Optional[str] = PY_UNARY_METHODS.get(expr.operator.__class__)
         if method is None:
@@ -610,9 +607,8 @@ class PythonTyper(
 
         operand: Type = self.type_of(expr.right)
 
-        result: Optional[Type]
         try:
-            result = self.call_method(
+            return self.call_method(
                 location=expr.location,
                 call_expr=expr,
                 obj=(expr.right, operand),
@@ -627,8 +623,6 @@ class PythonTyper(
             )
             return UnknownType()
 
-        return result or UnknownType()
-
     def visit_call_expr(self, expr: p.CallExpr) -> Type:
         match expr.callee:
             case p.VariableExpr(name="TypeVar"):
@@ -644,16 +638,13 @@ class PythonTyper(
         match expr.callee:
             case p.GetExpr(object=obj, name=method):
                 obj_type: Type = self.type_of(obj)
-                return (
-                    self.call_method(
-                        location=expr.location,
-                        call_expr=expr,
-                        obj=(obj, obj_type),
-                        method_name=method,
-                        positional=positional,
-                        keywords=keywords,
-                    )
-                    or UnknownType()
+                return self.call_method(
+                    location=expr.location,
+                    call_expr=expr,
+                    obj=(obj, obj_type),
+                    method_name=method,
+                    positional=positional,
+                    keywords=keywords,
                 )
 
         callee: Type = self.type_of(expr.callee)
@@ -668,6 +659,14 @@ class PythonTyper(
     def visit_get_expr(self, expr: p.GetExpr) -> Type:
         object: Type = self.type_of(expr.object)
         member: Optional[Type] = self.types.lookup_member(object, expr.name)
+
+        if member is None:
+            match object:
+                case DataFrameType():
+                    member = self.frame_mgr.get_attribute(object, expr.name)
+                case ColumnType():
+                    member = self.column_mgr.get_attribute(object, expr.name)
+
         if member is None:
             self.reporter.warning(
                 expr.location, f"Unknown member '{expr.name}' of {object}"

midas/checker/registry.py

@@ -113,6 +113,15 @@ class TypesRegistry:
             raise ValueError(f"Predicate {name} already defined")
         self._predicates[name] = predicate
 
+    def is_builtin_subtype(self, name1: str, name2: str) -> bool:
+        subtypes: set[str] = BUILTIN_SUBTYPES.get(name2, set())
+        if name1 in subtypes:
+            return True
+        for subtype in subtypes:
+            if self.is_builtin_subtype(name1, subtype):
+                return True
+        return False
+
     def is_subtype(self, type1: Type, type2: Type) -> bool:
         """Check whether `type1` is a subtype of `type2`
 
@@ -150,7 +159,7 @@ class TypesRegistry:
                 return self.is_subtype(base1, type2)
 
             case (BaseType(name=name1), BaseType(name=name2)):
-                return name1 in BUILTIN_SUBTYPES.get(name2, set())
+                return self.is_builtin_subtype(name1, name2)
 
             case (ComplexType(properties=props1), ComplexType(properties=props2)):
                 for k, t in props2.items():
@@ -443,3 +452,29 @@ class TypesRegistry:
 
     def lookup_predicate(self, name: str) -> Optional[Predicate]:
         return self._predicates.get(name)
+
+    def _by_name_or_type(self, name_or_type: str | Type) -> Type:
+        if isinstance(name_or_type, str):
+            return self.get_type(name_or_type)
+        return name_or_type
+
+    def list_of(self, item_type: str | Type) -> Type:
+        list_ = self.get_type("list")
+        return self.apply_generic(list_, [self._by_name_or_type(item_type)])
+
+    def tuple_of(self, *item_types: str | Type) -> Type:
+        tuple_ = self.get_type("tuple")
+        return self.apply_generic(
+            tuple_,
+            [self._by_name_or_type(item_type) for item_type in item_types],
+        )
+
+    def dict_of(self, key_type: str | Type, value_type: str | Type) -> Type:
+        dict_ = self.get_type("dict")
+        return self.apply_generic(
+            dict_,
+            [
+                self._by_name_or_type(key_type),
+                self._by_name_or_type(value_type),
+            ],
+        )

tests/__main__.py

@@ -0,0 +1,43 @@
+from typing import Type
+
+from midas.cli.ansi import Ansi
+from tests.base import Tester
+from tests.checker import CheckerTester
+from tests.generator import GeneratorTester
+from tests.midas import MidasTester
+from tests.python import PythonTester
+
+
+def print_banner(name: str):
+    horizontal: str = "+" + "-" * (len(name) + 2) + "+"
+    print(horizontal)
+    print(f"| {name} |")
+    print(horizontal)
+
+
+def run_tests(tester_cls: Type[Tester]) -> bool:
+    print_banner(tester_cls.__name__)
+    tester: Tester = tester_cls()
+    success: bool = tester.run_all_tests()
+    print()
+    return success
+
+
+def main():
+    testers: list[Type[Tester]] = [
+        PythonTester,
+        MidasTester,
+        CheckerTester,
+        GeneratorTester,
+    ]
+
+    success: bool = all(map(run_tests, testers))
+
+    if success:
+        print(Ansi.FG(Ansi.BRIGHT_GREEN) + "All tests passed!" + Ansi.RESET)
+    else:
+        print(Ansi.FG(Ansi.BRIGHT_RED) + "Some tests failed!" + Ansi.RESET)
+
+
+if __name__ == "__main__":
+    main()

tests/base.py

@@ -7,6 +7,8 @@ from abc import ABC, abstractmethod
 from pathlib import Path
 from typing import Iterator, Protocol
 
+from midas.cli.ansi import Ansi
+
 
 class CaseResult(Protocol):
     def dumps(self) -> str: ...
@@ -44,8 +46,11 @@ class Tester(ABC):
 
         print(rule)
         for i, test in enumerate(tests):
-            print(f"Case {i+1}/{n}: {test.resolve().relative_to(self.CASES_DIR)}")
+            path: Path = test.resolve().relative_to(self.CASES_DIR)
+            print(f"{Ansi.FG(Ansi.BRIGHT_CYAN)}Case {i+1}/{n}: {path}{Ansi.RESET}")
+            print(Ansi.DIM, end="")
             success: bool = self._run_test(test)
+            print(Ansi.RESET, end="")
             if success:
                 successes += 1
             else:
@@ -146,8 +151,9 @@ class Tester(ABC):
                 if not success:
                     sys.exit(1)
             case None:
-                print("No subcommand provided. Available subcommands: run, update")
-                sys.exit(1)
+                success: bool = tester.run_all_tests()
+                if not success:
+                    sys.exit(1)
             case _:
                 print(f"Unknown subcommand '{args.subcommand}'")
                 sys.exit(1)

tests/cases/checker/09_frame_ops.py

@@ -0,0 +1,117 @@
+# type: ignore
+# ruff: disable [F821]
+
+df1: Frame[a:int, b:float]
+df2: Frame[a:int, b:float]
+
+_: Any
+
+# Arithmetic
+_ = df1 + df2
+_ = df1 - df2
+_ = df1 * df2
+_ = df1 / df2
+_ = df1 // df2
+_ = df1 % df2
+_ = df1**df2
+
+# Comparisons
+_ = df1 < df2
+_ = df1 > df2
+_ = df1 <= df2
+_ = df1 >= df2
+_ = df1 != df2
+_ = df1 == df2
+
+# Aggregate
+_ = df1.kurt()
+_ = df1.kurtosis()
+_ = df1.max()
+_ = df1.mean()
+_ = df1.median()
+_ = df1.min()
+_ = df1.mode()
+_ = df1.prod()
+_ = df1.product()
+_ = df1.std()
+_ = df1.sum()
+_ = df1.var()
+
+# Groupby
+df_gb = df1.groupby(by="a")
+
+_ = df_gb.kurt()
+_ = df_gb.max()
+_ = df_gb.mean()
+_ = df_gb.median()
+_ = df_gb.min()
+_ = df_gb.prod()
+_ = df_gb.std()
+_ = df_gb.sum()
+_ = df_gb.var()
+
+
+# Columns
+
+col1 = df1["a"]
+col2 = df1["a"]
+
+# Arithmetic
+_ = col1 + col2
+_ = col1 - col2
+_ = col1 * col2
+_ = col1 / col2
+_ = col1 // col2
+_ = col1 % col2
+_ = col1**col2
+
+# Comparisons
+_ = col1 < col2
+_ = col1 > col2
+_ = col1 <= col2
+_ = col1 >= col2
+_ = col1 != col2
+_ = col1 == col2
+
+# Aggregate
+_ = col1.kurt()
+_ = col1.kurtosis()
+_ = col1.max()
+_ = col1.mean()
+_ = col1.median()
+_ = col1.min()
+_ = col1.mode()
+_ = col1.prod()
+_ = col1.product()
+_ = col1.std()
+_ = col1.sum()
+_ = col1.var()
+
+# Groupby
+col_gb = col1.groupby(level=0)
+
+_ = col_gb.kurt()
+_ = col_gb.max()
+_ = col_gb.mean()
+_ = col_gb.median()
+_ = col_gb.min()
+_ = col_gb.prod()
+_ = col_gb.std()
+_ = col_gb.sum()
+_ = col_gb.var()
+
+# Attributes
+_ = df1.ndim  # int
+_ = df1.size  # int
+_ = df1.shape  # (int, int)
+_ = col1.ndim  # int
+_ = col1.size  # int
+_ = col1.shape  # (int)
+_ = col1.T  # Column[int]
+
+
+# Misc
+_ = df1.head()
+_ = df1.tail()
+_ = col1.head()
+_ = col1.tail()