Files
midas/midas/checker/frame_methods.py

199 lines
5.6 KiB
Python

from __future__ import annotations
from dataclasses import dataclass
from typing import TYPE_CHECKING, Any, Callable, Optional
from midas.ast.location import Location
from midas.checker.registry import TypesRegistry
from midas.checker.reporter import FileReporter
from midas.checker.types import (
ColumnType,
DataFrameType,
Function,
OverloadedFunction,
TopType,
Type,
UnknownType,
unfold_type,
)
if TYPE_CHECKING:
from midas.checker.python import PythonTyper, TypedExpr
@staticmethod
def frame_method(*names: str):
def wrapper(func):
names_: tuple[str, ...] = names
if len(names_) == 0:
names_ = (func.__name__,)
setattr(func, "__method_names__", names_)
return func
return wrapper
@dataclass(frozen=True, kw_only=True)
class Call:
location: Location
frame: DataFrameType
positional: list[TypedExpr]
keywords: dict[str, TypedExpr]
class _MethodRegistryMeta(type):
_methods: dict[str, Callable[..., Type]] = {}
def __new__(
cls,
name: str,
bases: tuple[type, ...],
namespace: dict[str, Any],
):
new_class = super().__new__(cls, name, bases, namespace)
new_class._methods = {}
for attr in namespace.values():
if callable(attr) and hasattr(attr, "__method_names__"):
for name in attr.__method_names__: # type: ignore
new_class._methods[name] = attr # type: ignore
return new_class
class MethodRegistry(metaclass=_MethodRegistryMeta):
def __init__(self, typer: PythonTyper) -> None:
self.typer: PythonTyper = typer
@property
def reporter(self) -> FileReporter:
return self.typer.reporter
@property
def types(self) -> TypesRegistry:
return self.typer.types
def call(
self,
method: str,
call: Call,
) -> Type:
func: Optional[Callable[..., Type]] = self._methods.get(method)
if func is None:
self.reporter.warning(call.location, f"Unknown method {method}")
return UnknownType()
return func(self, call)
@frame_method("add", "__add__")
def add(
self,
call: Call,
) -> Type:
# TODO: support add with scalar, sequence, Series, dict
# TODO: check operation exists on inner column types
new_columns: list[DataFrameType.Column] = []
by_name: dict[str, DataFrameType.Column] = {}
frame2: Optional[DataFrameType] = None
if len(call.positional) != 0:
other: Type = call.positional[0][1]
unfolded_other: Type = unfold_type(other)
if isinstance(unfolded_other, DataFrameType):
frame2 = unfolded_other
by_name = {
col.name: col for col in frame2.columns if col.name is not None
}
in_frame1: set[str] = set()
for column in call.frame.columns:
if column.name is not None:
in_frame1.add(column.name)
col_type1: Type = column.type
col_type: Type = ColumnType(type=UnknownType())
if column.name in by_name:
column2 = by_name[column.name]
col_type2: Type = column2.type
if self.types.are_equivalent(col_type2, col_type1):
col_type = col_type1
new_column = DataFrameType.Column(
index=column.index,
name=column.name,
type=col_type,
)
new_columns.append(new_column)
if frame2 is not None:
for column in frame2.columns:
if column.name in in_frame1:
continue
new_columns.append(
DataFrameType.Column(
index=len(new_columns),
name=column.name,
type=ColumnType(type=UnknownType()),
)
)
signature = Function(
args=[
Function.Argument(
pos=0,
name="other",
type=DataFrameType(columns=[]),
required=True,
),
],
returns=DataFrameType(columns=new_columns),
)
return (
self.typer._get_call_result(
location=call.location,
callee=signature,
positional=call.positional,
keywords=call.keywords,
)
or UnknownType()
)
@frame_method()
def mean(self, call: Call) -> Type:
with_axis = Function(
kw_args=[
Function.Argument(
pos=0,
name="axis",
type=self.types.get_type("int"),
required=False,
)
],
returns=ColumnType(type=TopType()),
)
without_axis = Function(
kw_args=[
Function.Argument(
pos=0,
name="axis",
type=self.types.get_type("None"),
required=True,
)
],
returns=TopType(),
)
overload = OverloadedFunction(
overloads=[
with_axis,
without_axis,
]
)
return (
self.typer._get_call_result(
location=call.location,
callee=overload,
positional=call.positional,
keywords=call.keywords,
)
or UnknownType()
)