Remove Expr._required_attribute

dask_expr/_core.py

@@ -39,18 +39,6 @@ def __init__(self, *args, **kwargs):
         assert not kwargs, kwargs
         operands = [_unpack_collections(o) for o in operands]
         self.operands = operands
-        if self._required_attribute:
-            dep = next(iter(self.dependencies()))._meta
-            if not hasattr(dep, self._required_attribute):
-                # Raise a ValueError instead of AttributeError to
-                # avoid infinite recursion
-                raise ValueError(f"{dep} has no attribute {self._required_attribute}")
-
-    @property
-    def _required_attribute(self) -> str:
-        # Specify if the first `dependency` must support
-        # a specific attribute for valid behavior.
-        return None
 
     def __str__(self):
         s = ", ".join(
@@ -407,8 +395,8 @@ def __getattr__(self, key):
         try:
             return object.__getattribute__(self, key)
         except AttributeError as err:
-            if key == "_meta":
-                # Avoid a recursive loop if/when `self._meta`
+            if key.startswith("_meta"):
+                # Avoid a recursive loop if/when `self._meta*`
                 # produces an `AttributeError`
                 raise RuntimeError(
                     f"Failed to generate metadata for {self}. "
@@ -422,6 +410,8 @@ def __getattr__(self, key):
             if key in _parameters:
                 idx = _parameters.index(key)
                 return self.operands[idx]
+            if is_dataframe_like(self._meta) and key in self._meta.columns:
+                return self[key]
 
             link = "https://github.com/dask-contrib/dask-expr/blob/main/README.md#api-coverage"
             raise AttributeError(

dask_expr/_expr.py

@@ -88,35 +88,6 @@ def optimize(self, **kwargs):
     def __hash__(self):
         return hash(self._name)
 
-    def __getattr__(self, key):
-        try:
-            return object.__getattribute__(self, key)
-        except AttributeError as err:
-            if key == "_meta":
-                # Avoid a recursive loop if/when `self._meta`
-                # produces an `AttributeError`
-                raise RuntimeError(
-                    f"Failed to generate metadata for {self}. "
-                    "This operation may not be supported by the current backend."
-                )
-
-            # Allow operands to be accessed as attributes
-            # as long as the keys are not already reserved
-            # by existing methods/properties
-            _parameters = type(self)._parameters
-            if key in _parameters:
-                idx = _parameters.index(key)
-                return self.operands[idx]
-            if is_dataframe_like(self._meta) and key in self._meta.columns:
-                return self[key]
-
-            link = "https://github.com/dask-contrib/dask-expr/blob/main/README.md#api-coverage"
-            raise AttributeError(
-                f"{err}\n\n"
-                "This often means that you are attempting to use an unsupported "
-                f"API function. Current API coverage is documented here: {link}."
-            )
-
     @property
     def index(self):
         return Index(self)
@@ -493,12 +464,6 @@ class Blockwise(Expr):
     _projection_passthrough = False
     _filter_passthrough = False
 
-    @property
-    def _required_attribute(self):
-        if isinstance(self.operation, type(M.method_caller)):
-            return self.operation.method
-        return None
-
     @functools.cached_property
     def _meta(self):
         args = [op._meta if isinstance(op, Expr) else op for op in self._args]

dask_expr/_reductions.py

@@ -863,27 +863,27 @@ class IdxMin(Reduction):
     reduction_chunk = idxmaxmin_chunk
     reduction_combine = idxmaxmin_combine
     reduction_aggregate = idxmaxmin_agg
-    _required_attribute = "idxmin"
+    _reduction_attribute = "idxmin"
 
     @property
     def chunk_kwargs(self):
         return dict(
             skipna=self.skipna,
-            fn=self._required_attribute,
+            fn=self._reduction_attribute,
             numeric_only=self.numeric_only,
         )
 
     @property
     def combine_kwargs(self):
-        return dict(skipna=self.skipna, fn=self._required_attribute)
+        return dict(skipna=self.skipna, fn=self._reduction_attribute)
 
     @property
     def aggregate_kwargs(self):
         return {**self.chunk_kwargs, "scalar": is_series_like(self.frame._meta)}
 
 
 class IdxMax(IdxMin):
-    _required_attribute = "idxmax"
+    _reduction_attribute = "idxmax"
 
 
 class Cov(Reduction):
@@ -967,7 +967,6 @@ def _simplify_up(self, parent, dependents):
 class NBytes(Reduction):
     # Only supported for Series objects
     reduction_aggregate = sum
-    _required_attribute = "nbytes"
 
     @staticmethod
     def reduction_chunk(ser):