Refactor Python and Cython internals for groupby aggregation

python/cudf/cudf/_lib/aggregation.pxd

@@ -4,7 +4,7 @@ from libcpp.memory cimport unique_ptr
 from cudf._lib.cpp.aggregation cimport aggregation
 
 
-cdef unique_ptr[aggregation] make_aggregation(op, kwargs=*) except *
-
 cdef class Aggregation:
     cdef unique_ptr[aggregation] c_obj
+
+cdef Aggregation make_aggregation(op, kwargs=*)

python/cudf/cudf/_lib/aggregation.pyx

@@ -56,85 +56,55 @@ class AggregationKind(Enum):
 
 
 cdef class Aggregation:
-    def __init__(self, op, **kwargs):
-        self.c_obj = move(make_aggregation(op, kwargs))
-
+    """A Cython wrapper for aggregations.
+
+    **This class should never be instantiated using a standard constructor,
+    only using one of its many factories.** These factories handle mapping
+    different cudf operations to their libcudf analogs, e.g.
+    `cudf.DataFrame.idxmin` -> `libcudf.argmin`. Additionally, they perform
+    any additional configuration needed to translate Python arguments into
+    their corresponding C++ types (for instance, C++ enumerations used for
+    flag arguments). The factory approach is necessary to support operations
+    like `df.agg(lambda x: x.sum())`; such functions are called with this
+    class as an argument to generation the desired aggregation.
+    """
     @property
     def kind(self):
-        return AggregationKind(self.c_obj.get()[0].kind).name.lower()
-
-
-cdef unique_ptr[aggregation] make_aggregation(op, kwargs={}) except *:
-    """
-    Parameters
-    ----------
-    op : str or callable
-        If callable, must meet one of the following requirements:
-
-        * Is of the form lambda x: x.agg(*args, **kwargs), where
-          `agg` is the name of a supported aggregation. Used to
-          to specify aggregations that take arguments, e.g.,
-          `lambda x: x.quantile(0.5)`.
-        * Is a user defined aggregation function that operates on
-          group values. In this case, the output dtype must be
-          specified in the `kwargs` dictionary.
-
-    Returns
-    -------
-    unique_ptr[aggregation]
-    """
-    cdef Aggregation agg
-    if isinstance(op, str):
-        agg = getattr(_AggregationFactory, op)(**kwargs)
-    elif callable(op):
-        if op is list:
-            agg = _AggregationFactory.collect()
-        elif "dtype" in kwargs:
-            agg = _AggregationFactory.from_udf(op, **kwargs)
-        else:
-            agg = op(_AggregationFactory)
-    else:
-        raise TypeError("Unknown aggregation {}".format(op))
-    return move(agg.c_obj)
-
-# The Cython pattern below enables us to create an Aggregation
-# without ever calling its `__init__` method, which would otherwise
-# result in a RecursionError.
-cdef class _AggregationFactory:
+        return AggregationKind(self.c_obj.get()[0].kind).name
 
     @classmethod
     def sum(cls):
-        cdef Aggregation agg = Aggregation.__new__(Aggregation)
+        cdef Aggregation agg = cls()
         agg.c_obj = move(libcudf_aggregation.make_sum_aggregation())
         return agg
 
     @classmethod
     def min(cls):
-        cdef Aggregation agg = Aggregation.__new__(Aggregation)
+        cdef Aggregation agg = cls()
         agg.c_obj = move(libcudf_aggregation.make_min_aggregation())
         return agg
 
     @classmethod
     def max(cls):
-        cdef Aggregation agg = Aggregation.__new__(Aggregation)
+        cdef Aggregation agg = cls()
         agg.c_obj = move(libcudf_aggregation.make_max_aggregation())
         return agg
 
     @classmethod
     def idxmin(cls):
-        cdef Aggregation agg = Aggregation.__new__(Aggregation)
+        cdef Aggregation agg = cls()
         agg.c_obj = move(libcudf_aggregation.make_argmin_aggregation())
         return agg
 
     @classmethod
     def idxmax(cls):
-        cdef Aggregation agg = Aggregation.__new__(Aggregation)
+        cdef Aggregation agg = cls()
         agg.c_obj = move(libcudf_aggregation.make_argmax_aggregation())
         return agg
 
     @classmethod
     def mean(cls):
-        cdef Aggregation agg = Aggregation.__new__(Aggregation)
+        cdef Aggregation agg = cls()
         agg.c_obj = move(libcudf_aggregation.make_mean_aggregation())
         return agg
 
@@ -146,15 +116,15 @@ cdef class _AggregationFactory:
         else:
             c_null_handling = libcudf_types.null_policy.INCLUDE
 
-        cdef Aggregation agg = Aggregation.__new__(Aggregation)
+        cdef Aggregation agg = cls()
         agg.c_obj = move(libcudf_aggregation.make_count_aggregation(
             c_null_handling
         ))
         return agg
 
     @classmethod
     def size(cls):
-        cdef Aggregation agg = Aggregation.__new__(Aggregation)
+        cdef Aggregation agg = cls()
         agg.c_obj = move(libcudf_aggregation.make_count_aggregation(
             <libcudf_types.null_policy><underlying_type_t_null_policy>(
                 NullHandling.INCLUDE
@@ -164,63 +134,63 @@ cdef class _AggregationFactory:
 
     @classmethod
     def nunique(cls):
-        cdef Aggregation agg = Aggregation.__new__(Aggregation)
+        cdef Aggregation agg = cls()
         agg.c_obj = move(libcudf_aggregation.make_nunique_aggregation())
         return agg
 
     @classmethod
     def nth(cls, libcudf_types.size_type size):
-        cdef Aggregation agg = Aggregation.__new__(Aggregation)
+        cdef Aggregation agg = cls()
         agg.c_obj = move(
             libcudf_aggregation.make_nth_element_aggregation(size)
         )
         return agg
 
     @classmethod
     def any(cls):
-        cdef Aggregation agg = Aggregation.__new__(Aggregation)
+        cdef Aggregation agg = cls()
         agg.c_obj = move(libcudf_aggregation.make_any_aggregation())
         return agg
 
     @classmethod
     def all(cls):
-        cdef Aggregation agg = Aggregation.__new__(Aggregation)
+        cdef Aggregation agg = cls()
         agg.c_obj = move(libcudf_aggregation.make_all_aggregation())
         return agg
 
     @classmethod
     def product(cls):
-        cdef Aggregation agg = Aggregation.__new__(Aggregation)
+        cdef Aggregation agg = cls()
         agg.c_obj = move(libcudf_aggregation.make_product_aggregation())
         return agg
 
     @classmethod
     def sum_of_squares(cls):
-        cdef Aggregation agg = Aggregation.__new__(Aggregation)
+        cdef Aggregation agg = cls()
         agg.c_obj = move(libcudf_aggregation.make_sum_of_squares_aggregation())
         return agg
 
     @classmethod
     def var(cls, ddof=1):
-        cdef Aggregation agg = Aggregation.__new__(Aggregation)
+        cdef Aggregation agg = cls()
         agg.c_obj = move(libcudf_aggregation.make_variance_aggregation(ddof))
         return agg
 
     @classmethod
     def std(cls, ddof=1):
-        cdef Aggregation agg = Aggregation.__new__(Aggregation)
+        cdef Aggregation agg = cls()
         agg.c_obj = move(libcudf_aggregation.make_std_aggregation(ddof))
         return agg
 
     @classmethod
     def median(cls):
-        cdef Aggregation agg = Aggregation.__new__(Aggregation)
+        cdef Aggregation agg = cls()
         agg.c_obj = move(libcudf_aggregation.make_median_aggregation())
         return agg
 
     @classmethod
     def quantile(cls, q=0.5, interpolation="linear"):
-        cdef Aggregation agg = Aggregation.__new__(Aggregation)
+        cdef Aggregation agg = cls()
 
         if not pd.api.types.is_list_like(q):
             q = [q]
@@ -240,19 +210,19 @@ cdef class _AggregationFactory:
 
     @classmethod
     def collect(cls):
-        cdef Aggregation agg = Aggregation.__new__(Aggregation)
+        cdef Aggregation agg = cls()
         agg.c_obj = move(libcudf_aggregation.make_collect_list_aggregation())
         return agg
 
     @classmethod
     def unique(cls):
-        cdef Aggregation agg = Aggregation.__new__(Aggregation)
+        cdef Aggregation agg = cls()
         agg.c_obj = move(libcudf_aggregation.make_collect_set_aggregation())
         return agg
 
     @classmethod
     def from_udf(cls, op, *args, **kwargs):
-        cdef Aggregation agg = Aggregation.__new__(Aggregation)
+        cdef Aggregation agg = cls()
 
         cdef libcudf_types.type_id tid
         cdef libcudf_types.data_type out_dtype
@@ -282,3 +252,42 @@ cdef class _AggregationFactory:
             libcudf_aggregation.udf_type.PTX, cpp_str, out_dtype
         ))
         return agg
+
+
+cdef Aggregation make_aggregation(op, kwargs=None):
+    r"""
+    Parameters
+    ----------
+    op : str or callable
+        If callable, must meet one of the following requirements:
+
+        * Is of the form lambda x: x.agg(*args, **kwargs), where
+          `agg` is the name of a supported aggregation. Used to
+          to specify aggregations that take arguments, e.g.,
+          `lambda x: x.quantile(0.5)`.
+        * Is a user defined aggregation function that operates on
+          group values. In this case, the output dtype must be
+          specified in the `kwargs` dictionary.
+    \*\*kwargs : dict, optional
+        Any keyword arguments to be passed to the op.
+
+    Returns
+    -------
+    Aggregation
+    """
+    if kwargs is None:
+        kwargs = {}
+
+    cdef Aggregation agg
+    if isinstance(op, str):
+        agg = getattr(Aggregation, op)(**kwargs)
+    elif callable(op):
+        if op is list:
+            agg = Aggregation.collect()
+        elif "dtype" in kwargs:
+            agg = Aggregation.from_udf(op, **kwargs)
+        else:
+            agg = op(Aggregation)
+    else:
+        raise TypeError("Unknown aggregation {}".format(op))
+    return agg