API

docs/api.rst

@@ -24,9 +24,9 @@ Accessor
 .. autosummary::
    :toctree: generated/
 
-   akimbo.mixin.Accessor
+   Accessor
 
-.. autoclass:: akimbo.mixin.Accessor
+.. autoclass:: Accessor
    :members:
 
 
@@ -45,7 +45,7 @@ Backends
 
 .. autoclass:: akimbo.polars.PolarsAwkwardAccessor
 
-.. autoclass:: akimbo.polars.CudfAwkwardAccessor
+.. autoclass:: akimbo.cudf.CudfAwkwardAccessor
 
 
 Extensions
@@ -57,7 +57,7 @@ being acted on. Check the ``dir()`` of each (or use tab-completion)
 to see the operations available.
 
 .. autoclass:: akimbo.datetimes.DatetimeAccessor
-   :members: cast
+   :members:
 
 .. autoclass:: akimbo.strings.StringAccessor
    :members:
@@ -69,9 +69,3 @@ to see the operations available.
 
 The cuDF backend also has these implemented with GPU-specific variants,
 ``akimbo.cudf.CudfStringAccessor`` and ``akimbo.cudf.CudfDatetimeAccessor``.
-
-Adding Extensions (advanced)
-~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-
-The patterns used in the two builtin extensions above can be used to add
-type-specific functionality to ``akimbo``. One 

docs/index.rst

@@ -23,7 +23,7 @@ identical syntax:
 - pandas
 - dask.dataframe
 - polars
-- cuDF (in development)
+- cuDF
 
 
 numpy-like API
@@ -34,6 +34,7 @@ for slicing and accessing data deep in nested structures,
 Example: choose every second inner element in a list-of-lists
 
 .. code-block:: python
+
     series.ak[:, ::2]
 
 Any function, ufunc or aggregation at any level
@@ -43,6 +44,7 @@ For manipulating numerics at deeper levels of your nested structures or
 ragged arrays while maintaining the original layout
 
 .. code-block:: python
+
     series.ak.abs()  # absolute for all numerical values
     series.ak.sum(axis=3)  # sum over deeply nested level
     series.ak + 1  # numpy-like broadcasting into deeper levels
@@ -52,6 +54,7 @@ arrays of values, and they will only affect the appropriate parts of the structu
 without changing the layout.
 
 .. code-block:: python
+
     series.ak.str.upper()
 
 CPU/GPU numba support
@@ -64,6 +67,7 @@ in groupby/window operations. If your data is on the GPU, you can
 use numba-cuda with slight modifications to your original function.
 
 .. code-block:: python
+
     @numba.njit
     def sum_list_of_list(x):
         total = 0

src/akimbo/ak_from_cudf.py

@@ -1,12 +1,18 @@
-import cudf
-import pyarrow
-import cupy
-import numpy
+from typing import Optional
+
+from akimbo.utils import NoAttributes
 
+try:
+    import cudf
+    import cupy
+except ImportError:
+    cudf = NoAttributes()
+    cupy = NoAttributes()
 import awkward as ak
-from awkward._backends.numpy import NumpyBackend
+import numpy
+import pyarrow
 from awkward._backends.cupy import CupyBackend
-
+from awkward._backends.numpy import NumpyBackend
 
 # COPIED from awkward/studies/cudf-to-awkward.py
 
@@ -351,7 +357,7 @@ def remove_revertable(layout, **kwargs):
 def recurse_finalize(
     out: ak.contents.Content,
     column: cudf.core.column.column.ColumnBase,
-    validbits: None | cudf.core.buffer.buffer.Buffer,
+    validbits: Optional[cudf.core.buffer.buffer.Buffer],
     generate_bitmasks: bool,
     fix_offsets: bool = True,
 ):
@@ -569,13 +575,15 @@ def recurse(
         validbits = column.base_mask
 
         to64, dt = _pyarrow_to_numpy_dtype.get(str(arrow_type), (False, None))
-        if to64:
-            data = cupy.asarray(data).view(cupy.int32).astype(cupy.int64)
         if dt is None:
             dt = arrow_type.to_pandas_dtype()
+        if to64:
+            data = cupy.asarray(column.base_data).view(cupy.int32).astype(cupy.int64)
+        else:
+            data = cupy.asarray(column.base_data)
 
         out = ak.contents.NumpyArray(
-            cupy.asarray(column.base_data).view(dt),
+            data.view(dt),
             parameters=None,
             backend=CupyBackend.instance(),
         )

src/akimbo/apply_tree.py

@@ -41,10 +41,12 @@ def func(layout, **kwargs):
     return ak.transform(func, arr, *others)
 
 
-def dec(func: callable, match: Callable[[ak.contents.Content], bool] = leaf,
-        outtype: Callable[[ak.contents.Content], ak.contents.Content] | None = None,
-        inmode: Literal["arrow", "numpy", "ak"] = "arrow"):
-
+def dec(
+    func: callable,
+    match: Callable[[ak.contents.Content], bool] = leaf,
+    outtype: Callable[[ak.contents.Content], ak.contents.Content] | None = None,
+    inmode: Literal["arrow", "numpy", "ak"] = "arrow",
+):
     """Make a nested/ragged version of an operation to apply throughout a tree
 
     Parameters
@@ -121,8 +123,8 @@ def f(self, *args, where=None, match_kwargs=None, **kwargs):
 match_kwargs: None | dict
     any extra field identifiers for matching a record as OK to process
 
-{'-Kernel documentation follows from the original function-' if f.__doc__ else ''}
-===
+{'--Kernel documentation follows from the original function--' if f.__doc__ else ''}
+
 {f.__doc__ or str(f)}
 """
 

src/akimbo/cudf.py

@@ -2,16 +2,28 @@
 from typing import Callable
 
 import awkward as ak
-import cudf
-from cudf import DataFrame, Series, _lib as libcudf
-from cudf.core.column.string import StringMethods
-from cudf.core.column.datetime import DatetimeColumn
+
+from akimbo.utils import NoAttributes
+
+try:
+    import cudf
+    from cudf import DataFrame, Series
+    from cudf import _lib as libcudf
+    from cudf.core.column.datetime import DatetimeColumn
+    from cudf.core.column.string import StringMethods
+except ImportError:
+    StringMethods = NoAttributes()
+    DatetimeColumn = NoAttributes()
+    libcudf = NoAttributes()
+    DataFrame = Series = NoAttributes()
+
 
 from akimbo.ak_from_cudf import cudf_to_awkward as from_cudf
+from akimbo.apply_tree import dec, leaf
+from akimbo.datetimes import DatetimeAccessor
+from akimbo.datetimes import match as match_t
 from akimbo.mixin import Accessor
-from akimbo.datetimes import DatetimeAccessor, match as match_t
 from akimbo.strings import StringAccessor
-from akimbo.apply_tree import dec, leaf
 
 
 def match_string(arr):
@@ -22,14 +34,15 @@ class CudfStringAccessor(StringAccessor):
     """String operations on nested/var-length data"""
 
     def decode(self, encoding: str = "utf-8"):
-        raise NotImplementedError("cudf does not support bytearray type, so we can't automatically identify them")
+        raise NotImplementedError(
+            "cudf does not support bytearray type, so we can't automatically identify them"
+        )
 
     def encode(self, encoding: str = "utf-8"):
         raise NotImplementedError("cudf does not support bytearray type")
 
 
 def dec_cu(op, match=match_string):
-
     @functools.wraps(op)
     def f(lay, **kwargs):
         # op(column, ...)->column
@@ -47,14 +60,15 @@ def f(lay, **kwargs):
     def f(lay, method=meth, **kwargs):
         # this is different from dec_cu, because we need to instantiate StringMethods
         # before getting the method from it
-        col = getattr(StringMethods(cudf.Series(lay._to_cudf(cudf, None, len(lay)))), method)(**kwargs)
+        col = getattr(
+            StringMethods(cudf.Series(lay._to_cudf(cudf, None, len(lay)))), method
+        )(**kwargs)
         return from_cudf(col).layout
 
     setattr(CudfStringAccessor, meth, dec(func=f, match=match_string, inmode="ak"))
 
 
 class CudfDatetimeAccessor(DatetimeAccessor):
-
     ...
 
 
@@ -76,7 +90,11 @@ def f(lay, method=meth, **kwargs):
         return from_cudf(cudf.Series(col)).layout
 
     if isinstance(getattr(DatetimeColumn, meth), property):
-        setattr(CudfDatetimeAccessor, meth, property(dec(func=f, match=match_t, inmode="ak")))
+        setattr(
+            CudfDatetimeAccessor,
+            meth,
+            property(dec(func=f, match=match_t, inmode="ak")),
+        )
     else:
         setattr(CudfDatetimeAccessor, meth, dec(func=f, match=match_t, inmode="ak"))
 

src/akimbo/utils.py

@@ -0,0 +1,20 @@
+class NoAttributes:
+    """Allows importing akimbo.cudf even if cudf isn't installed
+
+    This is done so that sphinx can still build docs on non-GPU systems.
+    """
+
+    def __dir__(self):
+        return []
+
+    def __getattr__(self, item):
+        if item == "__qualname__":
+            return "akimbo.utils.DummyAttributesObject"
+        return self
+
+    def __call__(self, *args, **kwargs):
+        return self
+
+    __name__ = "DummyAttributesObject"
+    __doc__ = None
+    __annotations__ = None