Rename libcudf++ to libcudf.

cpp/doxygen/developer_guide/DEVELOPER_GUIDE.md

@@ -176,7 +176,7 @@ Resource ownership is an essential concept in libcudf. In short, an "owning" obj
 resource (such as device memory). It acquires that resource during construction and releases the
 resource in destruction ([RAII](https://en.cppreference.com/w/cpp/language/raii)). A "non-owning"
 object does not own resources. Any class in libcudf with the `*_view` suffix is non-owning. For more
-detail see the [`libcudf++` presentation.](https://docs.google.com/presentation/d/1zKzAtc1AWFKfMhiUlV5yRZxSiPLwsObxMlWRWz_f5hA/edit?usp=sharing)
+detail see the [`libcudf` presentation.](https://docs.google.com/presentation/d/1zKzAtc1AWFKfMhiUlV5yRZxSiPLwsObxMlWRWz_f5hA/edit?usp=sharing)
 
 libcudf functions typically take views as input (`column_view` or `table_view`)
 and produce `unique_ptr`s to owning objects as output. For example,
@@ -403,7 +403,7 @@ Functions like merge or groupby in libcudf make no guarantees about the order of
 Promising deterministic ordering is not, in general, conducive to fast parallel algorithms.
 Calling code is responsible for performing sorts after the fact if sorted outputs are needed.
 
-# libcudf++ API and Implementation
+# libcudf API and Implementation
 
 ## Streams
 

cpp/doxygen/developer_guide/DOCUMENTATION.md

@@ -1,4 +1,4 @@
-# libcudf++ C++ Documentation Guide
+# libcudf C++ Documentation Guide
 
 These guidelines apply to documenting all libcudf C++ source files using doxygen style formatting although only public APIs and classes are actually [published](https://docs.rapids.ai/api/libcudf/stable/index.html).
 

python/cudf/cudf/_lib/avro.pyx

@@ -1,4 +1,4 @@
-# Copyright (c) 2020, NVIDIA CORPORATION.
+# Copyright (c) 2020-2022, NVIDIA CORPORATION.
 
 from libcpp.string cimport string
 from libcpp.utility cimport move
@@ -16,7 +16,7 @@ from cudf._lib.utils cimport data_from_unique_ptr
 
 cpdef read_avro(datasource, columns=None, skip_rows=-1, num_rows=-1):
     """
-    Cython function to call libcudf++ read_avro, see `read_avro`.
+    Cython function to call libcudf read_avro, see `read_avro`.
 
     See Also
     --------

python/cudf/cudf/_lib/io/utils.pyx

@@ -30,7 +30,7 @@ import cudf
 from cudf.api.types import is_struct_dtype
 
 
-# Converts the Python source input to libcudf++ IO source_info
+# Converts the Python source input to libcudf IO source_info
 # with the appropriate type and source values
 cdef source_info make_source_info(list src) except*:
     if not src:
@@ -80,7 +80,7 @@ cdef source_info make_source_info(list src) except*:
 
     return source_info(c_host_buffers)
 
-# Converts the Python sink input to libcudf++ IO sink_info.
+# Converts the Python sink input to libcudf IO sink_info.
 cdef sink_info make_sinks_info(
     list src, vector[unique_ptr[data_sink]] & sink
 ) except*:
@@ -129,7 +129,7 @@ cdef sink_info make_sink_info(src, unique_ptr[data_sink] & sink) except*:
     return info
 
 
-# Adapts a python io.IOBase object as a libcudf++ IO data_sink. This lets you
+# Adapts a python io.IOBase object as a libcudf IO data_sink. This lets you
 # write from cudf to any python file-like object (File/BytesIO/SocketIO etc)
 cdef cppclass iobase_data_sink(data_sink):
     object buf

python/cudf/cudf/_lib/json.pyx

@@ -46,7 +46,7 @@ cpdef read_json(object filepaths_or_buffers,
 
     # If input data is a JSON string (or StringIO), hold a reference to
     # the encoded memoryview externally to ensure the encoded buffer
-    # isn't destroyed before calling libcudf++ `read_json()`
+    # isn't destroyed before calling libcudf `read_json()`
     for idx in range(len(filepaths_or_buffers)):
         if isinstance(filepaths_or_buffers[idx], io.StringIO):
             filepaths_or_buffers[idx] = \

python/cudf/cudf/_lib/reduce.pyx

@@ -35,7 +35,7 @@ cimport cudf._lib.cpp.types as libcudf_types
 
 def reduce(reduction_op, Column incol, dtype=None, **kwargs):
     """
-    Top level Cython reduce function wrapping libcudf++ reductions.
+    Top level Cython reduce function wrapping libcudf reductions.
 
     Parameters
     ----------
@@ -91,7 +91,7 @@ def reduce(reduction_op, Column incol, dtype=None, **kwargs):
 
 def scan(scan_op, Column incol, inclusive, **kwargs):
     """
-    Top level Cython scan function wrapping libcudf++ scans.
+    Top level Cython scan function wrapping libcudf scans.
 
     Parameters
     ----------
@@ -122,7 +122,7 @@ def scan(scan_op, Column incol, inclusive, **kwargs):
 
 def minmax(Column incol):
     """
-    Top level Cython minmax function wrapping libcudf++ minmax.
+    Top level Cython minmax function wrapping libcudf minmax.
 
     Parameters
     ----------

python/cudf/cudf/core/frame.py

@@ -1412,7 +1412,7 @@ def searchsorted(
         >>> df.searchsorted(values_df, ascending=False)
         array([4, 4, 4, 0], dtype=int32)
         """
-        # Call libcudf++ search_sorted primitive
+        # Call libcudf search_sorted primitive
 
         if na_position not in {"first", "last"}:
             raise ValueError(f"invalid na_position: {na_position}")