zero323 commented on a change in pull request #27109:
[SPARK-30434][PYTHON][SQL] Move pandas related functionalities into 'pandas'
sub-package
URL: https://github.com/apache/spark/pull/27109#discussion_r363760831
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File path: python/pyspark/sql/dataframe.py
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@@ -31,23 +31,23 @@
from pyspark import copy_func, since, _NoValue
from pyspark.rdd import RDD, _load_from_socket, _local_iterator_from_socket, \
- ignore_unicode_prefix, PythonEvalType
-from pyspark.serializers import ArrowCollectSerializer, BatchedSerializer,
PickleSerializer, \
+ ignore_unicode_prefix
+from pyspark.serializers import BatchedSerializer, PickleSerializer, \
UTF8Deserializer
from pyspark.storagelevel import StorageLevel
from pyspark.traceback_utils import SCCallSiteSync
from pyspark.sql.types import _parse_datatype_json_string
from pyspark.sql.column import Column, _to_seq, _to_list, _to_java_column
from pyspark.sql.readwriter import DataFrameWriter
from pyspark.sql.streaming import DataStreamWriter
-from pyspark.sql.types import IntegralType
from pyspark.sql.types import *
-from pyspark.util import _exception_message
+from pyspark.sql.pandas.conversion import PandasConversionMixin
+from pyspark.sql.pandas.map_ops import PandasMapOpsMixin
__all__ = ["DataFrame", "DataFrameNaFunctions", "DataFrameStatFunctions"]
-class DataFrame(object):
+class DataFrame(PandasMapOpsMixin, PandasConversionMixin):
Review comment:
> Either way the same APIs are exposed in the same class. It's also easily
switch to each other with minimised change.
While it is true, it is not equivalent from perspective of type checkers.
And since a lot of related discussions circles around typing, it might be
something to consider.
Nonetheless, I can take a hint.
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