Fix flake8 issues

Change-Id: I089463da34170b63f438c2afb2321b34ae077bbe
NonVolatileComputing · Oct 23, 2017 · 2eb8bf4 · 2eb8bf4
1 parent cef7a7c
commit 2eb8bf4
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Showing 2 changed files with 6 additions and 13 deletions.
diff --git a/python/pyarrow/serialization.py b/python/pyarrow/serialization.py
@@ -20,10 +20,10 @@
 
 import numpy as np
 
-import pyarrow as pa
 from pyarrow import serialize_pandas, deserialize_pandas
 from pyarrow.lib import _default_serialization_context
 
+
 def register_default_serialization_handlers(serialization_context):
 
     # ----------------------------------------------------------------------
@@ -43,58 +43,48 @@ def register_default_serialization_handlers(serialization_context):
             custom_serializer=lambda obj: str(obj),
             custom_deserializer=lambda data: long(data))  # noqa: F821
 
-
     def _serialize_ordered_dict(obj):
         return list(obj.keys()), list(obj.values())
 
-
     def _deserialize_ordered_dict(data):
         return OrderedDict(zip(data[0], data[1]))
 
-
     serialization_context.register_type(
         OrderedDict, "OrderedDict",
         custom_serializer=_serialize_ordered_dict,
         custom_deserializer=_deserialize_ordered_dict)
 
-
     def _serialize_default_dict(obj):
         return list(obj.keys()), list(obj.values()), obj.default_factory
 
-
     def _deserialize_default_dict(data):
         return defaultdict(data[2], zip(data[0], data[1]))
 
-
     serialization_context.register_type(
         defaultdict, "defaultdict",
         custom_serializer=_serialize_default_dict,
         custom_deserializer=_deserialize_default_dict)
 
-
     serialization_context.register_type(
         type(lambda: 0), "function",
         pickle=True)
 
     # ----------------------------------------------------------------------
     # Set up serialization for numpy with dtype object (primitive types are
-    # handled efficiently with Arrow's Tensor facilities, see python_to_arrow.cc)
-
+    # handled efficiently with Arrow's Tensor facilities, see
+    # python_to_arrow.cc)
 
     def _serialize_numpy_array(obj):
         return obj.tolist(), obj.dtype.str
 
-
     def _deserialize_numpy_array(data):
         return np.array(data[0], dtype=np.dtype(data[1]))
 
-
     serialization_context.register_type(
         np.ndarray, 'np.array',
         custom_serializer=_serialize_numpy_array,
         custom_deserializer=_deserialize_numpy_array)
 
-
     # ----------------------------------------------------------------------
     # Set up serialization for pandas Series and DataFrame
 

diff --git a/python/pyarrow/tests/test_serialization.py b/python/pyarrow/tests/test_serialization.py
@@ -300,6 +300,7 @@ def test_datetime_serialization(large_memory_map):
         for d in data:
             serialization_roundtrip(d, mmap)
 
+
 def test_torch_serialization(large_memory_map):
     pytest.importorskip("torch")
     import torch
@@ -311,6 +312,7 @@ def test_torch_serialization(large_memory_map):
             obj = torch.from_numpy(np.random.randn(1000).astype(t))
             serialization_roundtrip(obj, mmap)
 
+
 def test_numpy_immutable(large_memory_map):
     with pa.memory_map(large_memory_map, mode="r+") as mmap:
         obj = np.zeros([10])
@@ -342,6 +344,7 @@ def deserialize_dummy_class(serialized_obj):
 
     pa.serialize(DummyClass())
 
+
 def test_buffer_serialization():
 
     class BufferClass(object):