diff --git a/pyopencl/array.py b/pyopencl/array.py
index 279705c25fffb3447b7757069dfe5a847bacb34a..f40cfbbcd65d27f776f1fd60e2c37d79d431f516 100644
--- a/pyopencl/array.py
+++ b/pyopencl/array.py
@@ -28,7 +28,7 @@ OTHER DEALINGS IN THE SOFTWARE.
 """
 
 import six
-from six.moves import range, zip, reduce
+from six.moves import range, reduce
 
 import numpy as np
 import pyopencl.elementwise as elementwise
@@ -44,9 +44,10 @@ from pyopencl.compyte.array import (
 from pyopencl.characterize import has_double_support
 from pyopencl import cltypes
 
+
 def _get_common_dtype(obj1, obj2, queue):
     return _get_common_dtype_base(obj1, obj2,
-            has_double_support(queue.device))
+                                  has_double_support(queue.device))
 
 
 # Work around PyPy not currently supporting the object dtype.
@@ -70,10 +71,12 @@ class VecLookupWarner(object):
              DeprecationWarning, 2)
         return getattr(cltypes, name)
 
+
 vec = VecLookupWarner()
 
 # {{{ helper functionality
 
+
 def splay(queue, n, kernel_specific_max_wg_size=None):
     dev = queue.device
     max_work_items = _builtin_min(128, dev.max_work_group_size)
diff --git a/pyopencl/cltypes.py b/pyopencl/cltypes.py
index f15ab9d7c39da600ce7b2a811fb55b8538ffebba..c8ff35c378bd1eb395e54dc0efa5ce6a21ff9b85 100644
--- a/pyopencl/cltypes.py
+++ b/pyopencl/cltypes.py
@@ -43,14 +43,18 @@ half = np.float16
 float = np.float32
 double = np.float64
 
+
 # {{{ vector types
 
 
 def _create_vector_types():
-    _mapping = [(k, globals()[k]) for k in ['char', 'uchar', 'short', 'ushort', 'int',
-                                            'uint', 'long', 'ulong', 'float', 'double']]
+    _mapping = [(k, globals()[k]) for k in
+                ['char', 'uchar', 'short', 'ushort', 'int',
+                 'uint', 'long', 'ulong', 'float', 'double']]
+
     def set_global(key, val):
         globals()[key] = val
+
     field_names = ["x", "y", "z", "w"]
 
     set_global('types', {})
@@ -58,7 +62,6 @@ def _create_vector_types():
 
     counts = [2, 3, 4, 8, 16]
 
-
     for base_name, base_type in _mapping:
         for count in counts:
             name = "%s%d" % (base_name, count)
@@ -71,15 +74,15 @@ def _create_vector_types():
 
             names = ["s%d" % i for i in range(count)]
             while len(names) < padded_count:
-                names.append("padding%d" % (len(names)-count))
+                names.append("padding%d" % (len(names) - count))
 
             if len(titles) < len(names):
-                titles.extend((len(names)-len(titles))*[None])
+                titles.extend((len(names) - len(titles)) * [None])
 
             try:
                 dtype = np.dtype(dict(
                     names=names,
-                    formats=[base_type]*padded_count,
+                    formats=[base_type] * padded_count,
                     titles=titles))
             except NotImplementedError:
                 try:
@@ -97,31 +100,28 @@ def _create_vector_types():
                 if len(args) < count:
                     from warnings import warn
                     warn("default values for make_xxx are deprecated;"
-                            " instead specify all parameters or use"
-                            " cltypes.zeros_xxx", DeprecationWarning)
-                padded_args = tuple(list(args)+[0]*(padded_count-len(args)))
+                         " instead specify all parameters or use"
+                         " cltypes.zeros_xxx", DeprecationWarning)
+                padded_args = tuple(list(args) + [0] * (padded_count - len(args)))
                 array = eval("array(padded_args, dtype=dtype)",
-                        dict(array=np.array, padded_args=padded_args,
-                        dtype=dtype))
+                             dict(array=np.array, padded_args=padded_args,
+                                  dtype=dtype))
                 for key, val in list(kwargs.items()):
                     array[key] = val
                 return array
 
-            set_global("make_"+name, eval(
-                    "lambda *args, **kwargs: create_array(dtype, %i, %i, "
-                    "*args, **kwargs)" % (count, padded_count),
-                    dict(create_array=create_array, dtype=dtype)))
-            set_global("filled_"+name, eval(
-                    "lambda val: make_%s(*[val]*%i)" % (name, count)))
-            set_global("zeros_"+name, eval("lambda: filled_%s(0)" % (name)))
-            set_global("ones_"+name, eval("lambda: filled_%s(1)" % (name)))
+            set_global("make_" + name, eval(
+                "lambda *args, **kwargs: create_array(dtype, %i, %i, "
+                "*args, **kwargs)" % (count, padded_count),
+                dict(create_array=create_array, dtype=dtype)))
+            set_global("filled_" + name, eval(
+                "lambda val: make_%s(*[val]*%i)" % (name, count)))
+            set_global("zeros_" + name, eval("lambda: filled_%s(0)" % (name)))
+            set_global("ones_" + name, eval("lambda: filled_%s(1)" % (name)))
 
             globals()['types'][np.dtype(base_type), count] = dtype
             globals()['type_to_scalar_and_count'][dtype] = np.dtype(base_type), count
 
+
 _create_vector_types()
 # }}}
-
-
-
-