Merge pull request #6867 from gfyoung/print_fixes

DOC: No Print Statements When Using print_function from __future__

32 files changed, 136 insertions, 136 deletions

diff --git a/numpy/add_newdocs.py b/numpy/add_newdocs.py
index 01ef24a5b..7eef07c4a 100644
--- a/numpy/add_newdocs.py
+++ b/numpy/add_newdocs.py
@@ -49,7 +49,7 @@ add_newdoc('numpy.core', 'flatiter',
     >>> type(fl)
     <type 'numpy.flatiter'>
     >>> for item in fl:
-    ...     print item
+    ...     print(item)
     ...
     0
     1
@@ -1548,7 +1548,7 @@ add_newdoc('numpy.core.multiarray', 'lexsort',
     >>> a = [1,5,1,4,3,4,4] # First column
     >>> b = [9,4,0,4,0,2,1] # Second column
     >>> ind = np.lexsort((b,a)) # Sort by a, then by b
-    >>> print ind
+    >>> print(ind)
     [2 0 4 6 5 3 1]
 
     >>> [(a[i],b[i]) for i in ind]
@@ -4773,7 +4773,7 @@ add_newdoc('numpy.core.multiarray', 'ndarray', ('view',
     >>> y = x.view(dtype=np.int16, type=np.matrix)
     >>> y
     matrix([[513]], dtype=int16)
-    >>> print type(y)
+    >>> print(type(y))
     <class 'numpy.matrixlib.defmatrix.matrix'>
 
     Creating a view on a structured array so it can be used in calculations
@@ -4789,7 +4789,7 @@ add_newdoc('numpy.core.multiarray', 'ndarray', ('view',
     Making changes to the view changes the underlying array
 
     >>> xv[0,1] = 20
-    >>> print x
+    >>> print(x)
     [(1, 20) (3, 4)]
 
     Using a view to convert an array to a recarray:
@@ -4915,7 +4915,7 @@ add_newdoc('numpy.core.umath', 'geterrobj',
     [10000, 0, None]
 
     >>> def err_handler(type, flag):
-    ...     print "Floating point error (%s), with flag %s" % (type, flag)
+    ...     print("Floating point error (%s), with flag %s" % (type, flag))
     ...
     >>> old_bufsize = np.setbufsize(20000)
     >>> old_err = np.seterr(divide='raise')
@@ -4979,7 +4979,7 @@ add_newdoc('numpy.core.umath', 'seterrobj',
     [10000, 0, None]
 
     >>> def err_handler(type, flag):
-    ...     print "Floating point error (%s), with flag %s" % (type, flag)
+    ...     print("Floating point error (%s), with flag %s" % (type, flag))
     ...
     >>> new_errobj = [20000, 12, err_handler]
     >>> np.seterrobj(new_errobj)
@@ -5064,7 +5064,7 @@ add_newdoc('numpy.core.multiarray', 'digitize',
     >>> inds
     array([1, 4, 3, 2])
     >>> for n in range(x.size):
-    ...   print bins[inds[n]-1], "<=", x[n], "<", bins[inds[n]]
+    ...   print(bins[inds[n]-1], "<=", x[n], "<", bins[inds[n]])
     ...
     0.0 <= 0.2 < 1.0
     4.0 <= 6.4 < 10.0
@@ -5473,7 +5473,7 @@ add_newdoc('numpy.core', 'ufunc', ('identity',
     1
     >>> np.power.identity
     1
-    >>> print np.exp.identity
+    >>> print(np.exp.identity)
     None
     """))
 
@@ -6181,7 +6181,7 @@ add_newdoc('numpy.core.multiarray', 'dtype', ('fields',
     Examples
     --------
     >>> dt = np.dtype([('name', np.str_, 16), ('grades', np.float64, (2,))])
-    >>> print dt.fields
+    >>> print(dt.fields)
     {'grades': (dtype(('float64',(2,))), 16), 'name': (dtype('|S16'), 0)}
 
     """))
diff --git a/numpy/core/arrayprint.py b/numpy/core/arrayprint.py
index a28b5a89e..fefcb6493 100644
--- a/numpy/core/arrayprint.py
+++ b/numpy/core/arrayprint.py
@@ -114,13 +114,13 @@ def set_printoptions(precision=None, threshold=None, edgeitems=None,
     Floating point precision can be set:
 
     >>> np.set_printoptions(precision=4)
-    >>> print np.array([1.123456789])
+    >>> print(np.array([1.123456789]))
     [ 1.1235]
 
     Long arrays can be summarised:
 
     >>> np.set_printoptions(threshold=5)
-    >>> print np.arange(10)
+    >>> print(np.arange(10))
     [0 1 2 ..., 7 8 9]
 
     Small results can be suppressed:
@@ -420,8 +420,8 @@ def array2string(a, max_line_width=None, precision=None,
     Examples
     --------
     >>> x = np.array([1e-16,1,2,3])
-    >>> print np.array2string(x, precision=2, separator=',',
-    ...                       suppress_small=True)
+    >>> print(np.array2string(x, precision=2, separator=',',
+    ...                       suppress_small=True))
     [ 0., 1., 2., 3.]
 
     >>> x  = np.arange(3.)
diff --git a/numpy/core/fromnumeric.py b/numpy/core/fromnumeric.py
index 197513294..7d2078adf 100644
--- a/numpy/core/fromnumeric.py
+++ b/numpy/core/fromnumeric.py
@@ -1434,20 +1434,20 @@ def ravel(a, order='C'):
     It is equivalent to ``reshape(-1, order=order)``.
 
     >>> x = np.array([[1, 2, 3], [4, 5, 6]])
-    >>> print np.ravel(x)
+    >>> print(np.ravel(x))
     [1 2 3 4 5 6]
 
-    >>> print x.reshape(-1)
+    >>> print(x.reshape(-1))
     [1 2 3 4 5 6]
 
-    >>> print np.ravel(x, order='F')
+    >>> print(np.ravel(x, order='F'))
     [1 4 2 5 3 6]
 
     When ``order`` is 'A', it will preserve the array's 'C' or 'F' ordering:
 
-    >>> print np.ravel(x.T)
+    >>> print(np.ravel(x.T))
     [1 4 2 5 3 6]
-    >>> print np.ravel(x.T, order='A')
+    >>> print(np.ravel(x.T, order='A'))
     [1 2 3 4 5 6]
 
     When ``order`` is 'K', it will preserve orderings that are neither 'C'
diff --git a/numpy/core/numeric.py b/numpy/core/numeric.py
index 3b442ea78..4f3d418e6 100644
--- a/numpy/core/numeric.py
+++ b/numpy/core/numeric.py
@@ -1808,7 +1808,7 @@ def set_string_function(f, repr=True):
     >>> a = np.arange(10)
     >>> a
     HA! - What are you going to do now?
-    >>> print a
+    >>> print(a)
     [0 1 2 3 4 5 6 7 8 9]
 
     We can reset the function to the default:
@@ -2710,7 +2710,7 @@ def seterrcall(func):
     Callback upon error:
 
     >>> def err_handler(type, flag):
-    ...     print "Floating point error (%s), with flag %s" % (type, flag)
+    ...     print("Floating point error (%s), with flag %s" % (type, flag))
     ...
 
     >>> saved_handler = np.seterrcall(err_handler)
@@ -2729,7 +2729,7 @@ def seterrcall(func):
 
     >>> class Log(object):
     ...     def write(self, msg):
-    ...         print "LOG: %s" % msg
+    ...         print("LOG: %s" % msg)
     ...
 
     >>> log = Log()
@@ -2787,7 +2787,7 @@ def geterrcall():
 
     >>> oldsettings = np.seterr(all='call')
     >>> def err_handler(type, flag):
-    ...     print "Floating point error (%s), with flag %s" % (type, flag)
+    ...     print("Floating point error (%s), with flag %s" % (type, flag))
     >>> oldhandler = np.seterrcall(err_handler)
     >>> np.array([1, 2, 3]) / 0.0
     Floating point error (divide by zero), with flag 1
diff --git a/numpy/core/numerictypes.py b/numpy/core/numerictypes.py
index 7dc6e0bd8..1b6551e6c 100644
--- a/numpy/core/numerictypes.py
+++ b/numpy/core/numerictypes.py
@@ -822,7 +822,7 @@ def sctype2char(sctype):
     Examples
     --------
     >>> for sctype in [np.int32, np.float, np.complex, np.string_, np.ndarray]:
-    ...     print np.sctype2char(sctype)
+    ...     print(np.sctype2char(sctype))
     l
     d
     D
diff --git a/numpy/core/records.py b/numpy/core/records.py
index b07755384..ca6070cf7 100644
--- a/numpy/core/records.py
+++ b/numpy/core/records.py
@@ -567,7 +567,7 @@ def fromarrays(arrayList, dtype=None, shape=None, formats=None,
     >>> x2=np.array(['a','dd','xyz','12'])
     >>> x3=np.array([1.1,2,3,4])
     >>> r = np.core.records.fromarrays([x1,x2,x3],names='a,b,c')
-    >>> print r[1]
+    >>> print(r[1])
     (2, 'dd', 2.0)
     >>> x1[1]=34
     >>> r.a
@@ -643,7 +643,7 @@ def fromrecords(recList, dtype=None, shape=None, formats=None, names=None,
 
     >>> r=np.core.records.fromrecords([(456,'dbe',1.2),(2,'de',1.3)],
     ... names='col1,col2,col3')
-    >>> print r[0]
+    >>> print(r[0])
     (456, 'dbe', 1.2)
     >>> r.col1
     array([456,   2])
@@ -651,7 +651,7 @@ def fromrecords(recList, dtype=None, shape=None, formats=None, names=None,
     array(['dbe', 'de'],
           dtype='|S3')
     >>> import pickle
-    >>> print pickle.loads(pickle.dumps(r))
+    >>> print(pickle.loads(pickle.dumps(r)))
     [(456, 'dbe', 1.2) (2, 'de', 1.3)]
     """
 
@@ -736,7 +736,7 @@ def fromfile(fd, dtype=None, shape=None, offset=0, formats=None,
     >>> fd.seek(0)
     >>> r=np.core.records.fromfile(fd, formats='f8,i4,a5', shape=10,
     ... byteorder='<')
-    >>> print r[5]
+    >>> print(r[5])
     (0.5, 10, 'abcde')
     >>> r.shape
     (10,)
diff --git a/numpy/core/shape_base.py b/numpy/core/shape_base.py
index 0dd2e164a..599b48d82 100644
--- a/numpy/core/shape_base.py
+++ b/numpy/core/shape_base.py
@@ -150,7 +150,7 @@ def atleast_3d(*arys):
     True
 
     >>> for arr in np.atleast_3d([1, 2], [[1, 2]], [[[1, 2]]]):
-    ...     print arr, arr.shape
+    ...     print(arr, arr.shape)
     ...
     [[[1]
       [2]]] (1, 2, 1)
diff --git a/numpy/distutils/npy_pkg_config.py b/numpy/distutils/npy_pkg_config.py
index 1c801fd9c..fe64709ca 100644
--- a/numpy/distutils/npy_pkg_config.py
+++ b/numpy/distutils/npy_pkg_config.py
@@ -366,7 +366,7 @@ def read_config(pkgname, dirs=None):
     >>> npymath_info = np.distutils.npy_pkg_config.read_config('npymath')
     >>> type(npymath_info)
     <class 'numpy.distutils.npy_pkg_config.LibraryInfo'>
-    >>> print npymath_info
+    >>> print(npymath_info)
     Name: npymath
     Description: Portable, core math library implementing C99 standard
     Requires:
diff --git a/numpy/distutils/system_info.py b/numpy/distutils/system_info.py
index 94436243e..bf2762523 100644
--- a/numpy/distutils/system_info.py
+++ b/numpy/distutils/system_info.py
@@ -1947,7 +1947,7 @@ class _numpy_info(system_info):
 ##                  hex(vstr2hex(module.__version__))),
 ##                 )
 ##         except Exception as msg:
-##             print msg
+##             print(msg)
         dict_append(info, define_macros=macros)
         include_dirs = self.get_include_dirs()
         inc_dir = None
diff --git a/numpy/doc/glossary.py b/numpy/doc/glossary.py
index 9dacd1cb5..4a3238491 100644
--- a/numpy/doc/glossary.py
+++ b/numpy/doc/glossary.py
@@ -109,7 +109,7 @@ Glossary
 
          >>> def log(f):
          ...     def new_logging_func(*args, **kwargs):
-         ...         print "Logging call with parameters:", args, kwargs
+         ...         print("Logging call with parameters:", args, kwargs)
          ...         return f(*args, **kwargs)
          ...
          ...     return new_logging_func
@@ -185,7 +185,7 @@ Glossary
        It is often used in combintion with ``enumerate``::
          >>> keys = ['a','b','c']
          >>> for n, k in enumerate(keys):
-         ...     print "Key %d: %s" % (n, k)
+         ...     print("Key %d: %s" % (n, k))
          ...
          Key 0: a
          Key 1: b
@@ -315,7 +315,7 @@ Glossary
          ...     color = 'blue'
          ...
          ...     def paint(self):
-         ...         print "Painting the city %s!" % self.color
+         ...         print("Painting the city %s!" % self.color)
          ...
          >>> p = Paintbrush()
          >>> p.color = 'red'
diff --git a/numpy/doc/misc.py b/numpy/doc/misc.py
index 1709ad66d..e30caf0cb 100644
--- a/numpy/doc/misc.py
+++ b/numpy/doc/misc.py
@@ -86,7 +86,7 @@ Examples
  >>> np.sqrt(np.array([-1.]))
  FloatingPointError: invalid value encountered in sqrt
  >>> def errorhandler(errstr, errflag):
- ...      print "saw stupid error!"
+ ...      print("saw stupid error!")
  >>> np.seterrcall(errorhandler)
  <function err_handler at 0x...>
  >>> j = np.seterr(all='call')
diff --git a/numpy/doc/subclassing.py b/numpy/doc/subclassing.py
index a62fc2d6d..85327feab 100644
--- a/numpy/doc/subclassing.py
+++ b/numpy/doc/subclassing.py
@@ -123,13 +123,13 @@ For example, consider the following Python code:
 
   class C(object):
       def __new__(cls, *args):
-          print 'Cls in __new__:', cls
-          print 'Args in __new__:', args
+          print('Cls in __new__:', cls)
+          print('Args in __new__:', args)
           return object.__new__(cls, *args)
 
       def __init__(self, *args):
-          print 'type(self) in __init__:', type(self)
-          print 'Args in __init__:', args
+          print('type(self) in __init__:', type(self))
+          print('Args in __init__:', args)
 
 meaning that we get:
 
@@ -159,13 +159,13 @@ of some other class.  Consider the following:
 
   class D(C):
       def __new__(cls, *args):
-          print 'D cls is:', cls
-          print 'D args in __new__:', args
+          print('D cls is:', cls)
+          print('D args in __new__:', args)
           return C.__new__(C, *args)
 
       def __init__(self, *args):
           # we never get here
-          print 'In D __init__'
+          print('In D __init__')
 
 meaning that:
 
@@ -242,18 +242,18 @@ The following code allows us to look at the call sequences and arguments:
 
    class C(np.ndarray):
        def __new__(cls, *args, **kwargs):
-           print 'In __new__ with class %s' % cls
+           print('In __new__ with class %s' % cls)
            return np.ndarray.__new__(cls, *args, **kwargs)
 
        def __init__(self, *args, **kwargs):
            # in practice you probably will not need or want an __init__
            # method for your subclass
-           print 'In __init__ with class %s' % self.__class__
+           print('In __init__ with class %s' % self.__class__)
 
        def __array_finalize__(self, obj):
-           print 'In array_finalize:'
-           print '   self type is %s' % type(self)
-           print '   obj type is %s' % type(obj)
+           print('In array_finalize:')
+           print('   self type is %s' % type(self))
+           print('   obj type is %s' % type(obj))
 
 
 Now:
@@ -441,16 +441,16 @@ some print statements:
           return obj
 
       def __array_finalize__(self, obj):
-          print 'In __array_finalize__:'
-          print '   self is %s' % repr(self)
-          print '   obj is %s' % repr(obj)
+          print('In __array_finalize__:')
+          print('   self is %s' % repr(self))
+          print('   obj is %s' % repr(obj))
           if obj is None: return
           self.info = getattr(obj, 'info', None)
 
       def __array_wrap__(self, out_arr, context=None):
-          print 'In __array_wrap__:'
-          print '   self is %s' % repr(self)
-          print '   arr is %s' % repr(out_arr)
+          print('In __array_wrap__:')
+          print('   self is %s' % repr(self))
+          print('   arr is %s' % repr(out_arr))
           # then just call the parent
           return np.ndarray.__array_wrap__(self, out_arr, context)
 
diff --git a/numpy/f2py/auxfuncs.py b/numpy/f2py/auxfuncs.py
index b64aaa50d..289102e5a 100644
--- a/numpy/f2py/auxfuncs.py
+++ b/numpy/f2py/auxfuncs.py
@@ -673,7 +673,7 @@ def getcallprotoargument(rout, cb_map={}):
     proto_args = ','.join(arg_types + arg_types2)
     if not proto_args:
         proto_args = 'void'
-    # print proto_args
+    # print(proto_args)
     return proto_args
 
 
diff --git a/numpy/lib/arrayterator.py b/numpy/lib/arrayterator.py
index 80b369bd5..fb52ada86 100644
--- a/numpy/lib/arrayterator.py
+++ b/numpy/lib/arrayterator.py
@@ -80,7 +80,7 @@ class Arrayterator(object):
 
     >>> for subarr in a_itor:
     ...     if not subarr.all():
-    ...         print subarr, subarr.shape
+    ...         print(subarr, subarr.shape)
     ...
     [[[[0 1]]]] (1, 1, 1, 2)
 
@@ -158,7 +158,7 @@ class Arrayterator(object):
 
         >>> for subarr in a_itor.flat:
         ...     if not subarr:
-        ...         print subarr, type(subarr)
+        ...         print(subarr, type(subarr))
         ...
         0 <type 'numpy.int32'>
 
diff --git a/numpy/lib/financial.py b/numpy/lib/financial.py
index a7e4e60b6..c42424da1 100644
--- a/numpy/lib/financial.py
+++ b/numpy/lib/financial.py
@@ -247,7 +247,7 @@ def nper(rate, pmt, pv, fv=0, when='end'):
     If you only had $150/month to pay towards the loan, how long would it take
     to pay-off a loan of $8,000 at 7% annual interest?
 
-    >>> print round(np.nper(0.07/12, -150, 8000), 5)
+    >>> print(round(np.nper(0.07/12, -150, 8000), 5))
     64.07335
 
     So, over 64 months would be required to pay off the loan.
@@ -347,7 +347,7 @@ def ipmt(rate, per, nper, pv, fv=0.0, when='end'):
     >>> for payment in per:
     ...     index = payment - 1
     ...     principal = principal + ppmt[index]
-    ...     print fmt.format(payment, ppmt[index], ipmt[index], principal)
+    ...     print(fmt.format(payment, ppmt[index], ipmt[index], principal))
      1  -200.58   -17.17  2299.42
      2  -201.96   -15.79  2097.46
      3  -203.35   -14.40  1894.11
diff --git a/numpy/lib/function_base.py b/numpy/lib/function_base.py
index 8335b4fdb..c69185c1c 100644
--- a/numpy/lib/function_base.py
+++ b/numpy/lib/function_base.py
@@ -833,7 +833,7 @@ def asarray_chkfinite(a, dtype=None, order=None):
     >>> try:
     ...     np.asarray_chkfinite(a)
     ... except ValueError:
-    ...     print 'ValueError'
+    ...     print('ValueError')
     ...
     ValueError
 
@@ -2200,13 +2200,13 @@ def cov(m, y=None, rowvar=True, bias=False, ddof=None, fweights=None,
     >>> x = [-2.1, -1,  4.3]
     >>> y = [3,  1.1,  0.12]
     >>> X = np.vstack((x,y))
-    >>> print np.cov(X)
+    >>> print(np.cov(X))
     [[ 11.71        -4.286     ]
      [ -4.286        2.14413333]]
-    >>> print np.cov(x, y)
+    >>> print(np.cov(x, y))
     [[ 11.71        -4.286     ]
      [ -4.286        2.14413333]]
-    >>> print np.cov(x)
+    >>> print(np.cov(x))
     11.71
 
     """
diff --git a/numpy/lib/index_tricks.py b/numpy/lib/index_tricks.py
index 8bcc3fb53..a0875a25f 100644
--- a/numpy/lib/index_tricks.py
+++ b/numpy/lib/index_tricks.py
@@ -491,7 +491,7 @@ class ndenumerate(object):
     --------
     >>> a = np.array([[1, 2], [3, 4]])
     >>> for index, x in np.ndenumerate(a):
-    ...     print index, x
+    ...     print(index, x)
     (0, 0) 1
     (0, 1) 2
     (1, 0) 3
@@ -542,7 +542,7 @@ class ndindex(object):
     Examples
     --------
     >>> for index in np.ndindex(3, 2, 1):
-    ...     print index
+    ...     print(index)
     (0, 0, 0)
     (0, 1, 0)
     (1, 0, 0)
diff --git a/numpy/lib/polynomial.py b/numpy/lib/polynomial.py
index 2f677438b..a5d3f5f5f 100644
--- a/numpy/lib/polynomial.py
+++ b/numpy/lib/polynomial.py
@@ -715,12 +715,12 @@ def polyadd(a1, a2):
 
     >>> p1 = np.poly1d([1, 2])
     >>> p2 = np.poly1d([9, 5, 4])
-    >>> print p1
+    >>> print(p1)
     1 x + 2
-    >>> print p2
+    >>> print(p2)
        2
     9 x + 5 x + 4
-    >>> print np.polyadd(p1, p2)
+    >>> print(np.polyadd(p1, p2))
        2
     9 x + 6 x + 6
 
@@ -826,13 +826,13 @@ def polymul(a1, a2):
 
     >>> p1 = np.poly1d([1, 2, 3])
     >>> p2 = np.poly1d([9, 5, 1])
-    >>> print p1
+    >>> print(p1)
        2
     1 x + 2 x + 3
-    >>> print p2
+    >>> print(p2)
        2
     9 x + 5 x + 1
-    >>> print np.polymul(p1, p2)
+    >>> print(np.polymul(p1, p2))
        4      3      2
     9 x + 23 x + 38 x + 17 x + 3
 
@@ -966,7 +966,7 @@ class poly1d(object):
     Construct the polynomial :math:`x^2 + 2x + 3`:
 
     >>> p = np.poly1d([1, 2, 3])
-    >>> print np.poly1d(p)
+    >>> print(np.poly1d(p))
        2
     1 x + 2 x + 3
 
@@ -1022,7 +1022,7 @@ class poly1d(object):
     using the `variable` parameter:
 
     >>> p = np.poly1d([1,2,3], variable='z')
-    >>> print p
+    >>> print(p)
        2
     1 z + 2 z + 3
 
diff --git a/numpy/lib/tests/test_format.py b/numpy/lib/tests/test_format.py
index 1bf65fa61..a091ef5b3 100644
--- a/numpy/lib/tests/test_format.py
+++ b/numpy/lib/tests/test_format.py
@@ -112,7 +112,7 @@ Test the header writing.
     >>> for arr in basic_arrays + record_arrays:
     ...     f = BytesIO()
     ...     format.write_array_header_1_0(f, arr)   # XXX: arr is not a dict, items gets called on it
-    ...     print repr(f.getvalue())
+    ...     print(repr(f.getvalue()))
     ...
     "F\x00{'descr': '|u1', 'fortran_order': False, 'shape': (0,)}              \n"
     "F\x00{'descr': '|u1', 'fortran_order': False, 'shape': ()}                \n"
diff --git a/numpy/lib/twodim_base.py b/numpy/lib/twodim_base.py
index 464ffd914..b2f350bb7 100644
--- a/numpy/lib/twodim_base.py
+++ b/numpy/lib/twodim_base.py
@@ -664,7 +664,7 @@ def histogram2d(x, y, bins=10, range=None, normed=False, weights=None):
     Or we fill the histogram H with a determined bin content:
 
     >>> H = np.ones((4, 4)).cumsum().reshape(4, 4)
-    >>> print H[::-1]  # This shows the bin content in the order as plotted
+    >>> print(H[::-1])  # This shows the bin content in the order as plotted
     [[ 13.  14.  15.  16.]
      [  9.  10.  11.  12.]
      [  5.   6.   7.   8.]
diff --git a/numpy/lib/type_check.py b/numpy/lib/type_check.py
index 2fe4e7d23..1313adff7 100644
--- a/numpy/lib/type_check.py
+++ b/numpy/lib/type_check.py
@@ -501,7 +501,7 @@ def typename(char):
     >>> typechars = ['S1', '?', 'B', 'D', 'G', 'F', 'I', 'H', 'L', 'O', 'Q',
     ...              'S', 'U', 'V', 'b', 'd', 'g', 'f', 'i', 'h', 'l', 'q']
     >>> for typechar in typechars:
-    ...     print typechar, ' : ', np.typename(typechar)
+    ...     print(typechar, ' : ', np.typename(typechar))
     ...
     S1  :  character
     ?  :  bool
diff --git a/numpy/linalg/lapack_lite/clapack_scrub.py b/numpy/linalg/lapack_lite/clapack_scrub.py
index 4a517d531..9dfee0a84 100644
--- a/numpy/linalg/lapack_lite/clapack_scrub.py
+++ b/numpy/linalg/lapack_lite/clapack_scrub.py
@@ -14,9 +14,9 @@ class MyScanner(Scanner):
 
     def begin(self, state_name):
 #        if self.state_name == '':
-#            print '<default>'
+#            print('<default>')
 #        else:
-#            print self.state_name
+#            print(self.state_name)
         Scanner.begin(self, state_name)
 
 def sep_seq(sequence, sep):
diff --git a/numpy/linalg/linalg.py b/numpy/linalg/linalg.py
index 2e969727b..9dc879d31 100644
--- a/numpy/linalg/linalg.py
+++ b/numpy/linalg/linalg.py
@@ -1853,7 +1853,7 @@ def lstsq(a, b, rcond=-1):
            [ 3.,  1.]])
 
     >>> m, c = np.linalg.lstsq(A, y)[0]
-    >>> print m, c
+    >>> print(m, c)
     1.0 -0.95
 
     Plot the data along with the fitted line:
diff --git a/numpy/ma/core.py b/numpy/ma/core.py
index 25e542cd6..de716a669 100644
--- a/numpy/ma/core.py
+++ b/numpy/ma/core.py
@@ -2147,12 +2147,12 @@ def masked_object(x, value, copy=True, shrink=True):
     >>> food = np.array(['green_eggs', 'ham'], dtype=object)
     >>> # don't eat spoiled food
     >>> eat = ma.masked_object(food, 'green_eggs')
-    >>> print eat
+    >>> print(eat)
     [-- ham]
     >>> # plain ol` ham is boring
     >>> fresh_food = np.array(['cheese', 'ham', 'pineapple'], dtype=object)
     >>> eat = ma.masked_object(fresh_food, 'green_eggs')
-    >>> print eat
+    >>> print(eat)
     [cheese ham pineapple]
 
     Note that `mask` is set to ``nomask`` if possible.
@@ -2548,7 +2548,7 @@ class MaskedIterator(object):
     >>> type(fl)
     <class 'numpy.ma.core.MaskedIterator'>
     >>> for item in fl:
-    ...     print item
+    ...     print(item)
     ...
     0
     1
@@ -3064,11 +3064,11 @@ class MaskedArray(ndarray):
         Examples
         --------
         >>> x = np.ma.array([[1,2,3.1],[4,5,6],[7,8,9]], mask=[0] + [1,0]*4)
-        >>> print x
+        >>> print(x)
         [[1.0 -- 3.1]
          [-- 5.0 --]
          [7.0 -- 9.0]]
-        >>> print x.astype(int32)
+        >>> print(x.astype(int32))
         [[1 -- 3]
          [-- 5 --]
          [7 -- 9]]
@@ -3656,7 +3656,7 @@ class MaskedArray(ndarray):
         Examples
         --------
         >>> x = np.ma.array([[1,2,3],[4,5,6],[7,8,9]], mask=[0] + [1,0]*4)
-        >>> print x
+        >>> print(x)
         [[1 -- 3]
          [-- 5 --]
          [7 -- 9]]
@@ -4261,11 +4261,11 @@ class MaskedArray(ndarray):
         Examples
         --------
         >>> x = np.ma.array([[1,2,3],[4,5,6],[7,8,9]], mask=[0] + [1,0]*4)
-        >>> print x
+        >>> print(x)
         [[1 -- 3]
          [-- 5 --]
          [7 -- 9]]
-        >>> print x.ravel()
+        >>> print(x.ravel())
         [1 -- 3 -- 5 -- 7 -- 9]
 
         """
@@ -4317,11 +4317,11 @@ class MaskedArray(ndarray):
         Examples
         --------
         >>> x = np.ma.array([[1,2],[3,4]], mask=[1,0,0,1])
-        >>> print x
+        >>> print(x)
         [[-- 2]
          [3 --]]
         >>> x = x.reshape((4,1))
-        >>> print x
+        >>> print(x)
         [[--]
          [2]
          [3]
@@ -4382,18 +4382,18 @@ class MaskedArray(ndarray):
         Examples
         --------
         >>> x = np.ma.array([[1,2,3],[4,5,6],[7,8,9]], mask=[0] + [1,0]*4)
-        >>> print x
+        >>> print(x)
         [[1 -- 3]
          [-- 5 --]
          [7 -- 9]]
         >>> x.put([0,4,8],[10,20,30])
-        >>> print x
+        >>> print(x)
         [[10 -- 3]
          [-- 20 --]
          [7 -- 30]]
 
         >>> x.put(4,999)
-        >>> print x
+        >>> print(x)
         [[10 -- 3]
          [-- 999 --]
          [7 -- 30]]
@@ -4745,17 +4745,17 @@ class MaskedArray(ndarray):
         Examples
         --------
         >>> x = np.ma.array([[1,2,3],[4,5,6],[7,8,9]], mask=[0] + [1,0]*4)
-        >>> print x
+        >>> print(x)
         [[1 -- 3]
          [-- 5 --]
          [7 -- 9]]
-        >>> print x.sum()
+        >>> print(x.sum())
         25
-        >>> print x.sum(axis=1)
+        >>> print(x.sum(axis=1))
         [4 5 16]
-        >>> print x.sum(axis=0)
+        >>> print(x.sum(axis=0))
         [8 5 12]
-        >>> print type(x.sum(axis=0, dtype=np.int64)[0])
+        >>> print(type(x.sum(axis=0, dtype=np.int64)[0]))
         <type 'numpy.int64'>
 
         """
@@ -4823,7 +4823,7 @@ class MaskedArray(ndarray):
         Examples
         --------
         >>> marr = np.ma.array(np.arange(10), mask=[0,0,0,1,1,1,0,0,0,0])
-        >>> print marr.cumsum()
+        >>> print(marr.cumsum())
         [0 1 3 -- -- -- 9 16 24 33]
 
         """
@@ -5223,12 +5223,12 @@ class MaskedArray(ndarray):
         --------
         >>> x = np.ma.array(arange(4), mask=[1,1,0,0])
         >>> x.shape = (2,2)
-        >>> print x
+        >>> print(x)
         [[-- --]
          [2 3]]
-        >>> print x.argmin(axis=0, fill_value=-1)
+        >>> print(x.argmin(axis=0, fill_value=-1))
         [0 0]
-        >>> print x.argmin(axis=0, fill_value=9)
+        >>> print(x.argmin(axis=0, fill_value=9))
         [1 1]
 
         """
@@ -5324,19 +5324,19 @@ class MaskedArray(ndarray):
         >>> a = ma.array([1, 2, 5, 4, 3],mask=[0, 1, 0, 1, 0])
         >>> # Default
         >>> a.sort()
-        >>> print a
+        >>> print(a)
         [1 3 5 -- --]
 
         >>> a = ma.array([1, 2, 5, 4, 3],mask=[0, 1, 0, 1, 0])
         >>> # Put missing values in the front
         >>> a.sort(endwith=False)
-        >>> print a
+        >>> print(a)
         [-- -- 1 3 5]
 
         >>> a = ma.array([1, 2, 5, 4, 3],mask=[0, 1, 0, 1, 0])
         >>> # fill_value takes over endwith
         >>> a.sort(endwith=False, fill_value=3)
-        >>> print a
+        >>> print(a)
         [1 -- -- 3 5]
 
         """
@@ -5452,7 +5452,7 @@ class MaskedArray(ndarray):
         Examples
         --------
         >>> x = np.ma.array(np.arange(6), mask=[0 ,1, 0, 0, 0 ,1]).reshape(3, 2)
-        >>> print x
+        >>> print(x)
         [[0 --]
          [2 3]
          [4 --]]
@@ -5462,7 +5462,7 @@ class MaskedArray(ndarray):
         masked_array(data = [0 3],
                      mask = [False False],
                fill_value = 999999)
-        >>> print x.mini(axis=1)
+        >>> print(x.mini(axis=1))
         [0 2 4]
 
         """
@@ -5741,11 +5741,11 @@ class MaskedArray(ndarray):
         Examples
         --------
         >>> x = np.ma.array([[1,2,3],[4,5,6],[7,8,9]], mask=[0] + [1,0]*4)
-        >>> print x
+        >>> print(x)
         [[1 -- 3]
          [-- 5 --]
          [7 -- 9]]
-        >>> print x.toflex()
+        >>> print(x.toflex())
         [[(1, False) (2, True) (3, False)]
          [(4, True) (5, False) (6, True)]
          [(7, False) (8, True) (9, False)]]
@@ -6914,14 +6914,14 @@ def where(condition, x=_NoValue, y=_NoValue):
     >>> x = np.ma.array(np.arange(9.).reshape(3, 3), mask=[[0, 1, 0],
     ...                                                    [1, 0, 1],
     ...                                                    [0, 1, 0]])
-    >>> print x
+    >>> print(x)
     [[0.0 -- 2.0]
      [-- 4.0 --]
      [6.0 -- 8.0]]
     >>> np.ma.where(x > 5)    # return the indices where x > 5
     (array([2, 2]), array([0, 2]))
 
-    >>> print np.ma.where(x > 5, x, -3.1416)
+    >>> print(np.ma.where(x > 5, x, -3.1416))
     [[-3.1416 -- -3.1416]
      [-- -3.1416 --]
      [6.0 -- 8.0]]
diff --git a/numpy/ma/extras.py b/numpy/ma/extras.py
index e1d228e73..9855b4e76 100644
--- a/numpy/ma/extras.py
+++ b/numpy/ma/extras.py
@@ -439,7 +439,7 @@ if apply_over_axes.__doc__ is not None:
     >>> a = ma.arange(24).reshape(2,3,4)
     >>> a[:,0,1] = ma.masked
     >>> a[:,1,:] = ma.masked
-    >>> print a
+    >>> print(a)
     [[[0 -- 2 3]
       [-- -- -- --]
       [8 9 10 11]]
@@ -447,14 +447,14 @@ if apply_over_axes.__doc__ is not None:
      [[12 -- 14 15]
       [-- -- -- --]
       [20 21 22 23]]]
-    >>> print ma.apply_over_axes(ma.sum, a, [0,2])
+    >>> print(ma.apply_over_axes(ma.sum, a, [0,2]))
     [[[46]
       [--]
       [124]]]
 
     Tuple axis arguments to ufuncs are equivalent:
 
-    >>> print ma.sum(a, axis=(0,2)).reshape((1,-1,1))
+    >>> print(ma.sum(a, axis=(0,2)).reshape((1,-1,1)))
     [[[46]
       [--]
       [124]]]
@@ -502,13 +502,13 @@ def average(a, axis=None, weights=None, returned=False):
     1.25
 
     >>> x = np.ma.arange(6.).reshape(3, 2)
-    >>> print x
+    >>> print(x)
     [[ 0.  1.]
      [ 2.  3.]
      [ 4.  5.]]
     >>> avg, sumweights = np.ma.average(x, axis=0, weights=[1, 2, 3],
     ...                                 returned=True)
-    >>> print avg
+    >>> print(avg)
     [2.66666666667 3.66666666667]
 
     """
@@ -1476,7 +1476,7 @@ def flatnotmasked_edges(a):
     array([3, 8])
 
     >>> a[:] = np.ma.masked
-    >>> print flatnotmasked_edges(ma)
+    >>> print(flatnotmasked_edges(ma))
     None
 
     """
@@ -1578,7 +1578,7 @@ def flatnotmasked_contiguous(a):
     >>> np.ma.flatnotmasked_contiguous(a)
     [slice(3, 5, None), slice(6, 9, None)]
     >>> a[:] = np.ma.masked
-    >>> print np.ma.flatnotmasked_edges(a)
+    >>> print(np.ma.flatnotmasked_edges(a))
     None
 
     """
diff --git a/numpy/ma/tests/test_old_ma.py b/numpy/ma/tests/test_old_ma.py
index a32f358c0..d9a93efd4 100644
--- a/numpy/ma/tests/test_old_ma.py
+++ b/numpy/ma/tests/test_old_ma.py
@@ -831,13 +831,13 @@ def eqmask(m1, m2):
 #            t = testta(n, f)
 #            t1 = testtb(n, f)
 #            t2 = testtc(n, f)
-#            print f.test_name
-#            print """\
+#            print(f.test_name)
+#            print("""\
 #n = %7d
 #numpy time (ms) %6.1f
 #MA maskless ratio %6.1f
 #MA masked ratio %6.1f
-#""" % (n, t*1000.0, t1/t, t2/t)
+#""" % (n, t*1000.0, t1/t, t2/t))
 
 #def testta(n, f):
 #    x=np.arange(n) + 1.0
diff --git a/numpy/matrixlib/defmatrix.py b/numpy/matrixlib/defmatrix.py
index 170db87c8..134f4d203 100644
--- a/numpy/matrixlib/defmatrix.py
+++ b/numpy/matrixlib/defmatrix.py
@@ -233,7 +233,7 @@ class matrix(N.ndarray):
     Examples
     --------
     >>> a = np.matrix('1 2; 3 4')
-    >>> print a
+    >>> print(a)
     [[1 2]
      [3 4]]
 
diff --git a/numpy/testing/decorators.py b/numpy/testing/decorators.py
index df3d297ff..6cde298e1 100644
--- a/numpy/testing/decorators.py
+++ b/numpy/testing/decorators.py
@@ -48,7 +48,7 @@ def slow(t):
 
       @dec.slow
       def test_big(self):
-          print 'Big, slow test'
+          print('Big, slow test')
 
     """
 
diff --git a/numpy/testing/noseclasses.py b/numpy/testing/noseclasses.py
index 197e20bac..4a8e9b0d6 100644
--- a/numpy/testing/noseclasses.py
+++ b/numpy/testing/noseclasses.py
@@ -34,33 +34,33 @@ class NumpyDocTestFinder(doctest.DocTestFinder):
         module.
         """
         if module is None:
-            #print '_fm C1'  # dbg
+            #print('_fm C1')  # dbg
             return True
         elif inspect.isfunction(object):
-            #print '_fm C2'  # dbg
+            #print('_fm C2')  # dbg
             return module.__dict__ is object.__globals__
         elif inspect.isbuiltin(object):
-            #print '_fm C2-1'  # dbg
+            #print('_fm C2-1')  # dbg
             return module.__name__ == object.__module__
         elif inspect.isclass(object):
-            #print '_fm C3'  # dbg
+            #print('_fm C3')  # dbg
             return module.__name__ == object.__module__
         elif inspect.ismethod(object):
             # This one may be a bug in cython that fails to correctly set the
             # __module__ attribute of methods, but since the same error is easy
             # to make by extension code writers, having this safety in place
             # isn't such a bad idea
-            #print '_fm C3-1'  # dbg
+            #print('_fm C3-1')  # dbg
             return module.__name__ == object.__self__.__class__.__module__
         elif inspect.getmodule(object) is not None:
-            #print '_fm C4'  # dbg
-            #print 'C4 mod',module,'obj',object # dbg
+            #print('_fm C4')  # dbg
+            #print('C4 mod',module,'obj',object) # dbg
             return module is inspect.getmodule(object)
         elif hasattr(object, '__module__'):
-            #print '_fm C5'  # dbg
+            #print('_fm C5')  # dbg
             return module.__name__ == object.__module__
         elif isinstance(object, property):
-            #print '_fm C6'  # dbg
+            #print('_fm C6')  # dbg
             return True  # [XX] no way not be sure.
         else:
             raise ValueError("object must be a class or function")
@@ -95,10 +95,10 @@ class NumpyDocTestFinder(doctest.DocTestFinder):
 
         # Look for tests in a class's contained objects.
         if isclass(obj) and self._recurse:
-            #print 'RECURSE into class:',obj  # dbg
+            #print('RECURSE into class:',obj)  # dbg
             for valname, val in obj.__dict__.items():
                 #valname1 = '%s.%s' % (name, valname)  # dbg
-                #print 'N',name,'VN:',valname,'val:',str(val)[:77] # dbg
+                #print('N',name,'VN:',valname,'val:',str(val)[:77]) # dbg
                 # Special handling for staticmethod/classmethod.
                 if isinstance(val, staticmethod):
                     val = getattr(obj, valname)
diff --git a/numpy/testing/utils.py b/numpy/testing/utils.py
index 00f7ce4d1..49d249339 100644
--- a/numpy/testing/utils.py
+++ b/numpy/testing/utils.py
@@ -1293,7 +1293,7 @@ def measure(code_str,times=1,label=None):
     --------
     >>> etime = np.testing.measure('for i in range(1000): np.sqrt(i**2)',
     ...                            times=times)
-    >>> print "Time for a single execution : ", etime / times, "s"
+    >>> print("Time for a single execution : ", etime / times, "s")
     Time for a single execution :  0.005 s
 
     """
diff --git a/tools/swig/test/testFortran.py b/tools/swig/test/testFortran.py
index be4134d4e..c77d728e9 100644
--- a/tools/swig/test/testFortran.py
+++ b/tools/swig/test/testFortran.py
@@ -29,7 +29,7 @@ class FortranTestCase(unittest.TestCase):
     # commenting it out.  --WFS
     # def testSecondElementContiguous(self):
     #     "Test Fortran matrix initialized from reshaped default array"
-    #     print >>sys.stderr, self.typeStr, "... ",
+    #     print(self.typeStr, "... ", end="", file=sys.stderr)
     #     second = Fortran.__dict__[self.typeStr + "SecondElement"]
     #     matrix = np.arange(9).reshape(3, 3).astype(self.typeCode)
     #     self.assertEquals(second(matrix), 3)
diff --git a/tools/win32build/misc/x86analysis.py b/tools/win32build/misc/x86analysis.py
index 39b7cca79..0b5586406 100644
--- a/tools/win32build/misc/x86analysis.py
+++ b/tools/win32build/misc/x86analysis.py
@@ -148,9 +148,9 @@ def analyse(filename):
     sse3 = has_sse3(inst)
     #mmx = has_mmx(inst)
     #ppro = has_ppro(inst)
-    #print sse
-    #print sse2
-    #print sse3
+    #print(sse)
+    #print(sse2)
+    #print(sse3)
     print("SSE3 inst %d" % cntset(sse3))
     print("SSE2 inst %d" % cntset(sse2))
     print("SSE inst %d" % cntset(sse))