diff --git a/Lib/test/test_buffer.py b/Lib/test/test_buffer.py
new file mode 100644
index 0000000..25324ef
--- /dev/null
+++ b/Lib/test/test_buffer.py
@@ -0,0 +1,3437 @@
+#
+# The ndarray object from _testbuffer.c is a complete implementation of
+# a PEP-3118 buffer provider. It is independent from NumPy's ndarray
+# and the tests don't require NumPy.
+#
+# If NumPy is present, some tests check both ndarray implementations
+# against each other.
+#
+# Most ndarray tests also check that memoryview(ndarray) behaves in
+# the same way as the original. Thus, a substantial part of the
+# memoryview tests is now in this module.
+#
+
+import unittest
+from test import support
+from itertools import permutations, product
+from random import randrange, sample, choice
+from sysconfig import get_config_var
+from platform import architecture
+import warnings
+import sys, array, io
+from decimal import Decimal
+from fractions import Fraction
+
+try:
+    from _testbuffer import *
+except ImportError:
+    ndarray = None
+
+try:
+    import struct
+except ImportError:
+    struct = None
+
+try:
+    with warnings.catch_warnings():
+        from numpy import ndarray as numpy_array
+except ImportError:
+    numpy_array = None
+
+
+SHORT_TEST = True
+
+
+# ======================================================================
+#                    Random lists by format specifier
+# ======================================================================
+
+# Native format chars and their ranges.
+NATIVE = {
+    '?':0, 'c':0, 'b':0, 'B':0,
+    'h':0, 'H':0, 'i':0, 'I':0,
+    'l':0, 'L':0, 'n':0, 'N':0,
+    'f':0, 'd':0, 'P':0
+}
+
+if struct:
+    try:
+        # Add "qQ" if present in native mode.
+        struct.pack('Q', 2**64-1)
+        NATIVE['q'] = 0
+        NATIVE['Q'] = 0
+    except struct.error:
+        pass
+
+# Standard format chars and their ranges.
+STANDARD = {
+    '?':(0, 2),            'c':(0, 1<<8),
+    'b':(-(1<<7), 1<<7),   'B':(0, 1<<8),
+    'h':(-(1<<15), 1<<15), 'H':(0, 1<<16),
+    'i':(-(1<<31), 1<<31), 'I':(0, 1<<32),
+    'l':(-(1<<31), 1<<31), 'L':(0, 1<<32),
+    'q':(-(1<<63), 1<<63), 'Q':(0, 1<<64),
+    'f':(-(1<<63), 1<<63), 'd':(-(1<<1023), 1<<1023)
+}
+
+def native_type_range(fmt):
+    """Return range of a native type."""
+    if fmt == 'c':
+        lh = (0, 256)
+    elif fmt == '?':
+        lh = (0, 2)
+    elif fmt == 'f':
+        lh = (-(1<<63), 1<<63)
+    elif fmt == 'd':
+        lh = (-(1<<1023), 1<<1023)
+    else:
+        for exp in (128, 127, 64, 63, 32, 31, 16, 15, 8, 7):
+            try:
+                struct.pack(fmt, (1<<exp)-1)
+                break
+            except struct.error:
+                pass
+        lh = (-(1<<exp), 1<<exp) if exp & 1 else (0, 1<<exp)
+    return lh
+
+fmtdict = {
+    '':NATIVE,
+    '@':NATIVE,
+    '<':STANDARD,
+    '>':STANDARD,
+    '=':STANDARD,
+    '!':STANDARD
+}
+
+if struct:
+    for fmt in fmtdict['@']:
+        fmtdict['@'][fmt] = native_type_range(fmt)
+
+MEMORYVIEW = NATIVE.copy()
+ARRAY = NATIVE.copy()
+for k in NATIVE:
+    if not k in "bBhHiIlLfd":
+        del ARRAY[k]
+
+BYTEFMT = NATIVE.copy()
+for k in NATIVE:
+    if not k in "Bbc":
+        del BYTEFMT[k]
+
+fmtdict['m']  = MEMORYVIEW
+fmtdict['@m'] = MEMORYVIEW
+fmtdict['a']  = ARRAY
+fmtdict['b']  = BYTEFMT
+fmtdict['@b']  = BYTEFMT
+
+# Capabilities of the test objects:
+MODE = 0
+MULT = 1
+cap = {         # format chars                  # multiplier
+  'ndarray':    (['', '@', '<', '>', '=', '!'], ['', '1', '2', '3']),
+  'array':      (['a'],                         ['']),
+  'numpy':      ([''],                          ['']),
+  'memoryview': (['@m', 'm'],                   ['']),
+  'bytefmt':    (['@b', 'b'],                   ['']),
+}
+
+def randrange_fmt(mode, char, obj):
+    """Return random item for a type specified by a mode and a single
+       format character."""
+    x = randrange(*fmtdict[mode][char])
+    if char == 'c':
+        x = bytes(chr(x), 'latin1')
+    if char == '?':
+        x = bool(x)
+    if char == 'f' or char == 'd':
+        x = struct.pack(char, x)
+        x = struct.unpack(char, x)[0]
+    if obj == 'numpy' and x == b'\x00':
+        # http://projects.scipy.org/numpy/ticket/1925
+        x = b'\x01'
+    return x
+
+def gen_item(fmt, obj):
+    """Return single random item."""
+    mode, chars = fmt.split('#')
+    x = []
+    for c in chars:
+        x.append(randrange_fmt(mode, c, obj))
+    return x[0] if len(x) == 1 else tuple(x)
+
+def gen_items(n, fmt, obj):
+    """Return a list of random items (or a scalar)."""
+    if n == 0:
+        return gen_item(fmt, obj)
+    lst = [0] * n
+    for i in range(n):
+        lst[i] = gen_item(fmt, obj)
+    return lst
+
+def struct_items(n, obj):
+    mode = choice(cap[obj][MODE])
+    xfmt = mode + '#'
+    fmt = mode.strip('amb')
+    nmemb = randrange(2, 10) # number of struct members
+    for _ in range(nmemb):
+        char = choice(tuple(fmtdict[mode]))
+        multiplier = choice(cap[obj][MULT])
+        xfmt += (char * int(multiplier if multiplier else 1))
+        fmt += (multiplier + char)
+    items = gen_items(n, xfmt, obj)
+    item = gen_item(xfmt, obj)
+    return fmt, items, item
+
+def randitems(n, obj='ndarray', mode=None, char=None):
+    """Return random format, items, item."""
+    if mode is None:
+        mode = choice(cap[obj][MODE])
+    if char is None:
+        char = choice(tuple(fmtdict[mode]))
+    multiplier = choice(cap[obj][MULT])
+    fmt = mode + '#' + char * int(multiplier if multiplier else 1)
+    items = gen_items(n, fmt, obj)
+    item = gen_item(fmt, obj)
+    fmt = mode.strip('amb') + multiplier + char
+    return fmt, items, item
+
+def iter_mode(n, obj='ndarray'):
+    """Iterate through supported mode/char combinations."""
+    for mode in cap[obj][MODE]:
+        for char in fmtdict[mode]:
+            yield randitems(n, obj, mode, char)
+
+def iter_format(nitems, testobj='ndarray'):
+    """Yield (format, items, item) for all possible modes and format
+       characters plus one random compound format string."""
+    for t in iter_mode(nitems, testobj):
+        yield t
+    if testobj != 'ndarray':
+        raise StopIteration
+    yield struct_items(nitems, testobj)
+
+
+def is_byte_format(fmt):
+    return 'c' in fmt or 'b' in fmt or 'B' in fmt
+
+def is_memoryview_format(fmt):
+    """format suitable for memoryview"""
+    x = len(fmt)
+    return ((x == 1 or (x == 2 and fmt[0] == '@')) and
+            fmt[x-1] in MEMORYVIEW)
+
+NON_BYTE_FORMAT = [c for c in fmtdict['@'] if not is_byte_format(c)]
+
+
+# ======================================================================
+#       Multi-dimensional tolist(), slicing and slice assignments
+# ======================================================================
+
+def atomp(lst):
+    """Tuple items (representing structs) are regarded as atoms."""
+    return not isinstance(lst, list)
+
+def listp(lst):
+    return isinstance(lst, list)
+
+def prod(lst):
+    """Product of list elements."""
+    if len(lst) == 0:
+        return 0
+    x = lst[0]
+    for v in lst[1:]:
+        x *= v
+    return x
+
+def strides_from_shape(ndim, shape, itemsize, layout):
+    """Calculate strides of a contiguous array. Layout is 'C' or
+       'F' (Fortran)."""
+    if ndim == 0:
+        return ()
+    if layout == 'C':
+        strides = list(shape[1:]) + [itemsize]
+        for i in range(ndim-2, -1, -1):
+            strides[i] *= strides[i+1]
+    else:
+        strides = [itemsize] + list(shape[:-1])
+        for i in range(1, ndim):
+            strides[i] *= strides[i-1]
+    return strides
+
+def _ca(items, s):
+    """Convert flat item list to the nested list representation of a
+       multidimensional C array with shape 's'."""
+    if atomp(items):
+        return items
+    if len(s) == 0:
+        return items[0]
+    lst = [0] * s[0]
+    stride = len(items) // s[0] if s[0] else 0
+    for i in range(s[0]):
+        start = i*stride
+        lst[i] = _ca(items[start:start+stride], s[1:])
+    return lst
+
+def _fa(items, s):
+    """Convert flat item list to the nested list representation of a
+       multidimensional Fortran array with shape 's'."""
+    if atomp(items):
+        return items
+    if len(s) == 0:
+        return items[0]
+    lst = [0] * s[0]
+    stride = s[0]
+    for i in range(s[0]):
+        lst[i] = _fa(items[i::stride], s[1:])
+    return lst
+
+def carray(items, shape):
+    if listp(items) and not 0 in shape and prod(shape) != len(items):
+        raise ValueError("prod(shape) != len(items)")
+    return _ca(items, shape)
+
+def farray(items, shape):
+    if listp(items) and not 0 in shape and prod(shape) != len(items):
+        raise ValueError("prod(shape) != len(items)")
+    return _fa(items, shape)
+
+def indices(shape):
+    """Generate all possible tuples of indices."""
+    iterables = [range(v) for v in shape]
+    return product(*iterables)
+
+def getindex(ndim, ind, strides):
+    """Convert multi-dimensional index to the position in the flat list."""
+    ret = 0
+    for i in range(ndim):
+        ret += strides[i] * ind[i]
+    return ret
+
+def transpose(src, shape):
+    """Transpose flat item list that is regarded as a multi-dimensional
+       matrix defined by shape: dest...[k][j][i] = src[i][j][k]...  """
+    if not shape:
+        return src
+    ndim = len(shape)
+    sstrides = strides_from_shape(ndim, shape, 1, 'C')
+    dstrides = strides_from_shape(ndim, shape[::-1], 1, 'C')
+    dest = [0] * len(src)
+    for ind in indices(shape):
+        fr = getindex(ndim, ind, sstrides)
+        to = getindex(ndim, ind[::-1], dstrides)
+        dest[to] = src[fr]
+    return dest
+
+def _flatten(lst):
+    """flatten list"""
+    if lst == []:
+        return lst
+    if atomp(lst):
+        return [lst]
+    return _flatten(lst[0]) + _flatten(lst[1:])
+
+def flatten(lst):
+    """flatten list or return scalar"""
+    if atomp(lst): # scalar
+        return lst
+    return _flatten(lst)
+
+def slice_shape(lst, slices):
+    """Get the shape of lst after slicing: slices is a list of slice
+       objects."""
+    if atomp(lst):
+        return []
+    return [len(lst[slices[0]])] + slice_shape(lst[0], slices[1:])
+
+def multislice(lst, slices):
+    """Multi-dimensional slicing: slices is a list of slice objects."""
+    if atomp(lst):
+        return lst
+    return [multislice(sublst, slices[1:]) for sublst in lst[slices[0]]]
+
+def m_assign(llst, rlst, lslices, rslices):
+    """Multi-dimensional slice assignment: llst and rlst are the operands,
+       lslices and rslices are lists of slice objects. llst and rlst must
+       have the same structure.
+
+       For a two-dimensional example, this is not implemented in Python:
+
+         llst[0:3:2, 0:3:2] = rlst[1:3:1, 1:3:1]
+
+       Instead we write:
+
+         lslices = [slice(0,3,2), slice(0,3,2)]
+         rslices = [slice(1,3,1), slice(1,3,1)]
+         multislice_assign(llst, rlst, lslices, rslices)
+    """
+    if atomp(rlst):
+        return rlst
+    rlst = [m_assign(l, r, lslices[1:], rslices[1:])
+            for l, r in zip(llst[lslices[0]], rlst[rslices[0]])]
+    llst[lslices[0]] = rlst
+    return llst
+
+def cmp_structure(llst, rlst, lslices, rslices):
+    """Compare the structure of llst[lslices] and rlst[rslices]."""
+    lshape = slice_shape(llst, lslices)
+    rshape = slice_shape(rlst, rslices)
+    if (len(lshape) != len(rshape)):
+        return -1
+    for i in range(len(lshape)):
+        if lshape[i] != rshape[i]:
+            return -1
+        if lshape[i] == 0:
+            return 0
+    return 0
+
+def multislice_assign(llst, rlst, lslices, rslices):
+    """Return llst after assigning: llst[lslices] = rlst[rslices]"""
+    if cmp_structure(llst, rlst, lslices, rslices) < 0:
+        raise ValueError("lvalue and rvalue have different structures")
+    return m_assign(llst, rlst, lslices, rslices)
+
+
+# ======================================================================
+#                          Random structures
+# ======================================================================
+
+#
+# PEP-3118 is very permissive with respect to the contents of a
+# Py_buffer. In particular:
+#
+#   - shape can be zero
+#   - strides can be any integer, including zero
+#   - offset can point to any location in the underlying
+#     memory block, provided that it is a multiple of
+#     itemsize.
+#
+# The functions in this section test and verify random structures
+# in full generality. A structure is valid iff it fits in the
+# underlying memory block.
+#
+# The structure 't' (short for 'tuple') is fully defined by:
+#
+#   t = (memlen, itemsize, ndim, shape, strides, offset)
+#
+
+def verify_structure(memlen, itemsize, ndim, shape, strides, offset):
+    """Verify that the parameters represent a valid array within
+       the bounds of the allocated memory:
+           char *mem: start of the physical memory block
+           memlen: length of the physical memory block
+           offset: (char *)buf - mem
+    """
+    if offset % itemsize:
+        return False
+    if offset < 0 or offset+itemsize > memlen:
+        return False
+    if any(v % itemsize for v in strides):
+        return False
+
+    if ndim <= 0:
+        return ndim == 0 and not shape and not strides
+    if 0 in shape:
+        return True
+
+    imin = sum(strides[j]*(shape[j]-1) for j in range(ndim)
+               if strides[j] <= 0)
+    imax = sum(strides[j]*(shape[j]-1) for j in range(ndim)
+               if strides[j] > 0)
+
+    return 0 <= offset+imin and offset+imax+itemsize <= memlen
+
+def get_item(lst, indices):
+    for i in indices:
+        lst = lst[i]
+    return lst
+
+def memory_index(indices, t):
+    """Location of an item in the underlying memory."""
+    memlen, itemsize, ndim, shape, strides, offset = t
+    p = offset
+    for i in range(ndim):
+        p += strides[i]*indices[i]
+    return p
+
+def is_overlapping(t):
+    """The structure 't' is overlapping if at least one memory location
+       is visited twice while iterating through all possible tuples of
+       indices."""
+    memlen, itemsize, ndim, shape, strides, offset = t
+    visited = 1<<memlen
+    for ind in indices(shape):
+        i = memory_index(ind, t)
+        bit = 1<<i
+        if visited & bit:
+            return True
+        visited |= bit
+    return False
+
+def rand_structure(itemsize, valid, maxdim=5, maxshape=16, shape=()):
+    """Return random structure:
+           (memlen, itemsize, ndim, shape, strides, offset)
+       If 'valid' is true, the returned structure is valid, otherwise invalid.
+       If 'shape' is given, use that instead of creating a random shape.
+    """
+    if not shape:
+        ndim = randrange(maxdim+1)
+        if (ndim == 0):
+            if valid:
+                return itemsize, itemsize, ndim, (), (), 0
+            else:
+                nitems = randrange(1, 16+1)
+                memlen = nitems * itemsize
+                offset = -itemsize if randrange(2) == 0 else memlen
+                return memlen, itemsize, ndim, (), (), offset
+
+        minshape = 2
+        n = randrange(100)
+        if n >= 95 and valid:
+            minshape = 0
+        elif n >= 90:
+            minshape = 1
+        shape = [0] * ndim
+
+        for i in range(ndim):
+            shape[i] = randrange(minshape, maxshape+1)
+    else:
+        ndim = len(shape)
+
+    maxstride = 5
+    n = randrange(100)
+    zero_stride = True if n >= 95 and n & 1 else False
+
+    strides = [0] * ndim
+    strides[ndim-1] = itemsize * randrange(-maxstride, maxstride+1)
+    if not zero_stride and strides[ndim-1] == 0:
+        strides[ndim-1] = itemsize
+
+    for i in range(ndim-2, -1, -1):
+        maxstride *= shape[i+1] if shape[i+1] else 1
+        if zero_stride:
+            strides[i] = itemsize * randrange(-maxstride, maxstride+1)
+        else:
+            strides[i] = ((1,-1)[randrange(2)] *
+                          itemsize * randrange(1, maxstride+1))
+
+    imin = imax = 0
+    if not 0 in shape:
+        imin = sum(strides[j]*(shape[j]-1) for j in range(ndim)
+                   if strides[j] <= 0)
+        imax = sum(strides[j]*(shape[j]-1) for j in range(ndim)
+                   if strides[j] > 0)
+
+    nitems = imax - imin
+    if valid:
+        offset = -imin * itemsize
+        memlen = offset + (imax+1) * itemsize
+    else:
+        memlen = (-imin + imax) * itemsize
+        offset = -imin-itemsize if randrange(2) == 0 else memlen
+    return memlen, itemsize, ndim, shape, strides, offset
+
+def randslice_from_slicelen(slicelen, listlen):
+    """Create a random slice of len slicelen that fits into listlen."""
+    maxstart = listlen - slicelen
+    start = randrange(maxstart+1)
+    maxstep = (listlen - start) // slicelen if slicelen else 1
+    step = randrange(1, maxstep+1)
+    stop = start + slicelen * step
+    s = slice(start, stop, step)
+    _, _, _, control = slice_indices(s, listlen)
+    if control != slicelen:
+        raise RuntimeError
+    return s
+
+def randslice_from_shape(ndim, shape):
+    """Create two sets of slices for an array x with shape 'shape'
+       such that shapeof(x[lslices]) == shapeof(x[rslices])."""
+    lslices = [0] * ndim
+    rslices = [0] * ndim
+    for n in range(ndim):
+        l = shape[n]
+        slicelen = randrange(1, l+1) if l > 0 else 0
+        lslices[n] = randslice_from_slicelen(slicelen, l)
+        rslices[n] = randslice_from_slicelen(slicelen, l)
+    return tuple(lslices), tuple(rslices)
+
+def rand_aligned_slices(maxdim=5, maxshape=16):
+    """Create (lshape, rshape, tuple(lslices), tuple(rslices)) such that
+       shapeof(x[lslices]) == shapeof(y[rslices]), where x is an array
+       with shape 'lshape' and y is an array with shape 'rshape'."""
+    ndim = randrange(1, maxdim+1)
+    minshape = 2
+    n = randrange(100)
+    if n >= 95:
+        minshape = 0
+    elif n >= 90:
+        minshape = 1
+    all_random = True if randrange(100) >= 80 else False
+    lshape = [0]*ndim; rshape = [0]*ndim
+    lslices = [0]*ndim; rslices = [0]*ndim
+
+    for n in range(ndim):
+        small = randrange(minshape, maxshape+1)
+        big = randrange(minshape, maxshape+1)
+        if big < small:
+            big, small = small, big
+
+        # Create a slice that fits the smaller value.
+        if all_random:
+            start = randrange(-small, small+1)
+            stop = randrange(-small, small+1)
+            step = (1,-1)[randrange(2)] * randrange(1, small+2)
+            s_small = slice(start, stop, step)
+            _, _, _, slicelen = slice_indices(s_small, small)
+        else:
+            slicelen = randrange(1, small+1) if small > 0 else 0
+            s_small = randslice_from_slicelen(slicelen, small)
+
+        # Create a slice of the same length for the bigger value.
+        s_big = randslice_from_slicelen(slicelen, big)
+        if randrange(2) == 0:
+            rshape[n], lshape[n] = big, small
+            rslices[n], lslices[n] = s_big, s_small
+        else:
+            rshape[n], lshape[n] = small, big
+            rslices[n], lslices[n] = s_small, s_big
+
+    return lshape, rshape, tuple(lslices), tuple(rslices)
+
+def randitems_from_structure(fmt, t):
+    """Return a list of random items for structure 't' with format
+       'fmtchar'."""
+    memlen, itemsize, _, _, _, _ = t
+    return gen_items(memlen//itemsize, '#'+fmt, 'numpy')
+
+def ndarray_from_structure(items, fmt, t, flags=0):
+    """Return ndarray from the tuple returned by rand_structure()"""
+    memlen, itemsize, ndim, shape, strides, offset = t
+    return ndarray(items, shape=shape, strides=strides, format=fmt,
+                   offset=offset, flags=ND_WRITABLE|flags)
+
+def numpy_array_from_structure(items, fmt, t):
+    """Return numpy_array from the tuple returned by rand_structure()"""
+    memlen, itemsize, ndim, shape, strides, offset = t
+    buf = bytearray(memlen)
+    for j, v in enumerate(items):
+        struct.pack_into(fmt, buf, j*itemsize, v)
+    return numpy_array(buffer=buf, shape=shape, strides=strides,
+                       dtype=fmt, offset=offset)
+
+
+# ======================================================================
+#                          memoryview casts
+# ======================================================================
+
+def cast_items(exporter, fmt, itemsize, shape=None):
+    """Interpret the raw memory of 'exporter' as a list of items with
+       size 'itemsize'. If shape=None, the new structure is assumed to
+       be 1-D with n * itemsize = bytelen. If shape is given, the usual
+       constraint for contiguous arrays prod(shape) * itemsize = bytelen
+       applies. On success, return (items, shape). If the constraints
+       cannot be met, return (None, None). If a chunk of bytes is interpreted
+       as NaN as a result of float conversion, return ('nan', None)."""
+    bytelen = exporter.nbytes
+    if shape:
+        if prod(shape) * itemsize != bytelen:
+            return None, shape
+    elif shape == []:
+        if exporter.ndim == 0 or itemsize != bytelen:
+            return None, shape
+    else:
+        n, r = divmod(bytelen, itemsize)
+        shape = [n]
+        if r != 0:
+            return None, shape
+
+    mem = exporter.tobytes()
+    byteitems = [mem[i:i+itemsize] for i in range(0, len(mem), itemsize)]
+
+    items = []
+    for v in byteitems:
+        item = struct.unpack(fmt, v)[0]
+        if item != item:
+            return 'nan', shape
+        items.append(item)
+
+    return (items, shape) if shape != [] else (items[0], shape)
+
+def gencastshapes():
+    """Generate shapes to test casting."""
+    for n in range(32):
+        yield [n]
+    ndim = randrange(4, 6)
+    minshape = 1 if randrange(100) > 80 else 2
+    yield [randrange(minshape, 5) for _ in range(ndim)]
+    ndim = randrange(2, 4)
+    minshape = 1 if randrange(100) > 80 else 2
+    yield [randrange(minshape, 5) for _ in range(ndim)]
+
+
+# ======================================================================
+#                              Actual tests
+# ======================================================================
+
+def genslices(n):
+    """Generate all possible slices for a single dimension."""
+    return product(range(-n, n+1), range(-n, n+1), range(-n, n+1))
+
+def genslices_ndim(ndim, shape):
+    """Generate all possible slice tuples for 'shape'."""
+    iterables = [genslices(shape[n]) for n in range(ndim)]
+    return product(*iterables)
+
+def rslice(n, allow_empty=False):
+    """Generate random slice for a single dimension of length n.
+       If zero=True, the slices may be empty, otherwise they will
+       be non-empty."""
+    minlen = 0 if allow_empty or n == 0 else 1
+    slicelen = randrange(minlen, n+1)
+    return randslice_from_slicelen(slicelen, n)
+
+def rslices(n, allow_empty=False):
+    """Generate random slices for a single dimension."""
+    for _ in range(5):
+        yield rslice(n, allow_empty)
+
+def rslices_ndim(ndim, shape, iterations=5):
+    """Generate random slice tuples for 'shape'."""
+    # non-empty slices
+    for _ in range(iterations):
+        yield tuple(rslice(shape[n]) for n in range(ndim))
+    # possibly empty slices
+    for _ in range(iterations):
+        yield tuple(rslice(shape[n], allow_empty=True) for n in range(ndim))
+    # invalid slices
+    yield tuple(slice(0,1,0) for _ in range(ndim))
+
+def rpermutation(iterable, r=None):
+    pool = tuple(iterable)
+    r = len(pool) if r is None else r
+    yield tuple(sample(pool, r))
+
+def ndarray_print(nd):
+    """Print ndarray for debugging."""
+    try:
+        x = nd.tolist()
+    except (TypeError, NotImplementedError):
+        x = nd.tobytes()
+    if isinstance(nd, ndarray):
+        offset = nd.offset
+        flags = nd.flags
+    else:
+        offset = 'unknown'
+        flags = 'unknown'
+    print("ndarray(%s, shape=%s, strides=%s, suboffsets=%s, offset=%s, "
+          "format='%s', itemsize=%s, flags=%s)" %
+          (x, nd.shape, nd.strides, nd.suboffsets, offset,
+           nd.format, nd.itemsize, flags))
+    sys.stdout.flush()
+
+
+ITERATIONS = 100
+MAXDIM = 5
+MAXSHAPE = 10
+
+if SHORT_TEST:
+    ITERATIONS = 10
+    MAXDIM = 3
+    MAXSHAPE = 4
+    genslices = rslices
+    genslices_ndim = rslices_ndim
+    permutations = rpermutation
+
+
+@unittest.skipUnless(struct, 'struct module required for this test.')
+@unittest.skipUnless(ndarray, 'ndarray object required for this test')
+class TestBufferProtocol(unittest.TestCase):
+
+    def setUp(self):
+        self.sizeof_void_p = get_config_var('SIZEOF_VOID_P')
+        if not self.sizeof_void_p:
+            self.sizeof_void_p = 8 if architecture()[0] == '64bit' else 4
+
+    def verify(self, result, obj=-1,
+                     itemsize={1}, fmt=-1, readonly={1},
+                     ndim={1}, shape=-1, strides=-1,
+                     lst=-1, sliced=False, cast=False):
+        # Verify buffer contents against expected values. Default values
+        # are deliberately initialized to invalid types.
+        if shape:
+            expected_len = prod(shape)*itemsize
+        else:
+            if not fmt: # array has been implicitly cast to unsigned bytes
+                expected_len = len(lst)
+            else: # ndim = 0
+                expected_len = itemsize
+
+        # Reconstruct suboffsets from strides. Support for slicing
+        # could be added, but is currently only needed for test_getbuf().
+        suboffsets = ()
+        if result.suboffsets:
+            self.assertGreater(ndim, 0)
+
+            suboffset0 = 0
+            for n in range(1, ndim):
+                if shape[n] == 0:
+                    break
+                if strides[n] <= 0:
+                    suboffset0 += -strides[n] * (shape[n]-1)
+
+            suboffsets = [suboffset0] + [-1 for v in range(ndim-1)]
+
+            # Not correct if slicing has occurred in the first dimension.
+            stride0 = self.sizeof_void_p
+            if strides[0] < 0:
+                stride0 = -stride0
+            strides = [stride0] + list(strides[1:])
+
+        self.assertIs(result.obj, obj)
+        self.assertEqual(result.nbytes, expected_len)
+        self.assertEqual(result.itemsize, itemsize)
+        self.assertEqual(result.format, fmt)
+        self.assertEqual(result.readonly, readonly)
+        self.assertEqual(result.ndim, ndim)
+        self.assertEqual(result.shape, tuple(shape))
+        if not (sliced and suboffsets):
+            self.assertEqual(result.strides, tuple(strides))
+        self.assertEqual(result.suboffsets, tuple(suboffsets))
+
+        if isinstance(result, ndarray) or is_memoryview_format(fmt):
+            rep = result.tolist() if fmt else result.tobytes()
+            self.assertEqual(rep, lst)
+
+        if not fmt: # array has been cast to unsigned bytes,
+            return  # the remaining tests won't work.
+
+        # PyBuffer_GetPointer() is the definition how to access an item.
+        # If PyBuffer_GetPointer(indices) is correct for all possible
+        # combinations of indices, the buffer is correct.
+        #
+        # Also test tobytes() against the flattened 'lst', with all items
+        # packed to bytes.
+        if not cast: # casts chop up 'lst' in different ways
+            b = bytearray()
+            buf_err = None
+            for ind in indices(shape):
+                try:
+                    item1 = get_pointer(result, ind)
+                    item2 = get_item(lst, ind)
+                    if isinstance(item2, tuple):
+                        x = struct.pack(fmt, *item2)
+                    else:
+                        x = struct.pack(fmt, item2)
+                    b.extend(x)
+                except BufferError:
+                    buf_err = True # re-exporter does not provide full buffer
+                    break
+                self.assertEqual(item1, item2)
+
+            if not buf_err:
+                # test tobytes()
+                self.assertEqual(result.tobytes(), b)
+
+            if not buf_err and is_memoryview_format(fmt):
+
+                # lst := expected multi-dimensional logical representation
+                # flatten(lst) := elements in C-order
+                ff = fmt if fmt else 'B'
+                flattened = flatten(lst)
+
+                # Rules for 'A': if the array is already contiguous, return
+                # the array unaltered. Otherwise, return a contiguous 'C'
+                # representation.
+                for order in ['C', 'F', 'A']:
+                    expected = result
+                    if order == 'F':
+                        if not is_contiguous(result, 'A') or \
+                           is_contiguous(result, 'C'):
+                            # For constructing the ndarray, convert the
+                            # flattened logical representation to Fortran order.
+                            trans = transpose(flattened, shape)
+                            expected = ndarray(trans, shape=shape, format=ff,
+                                               flags=ND_FORTRAN)
+                    else: # 'C', 'A'
+                        if not is_contiguous(result, 'A') or \
+                           is_contiguous(result, 'F') and order == 'C':
+                            # The flattened list is already in C-order.
+                            expected = ndarray(flattened, shape=shape, format=ff)
+                            contig = get_contiguous(result, PyBUF_READ, order)
+                    contig = get_contiguous(result, PyBUF_READ, order)
+                    self.assertEqual(contig.tobytes(), b)
+                    self.assertTrue(cmp_contig(contig, expected))
+
+        if is_memoryview_format(fmt):
+            try:
+                m = memoryview(result)
+            except BufferError: # re-exporter does not provide full information
+                return
+            ex = result.obj if isinstance(result, memoryview) else result
+            self.assertIs(m.obj, ex)
+            self.assertEqual(m.nbytes, expected_len)
+            self.assertEqual(m.itemsize, itemsize)
+            self.assertEqual(m.format, fmt)
+            self.assertEqual(m.readonly, readonly)
+            self.assertEqual(m.ndim, ndim)
+            self.assertEqual(m.shape, tuple(shape))
+            if not (sliced and suboffsets):
+                self.assertEqual(m.strides, tuple(strides))
+            self.assertEqual(m.suboffsets, tuple(suboffsets))
+
+            n = 1 if ndim == 0 else len(lst)
+            self.assertEqual(len(m), n)
+
+            rep = result.tolist() if fmt else result.tobytes()
+            self.assertEqual(rep, lst)
+            self.assertEqual(m, result)
+
+    def verify_getbuf(self, orig_ex, ex, req, sliced=False):
+        def simple_fmt(ex):
+            return ex.format == '' or ex.format == 'B'
+        def match(req, flag):
+            return ((req&flag) == flag)
+
+        if (# writable request to read-only exporter
+            (ex.readonly and match(req, PyBUF_WRITABLE)) or
+            # cannot match explicit contiguity request
+            (match(req, PyBUF_C_CONTIGUOUS) and not ex.c_contiguous) or
+            (match(req, PyBUF_F_CONTIGUOUS) and not ex.f_contiguous) or
+            (match(req, PyBUF_ANY_CONTIGUOUS) and not ex.contiguous) or
+            # buffer needs suboffsets
+            (not match(req, PyBUF_INDIRECT) and ex.suboffsets) or
+            # buffer without strides must be C-contiguous
+            (not match(req, PyBUF_STRIDES) and not ex.c_contiguous) or
+            # PyBUF_SIMPLE|PyBUF_FORMAT and PyBUF_WRITABLE|PyBUF_FORMAT
+            (not match(req, PyBUF_ND) and match(req, PyBUF_FORMAT))):
+
+            self.assertRaises(BufferError, ndarray, ex, getbuf=req)
+            return
+
+        if isinstance(ex, ndarray) or is_memoryview_format(ex.format):
+            lst = ex.tolist()
+        else:
+            nd = ndarray(ex, getbuf=PyBUF_FULL_RO)
+            lst = nd.tolist()
+
+        # The consumer may have requested default values or a NULL format.
+        ro = 0 if match(req, PyBUF_WRITABLE) else ex.readonly
+        fmt = ex.format
+        itemsize = ex.itemsize
+        ndim = ex.ndim
+        if not match(req, PyBUF_FORMAT):
+            # itemsize refers to the original itemsize before the cast.
+            # The equality product(shape) * itemsize = len still holds.
+            # The equality calcsize(format) = itemsize does _not_ hold.
+            fmt = ''
+            lst = orig_ex.tobytes() # Issue 12834
+        if not match(req, PyBUF_ND):
+            ndim = 1
+        shape = orig_ex.shape if match(req, PyBUF_ND) else ()
+        strides = orig_ex.strides if match(req, PyBUF_STRIDES) else ()
+
+        nd = ndarray(ex, getbuf=req)
+        self.verify(nd, obj=ex,
+                    itemsize=itemsize, fmt=fmt, readonly=ro,
+                    ndim=ndim, shape=shape, strides=strides,
+                    lst=lst, sliced=sliced)
+
+    def test_ndarray_getbuf(self):
+        requests = (
+            # distinct flags
+            PyBUF_INDIRECT, PyBUF_STRIDES, PyBUF_ND, PyBUF_SIMPLE,
+            PyBUF_C_CONTIGUOUS, PyBUF_F_CONTIGUOUS, PyBUF_ANY_CONTIGUOUS,
+            # compound requests
+            PyBUF_FULL, PyBUF_FULL_RO,
+            PyBUF_RECORDS, PyBUF_RECORDS_RO,
+            PyBUF_STRIDED, PyBUF_STRIDED_RO,
+            PyBUF_CONTIG, PyBUF_CONTIG_RO,
+        )
+        # items and format
+        items_fmt = (
+            ([True if x % 2 else False for x in range(12)], '?'),
+            ([1,2,3,4,5,6,7,8,9,10,11,12], 'b'),
+            ([1,2,3,4,5,6,7,8,9,10,11,12], 'B'),
+            ([(2**31-x) if x % 2 else (-2**31+x) for x in range(12)], 'l')
+        )
+        # shape, strides, offset
+        structure = (
+            ([], [], 0),
+            ([12], [], 0),
+            ([12], [-1], 11),
+            ([6], [2], 0),
+            ([6], [-2], 11),
+            ([3, 4], [], 0),
+            ([3, 4], [-4, -1], 11),
+            ([2, 2], [4, 1], 4),
+            ([2, 2], [-4, -1], 8)
+        )
+        # ndarray creation flags
+        ndflags = (
+            0, ND_WRITABLE, ND_FORTRAN, ND_FORTRAN|ND_WRITABLE,
+            ND_PIL, ND_PIL|ND_WRITABLE
+        )
+        # flags that can actually be used as flags
+        real_flags = (0, PyBUF_WRITABLE, PyBUF_FORMAT,
+                      PyBUF_WRITABLE|PyBUF_FORMAT)
+
+        for items, fmt in items_fmt:
+            itemsize = struct.calcsize(fmt)
+            for shape, strides, offset in structure:
+                strides = [v * itemsize for v in strides]
+                offset *= itemsize
+                for flags in ndflags:
+
+                    if strides and (flags&ND_FORTRAN):
+                        continue
+                    if not shape and (flags&ND_PIL):
+                        continue
+
+                    _items = items if shape else items[0]
+                    ex1 = ndarray(_items, format=fmt, flags=flags,
+                                  shape=shape, strides=strides, offset=offset)
+                    ex2 = ex1[::-2] if shape else None
+
+                    m1 = memoryview(ex1)
+                    if ex2:
+                        m2 = memoryview(ex2)
+                    if ex1.ndim == 0 or (ex1.ndim == 1 and shape and strides):
+                        self.assertEqual(m1, ex1)
+                    if ex2 and ex2.ndim == 1 and shape and strides:
+                        self.assertEqual(m2, ex2)
+
+                    for req in requests:
+                        for bits in real_flags:
+                            self.verify_getbuf(ex1, ex1, req|bits)
+                            self.verify_getbuf(ex1, m1, req|bits)
+                            if ex2:
+                                self.verify_getbuf(ex2, ex2, req|bits,
+                                                   sliced=True)
+                                self.verify_getbuf(ex2, m2, req|bits,
+                                                   sliced=True)
+
+        items = [1,2,3,4,5,6,7,8,9,10,11,12]
+
+        # ND_GETBUF_FAIL
+        ex = ndarray(items, shape=[12], flags=ND_GETBUF_FAIL)
+        self.assertRaises(BufferError, ndarray, ex)
+
+        # Request complex structure from a simple exporter. In this
+        # particular case the test object is not PEP-3118 compliant.
+        base = ndarray([9], [1])
+        ex = ndarray(base, getbuf=PyBUF_SIMPLE)
+        self.assertRaises(BufferError, ndarray, ex, getbuf=PyBUF_WRITABLE)
+        self.assertRaises(BufferError, ndarray, ex, getbuf=PyBUF_ND)
+        self.assertRaises(BufferError, ndarray, ex, getbuf=PyBUF_STRIDES)
+        self.assertRaises(BufferError, ndarray, ex, getbuf=PyBUF_C_CONTIGUOUS)
+        self.assertRaises(BufferError, ndarray, ex, getbuf=PyBUF_F_CONTIGUOUS)
+        self.assertRaises(BufferError, ndarray, ex, getbuf=PyBUF_ANY_CONTIGUOUS)
+        nd = ndarray(ex, getbuf=PyBUF_SIMPLE)
+
+    def test_ndarray_exceptions(self):
+        nd = ndarray([9], [1])
+        ndm = ndarray([9], [1], flags=ND_VAREXPORT)
+
+        # Initialization of a new ndarray or mutation of an existing array.
+        for c in (ndarray, nd.push, ndm.push):
+            # Invalid types.
+            self.assertRaises(TypeError, c, {1,2,3})
+            self.assertRaises(TypeError, c, [1,2,'3'])
+            self.assertRaises(TypeError, c, [1,2,(3,4)])
+            self.assertRaises(TypeError, c, [1,2,3], shape={3})
+            self.assertRaises(TypeError, c, [1,2,3], shape=[3], strides={1})
+            self.assertRaises(TypeError, c, [1,2,3], shape=[3], offset=[])
+            self.assertRaises(TypeError, c, [1], shape=[1], format={})
+            self.assertRaises(TypeError, c, [1], shape=[1], flags={})
+            self.assertRaises(TypeError, c, [1], shape=[1], getbuf={})
+
+            # ND_FORTRAN flag is only valid without strides.
+            self.assertRaises(TypeError, c, [1], shape=[1], strides=[1],
+                              flags=ND_FORTRAN)
+
+            # ND_PIL flag is only valid with ndim > 0.
+            self.assertRaises(TypeError, c, [1], shape=[], flags=ND_PIL)
+
+            # Invalid items.
+            self.assertRaises(ValueError, c, [], shape=[1])
+            self.assertRaises(ValueError, c, ['XXX'], shape=[1], format="L")
+            # Invalid combination of items and format.
+            self.assertRaises(struct.error, c, [1000], shape=[1], format="B")
+            self.assertRaises(ValueError, c, [1,(2,3)], shape=[2], format="B")
+            self.assertRaises(ValueError, c, [1,2,3], shape=[3], format="QL")
+
+            # Invalid ndim.
+            n = ND_MAX_NDIM+1
+            self.assertRaises(ValueError, c, [1]*n, shape=[1]*n)
+
+            # Invalid shape.
+            self.assertRaises(ValueError, c, [1], shape=[-1])
+            self.assertRaises(ValueError, c, [1,2,3], shape=['3'])
+            self.assertRaises(OverflowError, c, [1], shape=[2**128])
+            # prod(shape) * itemsize != len(items)
+            self.assertRaises(ValueError, c, [1,2,3,4,5], shape=[2,2], offset=3)
+
+            # Invalid strides.
+            self.assertRaises(ValueError, c, [1,2,3], shape=[3], strides=['1'])
+            self.assertRaises(OverflowError, c, [1], shape=[1],
+                              strides=[2**128])
+
+            # Invalid combination of strides and shape.
+            self.assertRaises(ValueError, c, [1,2], shape=[2,1], strides=[1])
+            # Invalid combination of strides and format.
+            self.assertRaises(ValueError, c, [1,2,3,4], shape=[2], strides=[3],
+                              format="L")
+
+            # Invalid offset.
+            self.assertRaises(ValueError, c, [1,2,3], shape=[3], offset=4)
+            self.assertRaises(ValueError, c, [1,2,3], shape=[1], offset=3,
+                              format="L")
+
+            # Invalid format.
+            self.assertRaises(ValueError, c, [1,2,3], shape=[3], format="")
+            self.assertRaises(struct.error, c, [(1,2,3)], shape=[1],
+                              format="@#$")
+
+            # Striding out of the memory bounds.
+            items = [1,2,3,4,5,6,7,8,9,10]
+            self.assertRaises(ValueError, c, items, shape=[2,3],
+                              strides=[-3, -2], offset=5)
+
+            # Constructing consumer: format argument invalid.
+            self.assertRaises(TypeError, c, bytearray(), format="Q")
+
+            # Constructing original base object: getbuf argument invalid.
+            self.assertRaises(TypeError, c, [1], shape=[1], getbuf=PyBUF_FULL)
+
+            # Shape argument is mandatory for original base objects.
+            self.assertRaises(TypeError, c, [1])
+
+
+        # PyBUF_WRITABLE request to read-only provider.
+        self.assertRaises(BufferError, ndarray, b'123', getbuf=PyBUF_WRITABLE)
+
+        # ND_VAREXPORT can only be specified during construction.
+        nd = ndarray([9], [1], flags=ND_VAREXPORT)
+        self.assertRaises(ValueError, nd.push, [1], [1], flags=ND_VAREXPORT)
+
+        # Invalid operation for consumers: push/pop
+        nd = ndarray(b'123')
+        self.assertRaises(BufferError, nd.push, [1], [1])
+        self.assertRaises(BufferError, nd.pop)
+
+        # ND_VAREXPORT not set: push/pop fail with exported buffers
+        nd = ndarray([9], [1])
+        nd.push([1], [1])
+        m = memoryview(nd)
+        self.assertRaises(BufferError, nd.push, [1], [1])
+        self.assertRaises(BufferError, nd.pop)
+        m.release()
+        nd.pop()
+
+        # Single remaining buffer: pop fails
+        self.assertRaises(BufferError, nd.pop)
+        del nd
+
+        # get_pointer()
+        self.assertRaises(TypeError, get_pointer, {}, [1,2,3])
+        self.assertRaises(TypeError, get_pointer, b'123', {})
+
+        nd = ndarray(list(range(100)), shape=[1]*100)
+        self.assertRaises(ValueError, get_pointer, nd, [5])
+
+        nd = ndarray(list(range(12)), shape=[3,4])
+        self.assertRaises(ValueError, get_pointer, nd, [2,3,4])
+        self.assertRaises(ValueError, get_pointer, nd, [3,3])
+        self.assertRaises(ValueError, get_pointer, nd, [-3,3])
+        self.assertRaises(OverflowError, get_pointer, nd, [1<<64,3])
+
+        # tolist() needs format
+        ex = ndarray([1,2,3], shape=[3], format='L')
+        nd = ndarray(ex, getbuf=PyBUF_SIMPLE)
+        self.assertRaises(ValueError, nd.tolist)
+
+        # memoryview_from_buffer()
+        ex1 = ndarray([1,2,3], shape=[3], format='L')
+        ex2 = ndarray(ex1)
+        nd = ndarray(ex2)
+        self.assertRaises(TypeError, nd.memoryview_from_buffer)
+
+        nd = ndarray([(1,)*200], shape=[1], format='L'*200)
+        self.assertRaises(TypeError, nd.memoryview_from_buffer)
+
+        n = ND_MAX_NDIM
+        nd = ndarray(list(range(n)), shape=[1]*n)
+        self.assertRaises(ValueError, nd.memoryview_from_buffer)
+
+        # get_contiguous()
+        nd = ndarray([1], shape=[1])
+        self.assertRaises(TypeError, get_contiguous, 1, 2, 3, 4, 5)
+        self.assertRaises(TypeError, get_contiguous, nd, "xyz", 'C')
+        self.assertRaises(OverflowError, get_contiguous, nd, 2**64, 'C')
+        self.assertRaises(TypeError, get_contiguous, nd, PyBUF_READ, 961)
+        self.assertRaises(UnicodeEncodeError, get_contiguous, nd, PyBUF_READ,
+                          '\u2007')
+
+        # cmp_contig()
+        nd = ndarray([1], shape=[1])
+        self.assertRaises(TypeError, cmp_contig, 1, 2, 3, 4, 5)
+        self.assertRaises(TypeError, cmp_contig, {}, nd)
+        self.assertRaises(TypeError, cmp_contig, nd, {})
+
+        # is_contiguous()
+        nd = ndarray([1], shape=[1])
+        self.assertRaises(TypeError, is_contiguous, 1, 2, 3, 4, 5)
+        self.assertRaises(TypeError, is_contiguous, {}, 'A')
+        self.assertRaises(TypeError, is_contiguous, nd, 201)
+
+    def test_ndarray_linked_list(self):
+        for perm in permutations(range(5)):
+            m = [0]*5
+            nd = ndarray([1,2,3], shape=[3], flags=ND_VAREXPORT)
+            m[0] = memoryview(nd)
+
+            for i in range(1, 5):
+                nd.push([1,2,3], shape=[3])
+                m[i] = memoryview(nd)
+
+            for i in range(5):
+                m[perm[i]].release()
+
+            self.assertRaises(BufferError, nd.pop)
+            del nd
+
+    def test_ndarray_format_scalar(self):
+        # ndim = 0: scalar
+        for fmt, scalar, _ in iter_format(0):
+            itemsize = struct.calcsize(fmt)
+            nd = ndarray(scalar, shape=(), format=fmt)
+            self.verify(nd, obj=None,
+                        itemsize=itemsize, fmt=fmt, readonly=1,
+                        ndim=0, shape=(), strides=(),
+                        lst=scalar)
+
+    def test_ndarray_format_shape(self):
+        # ndim = 1, shape = [n]
+        nitems =  randrange(1, 10)
+        for fmt, items, _ in iter_format(nitems):
+            itemsize = struct.calcsize(fmt)
+            for flags in (0, ND_PIL):
+                nd = ndarray(items, shape=[nitems], format=fmt, flags=flags)
+                self.verify(nd, obj=None,
+                            itemsize=itemsize, fmt=fmt, readonly=1,
+                            ndim=1, shape=(nitems,), strides=(itemsize,),
+                            lst=items)
+
+    def test_ndarray_format_strides(self):
+        # ndim = 1, strides
+        nitems = randrange(1, 30)
+        for fmt, items, _ in iter_format(nitems):
+            itemsize = struct.calcsize(fmt)
+            for step in range(-5, 5):
+                if step == 0:
+                    continue
+
+                shape = [len(items[::step])]
+                strides = [step*itemsize]
+                offset = itemsize*(nitems-1) if step < 0 else 0
+
+                for flags in (0, ND_PIL):
+                    nd = ndarray(items, shape=shape, strides=strides,
+                                 format=fmt, offset=offset, flags=flags)
+                    self.verify(nd, obj=None,
+                                itemsize=itemsize, fmt=fmt, readonly=1,
+                                ndim=1, shape=shape, strides=strides,
+                                lst=items[::step])
+
+    def test_ndarray_fortran(self):
+        items = [1,2,3,4,5,6,7,8,9,10,11,12]
+        ex = ndarray(items, shape=(3, 4), strides=(1, 3))
+        nd = ndarray(ex, getbuf=PyBUF_F_CONTIGUOUS|PyBUF_FORMAT)
+        self.assertEqual(nd.tolist(), farray(items, (3, 4)))
+
+    def test_ndarray_multidim(self):
+        for ndim in range(5):
+            shape_t = [randrange(2, 10) for _ in range(ndim)]
+            nitems = prod(shape_t)
+            for shape in permutations(shape_t):
+
+                fmt, items, _ = randitems(nitems)
+                itemsize = struct.calcsize(fmt)
+
+                for flags in (0, ND_PIL):
+                    if ndim == 0 and flags == ND_PIL:
+                        continue
+
+                    # C array
+                    nd = ndarray(items, shape=shape, format=fmt, flags=flags)
+
+                    strides = strides_from_shape(ndim, shape, itemsize, 'C')
+                    lst = carray(items, shape)
+                    self.verify(nd, obj=None,
+                                itemsize=itemsize, fmt=fmt, readonly=1,
+                                ndim=ndim, shape=shape, strides=strides,
+                                lst=lst)
+
+                    if is_memoryview_format(fmt):
+                        # memoryview: reconstruct strides
+                        ex = ndarray(items, shape=shape, format=fmt)
+                        nd = ndarray(ex, getbuf=PyBUF_CONTIG_RO|PyBUF_FORMAT)
+                        self.assertTrue(nd.strides == ())
+                        mv = nd.memoryview_from_buffer()
+                        self.verify(mv, obj=None,
+                                    itemsize=itemsize, fmt=fmt, readonly=1,
+                                    ndim=ndim, shape=shape, strides=strides,
+                                    lst=lst)
+
+                    # Fortran array
+                    nd = ndarray(items, shape=shape, format=fmt,
+                                 flags=flags|ND_FORTRAN)
+
+                    strides = strides_from_shape(ndim, shape, itemsize, 'F')
+                    lst = farray(items, shape)
+                    self.verify(nd, obj=None,
+                                itemsize=itemsize, fmt=fmt, readonly=1,
+                                ndim=ndim, shape=shape, strides=strides,
+                                lst=lst)
+
+    def test_ndarray_index_invalid(self):
+        # not writable
+        nd = ndarray([1], shape=[1])
+        self.assertRaises(TypeError, nd.__setitem__, 1, 8)
+        mv = memoryview(nd)
+        self.assertEqual(mv, nd)
+        self.assertRaises(TypeError, mv.__setitem__, 1, 8)
+
+        # cannot be deleted
+        nd = ndarray([1], shape=[1], flags=ND_WRITABLE)
+        self.assertRaises(TypeError, nd.__delitem__, 1)
+        mv = memoryview(nd)
+        self.assertEqual(mv, nd)
+        self.assertRaises(TypeError, mv.__delitem__, 1)
+
+        # overflow
+        nd = ndarray([1], shape=[1], flags=ND_WRITABLE)
+        self.assertRaises(OverflowError, nd.__getitem__, 1<<64)
+        self.assertRaises(OverflowError, nd.__setitem__, 1<<64, 8)
+        mv = memoryview(nd)
+        self.assertEqual(mv, nd)
+        self.assertRaises(IndexError, mv.__getitem__, 1<<64)
+        self.assertRaises(IndexError, mv.__setitem__, 1<<64, 8)
+
+        # format
+        items = [1,2,3,4,5,6,7,8]
+        nd = ndarray(items, shape=[len(items)], format="B", flags=ND_WRITABLE)
+        self.assertRaises(struct.error, nd.__setitem__, 2, 300)
+        self.assertRaises(ValueError, nd.__setitem__, 1, (100, 200))
+        mv = memoryview(nd)
+        self.assertEqual(mv, nd)
+        self.assertRaises(ValueError, mv.__setitem__, 2, 300)
+        self.assertRaises(TypeError, mv.__setitem__, 1, (100, 200))
+
+        items = [(1,2), (3,4), (5,6)]
+        nd = ndarray(items, shape=[len(items)], format="LQ", flags=ND_WRITABLE)
+        self.assertRaises(ValueError, nd.__setitem__, 2, 300)
+        self.assertRaises(struct.error, nd.__setitem__, 1, (b'\x001', 200))
+
+    def test_ndarray_index_scalar(self):
+        # scalar
+        nd = ndarray(1, shape=(), flags=ND_WRITABLE)
+        mv = memoryview(nd)
+        self.assertEqual(mv, nd)
+
+        x = nd[()];  self.assertEqual(x, 1)
+        x = nd[...]; self.assertEqual(x.tolist(), nd.tolist())
+
+        x = mv[()];  self.assertEqual(x, 1)
+        x = mv[...]; self.assertEqual(x.tolist(), nd.tolist())
+
+        self.assertRaises(TypeError, nd.__getitem__, 0)
+        self.assertRaises(TypeError, mv.__getitem__, 0)
+        self.assertRaises(TypeError, nd.__setitem__, 0, 8)
+        self.assertRaises(TypeError, mv.__setitem__, 0, 8)
+
+        self.assertEqual(nd.tolist(), 1)
+        self.assertEqual(mv.tolist(), 1)
+
+        nd[()] = 9; self.assertEqual(nd.tolist(), 9)
+        mv[()] = 9; self.assertEqual(mv.tolist(), 9)
+
+        nd[...] = 5; self.assertEqual(nd.tolist(), 5)
+        mv[...] = 5; self.assertEqual(mv.tolist(), 5)
+
+    def test_ndarray_index_null_strides(self):
+        ex = ndarray(list(range(2*4)), shape=[2, 4], flags=ND_WRITABLE)
+        nd = ndarray(ex, getbuf=PyBUF_CONTIG)
+
+        # Sub-views are only possible for full exporters.
+        self.assertRaises(BufferError, nd.__getitem__, 1)
+        # Same for slices.
+        self.assertRaises(BufferError, nd.__getitem__, slice(3,5,1))
+
+    def test_ndarray_index_getitem_single(self):
+        # getitem
+        for fmt, items, _ in iter_format(5):
+            nd = ndarray(items, shape=[5], format=fmt)
+            for i in range(-5, 5):
+                self.assertEqual(nd[i], items[i])
+
+            self.assertRaises(IndexError, nd.__getitem__, -6)
+            self.assertRaises(IndexError, nd.__getitem__, 5)
+
+            if is_memoryview_format(fmt):
+                mv = memoryview(nd)
+                self.assertEqual(mv, nd)
+                for i in range(-5, 5):
+                    self.assertEqual(mv[i], items[i])
+
+                self.assertRaises(IndexError, mv.__getitem__, -6)
+                self.assertRaises(IndexError, mv.__getitem__, 5)
+
+        # getitem with null strides
+        for fmt, items, _ in iter_format(5):
+            ex = ndarray(items, shape=[5], flags=ND_WRITABLE, format=fmt)
+            nd = ndarray(ex, getbuf=PyBUF_CONTIG|PyBUF_FORMAT)
+
+            for i in range(-5, 5):
+                self.assertEqual(nd[i], items[i])
+
+            if is_memoryview_format(fmt):
+                mv = nd.memoryview_from_buffer()
+                self.assertIs(mv.__eq__(nd), NotImplemented)
+                for i in range(-5, 5):
+                    self.assertEqual(mv[i], items[i])
+
+        # getitem with null format
+        items = [1,2,3,4,5]
+        ex = ndarray(items, shape=[5])
+        nd = ndarray(ex, getbuf=PyBUF_CONTIG_RO)
+        for i in range(-5, 5):
+            self.assertEqual(nd[i], items[i])
+
+        # getitem with null shape/strides/format
+        items = [1,2,3,4,5]
+        ex = ndarray(items, shape=[5])
+        nd = ndarray(ex, getbuf=PyBUF_SIMPLE)
+
+        for i in range(-5, 5):
+            self.assertEqual(nd[i], items[i])
+
+    def test_ndarray_index_setitem_single(self):
+        # assign single value
+        for fmt, items, single_item in iter_format(5):
+            nd = ndarray(items, shape=[5], format=fmt, flags=ND_WRITABLE)
+            for i in range(5):
+                items[i] = single_item
+                nd[i] = single_item
+            self.assertEqual(nd.tolist(), items)
+
+            self.assertRaises(IndexError, nd.__setitem__, -6, single_item)
+            self.assertRaises(IndexError, nd.__setitem__, 5, single_item)
+
+            if not is_memoryview_format(fmt):
+                continue
+
+            nd = ndarray(items, shape=[5], format=fmt, flags=ND_WRITABLE)
+            mv = memoryview(nd)
+            self.assertEqual(mv, nd)
+            for i in range(5):
+                items[i] = single_item
+                mv[i] = single_item
+            self.assertEqual(mv.tolist(), items)
+
+            self.assertRaises(IndexError, mv.__setitem__, -6, single_item)
+            self.assertRaises(IndexError, mv.__setitem__, 5, single_item)
+
+
+        # assign single value: lobject = robject
+        for fmt, items, single_item in iter_format(5):
+            nd = ndarray(items, shape=[5], format=fmt, flags=ND_WRITABLE)
+            for i in range(-5, 4):
+                items[i] = items[i+1]
+                nd[i] = nd[i+1]
+            self.assertEqual(nd.tolist(), items)
+
+            if not is_memoryview_format(fmt):
+                continue
+
+            nd = ndarray(items, shape=[5], format=fmt, flags=ND_WRITABLE)
+            mv = memoryview(nd)
+            self.assertEqual(mv, nd)
+            for i in range(-5, 4):
+                items[i] = items[i+1]
+                mv[i] = mv[i+1]
+            self.assertEqual(mv.tolist(), items)
+
+    def test_ndarray_index_getitem_multidim(self):
+        shape_t = (2, 3, 5)
+        nitems = prod(shape_t)
+        for shape in permutations(shape_t):
+
+            fmt, items, _ = randitems(nitems)
+
+            for flags in (0, ND_PIL):
+                # C array
+                nd = ndarray(items, shape=shape, format=fmt, flags=flags)
+                lst = carray(items, shape)
+
+                for i in range(-shape[0], shape[0]):
+                    self.assertEqual(lst[i], nd[i].tolist())
+                    for j in range(-shape[1], shape[1]):
+                        self.assertEqual(lst[i][j], nd[i][j].tolist())
+                        for k in range(-shape[2], shape[2]):
+                            self.assertEqual(lst[i][j][k], nd[i][j][k])
+
+                # Fortran array
+                nd = ndarray(items, shape=shape, format=fmt,
+                             flags=flags|ND_FORTRAN)
+                lst = farray(items, shape)
+
+                for i in range(-shape[0], shape[0]):
+                    self.assertEqual(lst[i], nd[i].tolist())
+                    for j in range(-shape[1], shape[1]):
+                        self.assertEqual(lst[i][j], nd[i][j].tolist())
+                        for k in range(shape[2], shape[2]):
+                            self.assertEqual(lst[i][j][k], nd[i][j][k])
+
+    def test_ndarray_sequence(self):
+        nd = ndarray(1, shape=())
+        self.assertRaises(TypeError, eval, "1 in nd", locals())
+        mv = memoryview(nd)
+        self.assertEqual(mv, nd)
+        self.assertRaises(TypeError, eval, "1 in mv", locals())
+
+        for fmt, items, _ in iter_format(5):
+            nd = ndarray(items, shape=[5], format=fmt)
+            for i, v in enumerate(nd):
+                self.assertEqual(v, items[i])
+                self.assertTrue(v in nd)
+
+            if is_memoryview_format(fmt):
+                mv = memoryview(nd)
+                for i, v in enumerate(mv):
+                    self.assertEqual(v, items[i])
+                    self.assertTrue(v in mv)
+
+    def test_ndarray_slice_invalid(self):
+        items = [1,2,3,4,5,6,7,8]
+
+        # rvalue is not an exporter
+        xl = ndarray(items, shape=[8], flags=ND_WRITABLE)
+        ml = memoryview(xl)
+        self.assertRaises(TypeError, xl.__setitem__, slice(0,8,1), items)
+        self.assertRaises(TypeError, ml.__setitem__, slice(0,8,1), items)
+
+        # rvalue is not a full exporter
+        xl = ndarray(items, shape=[8], flags=ND_WRITABLE)
+        ex = ndarray(items, shape=[8], flags=ND_WRITABLE)
+        xr = ndarray(ex, getbuf=PyBUF_ND)
+        self.assertRaises(BufferError, xl.__setitem__, slice(0,8,1), xr)
+
+        # zero step
+        nd = ndarray(items, shape=[8], format="L", flags=ND_WRITABLE)
+        mv = memoryview(nd)
+        self.assertRaises(ValueError, nd.__getitem__, slice(0,1,0))
+        self.assertRaises(ValueError, mv.__getitem__, slice(0,1,0))
+
+        nd = ndarray(items, shape=[2,4], format="L", flags=ND_WRITABLE)
+        mv = memoryview(nd)
+
+        self.assertRaises(ValueError, nd.__getitem__,
+                          (slice(0,1,1), slice(0,1,0)))
+        self.assertRaises(ValueError, nd.__getitem__,
+                          (slice(0,1,0), slice(0,1,1)))
+        self.assertRaises(TypeError, nd.__getitem__, "@%$")
+        self.assertRaises(TypeError, nd.__getitem__, ("@%$", slice(0,1,1)))
+        self.assertRaises(TypeError, nd.__getitem__, (slice(0,1,1), {}))
+
+        # memoryview: not implemented
+        self.assertRaises(NotImplementedError, mv.__getitem__,
+                          (slice(0,1,1), slice(0,1,0)))
+        self.assertRaises(TypeError, mv.__getitem__, "@%$")
+
+        # differing format
+        xl = ndarray(items, shape=[8], format="B", flags=ND_WRITABLE)
+        xr = ndarray(items, shape=[8], format="b")
+        ml = memoryview(xl)
+        mr = memoryview(xr)
+        self.assertRaises(ValueError, xl.__setitem__, slice(0,1,1), xr[7:8])
+        self.assertEqual(xl.tolist(), items)
+        self.assertRaises(ValueError, ml.__setitem__, slice(0,1,1), mr[7:8])
+        self.assertEqual(ml.tolist(), items)
+
+        # differing itemsize
+        xl = ndarray(items, shape=[8], format="B", flags=ND_WRITABLE)
+        yr = ndarray(items, shape=[8], format="L")
+        ml = memoryview(xl)
+        mr = memoryview(xr)
+        self.assertRaises(ValueError, xl.__setitem__, slice(0,1,1), xr[7:8])
+        self.assertEqual(xl.tolist(), items)
+        self.assertRaises(ValueError, ml.__setitem__, slice(0,1,1), mr[7:8])
+        self.assertEqual(ml.tolist(), items)
+
+        # differing ndim
+        xl = ndarray(items, shape=[2, 4], format="b", flags=ND_WRITABLE)
+        xr = ndarray(items, shape=[8], format="b")
+        ml = memoryview(xl)
+        mr = memoryview(xr)
+        self.assertRaises(ValueError, xl.__setitem__, slice(0,1,1), xr[7:8])
+        self.assertEqual(xl.tolist(), [[1,2,3,4], [5,6,7,8]])
+        self.assertRaises(NotImplementedError, ml.__setitem__, slice(0,1,1),
+                          mr[7:8])
+
+        # differing shape
+        xl = ndarray(items, shape=[8], format="b", flags=ND_WRITABLE)
+        xr = ndarray(items, shape=[8], format="b")
+        ml = memoryview(xl)
+        mr = memoryview(xr)
+        self.assertRaises(ValueError, xl.__setitem__, slice(0,2,1), xr[7:8])
+        self.assertEqual(xl.tolist(), items)
+        self.assertRaises(ValueError, ml.__setitem__, slice(0,2,1), mr[7:8])
+        self.assertEqual(ml.tolist(), items)
+
+        # _testbuffer.c module functions
+        self.assertRaises(TypeError, slice_indices, slice(0,1,2), {})
+        self.assertRaises(TypeError, slice_indices, "###########", 1)
+        self.assertRaises(ValueError, slice_indices, slice(0,1,0), 4)
+
+        x = ndarray(items, shape=[8], format="b", flags=ND_PIL)
+        self.assertRaises(TypeError, x.add_suboffsets)
+
+        ex = ndarray(items, shape=[8], format="B")
+        x = ndarray(ex, getbuf=PyBUF_SIMPLE)
+        self.assertRaises(TypeError, x.add_suboffsets)
+
+    def test_ndarray_slice_zero_shape(self):
+        items = [1,2,3,4,5,6,7,8,9,10,11,12]
+
+        x = ndarray(items, shape=[12], format="L", flags=ND_WRITABLE)
+        y = ndarray(items, shape=[12], format="L")
+        x[4:4] = y[9:9]
+        self.assertEqual(x.tolist(), items)
+
+        ml = memoryview(x)
+        mr = memoryview(y)
+        self.assertEqual(ml, x)
+        self.assertEqual(ml, y)
+        ml[4:4] = mr[9:9]
+        self.assertEqual(ml.tolist(), items)
+
+        x = ndarray(items, shape=[3, 4], format="L", flags=ND_WRITABLE)
+        y = ndarray(items, shape=[4, 3], format="L")
+        x[1:2, 2:2] = y[1:2, 3:3]
+        self.assertEqual(x.tolist(), carray(items, [3, 4]))
+
+    def test_ndarray_slice_multidim(self):
+        shape_t = (2, 3, 5)
+        ndim = len(shape_t)
+        nitems = prod(shape_t)
+        for shape in permutations(shape_t):
+
+            fmt, items, _ = randitems(nitems)
+            itemsize = struct.calcsize(fmt)
+
+            for flags in (0, ND_PIL):
+                nd = ndarray(items, shape=shape, format=fmt, flags=flags)
+                lst = carray(items, shape)
+
+                for slices in rslices_ndim(ndim, shape):
+
+                    listerr = None
+                    try:
+                        sliced = multislice(lst, slices)
+                    except Exception as e:
+                        listerr = e.__class__
+
+                    nderr = None
+                    try:
+                        ndsliced = nd[slices]
+                    except Exception as e:
+                        nderr = e.__class__
+
+                    if nderr or listerr:
+                        self.assertIs(nderr, listerr)
+                    else:
+                        self.assertEqual(ndsliced.tolist(), sliced)
+
+    def test_ndarray_slice_redundant_suboffsets(self):
+        shape_t = (2, 3, 5, 2)
+        ndim = len(shape_t)
+        nitems = prod(shape_t)
+        for shape in permutations(shape_t):
+
+            fmt, items, _ = randitems(nitems)
+            itemsize = struct.calcsize(fmt)
+
+            nd = ndarray(items, shape=shape, format=fmt)
+            nd.add_suboffsets()
+            ex = ndarray(items, shape=shape, format=fmt)
+            ex.add_suboffsets()
+            mv = memoryview(ex)
+            lst = carray(items, shape)
+
+            for slices in rslices_ndim(ndim, shape):
+
+                listerr = None
+                try:
+                    sliced = multislice(lst, slices)
+                except Exception as e:
+                    listerr = e.__class__
+
+                nderr = None
+                try:
+                    ndsliced = nd[slices]
+                except Exception as e:
+                    nderr = e.__class__
+
+                if nderr or listerr:
+                    self.assertIs(nderr, listerr)
+                else:
+                    self.assertEqual(ndsliced.tolist(), sliced)
+
+    def test_ndarray_slice_assign_single(self):
+        for fmt, items, _ in iter_format(5):
+            for lslice in genslices(5):
+                for rslice in genslices(5):
+                    for flags in (0, ND_PIL):
+
+                        f = flags|ND_WRITABLE
+                        nd = ndarray(items, shape=[5], format=fmt, flags=f)
+                        ex = ndarray(items, shape=[5], format=fmt, flags=f)
+                        mv = memoryview(ex)
+
+                        lsterr = None
+                        diff_structure = None
+                        lst = items[:]
+                        try:
+                            lval = lst[lslice]
+                            rval = lst[rslice]
+                            lst[lslice] = lst[rslice]
+                            diff_structure = len(lval) != len(rval)
+                        except Exception as e:
+                            lsterr = e.__class__
+
+                        nderr = None
+                        try:
+                            nd[lslice] = nd[rslice]
+                        except Exception as e:
+                            nderr = e.__class__
+
+                        if diff_structure: # ndarray cannot change shape
+                            self.assertIs(nderr, ValueError)
+                        else:
+                            self.assertEqual(nd.tolist(), lst)
+                            self.assertIs(nderr, lsterr)
+
+                        if not is_memoryview_format(fmt):
+                            continue
+
+                        mverr = None
+                        try:
+                            mv[lslice] = mv[rslice]
+                        except Exception as e:
+                            mverr = e.__class__
+
+                        if diff_structure: # memoryview cannot change shape
+                            self.assertIs(mverr, ValueError)
+                        else:
+                            self.assertEqual(mv.tolist(), lst)
+                            self.assertEqual(mv, nd)
+                            self.assertIs(mverr, lsterr)
+                            self.verify(mv, obj=ex,
+                              itemsize=nd.itemsize, fmt=fmt, readonly=0,
+                              ndim=nd.ndim, shape=nd.shape, strides=nd.strides,
+                              lst=nd.tolist())
+
+    def test_ndarray_slice_assign_multidim(self):
+        shape_t = (2, 3, 5)
+        ndim = len(shape_t)
+        nitems = prod(shape_t)
+        for shape in permutations(shape_t):
+
+            fmt, items, _ = randitems(nitems)
+
+            for flags in (0, ND_PIL):
+                for _ in range(ITERATIONS):
+                    lslices, rslices = randslice_from_shape(ndim, shape)
+
+                    nd = ndarray(items, shape=shape, format=fmt,
+                                 flags=flags|ND_WRITABLE)
+                    lst = carray(items, shape)
+
+                    listerr = None
+                    try:
+                        result = multislice_assign(lst, lst, lslices, rslices)
+                    except Exception as e:
+                        listerr = e.__class__
+
+                    nderr = None
+                    try:
+                        nd[lslices] = nd[rslices]
+                    except Exception as e:
+                        nderr = e.__class__
+
+                    if nderr or listerr:
+                        self.assertIs(nderr, listerr)
+                    else:
+                        self.assertEqual(nd.tolist(), result)
+
+    def test_ndarray_random(self):
+        # construction of valid arrays
+        for _ in range(ITERATIONS):
+            for fmt in fmtdict['@']:
+                itemsize = struct.calcsize(fmt)
+
+                t = rand_structure(itemsize, True, maxdim=MAXDIM,
+                                   maxshape=MAXSHAPE)
+                self.assertTrue(verify_structure(*t))
+                items = randitems_from_structure(fmt, t)
+
+                x = ndarray_from_structure(items, fmt, t)
+                xlist = x.tolist()
+
+                mv = memoryview(x)
+                if is_memoryview_format(fmt):
+                    mvlist = mv.tolist()
+                    self.assertEqual(mvlist, xlist)
+
+                if t[2] > 0:
+                    # ndim > 0: test against suboffsets representation.
+                    y = ndarray_from_structure(items, fmt, t, flags=ND_PIL)
+                    ylist = y.tolist()
+                    self.assertEqual(xlist, ylist)
+
+                    mv = memoryview(y)
+                    if is_memoryview_format(fmt):
+                        self.assertEqual(mv, y)
+                        mvlist = mv.tolist()
+                        self.assertEqual(mvlist, ylist)
+
+                if numpy_array:
+                    shape = t[3]
+                    if 0 in shape:
+                        continue # http://projects.scipy.org/numpy/ticket/1910
+                    z = numpy_array_from_structure(items, fmt, t)
+                    self.verify(x, obj=None,
+                                itemsize=z.itemsize, fmt=fmt, readonly=0,
+                                ndim=z.ndim, shape=z.shape, strides=z.strides,
+                                lst=z.tolist())
+
+    def test_ndarray_random_invalid(self):
+        # exceptions during construction of invalid arrays
+        for _ in range(ITERATIONS):
+            for fmt in fmtdict['@']:
+                itemsize = struct.calcsize(fmt)
+
+                t = rand_structure(itemsize, False, maxdim=MAXDIM,
+                                   maxshape=MAXSHAPE)
+                self.assertFalse(verify_structure(*t))
+                items = randitems_from_structure(fmt, t)
+
+                nderr = False
+                try:
+                    x = ndarray_from_structure(items, fmt, t)
+                except Exception as e:
+                    nderr = e.__class__
+                self.assertTrue(nderr)
+
+                if numpy_array:
+                    numpy_err = False
+                    try:
+                        y = numpy_array_from_structure(items, fmt, t)
+                    except Exception as e:
+                        numpy_err = e.__class__
+
+                    if 0: # http://projects.scipy.org/numpy/ticket/1910
+                        self.assertTrue(numpy_err)
+
+    def test_ndarray_random_slice_assign(self):
+        # valid slice assignments
+        for _ in range(ITERATIONS):
+            for fmt in fmtdict['@']:
+                itemsize = struct.calcsize(fmt)
+
+                lshape, rshape, lslices, rslices = \
+                    rand_aligned_slices(maxdim=MAXDIM, maxshape=MAXSHAPE)
+                tl = rand_structure(itemsize, True, shape=lshape)
+                tr = rand_structure(itemsize, True, shape=rshape)
+                self.assertTrue(verify_structure(*tl))
+                self.assertTrue(verify_structure(*tr))
+                litems = randitems_from_structure(fmt, tl)
+                ritems = randitems_from_structure(fmt, tr)
+
+                xl = ndarray_from_structure(litems, fmt, tl)
+                xr = ndarray_from_structure(ritems, fmt, tr)
+                xl[lslices] = xr[rslices]
+                xllist = xl.tolist()
+                xrlist = xr.tolist()
+
+                ml = memoryview(xl)
+                mr = memoryview(xr)
+                self.assertEqual(ml.tolist(), xllist)
+                self.assertEqual(mr.tolist(), xrlist)
+
+                if tl[2] > 0 and tr[2] > 0:
+                    # ndim > 0: test against suboffsets representation.
+                    yl = ndarray_from_structure(litems, fmt, tl, flags=ND_PIL)
+                    yr = ndarray_from_structure(ritems, fmt, tr, flags=ND_PIL)
+                    yl[lslices] = yr[rslices]
+                    yllist = yl.tolist()
+                    yrlist = yr.tolist()
+                    self.assertEqual(xllist, yllist)
+                    self.assertEqual(xrlist, yrlist)
+
+                    ml = memoryview(yl)
+                    mr = memoryview(yr)
+                    self.assertEqual(ml.tolist(), yllist)
+                    self.assertEqual(mr.tolist(), yrlist)
+
+                if numpy_array:
+                    if 0 in lshape or 0 in rshape:
+                        continue # http://projects.scipy.org/numpy/ticket/1910
+
+                    zl = numpy_array_from_structure(litems, fmt, tl)
+                    zr = numpy_array_from_structure(ritems, fmt, tr)
+                    zl[lslices] = zr[rslices]
+
+                    if not is_overlapping(tl) and not is_overlapping(tr):
+                        # Slice assignment of overlapping structures
+                        # is undefined in NumPy.
+                        self.verify(xl, obj=None,
+                                    itemsize=zl.itemsize, fmt=fmt, readonly=0,
+                                    ndim=zl.ndim, shape=zl.shape,
+                                    strides=zl.strides, lst=zl.tolist())
+
+                    self.verify(xr, obj=None,
+                                itemsize=zr.itemsize, fmt=fmt, readonly=0,
+                                ndim=zr.ndim, shape=zr.shape,
+                                strides=zr.strides, lst=zr.tolist())
+
+    def test_ndarray_re_export(self):
+        items = [1,2,3,4,5,6,7,8,9,10,11,12]
+
+        nd = ndarray(items, shape=[3,4], flags=ND_PIL)
+        ex = ndarray(nd)
+
+        self.assertTrue(ex.flags & ND_PIL)
+        self.assertIs(ex.obj, nd)
+        self.assertEqual(ex.suboffsets, (0, -1))
+        self.assertFalse(ex.c_contiguous)
+        self.assertFalse(ex.f_contiguous)
+        self.assertFalse(ex.contiguous)
+
+    def test_ndarray_zero_shape(self):
+        # zeros in shape
+        for flags in (0, ND_PIL):
+            nd = ndarray([1,2,3], shape=[0], flags=flags)
+            mv = memoryview(nd)
+            self.assertEqual(mv, nd)
+            self.assertEqual(nd.tolist(), [])
+            self.assertEqual(mv.tolist(), [])
+
+            nd = ndarray([1,2,3], shape=[0,3,3], flags=flags)
+            self.assertEqual(nd.tolist(), [])
+
+            nd = ndarray([1,2,3], shape=[3,0,3], flags=flags)
+            self.assertEqual(nd.tolist(), [[], [], []])
+
+            nd = ndarray([1,2,3], shape=[3,3,0], flags=flags)
+            self.assertEqual(nd.tolist(),
+                             [[[], [], []], [[], [], []], [[], [], []]])
+
+    def test_ndarray_zero_strides(self):
+        # zero strides
+        for flags in (0, ND_PIL):
+            nd = ndarray([1], shape=[5], strides=[0], flags=flags)
+            mv = memoryview(nd)
+            self.assertEqual(mv, nd)
+            self.assertEqual(nd.tolist(), [1, 1, 1, 1, 1])
+            self.assertEqual(mv.tolist(), [1, 1, 1, 1, 1])
+
+    def test_ndarray_offset(self):
+        nd = ndarray(list(range(20)), shape=[3], offset=7)
+        self.assertEqual(nd.offset, 7)
+        self.assertEqual(nd.tolist(), [7,8,9])
+
+    def test_ndarray_memoryview_from_buffer(self):
+        for flags in (0, ND_PIL):
+            nd = ndarray(list(range(3)), shape=[3], flags=flags)
+            m = nd.memoryview_from_buffer()
+            self.assertEqual(m, nd)
+
+    def test_ndarray_get_pointer(self):
+        for flags in (0, ND_PIL):
+            nd = ndarray(list(range(3)), shape=[3], flags=flags)
+            for i in range(3):
+                self.assertEqual(nd[i], get_pointer(nd, [i]))
+
+    def test_ndarray_tolist_null_strides(self):
+        ex = ndarray(list(range(20)), shape=[2,2,5])
+
+        nd = ndarray(ex, getbuf=PyBUF_ND|PyBUF_FORMAT)
+        self.assertEqual(nd.tolist(), ex.tolist())
+
+        m = memoryview(ex)
+        self.assertEqual(m.tolist(), ex.tolist())
+
+    def test_ndarray_cmp_contig(self):
+
+        self.assertFalse(cmp_contig(b"123", b"456"))
+
+        x = ndarray(list(range(12)), shape=[3,4])
+        y = ndarray(list(range(12)), shape=[4,3])
+        self.assertFalse(cmp_contig(x, y))
+
+        x = ndarray([1], shape=[1], format="B")
+        self.assertTrue(cmp_contig(x, b'\x01'))
+        self.assertTrue(cmp_contig(b'\x01', x))
+
+    def test_ndarray_hash(self):
+
+        a = array.array('L', [1,2,3])
+        nd = ndarray(a)
+        self.assertRaises(ValueError, hash, nd)
+
+        # one-dimensional
+        b = bytes(list(range(12)))
+
+        nd = ndarray(list(range(12)), shape=[12])
+        self.assertEqual(hash(nd), hash(b))
+
+        # C-contiguous
+        nd = ndarray(list(range(12)), shape=[3,4])
+        self.assertEqual(hash(nd), hash(b))
+
+        nd = ndarray(list(range(12)), shape=[3,2,2])
+        self.assertEqual(hash(nd), hash(b))
+
+        # Fortran contiguous
+        b = bytes(transpose(list(range(12)), shape=[4,3]))
+        nd = ndarray(list(range(12)), shape=[3,4], flags=ND_FORTRAN)
+        self.assertEqual(hash(nd), hash(b))
+
+        b = bytes(transpose(list(range(12)), shape=[2,3,2]))
+        nd = ndarray(list(range(12)), shape=[2,3,2], flags=ND_FORTRAN)
+        self.assertEqual(hash(nd), hash(b))
+
+        # suboffsets
+        b = bytes(list(range(12)))
+        nd = ndarray(list(range(12)), shape=[2,2,3], flags=ND_PIL)
+        self.assertEqual(hash(nd), hash(b))
+
+        # non-byte formats
+        nd = ndarray(list(range(12)), shape=[2,2,3], format='L')
+        self.assertEqual(hash(nd), hash(nd.tobytes()))
+
+    def test_memoryview_construction(self):
+
+        items_shape = [(9, []), ([1,2,3], [3]), (list(range(2*3*5)), [2,3,5])]
+
+        # NumPy style, C-contiguous:
+        for items, shape in items_shape:
+
+            # From PEP-3118 compliant exporter:
+            ex = ndarray(items, shape=shape)
+            m = memoryview(ex)
+            self.assertTrue(m.c_contiguous)
+            self.assertTrue(m.contiguous)
+
+            ndim = len(shape)
+            strides = strides_from_shape(ndim, shape, 1, 'C')
+            lst = carray(items, shape)
+
+            self.verify(m, obj=ex,
+                        itemsize=1, fmt='B', readonly=1,
+                        ndim=ndim, shape=shape, strides=strides,
+                        lst=lst)
+
+            # From memoryview:
+            m2 = memoryview(m)
+            self.verify(m2, obj=ex,
+                        itemsize=1, fmt='B', readonly=1,
+                        ndim=ndim, shape=shape, strides=strides,
+                        lst=lst)
+
+            # PyMemoryView_FromBuffer(): no strides
+            nd = ndarray(ex, getbuf=PyBUF_CONTIG_RO|PyBUF_FORMAT)
+            self.assertEqual(nd.strides, ())
+            m = nd.memoryview_from_buffer()
+            self.verify(m, obj=None,
+                        itemsize=1, fmt='B', readonly=1,
+                        ndim=ndim, shape=shape, strides=strides,
+                        lst=lst)
+
+            # PyMemoryView_FromBuffer(): no format, shape, strides
+            nd = ndarray(ex, getbuf=PyBUF_SIMPLE)
+            self.assertEqual(nd.format, '')
+            self.assertEqual(nd.shape, ())
+            self.assertEqual(nd.strides, ())
+            m = nd.memoryview_from_buffer()
+
+            lst = [items] if ndim == 0 else items
+            self.verify(m, obj=None,
+                        itemsize=1, fmt='B', readonly=1,
+                        ndim=1, shape=[ex.nbytes], strides=(1,),
+                        lst=lst)
+
+        # NumPy style, Fortran contiguous:
+        for items, shape in items_shape:
+
+            # From PEP-3118 compliant exporter:
+            ex = ndarray(items, shape=shape, flags=ND_FORTRAN)
+            m = memoryview(ex)
+            self.assertTrue(m.f_contiguous)
+            self.assertTrue(m.contiguous)
+
+            ndim = len(shape)
+            strides = strides_from_shape(ndim, shape, 1, 'F')
+            lst = farray(items, shape)
+
+            self.verify(m, obj=ex,
+                        itemsize=1, fmt='B', readonly=1,
+                        ndim=ndim, shape=shape, strides=strides,
+                        lst=lst)
+
+            # From memoryview:
+            m2 = memoryview(m)
+            self.verify(m2, obj=ex,
+                        itemsize=1, fmt='B', readonly=1,
+                        ndim=ndim, shape=shape, strides=strides,
+                        lst=lst)
+
+        # PIL style:
+        for items, shape in items_shape[1:]:
+
+            # From PEP-3118 compliant exporter:
+            ex = ndarray(items, shape=shape, flags=ND_PIL)
+            m = memoryview(ex)
+
+            ndim = len(shape)
+            lst = carray(items, shape)
+
+            self.verify(m, obj=ex,
+                        itemsize=1, fmt='B', readonly=1,
+                        ndim=ndim, shape=shape, strides=ex.strides,
+                        lst=lst)
+
+            # From memoryview:
+            m2 = memoryview(m)
+            self.verify(m2, obj=ex,
+                        itemsize=1, fmt='B', readonly=1,
+                        ndim=ndim, shape=shape, strides=ex.strides,
+                        lst=lst)
+
+        # Invalid number of arguments:
+        self.assertRaises(TypeError, memoryview, b'9', 'x')
+        # Not a buffer provider:
+        self.assertRaises(TypeError, memoryview, {})
+        # Non-compliant buffer provider:
+        ex = ndarray([1,2,3], shape=[3])
+        nd = ndarray(ex, getbuf=PyBUF_SIMPLE)
+        self.assertRaises(BufferError, memoryview, nd)
+        nd = ndarray(ex, getbuf=PyBUF_CONTIG_RO|PyBUF_FORMAT)
+        self.assertRaises(BufferError, memoryview, nd)
+
+        # ndim > 64
+        nd = ndarray([1]*128, shape=[1]*128, format='L')
+        self.assertRaises(ValueError, memoryview, nd)
+        self.assertRaises(ValueError, nd.memoryview_from_buffer)
+        self.assertRaises(ValueError, get_contiguous, nd, PyBUF_READ, 'C')
+        self.assertRaises(ValueError, get_contiguous, nd, PyBUF_READ, 'F')
+        self.assertRaises(ValueError, get_contiguous, nd[::-1], PyBUF_READ, 'C')
+
+    def test_memoryview_cast_zero_shape(self):
+        # Casts are undefined if shape contains zeros. These arrays are
+        # regarded as C-contiguous by Numpy and PyBuffer_GetContiguous(),
+        # so they are not caught by the test for C-contiguity in memory_cast().
+        items = [1,2,3]
+        for shape in ([0,3,3], [3,0,3], [0,3,3]):
+            ex = ndarray(items, shape=shape)
+            self.assertTrue(ex.c_contiguous)
+            msrc = memoryview(ex)
+            self.assertRaises(TypeError, msrc.cast, 'c')
+
+    def test_memoryview_struct_module(self):
+
+        class INT(object):
+            def __init__(self, val):
+                self.val = val
+            def __int__(self):
+                return self.val
+
+        class IDX(object):
+            def __init__(self, val):
+                self.val = val
+            def __index__(self):
+                return self.val
+
+        def f(): return 7
+
+        values = [INT(9), IDX(9),
+                  2.2+3j, Decimal("-21.1"), 12.2, Fraction(5, 2),
+                  [1,2,3], {4,5,6}, {7:8}, (), (9,),
+                  True, False, None, NotImplemented,
+                  b'a', b'abc', bytearray(b'a'), bytearray(b'abc'),
+                  'a', 'abc', r'a', r'abc',
+                  f, lambda x: x]
+
+        for fmt, items, item in iter_format(10, 'memoryview'):
+            ex = ndarray(items, shape=[10], format=fmt, flags=ND_WRITABLE)
+            nd = ndarray(items, shape=[10], format=fmt, flags=ND_WRITABLE)
+            m = memoryview(ex)
+
+            struct.pack_into(fmt, nd, 0, item)
+            m[0] = item
+            self.assertEqual(m[0], nd[0])
+
+            itemsize = struct.calcsize(fmt)
+            if 'P' in fmt:
+                continue
+
+            for v in values:
+                struct_err = None
+                try:
+                    struct.pack_into(fmt, nd, itemsize, v)
+                except struct.error:
+                    struct_err = struct.error
+
+                mv_err = None
+                try:
+                    m[1] = v
+                except (TypeError, ValueError) as e:
+                    mv_err = e.__class__
+
+                if struct_err or mv_err:
+                    self.assertIsNot(struct_err, None)
+                    self.assertIsNot(mv_err, None)
+                else:
+                    self.assertEqual(m[1], nd[1])
+
+    def test_memoryview_cast_zero_strides(self):
+        # Casts are undefined if strides contains zeros. These arrays are
+        # (sometimes!) regarded as C-contiguous by Numpy, but not by
+        # PyBuffer_GetContiguous().
+        ex = ndarray([1,2,3], shape=[3], strides=[0])
+        self.assertFalse(ex.c_contiguous)
+        msrc = memoryview(ex)
+        self.assertRaises(TypeError, msrc.cast, 'c')
+
+    def test_memoryview_cast_invalid(self):
+        # invalid format
+        for sfmt in NON_BYTE_FORMAT:
+            sformat = '@' + sfmt if randrange(2) else sfmt
+            ssize = struct.calcsize(sformat)
+            for dfmt in NON_BYTE_FORMAT:
+                dformat = '@' + dfmt if randrange(2) else dfmt
+                dsize = struct.calcsize(dformat)
+                ex = ndarray(list(range(32)), shape=[32//ssize], format=sformat)
+                msrc = memoryview(ex)
+                self.assertRaises(TypeError, msrc.cast, dfmt, [32//dsize])
+
+        for sfmt, sitems, _ in iter_format(1):
+            ex = ndarray(sitems, shape=[1], format=sfmt)
+            msrc = memoryview(ex)
+            for dfmt, _, _ in iter_format(1):
+                if (not is_memoryview_format(sfmt) or
+                    not is_memoryview_format(dfmt)):
+                    self.assertRaises(ValueError, msrc.cast, dfmt,
+                                      [32//dsize])
+                else:
+                    if not is_byte_format(sfmt) and not is_byte_format(dfmt):
+                        self.assertRaises(TypeError, msrc.cast, dfmt,
+                                          [32//dsize])
+
+        # invalid shape
+        size_h = struct.calcsize('h')
+        size_d = struct.calcsize('d')
+        ex = ndarray(list(range(2*2*size_d)), shape=[2,2,size_d], format='h')
+        msrc = memoryview(ex)
+        self.assertRaises(TypeError, msrc.cast, shape=[2,2,size_h], format='d')
+
+        ex = ndarray(list(range(120)), shape=[1,2,3,4,5])
+        m = memoryview(ex)
+
+        # incorrect number of args
+        self.assertRaises(TypeError, m.cast)
+        self.assertRaises(TypeError, m.cast, 1, 2, 3)
+
+        # incorrect dest format type
+        self.assertRaises(TypeError, m.cast, {})
+
+        # incorrect dest format
+        self.assertRaises(ValueError, m.cast, "X")
+        self.assertRaises(ValueError, m.cast, "@X")
+        self.assertRaises(ValueError, m.cast, "@XY")
+
+        # dest format not implemented
+        self.assertRaises(ValueError, m.cast, "=B")
+        self.assertRaises(ValueError, m.cast, "!L")
+        self.assertRaises(ValueError, m.cast, "<P")
+        self.assertRaises(ValueError, m.cast, ">l")
+        self.assertRaises(ValueError, m.cast, "BI")
+        self.assertRaises(ValueError, m.cast, "xBI")
+
+        # src format not implemented
+        ex = ndarray([(1,2), (3,4)], shape=[2], format="II")
+        m = memoryview(ex)
+        self.assertRaises(NotImplementedError, m.__getitem__, 0)
+        self.assertRaises(NotImplementedError, m.__setitem__, 0, 8)
+        self.assertRaises(NotImplementedError, m.tolist)
+
+        # incorrect shape type
+        ex = ndarray(list(range(120)), shape=[1,2,3,4,5])
+        m = memoryview(ex)
+        self.assertRaises(TypeError, m.cast, "B", shape={})
+
+        # incorrect shape elements
+        ex = ndarray(list(range(120)), shape=[2*3*4*5])
+        m = memoryview(ex)
+        self.assertRaises(OverflowError, m.cast, "B", shape=[2**64])
+        self.assertRaises(ValueError, m.cast, "B", shape=[-1])
+        self.assertRaises(ValueError, m.cast, "B", shape=[2,3,4,5,6,7,-1])
+        self.assertRaises(ValueError, m.cast, "B", shape=[2,3,4,5,6,7,0])
+        self.assertRaises(TypeError, m.cast, "B", shape=[2,3,4,5,6,7,'x'])
+
+        # N-D -> N-D cast
+        ex = ndarray(list([9 for _ in range(3*5*7*11)]), shape=[3,5,7,11])
+        m = memoryview(ex)
+        self.assertRaises(TypeError, m.cast, "I", shape=[2,3,4,5])
+
+        # cast with ndim > 64
+        nd = ndarray(list(range(128)), shape=[128], format='I')
+        m = memoryview(nd)
+        self.assertRaises(ValueError, m.cast, 'I', [1]*128)
+
+        # view->len not a multiple of itemsize
+        ex = ndarray(list([9 for _ in range(3*5*7*11)]), shape=[3*5*7*11])
+        m = memoryview(ex)
+        self.assertRaises(TypeError, m.cast, "I", shape=[2,3,4,5])
+
+        # product(shape) * itemsize != buffer size
+        ex = ndarray(list([9 for _ in range(3*5*7*11)]), shape=[3*5*7*11])
+        m = memoryview(ex)
+        self.assertRaises(TypeError, m.cast, "B", shape=[2,3,4,5])
+
+        # product(shape) * itemsize overflow
+        nd = ndarray(list(range(128)), shape=[128], format='I')
+        m1 = memoryview(nd)
+        nd = ndarray(list(range(128)), shape=[128], format='B')
+        m2 = memoryview(nd)
+        if sys.maxsize == 2**63-1:
+            self.assertRaises(TypeError, m1.cast, 'B',
+                              [7, 7, 73, 127, 337, 92737, 649657])
+            self.assertRaises(ValueError, m1.cast, 'B',
+                              [2**20, 2**20, 2**10, 2**10, 2**3])
+            self.assertRaises(ValueError, m2.cast, 'I',
+                              [2**20, 2**20, 2**10, 2**10, 2**1])
+        else:
+            self.assertRaises(TypeError, m1.cast, 'B',
+                              [1, 2147483647])
+            self.assertRaises(ValueError, m1.cast, 'B',
+                              [2**10, 2**10, 2**5, 2**5, 2**1])
+            self.assertRaises(ValueError, m2.cast, 'I',
+                              [2**10, 2**10, 2**5, 2**3, 2**1])
+
+    def test_memoryview_cast(self):
+        bytespec = (
+          ('B', lambda ex: list(ex.tobytes())),
+          ('b', lambda ex: [x-256 if x > 127 else x for x in list(ex.tobytes())]),
+          ('c', lambda ex: [bytes(chr(x), 'latin-1') for x in list(ex.tobytes())]),
+        )
+
+        def iter_roundtrip(ex, m, items, fmt):
+            srcsize = struct.calcsize(fmt)
+            for bytefmt, to_bytelist in bytespec:
+
+                m2 = m.cast(bytefmt)
+                lst = to_bytelist(ex)
+                self.verify(m2, obj=ex,
+                            itemsize=1, fmt=bytefmt, readonly=0,
+                            ndim=1, shape=[31*srcsize], strides=(1,),
+                            lst=lst, cast=True)
+
+                m3 = m2.cast(fmt)
+                self.assertEqual(m3, ex)
+                lst = ex.tolist()
+                self.verify(m3, obj=ex,
+                            itemsize=srcsize, fmt=fmt, readonly=0,
+                            ndim=1, shape=[31], strides=(srcsize,),
+                            lst=lst, cast=True)
+
+        # cast from ndim = 0 to ndim = 1
+        srcsize = struct.calcsize('I')
+        ex = ndarray(9, shape=[], format='I')
+        destitems, destshape = cast_items(ex, 'B', 1)
+        m = memoryview(ex)
+        m2 = m.cast('B')
+        self.verify(m2, obj=ex,
+                    itemsize=1, fmt='B', readonly=1,
+                    ndim=1, shape=destshape, strides=(1,),
+                    lst=destitems, cast=True)
+
+        # cast from ndim = 1 to ndim = 0
+        destsize = struct.calcsize('I')
+        ex = ndarray([9]*destsize, shape=[destsize], format='B')
+        destitems, destshape = cast_items(ex, 'I', destsize, shape=[])
+        m = memoryview(ex)
+        m2 = m.cast('I', shape=[])
+        self.verify(m2, obj=ex,
+                    itemsize=destsize, fmt='I', readonly=1,
+                    ndim=0, shape=(), strides=(),
+                    lst=destitems, cast=True)
+
+        # array.array: roundtrip to/from bytes
+        for fmt, items, _ in iter_format(31, 'array'):
+            ex = array.array(fmt, items)
+            m = memoryview(ex)
+            iter_roundtrip(ex, m, items, fmt)
+
+        # ndarray: roundtrip to/from bytes
+        for fmt, items, _ in iter_format(31, 'memoryview'):
+            ex = ndarray(items, shape=[31], format=fmt, flags=ND_WRITABLE)
+            m = memoryview(ex)
+            iter_roundtrip(ex, m, items, fmt)
+
+    def test_memoryview_cast_1D_ND(self):
+        # Cast between C-contiguous buffers. At least one buffer must
+        # be 1D, at least one format must be 'c', 'b' or 'B'.
+        for _tshape in gencastshapes():
+            for char in fmtdict['@']:
+                tfmt = ('', '@')[randrange(2)] + char
+                tsize = struct.calcsize(tfmt)
+                n = prod(_tshape) * tsize
+                obj = 'memoryview' if is_byte_format(tfmt) else 'bytefmt'
+                for fmt, items, _ in iter_format(n, obj):
+                    size = struct.calcsize(fmt)
+                    shape = [n] if n > 0 else []
+                    tshape = _tshape + [size]
+
+                    ex = ndarray(items, shape=shape, format=fmt)
+                    m = memoryview(ex)
+
+                    titems, tshape = cast_items(ex, tfmt, tsize, shape=tshape)
+
+                    if titems is None:
+                        self.assertRaises(TypeError, m.cast, tfmt, tshape)
+                        continue
+                    if titems == 'nan':
+                        continue # NaNs in lists are a recipe for trouble.
+
+                    # 1D -> ND
+                    nd = ndarray(titems, shape=tshape, format=tfmt)
+
+                    m2 = m.cast(tfmt, shape=tshape)
+                    ndim = len(tshape)
+                    strides = nd.strides
+                    lst = nd.tolist()
+                    self.verify(m2, obj=ex,
+                                itemsize=tsize, fmt=tfmt, readonly=1,
+                                ndim=ndim, shape=tshape, strides=strides,
+                                lst=lst, cast=True)
+
+                    # ND -> 1D
+                    m3 = m2.cast(fmt)
+                    m4 = m2.cast(fmt, shape=shape)
+                    ndim = len(shape)
+                    strides = ex.strides
+                    lst = ex.tolist()
+
+                    self.verify(m3, obj=ex,
+                                itemsize=size, fmt=fmt, readonly=1,
+                                ndim=ndim, shape=shape, strides=strides,
+                                lst=lst, cast=True)
+
+                    self.verify(m4, obj=ex,
+                                itemsize=size, fmt=fmt, readonly=1,
+                                ndim=ndim, shape=shape, strides=strides,
+                                lst=lst, cast=True)
+
+    def test_memoryview_tolist(self):
+
+        # Most tolist() tests are in self.verify() etc.
+
+        a = array.array('h', list(range(-6, 6)))
+        m = memoryview(a)
+        self.assertEqual(m, a)
+        self.assertEqual(m.tolist(), a.tolist())
+
+        a = a[2::3]
+        m = m[2::3]
+        self.assertEqual(m, a)
+        self.assertEqual(m.tolist(), a.tolist())
+
+        ex = ndarray(list(range(2*3*5*7*11)), shape=[11,2,7,3,5], format='L')
+        m = memoryview(ex)
+        self.assertEqual(m.tolist(), ex.tolist())
+
+        ex = ndarray([(2, 5), (7, 11)], shape=[2], format='lh')
+        m = memoryview(ex)
+        self.assertRaises(NotImplementedError, m.tolist)
+
+        ex = ndarray([b'12345'], shape=[1], format="s")
+        m = memoryview(ex)
+        self.assertRaises(NotImplementedError, m.tolist)
+
+        ex = ndarray([b"a",b"b",b"c",b"d",b"e",b"f"], shape=[2,3], format='s')
+        m = memoryview(ex)
+        self.assertRaises(NotImplementedError, m.tolist)
+
+    def test_memoryview_repr(self):
+        m = memoryview(bytearray(9))
+        r = m.__repr__()
+        self.assertTrue(r.startswith("<memory"))
+
+        m.release()
+        r = m.__repr__()
+        self.assertTrue(r.startswith("<released"))
+
+    def test_memoryview_sequence(self):
+
+        for fmt in ('d', 'f'):
+            inf = float(3e400)
+            ex = array.array(fmt, [1.0, inf, 3.0])
+            m = memoryview(ex)
+            self.assertIn(1.0, m)
+            self.assertIn(5e700, m)
+            self.assertIn(3.0, m)
+
+        ex = ndarray(9.0, [], format='f')
+        m = memoryview(ex)
+        self.assertRaises(TypeError, eval, "9.0 in m", locals())
+
+    def test_memoryview_index(self):
+
+        # ndim = 0
+        ex = ndarray(12.5, shape=[], format='d')
+        m = memoryview(ex)
+        self.assertEqual(m[()], 12.5)
+        self.assertEqual(m[...], m)
+        self.assertEqual(m[...], ex)
+        self.assertRaises(TypeError, m.__getitem__, 0)
+
+        ex = ndarray((1,2,3), shape=[], format='iii')
+        m = memoryview(ex)
+        self.assertRaises(NotImplementedError, m.__getitem__, ())
+
+        # range
+        ex = ndarray(list(range(7)), shape=[7], flags=ND_WRITABLE)
+        m = memoryview(ex)
+
+        self.assertRaises(IndexError, m.__getitem__, 2**64)
+        self.assertRaises(TypeError, m.__getitem__, 2.0)
+        self.assertRaises(TypeError, m.__getitem__, 0.0)
+
+        # out of bounds
+        self.assertRaises(IndexError, m.__getitem__, -8)
+        self.assertRaises(IndexError, m.__getitem__, 8)
+
+        # Not implemented: multidimensional sub-views
+        ex = ndarray(list(range(12)), shape=[3,4], flags=ND_WRITABLE)
+        m = memoryview(ex)
+
+        self.assertRaises(NotImplementedError, m.__getitem__, 0)
+        self.assertRaises(NotImplementedError, m.__setitem__, 0, 9)
+        self.assertRaises(NotImplementedError, m.__getitem__, 0)
+
+    def test_memoryview_assign(self):
+
+        # ndim = 0
+        ex = ndarray(12.5, shape=[], format='f', flags=ND_WRITABLE)
+        m = memoryview(ex)
+        m[()] = 22.5
+        self.assertEqual(m[()], 22.5)
+        m[...] = 23.5
+        self.assertEqual(m[()], 23.5)
+        self.assertRaises(TypeError, m.__setitem__, 0, 24.7)
+
+        # read-only
+        ex = ndarray(list(range(7)), shape=[7])
+        m = memoryview(ex)
+        self.assertRaises(TypeError, m.__setitem__, 2, 10)
+
+        # range
+        ex = ndarray(list(range(7)), shape=[7], flags=ND_WRITABLE)
+        m = memoryview(ex)
+
+        self.assertRaises(IndexError, m.__setitem__, 2**64, 9)
+        self.assertRaises(TypeError, m.__setitem__, 2.0, 10)
+        self.assertRaises(TypeError, m.__setitem__, 0.0, 11)
+
+        # out of bounds
+        self.assertRaises(IndexError, m.__setitem__, -8, 20)
+        self.assertRaises(IndexError, m.__setitem__, 8, 25)
+
+        # pack_single() success:
+        for fmt in fmtdict['@']:
+            if fmt == 'c' or fmt == '?':
+                continue
+            ex = ndarray([1,2,3], shape=[3], format=fmt, flags=ND_WRITABLE)
+            m = memoryview(ex)
+            i = randrange(-3, 3)
+            m[i] = 8
+            self.assertEqual(m[i], 8)
+            self.assertEqual(m[i], ex[i])
+
+        ex = ndarray([b'1', b'2', b'3'], shape=[3], format='c',
+                     flags=ND_WRITABLE)
+        m = memoryview(ex)
+        m[2] = b'9'
+        self.assertEqual(m[2], b'9')
+
+        ex = ndarray([True, False, True], shape=[3], format='?',
+                     flags=ND_WRITABLE)
+        m = memoryview(ex)
+        m[1] = True
+        self.assertEqual(m[1], True)
+
+        # pack_single() exceptions:
+        nd = ndarray([b'x'], shape=[1], format='c', flags=ND_WRITABLE)
+        m = memoryview(nd)
+        self.assertRaises(TypeError, m.__setitem__, 0, 100)
+
+        ex = ndarray(list(range(120)), shape=[1,2,3,4,5], flags=ND_WRITABLE)
+        m1 = memoryview(ex)
+
+        for fmt, _range in fmtdict['@'].items():
+            if (fmt == '?'): # PyObject_IsTrue() accepts anything
+                continue
+            if fmt == 'c': # special case tested above
+                continue
+            m2 = m1.cast(fmt)
+            lo, hi = _range
+            if fmt == 'd' or fmt == 'f':
+                lo, hi = -2**1024, 2**1024
+            if fmt != 'P': # PyLong_AsVoidPtr() accepts negative numbers
+                self.assertRaises(ValueError, m2.__setitem__, 0, lo-1)
+                self.assertRaises(TypeError, m2.__setitem__, 0, "xyz")
+            self.assertRaises(ValueError, m2.__setitem__, 0, hi)
+
+        # invalid item
+        m2 = m1.cast('c')
+        self.assertRaises(ValueError, m2.__setitem__, 0, b'\xff\xff')
+
+        # format not implemented
+        ex = ndarray(list(range(1)), shape=[1], format="xL", flags=ND_WRITABLE)
+        m = memoryview(ex)
+        self.assertRaises(NotImplementedError, m.__setitem__, 0, 1)
+
+        ex = ndarray([b'12345'], shape=[1], format="s", flags=ND_WRITABLE)
+        m = memoryview(ex)
+        self.assertRaises(NotImplementedError, m.__setitem__, 0, 1)
+
+        # Not implemented: multidimensional sub-views
+        ex = ndarray(list(range(12)), shape=[3,4], flags=ND_WRITABLE)
+        m = memoryview(ex)
+
+        self.assertRaises(NotImplementedError, m.__setitem__, 0, [2, 3])
+
+    def test_memoryview_slice(self):
+
+        ex = ndarray(list(range(12)), shape=[12], flags=ND_WRITABLE)
+        m = memoryview(ex)
+
+        # zero step
+        self.assertRaises(ValueError, m.__getitem__, slice(0,2,0))
+        self.assertRaises(ValueError, m.__setitem__, slice(0,2,0),
+                          bytearray([1,2]))
+
+        # invalid slice key
+        self.assertRaises(TypeError, m.__getitem__, ())
+
+        # multidimensional slices
+        ex = ndarray(list(range(12)), shape=[12], flags=ND_WRITABLE)
+        m = memoryview(ex)
+
+        self.assertRaises(NotImplementedError, m.__getitem__,
+                          (slice(0,2,1), slice(0,2,1)))
+        self.assertRaises(NotImplementedError, m.__setitem__,
+                          (slice(0,2,1), slice(0,2,1)), bytearray([1,2]))
+
+        # invalid slice tuple
+        self.assertRaises(TypeError, m.__getitem__, (slice(0,2,1), {}))
+        self.assertRaises(TypeError, m.__setitem__, (slice(0,2,1), {}),
+                          bytearray([1,2]))
+
+        # rvalue is not an exporter
+        self.assertRaises(TypeError, m.__setitem__, slice(0,1,1), [1])
+
+        # non-contiguous slice assignment
+        for flags in (0, ND_PIL):
+            ex1 = ndarray(list(range(12)), shape=[12], strides=[-1], offset=11,
+                          flags=ND_WRITABLE|flags)
+            ex2 = ndarray(list(range(24)), shape=[12], strides=[2], flags=flags)
+            m1 = memoryview(ex1)
+            m2 = memoryview(ex2)
+
+            ex1[2:5] = ex1[2:5]
+            m1[2:5] = m2[2:5]
+
+            self.assertEqual(m1, ex1)
+            self.assertEqual(m2, ex2)
+
+            ex1[1:3][::-1] = ex2[0:2][::1]
+            m1[1:3][::-1] = m2[0:2][::1]
+
+            self.assertEqual(m1, ex1)
+            self.assertEqual(m2, ex2)
+
+            ex1[4:1:-2][::-1] = ex1[1:4:2][::1]
+            m1[4:1:-2][::-1] = m1[1:4:2][::1]
+
+            self.assertEqual(m1, ex1)
+            self.assertEqual(m2, ex2)
+
+    def test_memoryview_array(self):
+
+        def cmptest(testcase, a, b, m, singleitem):
+            for i, _ in enumerate(a):
+                ai = a[i]
+                mi = m[i]
+                testcase.assertEqual(ai, mi)
+                a[i] = singleitem
+                if singleitem != ai:
+                    testcase.assertNotEqual(a, m)
+                    testcase.assertNotEqual(a, b)
+                else:
+                    testcase.assertEqual(a, m)
+                    testcase.assertEqual(a, b)
+                m[i] = singleitem
+                testcase.assertEqual(a, m)
+                testcase.assertEqual(b, m)
+                a[i] = ai
+                m[i] = mi
+
+        for n in range(1, 5):
+            for fmt, items, singleitem in iter_format(n, 'array'):
+                for lslice in genslices(n):
+                    for rslice in genslices(n):
+
+                        a = array.array(fmt, items)
+                        b = array.array(fmt, items)
+                        m = memoryview(b)
+
+                        self.assertEqual(m, a)
+                        self.assertEqual(m.tolist(), a.tolist())
+                        self.assertEqual(m.tobytes(), a.tobytes())
+                        self.assertEqual(len(m), len(a))
+
+                        cmptest(self, a, b, m, singleitem)
+
+                        array_err = None
+                        have_resize = None
+                        try:
+                            al = a[lslice]
+                            ar = a[rslice]
+                            a[lslice] = a[rslice]
+                            have_resize = len(al) != len(ar)
+                        except Exception as e:
+                            array_err = e.__class__
+
+                        m_err = None
+                        try:
+                            m[lslice] = m[rslice]
+                        except Exception as e:
+                            m_err = e.__class__
+
+                        if have_resize: # memoryview cannot change shape
+                            self.assertIs(m_err, ValueError)
+                        elif m_err or array_err:
+                            self.assertIs(m_err, array_err)
+                        else:
+                            self.assertEqual(m, a)
+                            self.assertEqual(m.tolist(), a.tolist())
+                            self.assertEqual(m.tobytes(), a.tobytes())
+                            cmptest(self, a, b, m, singleitem)
+
+    def test_memoryview_compare(self):
+
+        a = array.array('L', [1, 2, 3])
+        b = array.array('L', [1, 2, 7])
+
+        # Ordering comparisons raise:
+        v = memoryview(a)
+        w = memoryview(b)
+        for attr in ('__lt__', '__le__', '__gt__', '__ge__'):
+            self.assertIs(getattr(v, attr)(w), NotImplemented)
+            self.assertIs(getattr(a, attr)(v), NotImplemented)
+
+        # Released views compare equal to themselves:
+        v = memoryview(a)
+        v.release()
+        self.assertEqual(v, v)
+        self.assertNotEqual(v, a)
+        self.assertNotEqual(a, v)
+
+        v = memoryview(a)
+        w = memoryview(a)
+        w.release()
+        self.assertNotEqual(v, w)
+        self.assertNotEqual(w, v)
+
+        # Operand does not implement the buffer protocol:
+        v = memoryview(a)
+        self.assertNotEqual(v, [1, 2, 3])
+
+        # Different formats:
+        c = array.array('l', [1, 2, 3])
+        v = memoryview(a)
+        self.assertNotEqual(v, c)
+        self.assertNotEqual(c, v)
+
+        # Not implemented formats. Ugly, but inevitable. This is the same as
+        # issue #2531: equality is also used for membership testing and must
+        # return a result.
+        a = ndarray([(1, 1.5), (2, 2.7)], shape=[2], format='ld')
+        v = memoryview(a)
+        self.assertNotEqual(v, a)
+        self.assertNotEqual(a, v)
+
+        a = ndarray([b'12345'], shape=[1], format="s")
+        v = memoryview(a)
+        self.assertNotEqual(v, a)
+        self.assertNotEqual(a, v)
+
+        nd = ndarray([(1,1,1), (2,2,2), (3,3,3)], shape=[3], format='iii')
+        v = memoryview(nd)
+        self.assertNotEqual(v, nd)
+        self.assertNotEqual(nd, v)
+
+        # '@' prefix can be dropped:
+        nd1 = ndarray([1,2,3], shape=[3], format='@i')
+        nd2 = ndarray([1,2,3], shape=[3], format='i')
+        v = memoryview(nd1)
+        w = memoryview(nd2)
+        self.assertEqual(v, w)
+        self.assertEqual(w, v)
+        self.assertEqual(v, nd2)
+        self.assertEqual(nd2, v)
+        self.assertEqual(w, nd1)
+        self.assertEqual(nd1, w)
+
+        # ndim = 0
+        nd1 = ndarray(1729, shape=[], format='@L')
+        nd2 = ndarray(1729, shape=[], format='L', flags=ND_WRITABLE)
+        v = memoryview(nd1)
+        w = memoryview(nd2)
+        self.assertEqual(v, w)
+        self.assertEqual(w, v)
+        self.assertEqual(v, nd2)
+        self.assertEqual(nd2, v)
+        self.assertEqual(w, nd1)
+        self.assertEqual(nd1, w)
+
+        self.assertFalse(v.__ne__(w))
+        self.assertFalse(w.__ne__(v))
+
+        w[()] = 1728
+        self.assertNotEqual(v, w)
+        self.assertNotEqual(w, v)
+        self.assertNotEqual(v, nd2)
+        self.assertNotEqual(nd2, v)
+        self.assertNotEqual(w, nd1)
+        self.assertNotEqual(nd1, w)
+
+        self.assertFalse(v.__eq__(w))
+        self.assertFalse(w.__eq__(v))
+
+        nd = ndarray(list(range(12)), shape=[12], flags=ND_WRITABLE|ND_PIL)
+        ex = ndarray(list(range(12)), shape=[12], flags=ND_WRITABLE|ND_PIL)
+        m = memoryview(ex)
+
+        self.assertEqual(m, nd)
+        m[9] = 100
+        self.assertNotEqual(m, nd)
+
+        # ndim = 1: contiguous
+        nd1 = ndarray([-529, 576, -625, 676, -729], shape=[5], format='@h')
+        nd2 = ndarray([-529, 576, -625, 676, 729], shape=[5], format='@h')
+        v = memoryview(nd1)
+        w = memoryview(nd2)
+
+        self.assertEqual(v, nd1)
+        self.assertEqual(w, nd2)
+        self.assertNotEqual(v, nd2)
+        self.assertNotEqual(w, nd1)
+        self.assertNotEqual(v, w)
+
+        # ndim = 1: non-contiguous
+        nd1 = ndarray([-529, -625, -729], shape=[3], format='@h')
+        nd2 = ndarray([-529, 576, -625, 676, -729], shape=[5], format='@h')
+        v = memoryview(nd1)
+        w = memoryview(nd2)
+
+        self.assertEqual(v, nd2[::2])
+        self.assertEqual(w[::2], nd1)
+        self.assertEqual(v, w[::2])
+        self.assertEqual(v[::-1], w[::-2])
+
+        # ndim = 1: non-contiguous, suboffsets
+        nd1 = ndarray([-529, -625, -729], shape=[3], format='@h')
+        nd2 = ndarray([-529, 576, -625, 676, -729], shape=[5], format='@h',
+                      flags=ND_PIL)
+        v = memoryview(nd1)
+        w = memoryview(nd2)
+
+        self.assertEqual(v, nd2[::2])
+        self.assertEqual(w[::2], nd1)
+        self.assertEqual(v, w[::2])
+        self.assertEqual(v[::-1], w[::-2])
+
+        # ndim = 1: zeros in shape
+        nd1 = ndarray([900, 961], shape=[0], format='@h')
+        nd2 = ndarray([-900, -961], shape=[0], format='@h')
+        v = memoryview(nd1)
+        w = memoryview(nd2)
+
+        self.assertEqual(v, nd1)
+        self.assertEqual(w, nd2)
+        self.assertEqual(v, nd2)
+        self.assertEqual(w, nd1)
+        self.assertEqual(v, w)
+
+        # ndim = 1: zero strides
+        nd1 = ndarray([900, 900, 900, 900], shape=[4], format='@L')
+        nd2 = ndarray([900], shape=[4], strides=[0], format='L')
+        v = memoryview(nd1)
+        w = memoryview(nd2)
+
+        self.assertEqual(v, nd1)
+        self.assertEqual(w, nd2)
+        self.assertEqual(v, nd2)
+        self.assertEqual(w, nd1)
+        self.assertEqual(v, w)
+
+        n = 10
+        for char in fmtdict['@m']:
+            fmt, items, singleitem = randitems(n, 'memoryview', '@', char)
+            for flags in (0, ND_PIL):
+                nd = ndarray(items, shape=[n], format=fmt, flags=flags)
+                m = memoryview(nd)
+                self.assertEqual(m, nd)
+
+                nd = nd[::-3]
+                m = memoryview(nd)
+                self.assertEqual(m, nd)
+
+        ##### ndim > 1: C-contiguous
+        # different values
+        nd1 = ndarray(list(range(-15, 15)), shape=[3, 2, 5], format='@h')
+        nd2 = ndarray(list(range(0, 30)), shape=[3, 2, 5], format='@h')
+        v = memoryview(nd1)
+        w = memoryview(nd2)
+
+        self.assertEqual(v, nd1)
+        self.assertEqual(w, nd2)
+        self.assertNotEqual(v, nd2)
+        self.assertNotEqual(w, nd1)
+        self.assertNotEqual(v, w)
+
+        # different shape
+        nd1 = ndarray(list(range(30)), shape=[2, 3, 5], format='L')
+        nd2 = ndarray(list(range(30)), shape=[3, 2, 5], format='L')
+        v = memoryview(nd1)
+        w = memoryview(nd2)
+
+        self.assertEqual(v, nd1)
+        self.assertEqual(w, nd2)
+        self.assertNotEqual(v, nd2)
+        self.assertNotEqual(w, nd1)
+        self.assertNotEqual(v, w)
+
+        # different format
+        nd1 = ndarray(list(range(30)), shape=[2, 3, 5], format='L')
+        nd2 = ndarray(list(range(30)), shape=[2, 3, 5], format='l')
+        v = memoryview(nd1)
+        w = memoryview(nd2)
+
+        self.assertEqual(v, nd1)
+        self.assertEqual(w, nd2)
+        self.assertNotEqual(v, nd2)
+        self.assertNotEqual(w, nd1)
+        self.assertNotEqual(v, w)
+
+        ##### ndim > 1: Fortran contiguous
+        # different values
+        nd1 = ndarray(list(range(-15, 15)), shape=[5, 2, 3], format='@h',
+                      flags=ND_FORTRAN)
+        nd2 = ndarray(list(range(0, 30)), shape=[5, 2, 3], format='@h',
+                      flags=ND_FORTRAN)
+        v = memoryview(nd1)
+        w = memoryview(nd2)
+
+        self.assertEqual(v, nd1)
+        self.assertEqual(w, nd2)
+        self.assertNotEqual(v, nd2)
+        self.assertNotEqual(w, nd1)
+        self.assertNotEqual(v, w)
+
+        # different shape
+        nd1 = ndarray(list(range(-15, 15)), shape=[2, 3, 5], format='l',
+                      flags=ND_FORTRAN)
+        nd2 = ndarray(list(range(-15, 15)), shape=[3, 2, 5], format='l',
+                      flags=ND_FORTRAN)
+        v = memoryview(nd1)
+        w = memoryview(nd2)
+
+        self.assertEqual(v, nd1)
+        self.assertEqual(w, nd2)
+        self.assertNotEqual(v, nd2)
+        self.assertNotEqual(w, nd1)
+        self.assertNotEqual(v, w)
+
+        # different format
+        nd1 = ndarray(list(range(30)), shape=[5, 2, 3], format='@h',
+                      flags=ND_FORTRAN)
+        nd2 = ndarray(list(range(30)), shape=[5, 2, 3], format='@b',
+                      flags=ND_FORTRAN)
+        v = memoryview(nd1)
+        w = memoryview(nd2)
+
+        self.assertEqual(v, nd1)
+        self.assertEqual(w, nd2)
+        self.assertNotEqual(v, nd2)
+        self.assertNotEqual(w, nd1)
+        self.assertNotEqual(v, w)
+
+        ##### ndim > 1: mixed C/Fortran contiguous
+        lst1 = list(range(-15, 15))
+        lst2 = transpose(lst1, [3, 2, 5])
+        nd1 = ndarray(lst1, shape=[3, 2, 5], format='@l')
+        nd2 = ndarray(lst2, shape=[3, 2, 5], format='l', flags=ND_FORTRAN)
+        v = memoryview(nd1)
+        w = memoryview(nd2)
+
+        self.assertEqual(v, nd1)
+        self.assertEqual(w, nd2)
+        self.assertEqual(v, w)
+
+        ##### ndim > 1: non-contiguous
+        # different values
+        ex1 = ndarray(list(range(40)), shape=[5, 8], format='@I')
+        nd1 = ex1[3:1:-1, ::-2]
+        ex2 = ndarray(list(range(40)), shape=[5, 8], format='I')
+        nd2 = ex2[1:3:1, ::-2]
+        v = memoryview(nd1)
+        w = memoryview(nd2)
+
+        self.assertEqual(v, nd1)
+        self.assertEqual(w, nd2)
+        self.assertNotEqual(v, nd2)
+        self.assertNotEqual(w, nd1)
+        self.assertNotEqual(v, w)
+
+        # different shape
+        ex1 = ndarray(list(range(30)), shape=[2, 3, 5], format='b')
+        nd1 = ex1[1:3:, ::-2]
+        nd2 = ndarray(list(range(30)), shape=[3, 2, 5], format='b')
+        nd2 = ex2[1:3:, ::-2]
+        v = memoryview(nd1)
+        w = memoryview(nd2)
+
+        self.assertEqual(v, nd1)
+        self.assertEqual(w, nd2)
+        self.assertNotEqual(v, nd2)
+        self.assertNotEqual(w, nd1)
+        self.assertNotEqual(v, w)
+
+        # different format
+        ex1 = ndarray(list(range(30)), shape=[5, 3, 2], format='i')
+        nd1 = ex1[1:3:, ::-2]
+        nd2 = ndarray(list(range(30)), shape=[5, 3, 2], format='@I')
+        nd2 = ex2[1:3:, ::-2]
+        v = memoryview(nd1)
+        w = memoryview(nd2)
+
+        self.assertEqual(v, nd1)
+        self.assertEqual(w, nd2)
+        self.assertNotEqual(v, nd2)
+        self.assertNotEqual(w, nd1)
+        self.assertNotEqual(v, w)
+
+        ##### ndim > 1: zeros in shape
+        nd1 = ndarray(list(range(30)), shape=[0, 3, 2], format='i')
+        nd2 = ndarray(list(range(30)), shape=[5, 0, 2], format='@i')
+        v = memoryview(nd1)
+        w = memoryview(nd2)
+
+        self.assertEqual(v, nd1)
+        self.assertEqual(w, nd2)
+        self.assertNotEqual(v, nd2)
+        self.assertNotEqual(w, nd1)
+        self.assertNotEqual(v, w)
+
+        # ndim > 1: zero strides
+        nd1 = ndarray([900]*80, shape=[4, 5, 4], format='@L')
+        nd2 = ndarray([900], shape=[4, 5, 4], strides=[0, 0, 0], format='L')
+        v = memoryview(nd1)
+        w = memoryview(nd2)
+
+        self.assertEqual(v, nd1)
+        self.assertEqual(w, nd2)
+        self.assertEqual(v, nd2)
+        self.assertEqual(w, nd1)
+        self.assertEqual(v, w)
+        self.assertEqual(v.tolist(), w.tolist())
+
+        ##### ndim > 1: suboffsets
+        ex1 = ndarray(list(range(40)), shape=[5, 8], format='@I')
+        nd1 = ex1[3:1:-1, ::-2]
+        ex2 = ndarray(list(range(40)), shape=[5, 8], format='I', flags=ND_PIL)
+        nd2 = ex2[1:3:1, ::-2]
+        v = memoryview(nd1)
+        w = memoryview(nd2)
+
+        self.assertEqual(v, nd1)
+        self.assertEqual(w, nd2)
+        self.assertNotEqual(v, nd2)
+        self.assertNotEqual(w, nd1)
+        self.assertNotEqual(v, w)
+
+        # different shape
+        ex1 = ndarray(list(range(30)), shape=[2, 3, 5], format='b', flags=ND_PIL)
+        nd1 = ex1[1:3:, ::-2]
+        nd2 = ndarray(list(range(30)), shape=[3, 2, 5], format='b')
+        nd2 = ex2[1:3:, ::-2]
+        v = memoryview(nd1)
+        w = memoryview(nd2)
+
+        self.assertEqual(v, nd1)
+        self.assertEqual(w, nd2)
+        self.assertNotEqual(v, nd2)
+        self.assertNotEqual(w, nd1)
+        self.assertNotEqual(v, w)
+
+        # different format
+        ex1 = ndarray(list(range(30)), shape=[5, 3, 2], format='i', flags=ND_PIL)
+        nd1 = ex1[1:3:, ::-2]
+        nd2 = ndarray(list(range(30)), shape=[5, 3, 2], format='@I', flags=ND_PIL)
+        nd2 = ex2[1:3:, ::-2]
+        v = memoryview(nd1)
+        w = memoryview(nd2)
+
+        self.assertEqual(v, nd1)
+        self.assertEqual(w, nd2)
+        self.assertNotEqual(v, nd2)
+        self.assertNotEqual(w, nd1)
+        self.assertNotEqual(v, w)
+
+        # initialize mixed C/Fortran + suboffsets
+        lst1 = list(range(-15, 15))
+        lst2 = transpose(lst1, [3, 2, 5])
+        nd1 = ndarray(lst1, shape=[3, 2, 5], format='@l', flags=ND_PIL)
+        nd2 = ndarray(lst2, shape=[3, 2, 5], format='l', flags=ND_FORTRAN|ND_PIL)
+        v = memoryview(nd1)
+        w = memoryview(nd2)
+
+        self.assertEqual(v, nd1)
+        self.assertEqual(w, nd2)
+        self.assertEqual(v, w)
+
+    def test_memoryview_check_released(self):
+
+        a = array.array('d', [1.1, 2.2, 3.3])
+
+        m = memoryview(a)
+        m.release()
+
+        # PyMemoryView_FromObject()
+        self.assertRaises(ValueError, memoryview, m)
+        # memoryview.cast()
+        self.assertRaises(ValueError, m.cast, 'c')
+        # getbuffer()
+        self.assertRaises(ValueError, ndarray, m)
+        # memoryview.tolist()
+        self.assertRaises(ValueError, m.tolist)
+        # memoryview.tobytes()
+        self.assertRaises(ValueError, m.tobytes)
+        # sequence
+        self.assertRaises(ValueError, eval, "1.0 in m", locals())
+        # subscript
+        self.assertRaises(ValueError, m.__getitem__, 0)
+        # assignment
+        self.assertRaises(ValueError, m.__setitem__, 0, 1)
+
+        for attr in ('obj', 'nbytes', 'readonly', 'itemsize', 'format', 'ndim',
+                     'shape', 'strides', 'suboffsets', 'c_contiguous',
+                     'f_contiguous', 'contiguous'):
+            self.assertRaises(ValueError, m.__getattribute__, attr)
+
+        # richcompare
+        b = array.array('d', [1.1, 2.2, 3.3])
+        m1 = memoryview(a)
+        m2 = memoryview(b)
+
+        self.assertEqual(m1, m2)
+        m1.release()
+        self.assertNotEqual(m1, m2)
+        self.assertNotEqual(m1, a)
+        self.assertEqual(m1, m1)
+
+    def test_memoryview_tobytes(self):
+        # Many implicit tests are already in self.verify().
+
+        nd = ndarray([-529, 576, -625, 676, -729], shape=[5], format='@h')
+
+        m = memoryview(nd)
+        self.assertEqual(m.tobytes(), nd.tobytes())
+
+    def test_memoryview_get_contiguous(self):
+        # Many implicit tests are already in self.verify().
+
+        # no buffer interface
+        self.assertRaises(TypeError, get_contiguous, {}, PyBUF_READ, 'F')
+
+        # writable request to read-only object
+        self.assertRaises(BufferError, get_contiguous, b'x', PyBUF_WRITE, 'C')
+
+        # writable request to non-contiguous object
+        nd = ndarray([1, 2, 3], shape=[2], strides=[2])
+        self.assertRaises(BufferError, get_contiguous, nd, PyBUF_WRITE, 'A')
+
+        # scalar, read-only request from read-only exporter
+        nd = ndarray(9, shape=(), format="L")
+        for order in ['C', 'F', 'A']:
+            m = get_contiguous(nd, PyBUF_READ, order)
+            self.assertEqual(m, nd)
+            self.assertEqual(m[()], 9)
+
+        # scalar, read-only request from writable exporter
+        nd = ndarray(9, shape=(), format="L", flags=ND_WRITABLE)
+        for order in ['C', 'F', 'A']:
+            m = get_contiguous(nd, PyBUF_READ, order)
+            self.assertEqual(m, nd)
+            self.assertEqual(m[()], 9)
+
+        # scalar, writable request
+        for order in ['C', 'F', 'A']:
+            nd[()] = 9
+            m = get_contiguous(nd, PyBUF_WRITE, order)
+            self.assertEqual(m, nd)
+            self.assertEqual(m[()], 9)
+
+            m[()] = 10
+            self.assertEqual(m[()], 10)
+            self.assertEqual(nd[()], 10)
+
+        # zeros in shape
+        nd = ndarray([1], shape=[0], format="L", flags=ND_WRITABLE)
+        for order in ['C', 'F', 'A']:
+            m = get_contiguous(nd, PyBUF_READ, order)
+            self.assertRaises(IndexError, m.__getitem__, 0)
+            self.assertEqual(m, nd)
+            self.assertEqual(m.tolist(), [])
+
+        nd = ndarray(list(range(8)), shape=[2, 0, 7], format="L",
+                     flags=ND_WRITABLE)
+        for order in ['C', 'F', 'A']:
+            m = get_contiguous(nd, PyBUF_READ, order)
+            self.assertEqual(ndarray(m).tolist(), [[], []])
+
+        # one-dimensional
+        nd = ndarray([1], shape=[1], format="h", flags=ND_WRITABLE)
+        for order in ['C', 'F', 'A']:
+            m = get_contiguous(nd, PyBUF_WRITE, order)
+            self.assertEqual(m, nd)
+            self.assertEqual(m.tolist(), nd.tolist())
+
+        nd = ndarray([1, 2, 3], shape=[3], format="b", flags=ND_WRITABLE)
+        for order in ['C', 'F', 'A']:
+            m = get_contiguous(nd, PyBUF_WRITE, order)
+            self.assertEqual(m, nd)
+            self.assertEqual(m.tolist(), nd.tolist())
+
+        # one-dimensional, non-contiguous
+        nd = ndarray([1, 2, 3], shape=[2], strides=[2], flags=ND_WRITABLE)
+        for order in ['C', 'F', 'A']:
+            m = get_contiguous(nd, PyBUF_READ, order)
+            self.assertEqual(m, nd)
+            self.assertEqual(m.tolist(), nd.tolist())
+            self.assertRaises(TypeError, m.__setitem__, 1, 20)
+            self.assertEqual(m[1], 3)
+            self.assertEqual(nd[1], 3)
+
+        nd = nd[::-1]
+        for order in ['C', 'F', 'A']:
+            m = get_contiguous(nd, PyBUF_READ, order)
+            self.assertEqual(m, nd)
+            self.assertEqual(m.tolist(), nd.tolist())
+            self.assertRaises(TypeError, m.__setitem__, 1, 20)
+            self.assertEqual(m[1], 1)
+            self.assertEqual(nd[1], 1)
+
+        # multi-dimensional, contiguous input
+        nd = ndarray(list(range(12)), shape=[3, 4], flags=ND_WRITABLE)
+        for order in ['C', 'A']:
+            m = get_contiguous(nd, PyBUF_WRITE, order)
+            self.assertEqual(ndarray(m).tolist(), nd.tolist())
+
+        self.assertRaises(BufferError, get_contiguous, nd, PyBUF_WRITE, 'F')
+        m = get_contiguous(nd, PyBUF_READ, order)
+        self.assertEqual(ndarray(m).tolist(), nd.tolist())
+
+        nd = ndarray(list(range(12)), shape=[3, 4],
+                     flags=ND_WRITABLE|ND_FORTRAN)
+        for order in ['F', 'A']:
+            m = get_contiguous(nd, PyBUF_WRITE, order)
+            self.assertEqual(ndarray(m).tolist(), nd.tolist())
+
+        self.assertRaises(BufferError, get_contiguous, nd, PyBUF_WRITE, 'C')
+        m = get_contiguous(nd, PyBUF_READ, order)
+        self.assertEqual(ndarray(m).tolist(), nd.tolist())
+
+        # multi-dimensional, non-contiguous input
+        nd = ndarray(list(range(12)), shape=[3, 4], flags=ND_WRITABLE|ND_PIL)
+        for order in ['C', 'F', 'A']:
+            self.assertRaises(BufferError, get_contiguous, nd, PyBUF_WRITE,
+                              order)
+            m = get_contiguous(nd, PyBUF_READ, order)
+            self.assertEqual(ndarray(m).tolist(), nd.tolist())
+
+        # flags
+        nd = ndarray([1,2,3,4,5], shape=[3], strides=[2])
+        m = get_contiguous(nd, PyBUF_READ, 'C')
+        self.assertTrue(m.c_contiguous)
+
+    def test_memoryview_serializing(self):
+
+        # C-contiguous
+        size = struct.calcsize('i')
+        a = array.array('i', [1,2,3,4,5])
+        m = memoryview(a)
+        buf = io.BytesIO(m)
+        b = bytearray(5*size)
+        buf.readinto(b)
+        self.assertEqual(m.tobytes(), b)
+
+        # C-contiguous, multi-dimensional
+        size = struct.calcsize('L')
+        nd = ndarray(list(range(12)), shape=[2,3,2], format="L")
+        m = memoryview(nd)
+        buf = io.BytesIO(m)
+        b = bytearray(2*3*2*size)
+        buf.readinto(b)
+        self.assertEqual(m.tobytes(), b)
+
+        # Fortran contiguous, multi-dimensional
+        #size = struct.calcsize('L')
+        #nd = ndarray(list(range(12)), shape=[2,3,2], format="L",
+        #             flags=ND_FORTRAN)
+        #m = memoryview(nd)
+        #buf = io.BytesIO(m)
+        #b = bytearray(2*3*2*size)
+        #buf.readinto(b)
+        #self.assertEqual(m.tobytes(), b)
+
+    def test_memoryview_hash(self):
+
+        # bytes exporter
+        b = bytes(list(range(12)))
+        m = memoryview(b)
+        self.assertEqual(hash(b), hash(m))
+
+        # C-contiguous
+        mc = m.cast('c', shape=[3,4])
+        self.assertEqual(hash(mc), hash(b))
+
+        # non-contiguous
+        mx = m[::-2]
+        b = bytes(list(range(12))[::-2])
+        self.assertEqual(hash(mx), hash(b))
+
+        # Fortran contiguous
+        nd = ndarray(list(range(30)), shape=[3,2,5], flags=ND_FORTRAN)
+        m = memoryview(nd)
+        self.assertEqual(hash(m), hash(nd))
+
+        # multi-dimensional slice
+        nd = ndarray(list(range(30)), shape=[3,2,5])
+        x = nd[::2, ::, ::-1]
+        m = memoryview(x)
+        self.assertEqual(hash(m), hash(x))
+
+        # multi-dimensional slice with suboffsets
+        nd = ndarray(list(range(30)), shape=[2,5,3], flags=ND_PIL)
+        x = nd[::2, ::, ::-1]
+        m = memoryview(x)
+        self.assertEqual(hash(m), hash(x))
+
+        # non-byte formats
+        nd = ndarray(list(range(12)), shape=[2,2,3], format='L')
+        m = memoryview(nd)
+        self.assertEqual(hash(m), hash(nd.tobytes()))
+
+        nd = ndarray(list(range(-6, 6)), shape=[2,2,3], format='h')
+        m = memoryview(nd)
+        self.assertEqual(hash(m), hash(nd.tobytes()))
+
+    def test_memoryview_release(self):
+
+        # Create re-exporter from getbuffer(memoryview), then release the view.
+        a = bytearray([1,2,3])
+        m = memoryview(a)
+        nd = ndarray(m) # re-exporter
+        self.assertRaises(BufferError, m.release)
+        del nd
+        m.release()
+
+        # chained views
+        a = bytearray([1,2,3])
+        m1 = memoryview(a)
+        m2 = memoryview(m1)
+        nd = ndarray(m2) # re-exporter
+        m1.release()
+        self.assertRaises(BufferError, m2.release)
+        del nd
+        m2.release()
+
+        # Allow changing layout while buffers are exported.
+        nd = ndarray([1,2,3], shape=[3], flags=ND_VAREXPORT)
+        m1 = memoryview(nd)
+
+        nd.push([4,5,6,7,8], shape=[5]) # mutate nd
+        m2 = memoryview(nd)
+
+        x = memoryview(m1)
+        self.assertEqual(x.tolist(), m1.tolist())
+
+        y = memoryview(m2)
+        self.assertEqual(y.tolist(), m2.tolist())
+        self.assertEqual(y.tolist(), nd.tolist())
+        m2.release()
+        y.release()
+
+        nd.pop() # pop the current view
+        self.assertEqual(x.tolist(), nd.tolist())
+
+        del nd
+        m1.release()
+        x.release()
+
+        # If multiple memoryviews share the same managed buffer, implicit
+        # release() in the context manager's __exit__() method should still
+        # work.
+        def catch22(b):
+            with memoryview(b) as m2:
+                pass
+
+        x = bytearray(b'123')
+        with memoryview(x) as m1:
+            catch22(m1)
+            self.assertEqual(m1[0], ord(b'1'))
+
+        # XXX If m1 has exports, raise BufferError.
+        # x = bytearray(b'123')
+        # with memoryview(x) as m1:
+        #     ex = ndarray(m1)
+        #     m1[0] == ord(b'1')
+
+    def test_issue_7385(self):
+        x = ndarray([1,2,3], shape=[3], flags=ND_GETBUF_FAIL)
+        self.assertRaises(BufferError, memoryview, x)
+
+
+def test_main():
+    support.run_unittest(TestBufferProtocol)
+
+
+if __name__ == "__main__":
+    test_main()
diff --git a/Lib/test/test_memoryview.py b/Lib/test/test_memoryview.py
index a5a0ca1..8809930 100644
--- a/Lib/test/test_memoryview.py
+++ b/Lib/test/test_memoryview.py
@@ -24,15 +24,14 @@
         return filter(None, [self.ro_type, self.rw_type])
 
     def check_getitem_with_type(self, tp):
-        item = self.getitem_type
         b = tp(self._source)
         oldrefcount = sys.getrefcount(b)
         m = self._view(b)
-        self.assertEqual(m[0], item(b"a"))
-        self.assertIsInstance(m[0], bytes)
-        self.assertEqual(m[5], item(b"f"))
-        self.assertEqual(m[-1], item(b"f"))
-        self.assertEqual(m[-6], item(b"a"))
+        self.assertEqual(m[0], ord(b"a"))
+        self.assertIsInstance(m[0], int)
+        self.assertEqual(m[5], ord(b"f"))
+        self.assertEqual(m[-1], ord(b"f"))
+        self.assertEqual(m[-6], ord(b"a"))
         # Bounds checking
         self.assertRaises(IndexError, lambda: m[6])
         self.assertRaises(IndexError, lambda: m[-7])
@@ -76,7 +75,9 @@
         b = self.rw_type(self._source)
         oldrefcount = sys.getrefcount(b)
         m = self._view(b)
-        m[0] = tp(b"0")
+        m[0] = ord(b'1')
+        self._check_contents(tp, b, b"1bcdef")
+        m[0:1] = tp(b"0")
         self._check_contents(tp, b, b"0bcdef")
         m[1:3] = tp(b"12")
         self._check_contents(tp, b, b"012def")
@@ -102,10 +103,17 @@
         # Wrong index/slice types
         self.assertRaises(TypeError, setitem, 0.0, b"a")
         self.assertRaises(TypeError, setitem, (0,), b"a")
+        self.assertRaises(TypeError, setitem, (slice(0,1,1), 0), b"a")
+        self.assertRaises(TypeError, setitem, (0, slice(0,1,1)), b"a")
+        self.assertRaises(TypeError, setitem, (0,), b"a")
         self.assertRaises(TypeError, setitem, "a", b"a")
+        # Not implemented: multidimensional slices
+        slices = (slice(0,1,1), slice(0,1,2))
+        self.assertRaises(NotImplementedError, setitem, slices, b"a")
         # Trying to resize the memory object
-        self.assertRaises(ValueError, setitem, 0, b"")
-        self.assertRaises(ValueError, setitem, 0, b"ab")
+        exc = ValueError if m.format == 'c' else TypeError
+        self.assertRaises(exc, setitem, 0, b"")
+        self.assertRaises(exc, setitem, 0, b"ab")
         self.assertRaises(ValueError, setitem, slice(1,1), b"a")
         self.assertRaises(ValueError, setitem, slice(0,2), b"a")
 
@@ -175,7 +183,7 @@
         self.assertEqual(m.shape, (6,))
         self.assertEqual(len(m), 6)
         self.assertEqual(m.strides, (self.itemsize,))
-        self.assertEqual(m.suboffsets, None)
+        self.assertEqual(m.suboffsets, ())
         return m
 
     def test_attributes_readonly(self):
@@ -209,12 +217,16 @@
                 # If tp is a factory rather than a plain type, skip
                 continue
 
+            class MyView():
+                def __init__(self, base):
+                    self.m = memoryview(base)
             class MySource(tp):
                 pass
             class MyObject:
                 pass
 
-            # Create a reference cycle through a memoryview object
+            # Create a reference cycle through a memoryview object.
+            # This exercises mbuf_clear().
             b = MySource(tp(b'abc'))
             m = self._view(b)
             o = MyObject()
@@ -226,6 +238,17 @@
             gc.collect()
             self.assertTrue(wr() is None, wr())
 
+            # This exercises memory_clear().
+            m = MyView(tp(b'abc'))
+            o = MyObject()
+            m.x = m
+            m.o = o
+            wr = weakref.ref(o)
+            m = o = None
+            # The cycle must be broken
+            gc.collect()
+            self.assertTrue(wr() is None, wr())
+
     def _check_released(self, m, tp):
         check = self.assertRaisesRegex(ValueError, "released")
         with check: bytes(m)
@@ -283,9 +306,12 @@
         i = io.BytesIO(b'ZZZZ')
         self.assertRaises(TypeError, i.readinto, m)
 
+    def test_getbuf_fail(self):
+        self.assertRaises(TypeError, self._view, {})
+
     def test_hash(self):
         # Memoryviews of readonly (hashable) types are hashable, and they
-        # hash as the corresponding object.
+        # hash as hash(obj.tobytes()).
         tp = self.ro_type
         if tp is None:
             self.skipTest("no read-only type to test")
diff --git a/Lib/test/test_sys.py b/Lib/test/test_sys.py
index bf22df2..551c3a5 100644
--- a/Lib/test/test_sys.py
+++ b/Lib/test/test_sys.py
@@ -773,8 +773,8 @@
         check(int(PyLong_BASE), size(vh) + 2*self.longdigit)
         check(int(PyLong_BASE**2-1), size(vh) + 2*self.longdigit)
         check(int(PyLong_BASE**2), size(vh) + 3*self.longdigit)
-        # memory (Py_buffer + hash value)
-        check(memoryview(b''), size(h + 'PP2P2i7P' + 'P'))
+        # memoryview
+        check(memoryview(b''), size(h + 'PPiP4P2i5P3cP'))
         # module
         check(unittest, size(h + '3P'))
         # None