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| author | Stefan Krah <skrah@bytereef.org> | 2012-02-25 11:24:21 (GMT) |
|---|---|---|
| committer | Stefan Krah <skrah@bytereef.org> | 2012-02-25 11:24:21 (GMT) |
| commit | 9a2d99e28a5c2989b2db4023acae4f550885f2ef (patch) | |
| tree | 29bb99fc008de30ecc1e765d6d14ee35cd5bdfe5 /Lib/test/test_buffer.py | |
| parent | 5a3d04623b0dc8219326989bc3619d5f56737a94 (diff) | |
| download | cpython-9a2d99e28a5c2989b2db4023acae4f550885f2ef.zip cpython-9a2d99e28a5c2989b2db4023acae4f550885f2ef.tar.gz cpython-9a2d99e28a5c2989b2db4023acae4f550885f2ef.tar.bz2 | |
- Issue #10181: New memoryview implementation fixes multiple ownership
and lifetime issues of dynamically allocated Py_buffer members (#9990)
as well as crashes (#8305, #7433). Many new features have been added
(See whatsnew/3.3), and the documentation has been updated extensively.
The ndarray test object from _testbuffer.c implements all aspects of
PEP-3118, so further development towards the complete implementation
of the PEP can proceed in a test-driven manner.
Thanks to Nick Coghlan, Antoine Pitrou and Pauli Virtanen for review
and many ideas.
- Issue #12834: Fix incorrect results of memoryview.tobytes() for
non-contiguous arrays.
- Issue #5231: Introduce memoryview.cast() method that allows changing
format and shape without making a copy of the underlying memory.
Diffstat (limited to 'Lib/test/test_buffer.py')
| -rw-r--r-- | Lib/test/test_buffer.py | 3437 |
1 files changed, 3437 insertions, 0 deletions
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() |