def make_registrations():
def make_date(p: Callable) -> datetime.date:
year, month, day = p(int), p(int), p(int)
# This condition isn't technically required, but it develops useful
# symbolic inequalities before the realization below:
if not (1 <= year <= 9999 and 1 <= month <= 12 and 1 <= day <= 31):
raise IgnoreAttempt('Invalid date')
try:
return datetime.date(realize(year), realize(month), realize(day))
except ValueError:
raise IgnoreAttempt('Invalid date')
register_type(datetime.date, make_date)
def make_timedelta(p: Callable) -> datetime.timedelta:
microseconds, seconds, days = p(int), p(int), p(int)
# the normalized ranges, per the docs:
if not (0 <= microseconds < 1000000 and 0 <= seconds < 3600 * 24
and -999999999 <= days <= 999999999):
raise IgnoreAttempt('Invalid timedelta')
try:
return datetime.timedelta(days=realize(days),
seconds=realize(seconds),
microseconds=realize(microseconds))
except OverflowError:
raise IgnoreAttempt('Invalid timedelta')
register_type(datetime.timedelta, make_timedelta)
def make_registrations():
# NOTE: defaultdict could be symbolic (but note the default_factory is changable/stateful):
register_type(collections.defaultdict,
lambda p, kt=Any, vt=Any: collections.defaultdict(
p(Callable[[], vt]), p(Dict[kt, vt]))) # type: ignore
register_type(collections.ChainMap,
lambda p, kt=Any, vt=Any: collections.ChainMap(*p(Tuple[Dict[
kt, vt], ...]))) # type: ignore
register_type(collections.abc.Mapping,
lambda p, kt=Any, vt=Any: p(Dict[kt, vt])) # type: ignore
register_type(collections.abc.MutableMapping,
lambda p, kt=Any, vt=Any: p(Dict[kt, vt])) # type: ignore
register_type(collections.OrderedDict,
lambda p, kt=Any, vt=Any: collections.OrderedDict(
p(Dict[kt, vt]))) # type: ignore
register_type(
collections.Counter,
lambda p, t=Any: collections.Counter(p(Dict[t, int]))) # type: ignore
# TODO: MappingView is missing
register_type(
collections.abc.ItemsView,
lambda p, kt=Any, vt=Any: p(Set[Tuple[kt, vt]])) # type: ignore
register_type(collections.abc.KeysView,
lambda p, t=Any: p(Set[t])) # type: ignore
register_type(collections.abc.ValuesView,
lambda p, t=Any: p(Set[t])) # type: ignore
register_type(collections.abc.Container, lambda p, t=Any: p(Tuple[t, ...]))
register_type(collections.abc.Collection,
lambda p, t=Any: p(Tuple[t, ...]))
register_type(collections.deque,
lambda p, t=Any: collections.deque(p(Tuple[t, ...])))
# TODO: When ready, use custom deque class instead:
# register_type(collections.deque, lambda p, t=Any: ListBasedDeque(p(List[t, ...]))) # type: ignore
register_type(collections.abc.Iterable, lambda p, t=Any: p(Tuple[t, ...]))
register_type(collections.abc.Iterator,
lambda p, t=Any: iter(p(Iterable[t]))) # type: ignore
register_type(collections.abc.MutableSequence,
lambda p, t=Any: p(List[t])) # type: ignore
register_type(collections.abc.Reversible,
lambda p, t=Any: p(Tuple[t, ...]))
register_type(collections.abc.Sequence, lambda p, t=Any: p(Tuple[t, ...]))
register_type(collections.abc.Sized, lambda p, t=Any: p(Tuple[t, ...]))
register_type(collections.abc.MutableSet,
lambda p, t=Any: p(Set[t])) # type: ignore
register_type(collections.abc.ByteString,
lambda p: bytes(b % 256 for b in p(List[int])))
register_type(collections.abc.Hashable, lambda p: p(int))
def make_registrations():
# WARNING: This is destructive for the datetime module.
# It disables the C implementation for the entire interpreter.
sys.modules["_datetime"] = None # type: ignore
importlib.reload(datetime)
# Default pickling will realize the symbolic args; avoid this:
datetime.date.__deepcopy__ = lambda s, _memo: datetime.date(
s.year, s.month, s.day)
datetime.time.__deepcopy__ = lambda s, _memo: datetime.time(
s.hour, s.minute, s.second, s.microsecond, s.tzinfo)
datetime.datetime.__deepcopy__ = lambda s, _memo: datetime.datetime(
s.year, s.month, s.day, s.hour, s.minute, s.second, s.microsecond, s.
tzinfo)
datetime.timedelta.__deepcopy__ = lambda d, _memo: _timedelta_skip_construct(
d.days, d.seconds, d.microseconds)
# Mokey patch validation so that we can defer it.
orig_check_date_fields = datetime._check_date_fields
orig_check_time_fields = datetime._check_time_fields
datetime._check_date_fields = lambda y, m, d: (y, m, d)
datetime._check_time_fields = lambda h, m, s, u, f: (h, m, s, u, f)
# TODO: `timezone` never makes a tzinfo with DST, so this is incomplete.
# A complete solution would require generating a symbolc dst() member function.
register_type(datetime.tzinfo, lambda p: p(datetime.timezone))
# NOTE: these bounds have changed over python versions (e.g. [1]), so we pull the
# following private constants from the runtime directly.
# [1] https://github.com/python/cpython/commit/92c7e30adf5c81a54d6e5e555a6bdfaa60157a0d#diff-2a8962dcecb109859cedd81ddc5729bea57d156e0947cb8413f99781a0860fd1R2272
_max_tz_offset = datetime.timezone._maxoffset
_min_tz_offset = datetime.timezone._minoffset
def make_timezone(p: Any) -> datetime.timezone:
if p.space.smt_fork(desc="use explicit timezone"):
delta = p(datetime.timedelta, "_offset")
with ResumedTracing():
if _min_tz_offset < delta < _max_tz_offset:
return datetime.timezone(delta, realize(p(str, "_name")))
else:
raise IgnoreAttempt("Invalid timezone offset")
else:
return datetime.timezone.utc
register_type(datetime.timezone, make_timezone)
def make_date(p: Any) -> datetime.date:
year, month, day = p(int, "_year"), p(int, "_month"), p(int, "_day")
try:
p.space.defer_assumption(
"Invalid date",
lambda: (not _raises_value_error(orig_check_date_fields,
(year, month, day))),
)
return datetime.date(year, month, day)
except ValueError:
raise IgnoreAttempt("Invalid date")
register_type(datetime.date, make_date)
def make_time(p: Any) -> datetime.time:
hour = p(int, "_hour")
minute = p(int, "_minute")
sec = p(int, "_sec")
usec = p(int, "_usec")
tzinfo = p(Optional[datetime.timezone], "_tzinfo")
try:
p.space.defer_assumption(
"Invalid datetime",
lambda:
(not _raises_value_error(orig_check_time_fields,
(hour, minute, sec, usec, 0))),
)
return datetime.time(hour, minute, sec, usec, tzinfo)
except ValueError:
raise IgnoreAttempt("Invalid datetime")
register_type(datetime.time, make_time)
def make_datetime(p: Any) -> datetime.datetime:
year, month, day, hour, minute, sec, usec = (
p(int, "_year"),
p(int, "_month"),
p(int, "_day"),
p(int, "_hour"),
p(int, "_minute"),
p(int, "_sec"),
p(int, "usec"),
)
tzinfo = p(Optional[datetime.timezone], "_tz")
try:
p.space.defer_assumption(
"Invalid datetime",
lambda:
(not _raises_value_error(orig_check_date_fields,
(year, month, day)) and
not _raises_value_error(orig_check_time_fields,
(hour, minute, sec, usec, 0))),
)
return datetime.datetime(year, month, day, hour, minute, sec, usec,
tzinfo)
except ValueError:
raise IgnoreAttempt("Invalid datetime")
register_type(datetime.datetime, make_datetime)
def make_timedelta(p: Callable) -> datetime.timedelta:
microseconds, seconds, days = p(int,
"_usec"), p(int,
"_sec"), p(int, "_days")
with ResumedTracing():
# the normalized ranges, per the docs:
if not (0 <= microseconds < 1000000 and 0 <= seconds < 3600 * 24
and -999999999 <= days <= 999999999):
raise IgnoreAttempt("Invalid timedelta")
try:
return _timedelta_skip_construct(days, seconds, microseconds)
except OverflowError:
raise IgnoreAttempt("Invalid timedelta")
register_type(datetime.timedelta, make_timedelta)
def __array__(self):
if any(size < 0 for size in self.shape):
raise IgnoreAttempt('ndarray disallows negative dimensions')
concrete_shape = tuple(map(int, self.shape))
concrete_dtype = realize(self.dtype)
# For the contents, we just construct it with ones. This makes it much
# less complete in terms of finding counterexamples, but is sufficient
# for array dimension and type reasoning. If we were more ambitious,
# we would rewrite a (slow) implementation of numpy in terms of native
# Python types.
return np.ones(concrete_shape, concrete_dtype)
# Make crosshair use our custom class whenever it needs a symbolic
# ndarray instance:
register_type(np.ndarray, SymbolicNdarray)
def matrix_multiply(image1: np.ndarray, image2: np.ndarray) -> np.ndarray:
'''
pre: image1.dtype == image2.dtype == np.float64
pre: len(image1.shape) == len(image2.shape) == 2
pre: image1.shape[1] == image2.shape[0]
post: __return__.shape == (image1.shape[0], image2.shape[1])
'''
return image1 @ image2
def unit_normalize(a: np.ndarray) -> np.ndarray:
'''
>>> unit_normalize(np.arange(-1, 2))
def make_registrations() -> None:
register_type(random.Random, lambda p: random.Random(p(int)))
def make_registrations():
register_type(collections.defaultdict,
lambda p, kt=Any, vt=Any: PureDefaultDict(
p(Optional[Callable[[], vt]], "_initalizer"),
p(Dict[kt, vt]))) # type: ignore
register_type(collections.ChainMap,
lambda p, kt=Any, vt=Any: collections.ChainMap(*p(Tuple[Dict[
kt, vt], ...]))) # type: ignore
register_type(collections.abc.Mapping,
lambda p, kt=Any, vt=Any: p(Dict[kt, vt])) # type: ignore
register_type(collections.abc.MutableMapping,
lambda p, kt=Any, vt=Any: p(Dict[kt, vt])) # type: ignore
register_type(collections.OrderedDict,
lambda p, kt=Any, vt=Any: collections.OrderedDict(
p(Dict[kt, vt]))) # type: ignore
register_type(
collections.Counter,
lambda p, t=Any: collections.Counter(p(Dict[t, int]))) # type: ignore
# TODO: MappingView is missing
register_type(
collections.abc.ItemsView,
lambda p, kt=Any, vt=Any: p(Set[Tuple[kt, vt]])) # type: ignore
register_type(collections.abc.KeysView,
lambda p, t=Any: p(Set[t])) # type: ignore
register_type(collections.abc.ValuesView,
lambda p, t=Any: p(List[t])) # type: ignore
register_type(collections.abc.Container, lambda p, t=Any: p(Tuple[t, ...]))
register_type(collections.abc.Collection,
lambda p, t=Any: p(Tuple[t, ...]))
register_type(collections.deque,
lambda p, t=Any: ListBasedDeque(p(List[t]))) # type: ignore
register_type(collections.abc.Iterable, lambda p, t=Any: p(Tuple[t, ...]))
register_type(collections.abc.Iterator,
lambda p, t=Any: iter(p(Iterable[t]))) # type: ignore
register_type(collections.abc.MutableSequence,
lambda p, t=Any: p(List[t])) # type: ignore
register_type(collections.abc.Reversible,
lambda p, t=Any: p(Tuple[t, ...]))
register_type(collections.abc.Sequence, lambda p, t=Any: p(Tuple[t, ...]))
register_type(collections.abc.Sized, lambda p, t=Any: p(Tuple[t, ...]))
register_type(collections.abc.MutableSet,
lambda p, t=Any: p(Set[t])) # type: ignore
register_type(collections.abc.ByteString, make_byte_string)
register_type(collections.abc.Hashable, lambda p: p(int))
def make_registrations():
# WARNING: This is destructive for the datetime module.
# It disables the C implementation for the entire interpreter.
sys.modules['_datetime'] = None # type: ignore
importlib.reload(datetime)
# Default pickling will realize the symbolic args; avoid this:
datetime.date.__deepcopy__ = lambda s, _memo: datetime.date(
s.year, s.month, s.day)
datetime.time.__deepcopy__ = lambda s, _memo: datetime.time(
s.hour, s.minute, s.second, s.microsecond, s.tzinfo)
datetime.datetime.__deepcopy__ = lambda s, _memo: datetime.datetime(
s.year, s.month, s.day, s.hour, s.minute, s.second, s.microsecond, s.
tzinfo)
datetime.timedelta.__deepcopy__ = lambda d, _memo: _timedelta_skip_construct(
d.days, d.seconds, d.microseconds)
# Mokey patch validation so that we can defer it.
orig_check_date_fields = datetime._check_date_fields
orig_check_time_fields = datetime._check_time_fields
datetime._check_date_fields = lambda y, m, d: (y, m, d)
datetime._check_time_fields = lambda h, m, s, u, f: (h, m, s, u, f)
# TODO: `timezone` never makes a tzinfo with DST, so this is incomplete.
# A complete solution would require generating a symbolc dst() member function.
register_type(datetime.tzinfo, lambda p: p(datetime.timezone))
_min_tz_offset, _max_tz_offset = -datetime.timedelta(
hours=24), datetime.timedelta(hours=24)
def make_timezone(p: Any) -> datetime.timezone:
if p.space.smt_fork():
delta = p(datetime.timedelta)
if _min_tz_offset < delta < _max_tz_offset:
return datetime.timezone(delta, p(str))
else:
raise IgnoreAttempt('Invalid timezone offset')
else:
return datetime.timezone.utc
register_type(datetime.timezone, make_timezone)
def make_date(p: Any) -> datetime.date:
year, month, day = p(int), p(int), p(int)
try:
p.space.defer_assumption(
'Invalid date', lambda:
(not _raises_value_error(orig_check_date_fields,
(year, month, day))))
return datetime.date(year, month, day)
except ValueError:
raise IgnoreAttempt('Invalid date')
register_type(datetime.date, make_date)
def make_time(p: Any) -> datetime.time:
hour, minute, sec, usec = p(int), p(int), p(int), p(int)
tzinfo = p(datetime.timezone) if p.space.smt_fork() else None
try:
p.space.defer_assumption(
'Invalid datetime', lambda:
(not _raises_value_error(orig_check_time_fields,
(hour, minute, sec, usec, 0))))
return datetime.time(hour, minute, sec, usec, tzinfo)
except ValueError:
raise IgnoreAttempt('Invalid datetime')
register_type(datetime.time, make_time)
def make_datetime(p: Any) -> datetime.datetime:
year, month, day, hour, minute, sec, usec = p(int), p(int), p(int), p(
int), p(int), p(int), p(int)
tzinfo = p(datetime.tzinfo) if p.space.smt_fork() else None
try:
p.space.defer_assumption(
'Invalid datetime', lambda:
(not _raises_value_error(orig_check_date_fields,
(year, month, day)) and
not _raises_value_error(orig_check_time_fields,
(hour, minute, sec, usec, 0))))
return datetime.datetime(year, month, day, hour, minute, sec, usec,
tzinfo)
except ValueError:
raise IgnoreAttempt('Invalid datetime')
register_type(datetime.datetime, make_datetime)
def make_timedelta(p: Callable) -> datetime.timedelta:
microseconds, seconds, days = p(int), p(int), p(int)
# the normalized ranges, per the docs:
if not (0 <= microseconds < 1000000 and 0 <= seconds < 3600 * 24
and -999999999 <= days <= 999999999):
raise IgnoreAttempt('Invalid timedelta')
try:
return _timedelta_skip_construct(days, seconds, microseconds)
except OverflowError:
raise IgnoreAttempt('Invalid timedelta')
register_type(datetime.timedelta, make_timedelta)
