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How to use try_shrinking_blocks method in hypothesis

Best Python code snippet using hypothesis

shrinker.py

Source:shrinker.py

...644            self.__all_changed_blocks = set()645            self.__last_checked_changed_at = new_target646        self.shrink_target = new_target647        self.__derived_values = {}648    def try_shrinking_blocks(self, blocks, b):649        """Attempts to replace each block in the blocks list with b. Returns650        True if it succeeded (which may include some additional modifications651        to shrink_target).652        In current usage it is expected that each of the blocks currently have653        the same value, although this is not essential. Note that b must be654        < the block at min(blocks) or this is not a valid shrink.655        This method will attempt to do some small amount of work to delete data656        that occurs after the end of the blocks. This is useful for cases where657        there is some size dependency on the value of a block.658        """659        initial_attempt = bytearray(self.shrink_target.buffer)660        for i, block in enumerate(blocks):661            if block >= len(self.blocks):662                blocks = blocks[:i]663                break664            u, v = self.blocks[block].bounds665            n = min(self.blocks[block].length, len(b))666            initial_attempt[v - n : v] = b[-n:]667        if not blocks:668            return False669        start = self.shrink_target.blocks[blocks[0]].start670        end = self.shrink_target.blocks[blocks[-1]].end671        initial_data = self.cached_test_function(initial_attempt)672        if initial_data is self.shrink_target:673            self.lower_common_block_offset()674            return True675        # If this produced something completely invalid we ditch it676        # here rather than trying to persevere.677        if initial_data.status < Status.VALID:678            return False679        # We've shrunk inside our group of blocks, so we have no way to680        # continue. (This only happens when shrinking more than one block at681        # a time).682        if len(initial_data.buffer) < v:683            return False684        lost_data = len(self.shrink_target.buffer) - len(initial_data.buffer)685        # If this did not in fact cause the data size to shrink we686        # bail here because it's not worth trying to delete stuff from687        # the remainder.688        if lost_data <= 0:689            return False690        # We now look for contiguous regions to delete that might help fix up691        # this failed shrink. We only look for contiguous regions of the right692        # lengths because doing anything more than that starts to get very693        # expensive. See minimize_individual_blocks for where we694        # try to be more aggressive.695        regions_to_delete = {(end, end + lost_data)}696        for j in (blocks[-1] + 1, blocks[-1] + 2):697            if j >= min(len(initial_data.blocks), len(self.blocks)):698                continue699            # We look for a block very shortly after the last one that has700            # lost some of its size, and try to delete from the beginning so701            # that it retains the same integer value. This is a bit of a hyper702            # specific trick designed to make our integers() strategy shrink703            # well.704            r1, s1 = self.shrink_target.blocks[j].bounds705            r2, s2 = initial_data.blocks[j].bounds706            lost = (s1 - r1) - (s2 - r2)707            # Apparently a coverage bug? An assert False in the body of this708            # will reliably fail, but it shows up as uncovered.709            if lost <= 0 or r1 != r2:  # pragma: no cover710                continue711            regions_to_delete.add((r1, r1 + lost))712        for ex in self.shrink_target.examples:713            if ex.start > start:714                continue715            if ex.end <= end:716                continue717            replacement = initial_data.examples[ex.index]718            in_original = [c for c in ex.children if c.start >= end]719            in_replaced = [c for c in replacement.children if c.start >= end]720            if len(in_replaced) >= len(in_original) or not in_replaced:721                continue722            # We've found an example where some of the children went missing723            # as a result of this change, and just replacing it with the data724            # it would have had and removing the spillover didn't work. This725            # means that some of its children towards the right must be726            # important, so we try to arrange it so that it retains its727            # rightmost children instead of its leftmost.728            regions_to_delete.add(729                (in_original[0].start, in_original[-len(in_replaced)].start)730            )731        for u, v in sorted(regions_to_delete, key=lambda x: x[1] - x[0], reverse=True):732            try_with_deleted = bytearray(initial_attempt)733            del try_with_deleted[u:v]734            if self.incorporate_new_buffer(try_with_deleted):735                return True736        return False737    def remove_discarded(self):738        """Try removing all bytes marked as discarded.739        This is primarily to deal with data that has been ignored while740        doing rejection sampling - e.g. as a result of an integer range, or a741        filtered strategy.742        Such data will also be handled by the adaptive_example_deletion pass,743        but that pass is necessarily more conservative and will try deleting744        each interval individually. The common case is that all data drawn and745        rejected can just be thrown away immediately in one block, so this pass746        will be much faster than trying each one individually when it works.747        returns False if there is discarded data and removing it does not work,748        otherwise returns True.749        """750        while self.shrink_target.has_discards:751            discarded = []752            for ex in self.shrink_target.examples:753                if (754                    ex.length > 0755                    and ex.discarded756                    and (not discarded or ex.start >= discarded[-1][-1])757                ):758                    discarded.append((ex.start, ex.end))759            # This can happen if we have discards but they are all of760            # zero length. This shouldn't happen very often so it's761            # faster to check for it here than at the point of example762            # generation.763            if not discarded:764                break765            attempt = bytearray(self.shrink_target.buffer)766            for u, v in reversed(discarded):767                del attempt[u:v]768            if not self.incorporate_new_buffer(attempt):769                return False770        return True771    @defines_shrink_pass()772    def adaptive_example_deletion(self, chooser):773        """Attempts to delete every example from the test case.774        That is, it is logically equivalent to trying ``self.buffer[:ex.start] +775        self.buffer[ex.end:]`` for every example ``ex``. The order in which776        examples are tried is randomized, and when deletion is successful it777        will attempt to adapt to delete more than one example at a time.778        """779        example = chooser.choose(self.examples)780        if not self.incorporate_new_buffer(781            self.buffer[: example.start] + self.buffer[example.end :]782        ):783            return784        # If we successfully deleted one example there may be a useful785        # deletable region around here.786        original = self.shrink_target787        endpoints = set()788        for ex in original.examples:789            if ex.depth <= example.depth:790                endpoints.add(ex.start)791                endpoints.add(ex.end)792        partition = sorted(endpoints)793        j = partition.index(example.start)794        def delete_region(a, b):795            assert a <= j <= b796            if a < 0 or b >= len(partition) - 1:797                return False798            return self.consider_new_buffer(799                original.buffer[: partition[a]] + original.buffer[partition[b] :]800            )801        to_right = find_integer(lambda n: delete_region(j, j + n))802        find_integer(lambda n: delete_region(j - n, j + to_right))803    def try_zero_example(self, ex):804        u = ex.start805        v = ex.end806        attempt = self.cached_test_function(807            self.buffer[:u] + bytes(v - u) + self.buffer[v:]808        )809        if attempt is Overrun:810            return False811        in_replacement = attempt.examples[ex.index]812        used = in_replacement.length813        if attempt is not self.shrink_target:814            if in_replacement.end < len(attempt.buffer) and used < ex.length:815                self.incorporate_new_buffer(816                    self.buffer[:u] + bytes(used) + self.buffer[v:]817                )818        return self.examples[ex.index].trivial819    @defines_shrink_pass()820    def zero_examples(self, chooser):821        """Attempt to replace each example with a minimal version of itself."""822        ex = chooser.choose(self.examples, lambda ex: not ex.trivial)823        # If the example is already trivial, assume there's nothing to do here.824        # We could attempt to use it as an adaptive replacement for other825        # similar examples, but that seems to be ineffective, resulting mostly826        # in redundant work rather than helping.827        if not self.try_zero_example(ex):828            return829        # If we zeroed the example we need to get the new one that replaced it.830        ex = self.examples[ex.index]831        original = self.shrink_target832        group = self.examples_by_label[ex.label]833        i = group.index(ex)834        replacement = self.buffer[ex.start : ex.end]835        # We first expand to cover the trivial region surrounding this group.836        # This avoids a situation where the adaptive phase "succeeds" a lot by837        # virtue of not doing anything and then goes into a galloping phase838        # where it does a bunch of useless work.839        def all_trivial(a, b):840            if a < 0 or b > len(group):841                return False842            return all(e.trivial for e in group[a:b])843        start, end = expand_region(all_trivial, i, i + 1)844        # If we've got multiple trivial examples of different lengths then845        # this isn't going to work as a replacement for all of them and so we846        # skip out early.847        if any(e.length != len(replacement) for e in group[start:end]):848            return849        def can_zero(a, b):850            if a < 0 or b > len(group):851                return False852            regions = []853            for e in group[a:b]:854                t = (e.start, e.end, replacement)855                if not regions or t[0] >= regions[-1][1]:856                    regions.append(t)857            return self.consider_new_buffer(replace_all(original.buffer, regions))858        expand_region(can_zero, start, end)859    @derived_value860    def blocks_by_non_zero_suffix(self):861        """Returns a list of blocks grouped by their non-zero suffix,862        as a list of (suffix, indices) pairs, skipping all groupings863        where there is only one index.864        This is only used for the arguments of minimize_duplicated_blocks.865        """866        duplicates = defaultdict(list)867        for block in self.blocks:868            duplicates[non_zero_suffix(self.buffer[block.start : block.end])].append(869                block.index870            )871        return duplicates872    @derived_value873    def duplicated_block_suffixes(self):874        return sorted(self.blocks_by_non_zero_suffix)875    @defines_shrink_pass()876    def minimize_duplicated_blocks(self, chooser):877        """Find blocks that have been duplicated in multiple places and attempt878        to minimize all of the duplicates simultaneously.879        This lets us handle cases where two values can't be shrunk880        independently of each other but can easily be shrunk together.881        For example if we had something like:882        ls = data.draw(lists(integers()))883        y = data.draw(integers())884        assert y not in ls885        Suppose we drew y = 3 and after shrinking we have ls = [3]. If we were886        to replace both 3s with 0, this would be a valid shrink, but if we were887        to replace either 3 with 0 on its own the test would start passing.888        It is also useful for when that duplication is accidental and the value889        of the blocks doesn't matter very much because it allows us to replace890        more values at once.891        """892        block = chooser.choose(self.duplicated_block_suffixes)893        targets = self.blocks_by_non_zero_suffix[block]894        if len(targets) <= 1:895            return896        Lexical.shrink(897            block,898            lambda b: self.try_shrinking_blocks(targets, b),899            random=self.random,900            full=False,901        )902    @defines_shrink_pass()903    def minimize_floats(self, chooser):904        """Some shrinks that we employ that only really make sense for our905        specific floating point encoding that are hard to discover from any906        sort of reasonable general principle. This allows us to make907        transformations like replacing a NaN with an Infinity or replacing908        a float with its nearest integers that we would otherwise not be909        able to due to them requiring very specific transformations of910        the bit sequence.911        We only apply these transformations to blocks that "look like" our912        standard float encodings because they are only really meaningful913        there. The logic for detecting this is reasonably precise, but914        it doesn't matter if it's wrong. These are always valid915        transformations to make, they just don't necessarily correspond to916        anything particularly meaningful for non-float values.917        """918        ex = chooser.choose(919            self.examples,920            lambda ex: (921                ex.label == DRAW_FLOAT_LABEL922                and len(ex.children) == 2923                and ex.children[0].length == 8924            ),925        )926        u = ex.children[0].start927        v = ex.children[0].end928        buf = self.shrink_target.buffer929        b = buf[u:v]930        f = lex_to_float(int_from_bytes(b))931        b2 = int_to_bytes(float_to_lex(f), 8)932        if b == b2 or self.consider_new_buffer(buf[:u] + b2 + buf[v:]):933            Float.shrink(934                f,935                lambda x: self.consider_new_buffer(936                    self.shrink_target.buffer[:u]937                    + int_to_bytes(float_to_lex(x), 8)938                    + self.shrink_target.buffer[v:]939                ),940                random=self.random,941            )942    @defines_shrink_pass()943    def minimize_individual_blocks(self, chooser):944        """Attempt to minimize each block in sequence.945        This is the pass that ensures that e.g. each integer we draw is a946        minimum value. So it's the part that guarantees that if we e.g. do947        x = data.draw(integers())948        assert x < 10949        then in our shrunk example, x = 10 rather than say 97.950        If we are unsuccessful at minimizing a block of interest we then951        check if that's because it's changing the size of the test case and,952        if so, we also make an attempt to delete parts of the test case to953        see if that fixes it.954        We handle most of the common cases in try_shrinking_blocks which is955        pretty good at clearing out large contiguous blocks of dead space,956        but it fails when there is data that has to stay in particular places957        in the list.958        """959        block = chooser.choose(self.blocks, lambda b: not b.trivial)960        initial = self.shrink_target961        u, v = block.bounds962        i = block.index963        Lexical.shrink(964            self.shrink_target.buffer[u:v],965            lambda b: self.try_shrinking_blocks((i,), b),966            random=self.random,967            full=False,968        )969        if self.shrink_target is not initial:970            return971        lowered = (972            self.buffer[: block.start]973            + int_to_bytes(974                int_from_bytes(self.buffer[block.start : block.end]) - 1, block.length975            )976            + self.buffer[block.end :]977        )978        attempt = self.cached_test_function(lowered)979        if (...

test_shrinker.py

Source:test_shrinker.py

...188    )189    monkeypatch.setattr(190        Shrinker,191        "shrink",192        lambda self: self.try_shrinking_blocks((0, 1, 5), bytes([2])),193    )194    @run_to_buffer195    def x(data):196        n1 = data.draw_bits(8)197        data.draw_bits(8)198        if n1 == 3:199            data.draw_bits(8)200        k = data.draw_bits(8)201        if k == 1:202            data.mark_interesting()203    assert list(x) == [2, 2, 1]204def test_dependent_block_pairs_is_up_to_shrinking_integers():205    # Unit test extracted from a failure in tests/nocover/test_integers.py206    distribution = Sampler([4.0, 8.0, 1.0, 1.0, 0.5])207    sizes = [8, 16, 32, 64, 128]208    @shrinking_from(b"\x03\x01\x00\x00\x00\x00\x00\x01\x00\x02\x01")209    def shrinker(data):210        size = sizes[distribution.sample(data)]211        result = data.draw_bits(size)212        sign = (-1) ** (result & 1)213        result = (result >> 1) * sign214        cap = data.draw_bits(8)215        if result >= 32768 and cap == 1:216            data.mark_interesting()217    shrinker.fixate_shrink_passes(["minimize_individual_blocks"])218    assert list(shrinker.shrink_target.buffer) == [1, 1, 0, 1, 0, 0, 1]219def test_finding_a_minimal_balanced_binary_tree():220    # Tests iteration while the shape of the thing being iterated over can221    # change. In particular the current example can go from trivial to non222    # trivial.223    def tree(data):224        # Returns height of a binary tree and whether it is height balanced.225        data.start_example("tree")226        n = data.draw_bits(1)227        if n == 0:228            result = (1, True)229        else:230            h1, b1 = tree(data)231            h2, b2 = tree(data)232            result = (1 + max(h1, h2), b1 and b2 and abs(h1 - h2) <= 1)233        data.stop_example("tree")234        return result235    # Starting from an unbalanced tree of depth six236    @shrinking_from([1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0])237    def shrinker(data):238        _, b = tree(data)239        if not b:240            data.mark_interesting()241    shrinker.shrink()242    assert list(shrinker.shrink_target.buffer) == [1, 0, 1, 0, 1, 0, 0]243def test_float_shrink_can_run_when_canonicalisation_does_not_work(monkeypatch):244    # This should be an error when called245    monkeypatch.setattr(Float, "shrink", None)246    base_buf = int_to_bytes(flt.base_float_to_lex(1000.0), 8) + bytes(1)247    @shrinking_from(base_buf)248    def shrinker(data):249        flt.draw_float(data)250        if bytes(data.buffer) == base_buf:251            data.mark_interesting()252    shrinker.fixate_shrink_passes(["minimize_floats"])253    assert shrinker.shrink_target.buffer == base_buf254def test_try_shrinking_blocks_out_of_bounds():255    @shrinking_from(bytes([1]))256    def shrinker(data):257        data.draw_bits(1)258        data.mark_interesting()259    assert not shrinker.try_shrinking_blocks((1,), bytes([1]))260def test_block_programs_are_adaptive():261    @shrinking_from(bytes(1000) + bytes([1]))262    def shrinker(data):263        while not data.draw_bits(1):264            pass265        data.mark_interesting()266    p = shrinker.add_new_pass(block_program("X"))267    shrinker.fixate_shrink_passes([p.name])268    assert len(shrinker.shrink_target.buffer) == 1269    assert shrinker.calls <= 60270def test_zero_examples_with_variable_min_size():271    @shrinking_from(bytes([255]) * 100)272    def shrinker(data):273        any_nonzero = False...

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