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How to use pareto_optimise method in hypothesis

Best Python code snippet using hypothesis

engine.py

Source:engine.py

...674                break675            max_improvements *= 2676            if any_improvements:677                continue678            self.pareto_optimise()679            if prev_calls == self.call_count:680                break681    def pareto_optimise(self):682        if self.pareto_front is not None:683            ParetoOptimiser(self).run()684    def _run(self):685        self.reuse_existing_examples()686        self.generate_new_examples()687        # We normally run the targeting phase mixed in with the generate phase,688        # but if we've been asked to run it but not generation then we have to689        # run it explciitly on its own here.690        if Phase.generate not in self.settings.phases:691            self.optimise_targets()692        self.shrink_interesting_examples()693        self.exit_with(ExitReason.finished)694    def new_conjecture_data(self, prefix, max_length=BUFFER_SIZE, observer=None):695        return ConjectureData(...

test_pareto.py

Source:test_pareto.py

...148        settings=settings(max_examples=10000, database=InMemoryExampleDatabase()),149        database_key=b"stuff",150    )151    runner.cached_test_function([255] * 20 + [0])152    runner.pareto_optimise()153    assert len(runner.pareto_front) == 6154    for i, data in enumerate(runner.pareto_front):155        assert list(data.buffer) == [1] * i + [0]156def test_does_not_optimise_the_pareto_front_if_interesting():157    def test(data):158        n = data.draw_bits(8)159        data.target_observations[""] = n160        if n == 255:161            data.mark_interesting()162    runner = ConjectureRunner(163        test,164        settings=settings(max_examples=10000, database=InMemoryExampleDatabase()),165        database_key=b"stuff",166    )167    runner.cached_test_function([0])168    runner.pareto_optimise = None169    runner.optimise_targets()170    assert runner.interesting_examples171def test_stops_optimising_once_interesting():172    hi = 2 ** 16 - 1173    def test(data):174        n = data.draw_bits(16)175        data.target_observations[""] = n176        if n < hi:177            data.mark_interesting()178    runner = ConjectureRunner(179        test,180        settings=settings(max_examples=10000, database=InMemoryExampleDatabase()),181        database_key=b"stuff",182    )183    data = runner.cached_test_function([255] * 2)184    assert data.status == Status.VALID185    runner.pareto_optimise()186    assert runner.call_count <= 20...

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