# coding=utf-8
#
# This file is part of Hypothesis, which may be found at
# https://github.com/HypothesisWorks/hypothesis-python
#
# Most of this work is copyright (C) 2013-2018 David R. MacIver
# (david@drmaciver.com), but it contains contributions by others. See
# CONTRIBUTING.rst for a full list of people who may hold copyright, and
# consult the git log if you need to determine who owns an individual
# contribution.
#
# This Source Code Form is subject to the terms of the Mozilla Public License,
# v. 2.0. If a copy of the MPL was not distributed with this file, You can
# obtain one at http://mozilla.org/MPL/2.0/.
#
# END HEADER

"""This module provides the core primitives of Hypothesis, such as given."""


from __future__ import division, print_function, absolute_import

import os
import ast
import zlib
import base64
import random as rnd_module
import inspect
import warnings
import traceback
import contextlib
from random import Random
from unittest import TestCase

import attr

import hypothesis.strategies as st
from hypothesis.errors import Flaky, Timeout, NoSuchExample, \
    Unsatisfiable, DidNotReproduce, InvalidArgument, DeadlineExceeded, \
    MultipleFailures, FailedHealthCheck, HypothesisWarning, \
    UnsatisfiedAssumption, HypothesisDeprecationWarning
from hypothesis.control import BuildContext
from hypothesis.version import __version__
from hypothesis._settings import Phase, Verbosity, HealthCheck, \
    PrintSettings
from hypothesis._settings import settings as Settings
from hypothesis._settings import local_settings, note_deprecation
from hypothesis.executors import new_style_executor
from hypothesis.reporting import report, verbose_report, current_verbosity
from hypothesis.statistics import note_engine_for_statistics
from hypothesis.internal.compat import PY2, ceil, hbytes, qualname, \
    binary_type, str_to_bytes, benchmark_time, get_type_hints, \
    getfullargspec, int_from_bytes, bad_django_TestCase
from hypothesis.internal.entropy import deterministic_PRNG
from hypothesis.utils.conventions import infer, not_set
from hypothesis.internal.escalation import get_trimmed_traceback, \
    escalate_hypothesis_internal_error
from hypothesis.internal.reflection import is_mock, proxies, nicerepr, \
    arg_string, impersonate, function_digest, fully_qualified_name, \
    define_function_signature, convert_positional_arguments, \
    get_pretty_function_description
from hypothesis.internal.healthcheck import fail_health_check
from hypothesis.internal.conjecture.data import StopTest, ConjectureData
from hypothesis.searchstrategy.strategies import SearchStrategy
from hypothesis.internal.conjecture.engine import ExitReason, \
    ConjectureRunner, sort_key
from hypothesis.searchstrategy.collections import TupleStrategy

if False:
    from typing import (  # noqa
        Any, Dict, Callable, Hashable, Optional, Union, TypeVar,
    )
    from hypothesis.utils.conventions import InferType  # noqa

    TestFunc = TypeVar('TestFunc', bound=Callable)


running_under_pytest = False
global_force_seed = None


def new_random():
    return rnd_module.Random(rnd_module.getrandbits(128))


@attr.s()
class Example(object):
    args = attr.ib()
    kwargs = attr.ib()


def example(*args, **kwargs):
    # type: (*Any, **Any) -> Callable[[TestFunc], TestFunc]
    """A decorator which ensures a specific example is always tested."""
    if args and kwargs:
        raise InvalidArgument(
            'Cannot mix positional and keyword arguments for examples'
        )
    if not (args or kwargs):
        raise InvalidArgument(
            'An example must provide at least one argument'
        )

    def accept(test):
        if not hasattr(test, 'hypothesis_explicit_examples'):
            test.hypothesis_explicit_examples = []
        test.hypothesis_explicit_examples.append(Example(tuple(args), kwargs))
        return test
    return accept


def seed(seed):
    # type: (Hashable) -> Callable[[TestFunc], TestFunc]
    """seed: Start the test execution from a specific seed.

    May be any hashable object. No exact meaning for seed is provided
    other than that for a fixed seed value Hypothesis will try the same
    actions (insofar as it can given external sources of non-
    determinism. e.g. timing and hash randomization).

    Overrides the derandomize setting, which is designed to enable
    deterministic builds rather than reproducing observed failures.

    """
    def accept(test):
        test._hypothesis_internal_use_seed = seed
        return test
    return accept


def reproduce_failure(version, blob):
    """Run the example that corresponds to this data blob in order to reproduce
    a failure.

    A test with this decorator *always* runs only one example and always fails.
    If the provided example does not cause a failure, or is in some way invalid
    for this test, then this will fail with a DidNotReproduce error.

    This decorator is not intended to be a permanent addition to your test
    suite. It's simply some code you can add to ease reproduction of a problem
    in the event that you don't have access to the test database. Because of
    this, *no* compatibility guarantees are made between different versions of
    Hypothesis - its API may change arbitrarily from version to version.
    """
    def accept(test):
        test._hypothesis_internal_use_reproduce_failure = (version, blob)
        return test
    return accept


def encode_failure(buffer):
    # This needs to be a real bytes() instance, so we use binary_type()
    # instead of hbytes() here.
    buffer = binary_type(buffer)
    compressed = zlib.compress(buffer)
    if len(compressed) < len(buffer):
        buffer = b'\1' + compressed
    else:
        buffer = b'\0' + buffer
    return base64.b64encode(buffer)


def decode_failure(blob):
    try:
        buffer = base64.b64decode(blob)
    except Exception:
        raise InvalidArgument('Invalid base64 encoded string: %r' % (blob,))
    prefix = buffer[:1]
    if prefix == b'\0':
        return buffer[1:]
    elif prefix == b'\1':
        try:
            return zlib.decompress(buffer[1:])
        except zlib.error:
            raise InvalidArgument(
                'Invalid zlib compression for blob %r' % (blob,)
            )
    else:
        raise InvalidArgument(
            'Could not decode blob %r: Invalid start byte %r' % (
                blob, prefix
            ))


class WithRunner(SearchStrategy):

    def __init__(self, base, runner):
        assert runner is not None
        self.base = base
        self.runner = runner

    def do_draw(self, data):
        data.hypothesis_runner = self.runner
        return self.base.do_draw(data)


def is_invalid_test(
    name, original_argspec, generator_arguments, generator_kwargs
):
    def invalid(message):
        def wrapped_test(*arguments, **kwargs):
            raise InvalidArgument(message)
        return wrapped_test

    if not (generator_arguments or generator_kwargs):
        return invalid(
            'given must be called with at least one argument')

    if generator_arguments and any([original_argspec.varargs,
                                    original_argspec.varkw,
                                    original_argspec.kwonlyargs]):
        return invalid(
            'positional arguments to @given are not supported with varargs, '
            'varkeywords, or keyword-only arguments'
        )

    if len(generator_arguments) > len(original_argspec.args):
        return invalid((
            'Too many positional arguments for %s() (got %d but'
            ' expected at most %d') % (
                name, len(generator_arguments),
                len(original_argspec.args)))

    if infer in generator_arguments:
        return invalid('infer was passed as a positional argument to @given, '
                       'but may only be passed as a keyword argument')

    if generator_arguments and generator_kwargs:
        return invalid(
            'cannot mix positional and keyword arguments to @given'
        )
    extra_kwargs = [
        k for k in generator_kwargs
        if k not in original_argspec.args + original_argspec.kwonlyargs
    ]
    if extra_kwargs and not original_argspec.varkw:
        return invalid(
            '%s() got an unexpected keyword argument %r' % (
                name,
                extra_kwargs[0]
            ))
    for a in original_argspec.args:
        if isinstance(a, list):  # pragma: no cover
            return invalid((
                'Cannot decorate function %s() because it has '
                'destructuring arguments') % (
                    name,
            ))
    if original_argspec.defaults or original_argspec.kwonlydefaults:
        return invalid('Cannot apply @given to a function with defaults.')
    missing = [repr(kw) for kw in original_argspec.kwonlyargs
               if kw not in generator_kwargs]
    if missing:
        raise InvalidArgument('Missing required kwarg{}: {}'.format(
            's' if len(missing) > 1 else '', ', '.join(missing)))


def execute_explicit_examples(
    test_runner, test, wrapped_test, settings, arguments, kwargs
):
    original_argspec = getfullargspec(test)

    for example in reversed(getattr(
        wrapped_test, 'hypothesis_explicit_examples', ()
    )):
        example_kwargs = dict(original_argspec.kwonlydefaults or {})
        if example.args:
            if len(example.args) > len(original_argspec.args):
                raise InvalidArgument(
                    'example has too many arguments for test. '
                    'Expected at most %d but got %d' % (
                        len(original_argspec.args), len(example.args)))
            example_kwargs.update(dict(zip(
                original_argspec.args[-len(example.args):],
                example.args
            )))
        else:
            example_kwargs.update(example.kwargs)
        if Phase.explicit not in settings.phases:
            continue
        example_kwargs.update(kwargs)
        # Note: Test may mutate arguments and we can't rerun explicit
        # examples, so we have to calculate the failure message at this
        # point rather than than later.
        example_string = '%s(%s)' % (
            test.__name__, arg_string(test, arguments, example_kwargs)
        )
        with local_settings(settings):
            try:
                with BuildContext(None) as b:
                    verbose_report('Trying example: ' + example_string)
                    test_runner(
                        None, lambda data: test(*arguments, **example_kwargs)
                    )
            except BaseException:
                report('Falsifying example: ' + example_string)
                for n in b.notes:
                    report(n)
                raise


def get_random_for_wrapped_test(test, wrapped_test):
    settings = wrapped_test._hypothesis_internal_use_settings
    wrapped_test._hypothesis_internal_use_generated_seed = None

    if wrapped_test._hypothesis_internal_use_seed is not None:
        return Random(
            wrapped_test._hypothesis_internal_use_seed)
    elif settings.derandomize:
        return Random(int_from_bytes(function_digest(test)))
    elif global_force_seed is not None:
        return Random(global_force_seed)
    else:
        seed = rnd_module.getrandbits(128)
        wrapped_test._hypothesis_internal_use_generated_seed = seed
        return Random(seed)


def process_arguments_to_given(
    wrapped_test, arguments, kwargs, generator_arguments, generator_kwargs,
    argspec, test, settings
):
    selfy = None
    arguments, kwargs = convert_positional_arguments(
        wrapped_test, arguments, kwargs)

    # If the test function is a method of some kind, the bound object
    # will be the first named argument if there are any, otherwise the
    # first vararg (if any).
    if argspec.args:
        selfy = kwargs.get(argspec.args[0])
    elif arguments:
        selfy = arguments[0]

    # Ensure that we don't mistake mocks for self here.
    # This can cause the mock to be used as the test runner.
    if is_mock(selfy):
        selfy = None

    test_runner = new_style_executor(selfy)

    arguments = tuple(arguments)

    # We use TupleStrategy over tuples() here to avoid polluting
    # st.STRATEGY_CACHE with references (see #493), and because this is
    # trivial anyway if the fixed_dictionaries strategy is cacheable.
    search_strategy = TupleStrategy((
        st.just(arguments),
        st.fixed_dictionaries(generator_kwargs).map(
            lambda args: dict(args, **kwargs)
        )
    ))

    if selfy is not None:
        search_strategy = WithRunner(search_strategy, selfy)

    search_strategy.validate()

    return arguments, kwargs, test_runner, search_strategy


def skip_exceptions_to_reraise():
    """Return a tuple of exceptions meaning 'skip this test', to re-raise.

    This is intended to cover most common test runners; if you would
    like another to be added please open an issue or pull request.
    """
    import unittest
    # This is a set because nose may simply re-export unittest.SkipTest
    exceptions = set([unittest.SkipTest])

    try:  # pragma: no cover
        from unittest2 import SkipTest
        exceptions.add(SkipTest)
    except ImportError:
        pass

    try:  # pragma: no cover
        from pytest.runner import Skipped
        exceptions.add(Skipped)
    except ImportError:
        pass

    try:  # pragma: no cover
        from nose import SkipTest as NoseSkipTest
        exceptions.add(NoseSkipTest)
    except ImportError:
        pass

    return tuple(sorted(exceptions, key=str))


EXCEPTIONS_TO_RERAISE = skip_exceptions_to_reraise()


def failure_exceptions_to_catch():
    """Return a tuple of exceptions meaning 'this test has failed', to catch.

    This is intended to cover most common test runners; if you would
    like another to be added please open an issue or pull request.
    """
    exceptions = [Exception]
    try:  # pragma: no cover
        from _pytest.outcomes import Failed
        exceptions.append(Failed)
    except ImportError:
        pass
    return tuple(exceptions)


EXCEPTIONS_TO_FAIL = failure_exceptions_to_catch()


def new_given_argspec(original_argspec, generator_kwargs):
    """Make an updated argspec for the wrapped test."""
    new_args = [a for a in original_argspec.args if a not in generator_kwargs]
    new_kwonlyargs = [a for a in original_argspec.kwonlyargs
                      if a not in generator_kwargs]
    annots = {k: v for k, v in original_argspec.annotations.items()
              if k in new_args + new_kwonlyargs}
    annots['return'] = None
    return original_argspec._replace(
        args=new_args, kwonlyargs=new_kwonlyargs, annotations=annots)


ROOT = os.path.dirname(__file__)

STDLIB = os.path.dirname(os.__file__)


class StateForActualGivenExecution(object):

    def __init__(
        self, test_runner, search_strategy, test, settings, random, had_seed
    ):
        self.test_runner = test_runner
        self.search_strategy = search_strategy
        self.settings = settings
        self.last_exception = None
        self.falsifying_examples = ()
        self.__was_flaky = False
        self.random = random
        self.__warned_deadline = False
        self.__test_runtime = None
        self.__had_seed = had_seed

        self.test = test

        self.files_to_propagate = set()
        self.failed_normally = False

        self.used_examples_from_database = False

    def execute(
        self, data,
        print_example=False,
        is_final=False,
        expected_failure=None, collect=False,
    ):
        text_repr = [None]
        if self.settings.deadline is None:
            test = self.test
        else:
            @proxies(self.test)
            def test(*args, **kwargs):
                self.__test_runtime = None
                initial_draws = len(data.draw_times)
                start = benchmark_time()
                result = self.test(*args, **kwargs)
                finish = benchmark_time()
                internal_draw_time = sum(data.draw_times[initial_draws:])
                runtime = (finish - start - internal_draw_time) * 1000
                self.__test_runtime = runtime
                if self.settings.deadline is not_set:
                    if (
                        not self.__warned_deadline and
                        runtime >= 200
                    ):
                        self.__warned_deadline = True
                        note_deprecation((
                            'Test: %s took %.2fms to run. In future the '
                            'default deadline setting will be 200ms, which '
                            'will make this an error. You can set deadline to '
                            'an explicit value of e.g. %d to turn tests '
                            'slower than this into an error, or you can set '
                            'it to None to disable this check entirely.') % (
                                self.test.__name__, runtime,
                                ceil(runtime / 100) * 100,
                        ))
                else:
                    current_deadline = self.settings.deadline
                    if not is_final:
                        current_deadline *= 1.25
                    if runtime >= current_deadline:
                        raise DeadlineExceeded(runtime, self.settings.deadline)
                return result

        def run(data):
            if not hasattr(data, 'can_reproduce_example_from_repr'):
                data.can_reproduce_example_from_repr = True
            with local_settings(self.settings):
                with BuildContext(data, is_final=is_final):
                    with deterministic_PRNG():
                        args, kwargs = data.draw(self.search_strategy)
                    if expected_failure is not None:
                        text_repr[0] = arg_string(test, args, kwargs)

                    if print_example:
                        example = '%s(%s)' % (
                            test.__name__, arg_string(test, args, kwargs))
                        try:
                            ast.parse(example)
                        except SyntaxError:
                            data.can_reproduce_example_from_repr = False
                        report('Falsifying example: %s' % (example,))
                    elif current_verbosity() >= Verbosity.verbose:
                        report(
                            lambda: 'Trying example: %s(%s)' % (
                                test.__name__, arg_string(test, args, kwargs)))

                    with deterministic_PRNG():
                        return test(*args, **kwargs)

        result = self.test_runner(data, run)
        if expected_failure is not None:
            exception, traceback = expected_failure
            if (
                isinstance(
                    exception,
                    DeadlineExceeded
                ) and self.__test_runtime is not None
            ):
                report((
                    'Unreliable test timings! On an initial run, this '
                    'test took %.2fms, which exceeded the deadline of '
                    '%.2fms, but on a subsequent run it took %.2f ms, '
                    'which did not. If you expect this sort of '
                    'variability in your test timings, consider turning '
                    'deadlines off for this test by setting deadline=None.'
                ) % (
                    exception.runtime,
                    self.settings.deadline, self.__test_runtime
                ))
            else:
                report(
                    'Failed to reproduce exception. Expected: \n' +
                    traceback,
                )
            self.__flaky((
                'Hypothesis %s(%s) produces unreliable results: Falsified'
                ' on the first call but did not on a subsequent one'
            ) % (test.__name__, text_repr[0],))
        return result

    def evaluate_test_data(self, data):
        try:
            result = self.execute(data)
            if result is not None:
                fail_health_check(self.settings, (
                    'Tests run under @given should return None, but '
                    '%s returned %r instead.'
                ) % (self.test.__name__, result), HealthCheck.return_value)
        except UnsatisfiedAssumption:
            data.mark_invalid()
        except (
            HypothesisDeprecationWarning, FailedHealthCheck,
            StopTest,
        ) + EXCEPTIONS_TO_RERAISE:
            raise
        except EXCEPTIONS_TO_FAIL as e:
            escalate_hypothesis_internal_error()
            tb = get_trimmed_traceback()
            data.__expected_traceback = ''.join(
                traceback.format_exception(type(e), e, tb)
            )
            data.__expected_exception = e
            verbose_report(data.__expected_traceback)

            origin = traceback.extract_tb(tb)[-1]
            filename = origin[0]
            lineno = origin[1]
            data.mark_interesting((type(e), filename, lineno))

    def run(self):
        # Tell pytest to omit the body of this function from tracebacks
        __tracebackhide__ = True
        if global_force_seed is None:
            database_key = str_to_bytes(fully_qualified_name(self.test))
        else:
            database_key = None
        self.start_time = benchmark_time()
        runner = ConjectureRunner(
            self.evaluate_test_data,
            settings=self.settings, random=self.random,
            database_key=database_key,
        )
        try:
            runner.run()
        finally:
            self.used_examples_from_database = \
                runner.used_examples_from_database
        note_engine_for_statistics(runner)
        run_time = benchmark_time() - self.start_time

        self.used_examples_from_database = runner.used_examples_from_database

        if runner.used_examples_from_database:
            if self.settings.derandomize:
                note_deprecation((
                    'In future derandomize will imply database=None, but your '
                    'test: %s is currently using examples from the database. '
                    'To get the future behaviour, update your settings to '
                    'include database=None.') % (self.test.__name__, )
                )
            if self.__had_seed:
                note_deprecation((
                    'In future use of @seed will imply database=None in your '
                    'settings, but your test: %s is currently using examples '
                    'from the database. To get the future behaviour, update '
                    'your settings for this test to include database=None.')
                    % (self.test.__name__,)
                )

        timed_out = runner.exit_reason == ExitReason.timeout
        if runner.call_count == 0:
            return
        if runner.interesting_examples:
            self.falsifying_examples = sorted(
                [d for d in runner.interesting_examples.values()],
                key=lambda d: sort_key(d.buffer), reverse=True
            )
        else:
            if runner.valid_examples == 0:
                if timed_out:
                    raise Timeout((
                        'Ran out of time before finding a satisfying '
                        'example for %s. Only found %d examples in %.2fs.'
                    ) % (
                        get_pretty_function_description(self.test),
                        runner.valid_examples, run_time
                    ))
                else:
                    raise Unsatisfiable(
                        'Unable to satisfy assumptions of hypothesis %s.' %
                        (get_pretty_function_description(self.test),)
                    )

        if not self.falsifying_examples:
            return

        self.failed_normally = True

        flaky = 0

        for falsifying_example in self.falsifying_examples:
            ran_example = ConjectureData.for_buffer(falsifying_example.buffer)
            self.__was_flaky = False
            assert falsifying_example.__expected_exception is not None
            try:
                self.execute(
                    ran_example,
                    print_example=True, is_final=True,
                    expected_failure=(
                        falsifying_example.__expected_exception,
                        falsifying_example.__expected_traceback,
                    )
                )
            except (UnsatisfiedAssumption, StopTest):
                report(traceback.format_exc())
                self.__flaky(
                    'Unreliable assumption: An example which satisfied '
                    'assumptions on the first run now fails it.'
                )
            except BaseException as e:
                if len(self.falsifying_examples) <= 1:
                    raise
                tb = get_trimmed_traceback()
                report(''.join(traceback.format_exception(type(e), e, tb)))
            finally:  # pragma: no cover
                # This section is in fact entirely covered by the tests in
                # test_reproduce_failure, but it seems to trigger a lovely set
                # of coverage bugs: The branches show up as uncovered (despite
                # definitely being covered - you can add an assert False else
                # branch to verify this and see it fail - and additionally the
                # second branch still complains about lack of coverage even if
                # you add a pragma: no cover to it!
                # See https://bitbucket.org/ned/coveragepy/issues/623/
                if self.settings.print_blob is not PrintSettings.NEVER:
                    failure_blob = encode_failure(falsifying_example.buffer)
                    # Have to use the example we actually ran, not the original
                    # falsifying example! Otherwise we won't catch problems
                    # where the repr of the generated example doesn't parse.
                    can_use_repr = ran_example.can_reproduce_example_from_repr
                    if (
                        self.settings.print_blob is PrintSettings.ALWAYS or (
                            self.settings.print_blob is PrintSettings.INFER and
                            self.settings.verbosity >= Verbosity.normal and
                            not can_use_repr and
                            len(failure_blob) < 200
                        )
                    ):
                        report((
                            '\n'
                            'You can reproduce this example by temporarily '
                            'adding @reproduce_failure(%r, %r) as a decorator '
                            'on your test case') % (
                                __version__, failure_blob,))
            if self.__was_flaky:
                flaky += 1

        # If we only have one example then we should have raised an error or
        # flaky prior to this point.
        assert len(self.falsifying_examples) > 1

        if flaky > 0:
            raise Flaky((
                'Hypothesis found %d distinct failures, but %d of them '
                'exhibited some sort of flaky behaviour.') % (
                    len(self.falsifying_examples), flaky))
        else:
            raise MultipleFailures((
                'Hypothesis found %d distinct failures.') % (
                    len(self.falsifying_examples,)))

    def __flaky(self, message):
        if len(self.falsifying_examples) <= 1:
            raise Flaky(message)
        else:
            self.__was_flaky = True
            report('Flaky example! ' + message)


@contextlib.contextmanager
def fake_subTest(self, msg=None, **__):
    """Monkeypatch for `unittest.TestCase.subTest` during `@given`.

    If we don't patch this out, each failing example is reported as a
    seperate failing test by the unittest test runner, which is
    obviously incorrect. We therefore replace it for the duration with
    this version.
    """
    warnings.warn(
        'subTest per-example reporting interacts badly with Hypothesis '
        'trying hundreds of examples, so we disable it for the duration of '
        'any test that uses `@given`.', HypothesisWarning, stacklevel=2
    )
    yield


@attr.s()
class HypothesisHandle(object):
    """This object is provided as the .hypothesis attribute on @given tests.

    Downstream users can reassign its attributes to insert custom logic into
    the execution of each case, for example by converting an async into a
    sync function.

    This must be an attribute of an attribute, because reassignment of a
    first-level attribute would not be visible to Hypothesis if the function
    had been decorated before the assignment.

    See https://github.com/HypothesisWorks/hypothesis/issues/1257 for more
    information.
    """

    inner_test = attr.ib()


def given(
    *given_arguments,  # type: Union[SearchStrategy, InferType]
    **given_kwargs  # type: Union[SearchStrategy, InferType]
):
    # type: (...) -> Callable[[Callable[..., None]], Callable[..., None]]
    """A decorator for turning a test function that accepts arguments into a
    randomized test.

    This is the main entry point to Hypothesis.
    """
    def run_test_with_generator(test):
        if hasattr(test, '_hypothesis_internal_test_function_without_warning'):
            # Pull out the original test function to avoid the warning we
            # stuck in about using @settings without @given.
            test = test._hypothesis_internal_test_function_without_warning
        if inspect.isclass(test):
            # Provide a meaningful error to users, instead of exceptions from
            # internals that assume we're dealing with a function.
            raise InvalidArgument('@given cannot be applied to a class.')
        generator_arguments = tuple(given_arguments)
        generator_kwargs = dict(given_kwargs)

        original_argspec = getfullargspec(test)

        check_invalid = is_invalid_test(
            test.__name__, original_argspec,
            generator_arguments, generator_kwargs)

        if check_invalid is not None:
            return check_invalid

        for name, strategy in zip(reversed(original_argspec.args),
                                  reversed(generator_arguments)):
            generator_kwargs[name] = strategy

        argspec = new_given_argspec(original_argspec, generator_kwargs)

        @impersonate(test)
        @define_function_signature(
            test.__name__, test.__doc__, argspec
        )
        def wrapped_test(*arguments, **kwargs):
            # Tell pytest to omit the body of this function from tracebacks
            __tracebackhide__ = True

            test = wrapped_test.hypothesis.inner_test

            if getattr(test, 'is_hypothesis_test', False):
                note_deprecation((
                    'You have applied @given to test: %s more than once. In '
                    'future this will be an error. Applying @given twice '
                    'wraps the test twice, which can be extremely slow. A '
                    'similar effect can be gained by combining the arguments '
                    'of the two calls to given. For example, instead of '
                    '@given(booleans()) @given(integers()), you could write '
                    '@given(booleans(), integers())') % (test.__name__, )
                )

            settings = wrapped_test._hypothesis_internal_use_settings

            random = get_random_for_wrapped_test(test, wrapped_test)

            if infer in generator_kwargs.values():
                hints = get_type_hints(test)
            for name in [name for name, value in generator_kwargs.items()
                         if value is infer]:
                if name not in hints:
                    raise InvalidArgument(
                        'passed %s=infer for %s, but %s has no type annotation'
                        % (name, test.__name__, name))
                generator_kwargs[name] = st.from_type(hints[name])

            processed_args = process_arguments_to_given(
                wrapped_test, arguments, kwargs, generator_arguments,
                generator_kwargs, argspec, test, settings
            )
            arguments, kwargs, test_runner, search_strategy = processed_args

            runner = getattr(search_strategy, 'runner', None)
            if isinstance(runner, TestCase) and test.__name__ in dir(TestCase):
                msg = ('You have applied @given to the method %s, which is '
                       'used by the unittest runner but is not itself a test.'
                       '  This is not useful in any way.' % test.__name__)
                fail_health_check(settings, msg, HealthCheck.not_a_test_method)
            if bad_django_TestCase(runner):  # pragma: no cover
                # Covered by the Django tests, but not the pytest coverage task
                raise InvalidArgument(
                    'You have applied @given to a method on %s, but this '
                    'class does not inherit from the supported versions in '
                    '`hypothesis.extra.django`.  Use the Hypothesis variants '
                    'to ensure that each example is run in a separate '
                    'database transaction.' % qualname(type(runner))
                )

            state = StateForActualGivenExecution(
                test_runner, search_strategy, test, settings, random,
                had_seed=wrapped_test._hypothesis_internal_use_seed
            )

            reproduce_failure = \
                wrapped_test._hypothesis_internal_use_reproduce_failure

            if reproduce_failure is not None:
                expected_version, failure = reproduce_failure
                if expected_version != __version__:
                    raise InvalidArgument((
                        'Attempting to reproduce a failure from a different '
                        'version of Hypothesis. This failure is from %s, but '
                        'you are currently running %r. Please change your '
                        'Hypothesis version to a matching one.'
                    ) % (expected_version, __version__))
                try:
                    state.execute(ConjectureData.for_buffer(
                        decode_failure(failure)),
                        print_example=True, is_final=True,
                    )
                    raise DidNotReproduce(
                        'Expected the test to raise an error, but it '
                        'completed successfully.'
                    )
                except StopTest:
                    raise DidNotReproduce(
                        'The shape of the test data has changed in some way '
                        'from where this blob was defined. Are you sure '
                        "you're running the same test?"
                    )
                except UnsatisfiedAssumption:
                    raise DidNotReproduce(
                        'The test data failed to satisfy an assumption in the '
                        'test. Have you added it since this blob was '
                        'generated?'
                    )

            execute_explicit_examples(
                test_runner, test, wrapped_test, settings, arguments, kwargs
            )

            if settings.max_examples <= 0:
                return

            if not (
                Phase.reuse in settings.phases or
                Phase.generate in settings.phases
            ):
                return

            try:
                if isinstance(runner, TestCase) and hasattr(runner, 'subTest'):
                    subTest = runner.subTest
                    try:
                        setattr(runner, 'subTest', fake_subTest)
                        state.run()
                    finally:
                        setattr(runner, 'subTest', subTest)
                else:
                    state.run()
            except BaseException as e:
                generated_seed = \
                    wrapped_test._hypothesis_internal_use_generated_seed
                with local_settings(settings):
                    if not (state.failed_normally or generated_seed is None):
                        if running_under_pytest:
                            report(
                                'You can add @seed(%(seed)d) to this test or '
                                'run pytest with --hypothesis-seed=%(seed)d '
                                'to reproduce this failure.' % {
                                    'seed': generated_seed})
                        else:
                            report(
                                'You can add @seed(%d) to this test to '
                                'reproduce this failure.' % (generated_seed,))
                    # The dance here is to avoid showing users long tracebacks
                    # full of Hypothesis internals they don't care about.
                    # We have to do this inline, to avoid adding another
                    # internal stack frame just when we've removed the rest.
                    if PY2:
                        # Python 2 doesn't have Exception.with_traceback(...);
                        # instead it has a three-argument form of the `raise`
                        # statement.  Unfortunately this is a SyntaxError on
                        # Python 3, and before Python 2.7.9 it was *also* a
                        # SyntaxError to use it in a nested function so we
                        # can't `exec` or `eval` our way out (BPO-21591).
                        # So unless we break some versions of Python 2, none
                        # of them get traceback elision.
                        raise
                    # On Python 3, we swap out the real traceback for our
                    # trimmed version.  Using a variable ensures that the line
                    # which will actually appear in trackbacks is as clear as
                    # possible - "raise the_error_hypothesis_found".
                    the_error_hypothesis_found = \
                        e.with_traceback(get_trimmed_traceback())
                    raise the_error_hypothesis_found

        for attrib in dir(test):
            if not (attrib.startswith('_') or hasattr(wrapped_test, attrib)):
                setattr(wrapped_test, attrib, getattr(test, attrib))
        wrapped_test.is_hypothesis_test = True
        if hasattr(test, '_hypothesis_internal_settings_applied'):
            # Used to check if @settings is applied twice.
            wrapped_test._hypothesis_internal_settings_applied = True
        wrapped_test._hypothesis_internal_use_seed = getattr(
            test, '_hypothesis_internal_use_seed', None
        )
        wrapped_test._hypothesis_internal_use_settings = getattr(
            test, '_hypothesis_internal_use_settings', None
        ) or Settings.default
        wrapped_test._hypothesis_internal_use_reproduce_failure = getattr(
            test, '_hypothesis_internal_use_reproduce_failure', None
        )
        wrapped_test.hypothesis = HypothesisHandle(test)
        return wrapped_test
    return run_test_with_generator


def find(
    specifier,  # type: SearchStrategy
    condition,  # type: Callable[[Any], bool]
    settings=None,  # type: Settings
    random=None,   # type: Any
    database_key=None,  # type: bytes
):
    # type: (...) -> Any
    """Returns the minimal example from the given strategy ``specifier`` that
    matches the predicate function ``condition``."""
    if settings is None:
        settings = Settings(max_examples=2000)
    settings = Settings(settings, suppress_health_check=HealthCheck.all())

    if database_key is None and settings.database is not None:
        database_key = function_digest(condition)

    if not isinstance(specifier, SearchStrategy):
        raise InvalidArgument(
            'Expected SearchStrategy but got %r of type %s' % (
                specifier, type(specifier).__name__
            ))
    specifier.validate()

    search = specifier

    random = random or new_random()
    successful_examples = [0]
    last_data = [None]
    last_repr = [None]

    def template_condition(data):
        with BuildContext(data):
            try:
                data.is_find = True
                with deterministic_PRNG():
                    result = data.draw(search)
                    data.note(result)
                    success = condition(result)
            except UnsatisfiedAssumption:
                data.mark_invalid()

        if success:
            successful_examples[0] += 1

        if settings.verbosity >= Verbosity.verbose:
            if not successful_examples[0]:
                report(
                    u'Tried non-satisfying example %s' % (nicerepr(result),))
            elif success:
                if successful_examples[0] == 1:
                    last_repr[0] = nicerepr(result)
                    report(u'Found satisfying example %s' % (last_repr[0],))
                    last_data[0] = data
                elif (
                    sort_key(hbytes(data.buffer)) <
                    sort_key(last_data[0].buffer)
                ) and nicerepr(result) != last_repr[0]:
                    last_repr[0] = nicerepr(result)
                    report(u'Shrunk example to %s' % (last_repr[0],))
                    last_data[0] = data
        if success and not data.frozen:
            data.mark_interesting()
    start = benchmark_time()
    runner = ConjectureRunner(
        template_condition, settings=settings, random=random,
        database_key=database_key,
    )
    runner.run()
    note_engine_for_statistics(runner)
    run_time = benchmark_time() - start
    if runner.interesting_examples:
        data = ConjectureData.for_buffer(
            list(runner.interesting_examples.values())[0].buffer)
        with BuildContext(data):
            with deterministic_PRNG():
                return data.draw(search)
    if runner.valid_examples == 0 and (
        runner.exit_reason != ExitReason.finished
    ):
        if settings.timeout > 0 and run_time > settings.timeout:
            raise Timeout((  # pragma: no cover
                'Ran out of time before finding enough valid examples for '
                '%s. Only %d valid examples found in %.2f seconds.'
            ) % (
                get_pretty_function_description(condition),
                runner.valid_examples, run_time))

        else:
            raise Unsatisfiable(
                'Unable to satisfy assumptions of %s.' %
                (get_pretty_function_description(condition),)
            )

    raise NoSuchExample(get_pretty_function_description(condition))
