Source code for hypothesis.control

# This file is part of Hypothesis, which may be found at
# Most of this work is copyright (C) 2013-2020 David R. MacIver
# (, 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

import math
import traceback
from typing import Any

from hypothesis import Verbosity, settings
from hypothesis.errors import CleanupFailed, InvalidArgument, UnsatisfiedAssumption
from import ConjectureData
from hypothesis.internal.reflection import deprecated_posargs
from hypothesis.internal.validation import check_type
from hypothesis.reporting import report, verbose_report
from hypothesis.utils.dynamicvariables import DynamicVariable

def reject():
    raise UnsatisfiedAssumption()

[docs]def assume(condition: Any) -> bool: """Calling ``assume`` is like an :ref:`assert <python:assert>` that marks the example as bad, rather than failing the test. This allows you to specify properties that you *assume* will be true, and let Hypothesis try to avoid similar examples in future. """ if not condition: raise UnsatisfiedAssumption() return True
_current_build_context = DynamicVariable(None) def current_build_context(): context = _current_build_context.value if context is None: raise InvalidArgument("No build context registered") return context class BuildContext: def __init__(self, data, is_final=False, close_on_capture=True): assert isinstance(data, ConjectureData) = data self.tasks = [] self.is_final = is_final self.close_on_capture = close_on_capture self.close_on_del = False def __enter__(self): self.assign_variable = _current_build_context.with_value(self) self.assign_variable.__enter__() return self def __exit__(self, exc_type, exc_value, tb): self.assign_variable.__exit__(exc_type, exc_value, tb) if self.close() and exc_type is None: raise CleanupFailed() def close(self): any_failed = False for task in self.tasks: try: task() except BaseException: any_failed = True report(traceback.format_exc()) return any_failed def cleanup(teardown): """Register a function to be called when the current test has finished executing. Any exceptions thrown in teardown will be printed but not rethrown. Inside a test this isn't very interesting, because you can just use a finally block, but note that you can use this inside map, flatmap, etc. in order to e.g. insist that a value is closed at the end. """ context = _current_build_context.value if context is None: raise InvalidArgument("Cannot register cleanup outside of build context") context.tasks.append(teardown) def should_note(): context = _current_build_context.value if context is None: raise InvalidArgument("Cannot make notes outside of a test") return context.is_final or settings.default.verbosity >= Verbosity.verbose
[docs]def note(value: str) -> None: """Report this value in the final execution.""" if should_note(): report(value)
[docs]def event(value: str) -> None: """Record an event that occurred this test. Statistics on number of test runs with each event will be reported at the end if you run Hypothesis in statistics reporting mode. Events should be strings or convertible to them. """ context = _current_build_context.value if context is None: raise InvalidArgument("Cannot make record events outside of a test")
[docs]@deprecated_posargs def target(observation: float, *, label: str = "") -> None: """Calling this function with a ``float`` observation gives it feedback with which to guide our search for inputs that will cause an error, in addition to all the usual heuristics. Observations must always be finite. Hypothesis will try to maximize the observed value over several examples; almost any metric will work so long as it makes sense to increase it. For example, ``-abs(error)`` is a metric that increases as ``error`` approaches zero. Example metrics: - Number of elements in a collection, or tasks in a queue - Mean or maximum runtime of a task (or both, if you use ``label``) - Compression ratio for data (perhaps per-algorithm or per-level) - Number of steps taken by a state machine The optional ``label`` argument can be used to distinguish between and therefore separately optimise distinct observations, such as the mean and standard deviation of a dataset. It is an error to call ``target()`` with any label more than once per test case. .. note:: **The more examples you run, the better this technique works.** As a rule of thumb, the targeting effect is noticeable above :obj:`max_examples=1000 <hypothesis.settings.max_examples>`, and immediately obvious by around ten thousand examples *per label* used by your test. .. note:: ```` is considered experimental, and may be radically changed or even removed in a future version. If you find it useful, please let us know so we can share and build on that success! :ref:`statistics` include the best score seen for each label, which can help avoid `the threshold problem <>`__ when the minimal example shrinks right down to the threshold of failure (:issue:`2180`). """ check_type(float, observation, "observation") if not math.isfinite(observation): raise InvalidArgument("observation=%r must be a finite float." % observation) check_type(str, label, "label") context = _current_build_context.value if context is None: raise InvalidArgument("Calling target() outside of a test is invalid.") verbose_report("Saw target(observation=%r, label=%r)" % (observation, label)) if label in raise InvalidArgument( "Calling target(%r, label=%r) would overwrite target(%r, label=%r)" % (observation, label,[label], label) ) else:[label] = observation