Skip to main content

Level-up your Hypothesis tests with CrossHair.

Project description

hypothesis-crosshair

Downloads

Add the power of solver-based symbolic execution to your Hypothesis tests with CrossHair.

Just

pip install hypothesis-crosshair

and then add a backend="crosshair" setting, like so:

from hypothesis import given, settings, strategies as st

@settings(backend="crosshair")
@given(st.integers())
def test_needs_solver(x):
    assert x != 123456789

Docs hopefully coming soon. In the meantime, start a discussion or file an issue.

FAQ

Can I try using crosshair for ALL my hypothesis tests?

Yes! Create or edit your pytest conftest.py file to register a profile like the following:

from hypothesis import settings

settings.register_profile(
    "crosshair",
    backend="crosshair",
)

And then run pytest using the profile you've defined:

pytest . --hypothesis-profile=crosshair 

Changelog

Next Version

  • Nothing yet

0.0.24

  • Do not attempt to capture and retry hypothesis internal exceptions. (fixes #34)

0.0.23

0.0.22

  • Abort concrete executions with invalid draws. (fixes #29)
  • Adjust how the preventative measures in v0.0.21 work for recursive datastructures.

0.0.21

  • Avoid occasional unexpected errors when stopping a test run with Ctrl-C.
  • Prevent over-expansion when generating recursive datastructures. (fixes #27)

0.0.20

  • Avoid potential import warning when registering ourself with hypothesis.
  • Skip constraint checking when performing a concrete re-execution.

0.0.19

  • Limit the re-thow behavior in 0.0.17 to Unsatisfiable errors exclusively
  • Change default path timeout to 2.5 seconds
  • Prevent false positives by ensuring user exceptions are only exposed under concrete executions.

0.0.18

  • Ensure drawn floats respect hypothesis signed-zero semantics for min_value/max_value.

0.0.17

  • Do not interpret Unsatisfiable errors as user exceptions; just re-throw, so that hypothesis can act appropriately.
  • Report CrossHair path abortions to hypothesis as discard_test_case instead of verified. This lets Hypothesis report unsatisfiable strategies correctly when run under crosshair.

0.0.16

  • Integrate hypothesis's new BackCannotProceed exception, which will reduce the likelihood of FlakeyReplay errors.
  • Validate suspected counterexamples with concrete executions.
  • Treat nondeterminism as an unexplored path rather than a user error. (though we might change this back later)
  • Ensure realization logic called by hypothesis cannot grow the path tree.
  • Allow for collapsing more SMT expressions when drawing strings and floats.

0.0.15

  • (was never released)

0.0.14

  • Support the revised hypothesis provider draw interfaces as of hypothesis v6.112.0.

0.0.13

0.0.12

  • Error early when trying to nest hypothesis tests. (which will otherwise put CrossHair into a bad state)

0.0.11

  • Address errors when the solver can't keep up (fixes #20)

0.0.10

  • Reduce the numebr of iterations required to generate valid datetimes

0.0.9

  • Quietly ignore iterations that appear to be failing due to symbolic intolerance.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

hypothesis_crosshair-0.0.24.tar.gz (11.0 kB view details)

Uploaded Source

Built Distribution

hypothesis_crosshair-0.0.24-py3-none-any.whl (12.4 kB view details)

Uploaded Python 3

File details

Details for the file hypothesis_crosshair-0.0.24.tar.gz.

File metadata

  • Download URL: hypothesis_crosshair-0.0.24.tar.gz
  • Upload date:
  • Size: 11.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.9.22

File hashes

Hashes for hypothesis_crosshair-0.0.24.tar.gz
Algorithm Hash digest
SHA256 e455589d3945c87a4f1efa8dcd5432bdec4be5592339c5de71e99e96322e8df0
MD5 3adcbb3e33a61b2867d7709bf8a5737e
BLAKE2b-256 38b65c55549b3ccbcd7d5f5942e8f1b5aeb5a7ec31d2bca41f3ab67f9767189d

See more details on using hashes here.

File details

Details for the file hypothesis_crosshair-0.0.24-py3-none-any.whl.

File metadata

File hashes

Hashes for hypothesis_crosshair-0.0.24-py3-none-any.whl
Algorithm Hash digest
SHA256 2b3cbc10f03647192914b1fc81ab77be35945bf319bf1201bdab41792d88971c
MD5 6faac4dea03b10676bf9ede61a8ba5e1
BLAKE2b-256 c81b626919a3506d51fccf1ca4dfb0f5067292977618554ee5ab7c1783a20441

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page