Level-up your Hypothesis tests with CrossHair.
Project description
hypothesis-crosshair
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 comming soon. In the meantime, start a discussion or file an issue.
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
Built Distribution
Close
Hashes for hypothesis-crosshair-0.0.2.tar.gz
Algorithm | Hash digest | |
---|---|---|
SHA256 | 0c6a06ff39568d91051625f52dd33fb52ec03326a3876be688edaaa76a5a9902 |
|
MD5 | a6e716849a77001751f8a08baac00998 |
|
BLAKE2b-256 | a44702dfeca80bdada816fff238ab968e568aa99e8b6aae760cc15235a80fe45 |
Close
Hashes for hypothesis_crosshair-0.0.2-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 431c120a6bd1a2146987961f978fa4aefec6d80cbe551d3f7e0088b58dce8d02 |
|
MD5 | f54cd457fedf1ad583622f74c4695cbd |
|
BLAKE2b-256 | 8437a0490d5dfafbd20233de4132188c7e4ecc9aed6afa0a6afeddfbd8c36ed2 |