Welcome to Hypothesis! Hypothesis is a Python library for creating unit tests which are simpler to write and more powerful when run, finding edge cases in your code you wouldn't have thought to look for. It is stable, powerful and easy to add to any existing test suite. It works by letting you write tests that assert that something should be ...
What you can generate and how
For example, everything_except(int) returns a strategy that can generate anything that from_type() can ever generate, except for instances of int, and excluding instances of types added via register_type_strategy(). This is useful when writing tests which check that invalid input is rejected in a certain way. hypothesis.strategies. frozensets (elements, *, min_size = 0, max_size = None) [source]
Details and advanced features
It aims to improve the integration between Hypothesis and Pytest by providing extra information and convenient access to config options. pytest --hypothesis-show-statistics can be used to display test and data generation statistics. pytest --hypothesis-profile=<profile name> can be used to load a settings profile.
Tools, Plug-ins, and Integrations
Readwise has a built-in integration with Hypothesis. Visit your syncs to set it up. Obsidian: Obsidian Hypothesis Plugin. Obsidian Hypothesis (Community Plugin) is an unofficial plugin to synchronize Hypothesis web article highlights/annotations into your Obsidian Vault. ... Annotation tools: python tools to link Hypothesis and Pinboard ...
How to Use Python Hypothesis in Integration Tests
Now for our integration tests, we'd like to use the same functionality, the only difference is that they should run only once regardless of the result of the test. One solution is to call example() on the composite strategy in the test (or test fixture) which works fine, but it prints a warning asking not to do it.
Products
Enough of the core Hypothesis model to be useful. Good JUnit integration. A small library of data generators. The end goal is for Hypothesis for Java to have feature parity with Hypothesis for Python, and to take advantage of the JVM's excellent concurrency support to provide parallel testing of your code, but it's not there yet.
hypothesis/hypothesis-python/examples/README.rst at master ...
This is a directory for examples of using Hypothesis that show case its features or demonstrate a useful way of testing something. Right now it's a bit small and fairly algorithmically focused. Pull requests to add more examples would be greatly appreciated, especially ones using e.g. the Django integration or testing something "Businessy".
Newest 'python-hypothesis' Questions
1vote. 1answer. 45views. hypothesis lists strategy where length of list depends on another argument. I have a function which takes two arguments, an integer x and a list l of floats. This function requires that len(l) == x. I wish to write a unit test, with my function arguments x and l both being ... python. pytest.
Automating Unit Tests in Python with Hypothesis
Aug 30, 2020. --. 4. Unit testing is key to developing quality code. There's a host of libraries and services available that you can use to perfect testing of your Python code. However, "traditional" unit testing is time intensive and is unlikely to cover the full spectrum of cases that your code is supposed to be able to handle. In this ...
Projects extending Hypothesis
Hypothesis integration via setuptools entry points ... Entry points are Python's standard way of automating the latter: when you register a "hypothesis" entry point in your setup.py, we'll import and run it automatically when hypothesis is imported. Nothing happens unless Hypothesis is already in use, and it's totally seamless for ...
COMMENTS
Welcome to Hypothesis! Hypothesis is a Python library for creating unit tests which are simpler to write and more powerful when run, finding edge cases in your code you wouldn't have thought to look for. It is stable, powerful and easy to add to any existing test suite. It works by letting you write tests that assert that something should be ...
For example, everything_except(int) returns a strategy that can generate anything that from_type() can ever generate, except for instances of int, and excluding instances of types added via register_type_strategy(). This is useful when writing tests which check that invalid input is rejected in a certain way. hypothesis.strategies. frozensets (elements, *, min_size = 0, max_size = None) [source]
It aims to improve the integration between Hypothesis and Pytest by providing extra information and convenient access to config options. pytest --hypothesis-show-statistics can be used to display test and data generation statistics. pytest --hypothesis-profile=<profile name> can be used to load a settings profile.
Readwise has a built-in integration with Hypothesis. Visit your syncs to set it up. Obsidian: Obsidian Hypothesis Plugin. Obsidian Hypothesis (Community Plugin) is an unofficial plugin to synchronize Hypothesis web article highlights/annotations into your Obsidian Vault. ... Annotation tools: python tools to link Hypothesis and Pinboard ...
Now for our integration tests, we'd like to use the same functionality, the only difference is that they should run only once regardless of the result of the test. One solution is to call example() on the composite strategy in the test (or test fixture) which works fine, but it prints a warning asking not to do it.
Enough of the core Hypothesis model to be useful. Good JUnit integration. A small library of data generators. The end goal is for Hypothesis for Java to have feature parity with Hypothesis for Python, and to take advantage of the JVM's excellent concurrency support to provide parallel testing of your code, but it's not there yet.
This is a directory for examples of using Hypothesis that show case its features or demonstrate a useful way of testing something. Right now it's a bit small and fairly algorithmically focused. Pull requests to add more examples would be greatly appreciated, especially ones using e.g. the Django integration or testing something "Businessy".
1vote. 1answer. 45views. hypothesis lists strategy where length of list depends on another argument. I have a function which takes two arguments, an integer x and a list l of floats. This function requires that len(l) == x. I wish to write a unit test, with my function arguments x and l both being ... python. pytest.
Aug 30, 2020. --. 4. Unit testing is key to developing quality code. There's a host of libraries and services available that you can use to perfect testing of your Python code. However, "traditional" unit testing is time intensive and is unlikely to cover the full spectrum of cases that your code is supposed to be able to handle. In this ...
Hypothesis integration via setuptools entry points ... Entry points are Python's standard way of automating the latter: when you register a "hypothesis" entry point in your setup.py, we'll import and run it automatically when hypothesis is imported. Nothing happens unless Hypothesis is already in use, and it's totally seamless for ...