Downstream packagers often want to package Hypothesis. Here are some guidelines.
The primary guideline is this: If you are not prepared to keep up with the Hypothesis release schedule, don’t. You will annoy me and are doing your users a disservice.
Hypothesis has a very frequent release schedule. It’s rare that it goes a week without a release, and there are often multiple releases in a given week.
If you are prepared to keep up with this schedule, you might find the rest of this document useful.
These are available from the GitHub releases page. The tarballs on pypi are intended for installation from a Python tool such as pip and should not be considered complete releases. Requests to include additional files in them will not be granted. Their absence is not a bug.
Hypothesis is designed to work with a range of Python versions. Currently supported are:
- pypy-2.6.1 (earlier versions of pypy may work)
- CPython 2.7.x
- CPython 3.4.x
- CPython 3.5.x
- CPython 3.6.x
- CPython 3.7.x
If you feel the need to have separate Python 3 and Python 2 packages you can, but Hypothesis works unmodified on either.
Other Python libraries¶
Hypothesis has mandatory dependencies on the following libraries:
Hypothesis has optional dependencies on the following libraries:
- pytz (almost any version should work)
- Faker, version 0.7 or later
- Django, all supported versions
- numpy, 1.10 or later (earlier versions will probably work fine)
- pandas, 1.19 or later
- pytest (3.0 or greater). This is a mandatory dependency for testing Hypothesis itself but optional for users.
The way this works when installing Hypothesis normally is that these features become available if the relevant library is installed.
If you want to test Hypothesis as part of your packaging you will probably not want to use the mechanisms Hypothesis itself uses for running its tests, because it has a lot of logic for installing and testing against different versions of Python.
The tests must be run with pytest >= 3.0; check the requirements/ directory for details.
Tests are organised into a number of top level subdirectories of the tests/ directory.
- cover: This is a small, reasonably fast, collection of tests designed to give 100% coverage of all but a select subset of the files when run under Python 3.
- nocover: This is a much slower collection of tests that should not be run under coverage for performance reasons.
- py2: Tests that can only be run under Python 2
- py3: Tests that can only be run under Python 3
- datetime: This tests the subset of Hypothesis that depends on pytz
- fakefactory: This tests the subset of Hypothesis that depends on fakefactory.
- django: This tests the subset of Hypothesis that depends on django
An example invocation for running the coverage subset of these tests:
pip install -e . pip install pytest # you will probably want to use your own packaging here python -m pytest tests/cover