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| Name: python2-hypothesis | Distribution: openSUSE Leap 15.2 |
| Version: 3.40.1 | Vendor: openSUSE |
| Release: lp152.3.3 | Build date: Sun Mar 1 12:24:24 2020 |
| Group: Development/Languages/Python | Build host: lamb10 |
| Size: 1479556 | Source RPM: python-hypothesis-3.40.1-lp152.3.3.src.rpm |
| Packager: https://bugs.opensuse.org | |
| Url: https://github.com/HypothesisWorks/hypothesis-python | |
| Summary: A library for property based testing | |
Hypothesis is a library for testing your Python code against a much larger range of examples than you would ever want to write by hand. It's based on the Haskell library, Quickcheck, and is designed to integrate seamlessly into your existing Python unit testing work flow. Hypothesis works with most widely used versions of Python. It supports implementations compatible with 2.6, 2.7 and 3.3+, and is known to work on CPython and PyPy (but not PyPy3 until they support a 3.3 compatible version of the language). It does *not* currently work on Jython or on Python 3.0 through 3.2.
MPL-2.0
* Wed Dec 06 2017 arun@gmx.de
- update to version 3.40.1:
3.40.1 - 2017-12-04
* This release makes two changes:
+ It makes the calculation of some of the metadata that Hypothesis
uses for shrinking occur lazily. This should speed up
performance of test case generation a bit because it no longer
calculates information it doesn’t need.
+ It improves the shrinker for certain classes of nested
examples. e.g. when shrinking lists of lists, the shrinker is
now able to concatenate two adjacent lists together into a
single list. As a result of this change, shrinking may get
somewhat slower when the minimal example found is large.
- changes from version 3.40.0:
* This release improves how various ways of seeding Hypothesis
interact with the example database:
+ Using the example database with seed() is now deprecated. You
should set database=None if you are doing that. This will only
warn if you actually load examples from the database while using
@seed.
+ The derandomize will behave the same way as @seed.
+ Using --hypothesis-seed will disable use of the database.
+ If a test used examples from the database, it will not suggest
using a seed to reproduce it, because that won’t work.
- changes from version 3.39.0:
* This release adds a new health check that checks if the smallest
“natural” possible example of your test case is very large - this
will tend to cause Hypothesis to generate bad examples and be
quite slow.
- changes from version 3.38.9:
* This is a documentation release to improve the documentation of
shrinking behaviour for Hypothesis’s strategies.
- changes from version 3.38.8:
* This release improves the performance of characters() when using
blacklist_characters and from_regex() when using negative
character classes.
- changes from version 3.38.7:
* This is a patch release for from_regex(), which had a bug in
handling of the re.VERBOSE flag (issue #992). Flags are now
handled correctly when parsing regex.
* Tue Nov 28 2017 arun@gmx.de
- update to version 3.38.6:
* This patch changes a few byte-string literals from double to
single quotes, thanks to an update in unify. There are no
user-visible changes.
* Sun Nov 26 2017 arun@gmx.de
- update to version 3.38.5:
* This fixes the repr of strategies using lambda that are defined
inside decorators to include the lambda source.
This would mostly have been visible when using the statistics
functionality - lambdas used for e.g. filtering would have shown
up with a <unknown> as their body. This can still happen, but it
should happen less often now.
* Wed Nov 22 2017 arun@gmx.de
- update to version 3.38.4:
* This release updates the reported statistics so that they show
approximately what fraction of your test run time is spent in data
generation (as opposed to test execution).
- changes from version 3.38.3:
* This is a documentation release, which ensures code examples are
up to date by running them as doctests in CI (issue #711).
- changes from version 3.38.2:
* This release changes the behaviour of the deadline setting when
used with data(): Time spent inside calls to data.draw will no
longer be counted towards the deadline time.
* As a side effect of some refactoring required for this work, the
way flaky tests are handled has changed slightly. You are unlikely
to see much difference from this, but some error messages will
have changed.
- changes from version 3.38.1:
* This patch has a variety of non-user-visible refactorings,
removing various minor warts ranging from indirect imports to
typos in comments.
* Sun Nov 19 2017 arun@gmx.de
- update to version 3.38.0:
* This release overhauls the health check system in a variety of
small ways. It adds no new features, but is nevertheless a minor
release because it changes which tests are likely to fail health
checks.
* The most noticeable effect is that some tests that used to fail
health checks will now pass, and some that used to pass will
fail. These should all be improvements in accuracy. In particular:
+ New failures will usually be because they are now taking into
account things like use of data() and assume() inside the test
body.
+ New failures may also be because for some classes of example the
way data generation performance was measured was artificially
faster than real data generation (for most examples that are
hitting performance health checks the opposite should be the
case).
+ Tests that used to fail health checks and now pass do so because
the health check system used to run in a way that was subtly
different than the main Hypothesis data generation and lacked
some of its support for e.g. large examples.
* If your data generation is especially slow, you may also see your
tests get somewhat faster, as there is no longer a separate health
check phase. This will be particularly noticeable when rerunning
test failures.
* Tue Nov 14 2017 arun@gmx.de
- update to version 3.37.0:
* This is a deprecation release for some health check related
features.
* The following are now deprecated:
+ Passing exception_in_generation to suppress_health_check. This
no longer does anything even when passed - All errors that occur
during data generation will now be immediately reraised rather
than going through the health check mechanism.
+ Passing random_module to suppress_health_check. This hasn’t done
anything for a long time, but was never explicitly
deprecated. Hypothesis always seeds the random module when
running @given tests, so this is no longer an error and
suppressing it doesn’t do anything.
+ Passing non-HealthCheck values in suppress_health_check. This
was previously allowed but never did anything useful.
* Sat Nov 11 2017 arun@gmx.de
- update to version 3.36.1:
* This is a yak shaving release, mostly concerned with our own
tests.
While getfullargspec() was documented as deprecated in Python 3.5,
it never actually emitted a warning. Our code to silence this
(nonexistent) warning has therefore been removed.
We now run our tests with DeprecationWarning as an error, and made
some minor changes to our own tests as a result. This required
similar upstream updates to coverage and execnet (a test-time
dependency via pytest-xdist).
There is no user-visible change in Hypothesis itself, but we
encourage you to consider enabling deprecations as errors in your
own tests.
* Tue Nov 07 2017 arun@gmx.de
- update to version 3.36.0:
* This release adds a setting to the public API, and does some
internal cleanup:
+ The derandomize setting is now documented (issue #890)
+ Removed - and disallowed - all ‘bare excepts’ in Hypothesis
(issue #953)
+ Documented the strict setting as deprecated, and updated the
build so our docs always match deprecations in the code.
- changes from version 3.35.0:
* This minor release supports constraining uuids() to generate
uuid.UUID`s of a particular version. (:issue:`721)
* Sat Nov 04 2017 arun@gmx.de
- update to version 3.34.1:
* This patch updates the documentation to suggest builds(callable)
instead of just(callable()).
* Fri Nov 03 2017 arun@gmx.de
- update to version 3.34.0:
* Hypothesis now emits deprecation warnings if you apply @given more
than once to a target.
Applying @given repeatedly wraps the target multiple times. Each
wrapper will search the space of of possible parameters
separately. This is equivalent but will be much more inefficient
than doing it with a single call to @given.
For example, instead of @given(booleans()) @given(integers()), you
could write @given(booleans(), integers())
- changes from version 3.33.1 :
* builds() would try to infer a strategy for required positional
arguments of the target from type hints, even if they had been
given to builds() as positional arguments (issue #946). Now it
only infers missing required arguments.
* An internal introspection function wrongly reported self as a
required argument for bound methods, which might also have
affected builds(). Now it knows better.
* Tue Oct 17 2017 arun@gmx.de
- update to version 3.33.0:
* This release supports strategy inference for more field types in
Django models() - you can now omit an argument for Date, Time,
Duration, Slug, IP Address, and UUID fields. (issue #642)
* Strategy generation for fields with grouped choices now selects
choices from each group, instead of selecting from the group
names.
* Sun Oct 15 2017 arun@gmx.de
- specfile:
* removed sed for src/hypothesis/tools/mergedbs.py, not in tar-ball anymore
- update to version 3.32.2:
* This patch removes the mergedb tool, introduced in Hypothesis
1.7.1 on an experimental basis. It has never actually worked, and
the new Hypothesis example database is designed to make such a
tool unnecessary.
- changes from version 3.32.1:
* This patch has two improvements for strategies based on
enumerations.
* from_type() now handles enumerations correctly, delegating to
sampled_from(). Previously it noted that Enum.__init__ has no
required arguments and therefore delegated to builds(), which
would subsequently fail.
* When sampling from an enum.Flag, we also generate combinations of
members. Eg for Flag('Permissions', 'READ, WRITE, EXECUTE') we can
now generate, Permissions.READ, Permissions.READ|WRITE, and so on.
* Mon Oct 09 2017 arun@gmx.de
- update to version 3.32.0:
* This changes the default value of use_coverage=True to True when
running on pypy (it was already True on CPython).
It was previously set to False because we expected it to be too
slow, but recent benchmarking shows that actually performance of
the feature on pypy is fairly acceptable - sometimes it’s slower
than on CPython, sometimes it’s faster, but it’s generally within
a factor of two either way.
- changes from version 3.31.6:
* This patch improves the quality of strategies inferred from Numpy
dtypes:
+ Integer dtypes generated examples with the upper half of their
(non-sign) bits set to zero. The inferred strategies can now
produce any representable integer.
+ Fixed-width unicode- and byte-string dtypes now cap the internal
example length, which should improve example and shrink quality.
+ Numpy arrays can only store fixed-size strings internally, and
allow shorter strings by right-padding them with null
bytes. Inferred string strategies no longer generate such
values, as they can never be retrieved from an array. This
improves shrinking performance by skipping useless values.
+ This has already been useful in Hypothesis - we found an
overflow bug in our Pandas support, and as a result indexes()
and range_indexes() now check that min_size and max_size are at
least zero.
- changes from version 3.31.5:
* This release fixes a performance problem in tests where
+ use_coverage is set to True.
+ Tests experience a slow-down proportionate to the amount of code
they cover. This is still the case, but the factor is now low
enough that it should be unnoticeable. Previously it was large
and became much larger in 3.28.4.
- changes from version 3.31.4:
* from_type() failed with a very confusing error if passed a
NewType() (issue #901). These psudeo-types are now unwrapped
correctly, and strategy inference works as expected.
* Fri Oct 06 2017 arun@gmx.de
- update to version 3.31.3:
* This release makes some small optimisations to our use of coverage
that should reduce constant per-example overhead. This is probably
only noticeable on examples where the test itself is quite
fast. On no-op tests that don’t test anything you may see up to a
fourfold speed increase (which is still significantly slower than
without coverage). On more realistic tests the speed up is likely
to be less than that.
* Thu Oct 05 2017 dimstar@opensuse.org
- Add python-attrs and python-coverage requires, matching the info
of setup.py.
* Tue Oct 03 2017 arun@gmx.de
- update to version 3.31.2:
* long list of updates, see
https://hypothesis.readthedocs.io/en/latest/changes.html
* Mon Jul 10 2017 jengelh@inai.de
- Ensure neutrality of description.
* Thu Jun 29 2017 aloisio@gmx.com
- Update to version 3.11.6
(see https://github.com/HypothesisWorks/hypothesis-python/blob/3.11.6/docs/changes.rst)
- Added fdupes
- Updated homepage URL
* Tue Feb 21 2017 jmatejek@suse.com
- update for singlespec
- test requirements are now conditional --with=test, to shorten build loop
for new submission
(this will be reverted soon)
- update to 3.6.1
* better thread safety
* support for --hypothesis-show-statistics in pytest
* better python 3.4 support
* renamed fake-factory dependency to Faker
* Thu May 12 2016 toddrme2178@gmail.com
- Fix download URL.
* Mon May 09 2016 toddrme2178@gmail.com
- Update to 3.1.3
+ Single bug fix release
* Another charmap problem. In 3.1.2 text/characters would break on systems
which had /tmp/ mounted on a different partition than the Hypothesis
storage directory (usually in home). This fixes that.
- Update to 3.1.2
+ Single bug fix release:
* Anything which used a text() or characters() strategy was broken on
Windows and I hadn’t updated appveyor to use the new repository location
so I didn’t notice. This is now fixed and windows support should work
correctly.
- Update to 3.1.1
+ Minor bug fix release.
* Fix concurrency issue when running tests that use text() from multiple
processes at once (Bug #302, thanks to Alex Chan).
* Improve performance of code using lists with max_size (thanks to Cristi
Cobzarenco).
* Fix install on Python 2 with ancient versions of pip so that it installs
the enum34 backport (thanks to Donald Stufft for telling me how to do
this).
* Remove duplicated __all__ exports from hypothesis.strategies (thanks to
Piët Delport).
* Update headers to point to new repository location.
* Allow use of strategies that can’t be used in find() (e.g. choices) in
stateful testing.
- Update to 3.1.0
* Add a ‘nothing’ strategy that never successfully generates values.
* sampled_from() and one_of() can both now be called with an empty argument
list, in which case they also never generate any values.
* one_of may now be called with a single argument that is a collection of
strategies as well as as varargs.
* Add a ‘runner’ strategy which returns the instance of the current test
object if there is one.
* ‘Bundle’ for RuleBasedStateMachine is now a normal(ish) strategy and can be
used as such.
* Tests using RuleBasedStateMachine should now shrink significantly better.
* Hypothesis now uses a pretty-printing library internally, compatible with
IPython’s pretty printing protocol (actually using the same code). This may
improve the quality of output in some cases.
* As a ‘phases’ setting that allows more fine grained control over which
parts of the process Hypothesis runs
* Add a suppress_health_check setting which allows you to turn off specific
health checks in a fine grained manner.
* Fix a bug where lists of non fixed size would always draw one more element
than they included. This mostly didn’t matter, but if would cause problems with
empty strategies or ones with side effects.
* Add a mechanism to the Django model generator to allow you to explicitly
request the default value (thanks to Jeremy Thurgood for this one).
- Update to 3.0.5
* Fix a bug where Hypothesis would now error on py.test development versions.
- Update to 3.0.4
* Fix a bug where Hypothesis would error when running on Python 2.7.3 or
earlier because it was trying to pass a bytearray object to struct.unpack
(which is only supported since 2.7.4).
- Update to 3.0.3
* Fix version parsing of py.test to work with py.test release candidates
* More general handling of the health check problem where things could fail
because of a cache miss - now one “free” example is generated before the
start of the health check run.
- Update to 3.0.2
* Under certain circumstances, strategies involving text() buried inside some
other strategy (e.g. text().filter(...) or recursive(text(), ...)) would
cause a test to fail its health checks the first time it ran. This was
caused by having to compute some related data and cache it to disk. On
travis or anywhere else where the .hypothesis directory was recreated this
would have caused the tests to fail their health check on every run. This
is now fixed for all the known cases, although there could be others
lurking.
- Update to 3.0.1
* Fix a case where it was possible to trigger an “Unreachable” assertion when
running certain flaky stateful tests.
* Improve shrinking of large stateful tests by eliminating a case where it
was hard to delete early steps.
* Improve efficiency of drawing binary(min_size=n, max_size=n) significantly
by provide a custom implementation for fixed size blocks that can bypass a
lot of machinery.
* Set default home directory based on the current working directory at the
point Hypothesis is imported, not whenever the function first happens to be
called.
- Update to 3.0.0
+ Externally this looks like a very small release. It has one small breaking
change that probably doesn’t affect anyone at all (some behaviour that
never really worked correctly is now outright forbidden) but necessitated a
major version bump and one visible new feature.
Internally this is a complete rewrite. Almost nothing other than the
public API is the same.
+ New features:
* Addition of data() strategy which allows you to draw arbitrary data
interactively within the test.
* New “exploded” database format which allows you to more easily check the
example database into a source repository while supporting merging.
* Better management of how examples are saved in the database.
* Health checks will now raise as errors when they fail. It was too easy to
have the warnings be swallowed entirely.
+ New limitations:
* choices and streaming strategies may no longer be used with find().
Neither may data() (this is the change that necessitated a major version
bump).
+ Feature removal:
* The ForkingTestCase executor has gone away. It may return in some more
working form at a later date.
+ Performance improvements:
* A new model which allows flatmap, composite strategies and stateful
testing to perform much better. They should also be more reliable.
* Filtering may in some circumstances have improved significantly. This
will help especially in cases where you have lots of values with
individual filters on them, such as lists(x.filter(...)).
* Modest performance improvements to the general test runner by avoiding
expensive operations
* In general your tests should have got faster. If they’ve instead got
significantly slower, I’m interested in hearing about it.
+ Data distribution:
* The data distribution should have changed significantly. This may uncover
bugs the previous version missed. It may also miss bugs the previous
version could have uncovered. Hypothesis is now producing less strongly
correlated data than it used to, but the correlations are extended over
more of the structure.
+ Shrinking:
* Shrinking quality should have improved. In particular Hypothesis can now
perform simultaneous shrinking of separate examples within a single test
(previously it was only able to do this for elements of a single
collection).
In some cases performance will have improved, in some cases it will have
got worse but generally shouldn’t have by much.
- Update to 2.0.0
+ This release cleans up all of the legacy that accrued in the course of
Hypothesis 1.0. These are mostly things that were emitting deprecation
warnings in 1.19.0, but there were a few additional changes.
In particular:
* non-strategy values will no longer be converted to strategies when used
in given or find.
* FailedHealthCheck is now an error and not a warning.
* Handling of non-ascii reprs in user types have been simplified by using
raw strings in more places in Python 2.
* given no longer allows mixing positional and keyword arguments.
* given no longer works with functions with defaults.
* given no longer turns provided arguments into defaults - they will not
appear in the argspec at all.
* the basic() strategy no longer exists.
* the n_ary_tree strategy no longer exists.
* the average_list_length setting no longer exists. Note: If you’re using
using recursive() this will cause you a significant slow down. You should
pass explicit average_size parameters to collections in recursive calls.
* @rule can no longer be applied to the same method twice.
* Python 2.6 and 3.3 are no longer officially supported, although in
practice they still work fine.
+ This also includes two non-deprecation changes:
* given’s keyword arguments no longer have to be the rightmost arguments
and can appear anywhere in the method signature.
* The max_shrinks setting would sometimes not have been respected.
- Update to 1.19.0
+ This release heralds the beginning of a new and terrible age of Hypothesis
2.0.
It’s primary purpose is some final deprecations prior to said release. The
goal is that if your code emits no warnings under this release then it
will probably run unchanged under Hypothesis 2.0 (there are some caveats
to this: 2.0 will drop support for some Python versions, and if you’re
using internal APIs then as usual that may break without warning).
+ It does have two new features:
* New @seed() decorator which allows you to manually seed a test. This may
be harmlessly combined with and overrides the derandomize setting.
* settings objects may now be used as a decorator to fix those settings to
a particular @given test.
+ API changes (old usage still works but is deprecated):
* Settings has been renamed to settings (lower casing) in order to make the
decorator usage more natural.
* Functions for the storage directory that were in hypothesis.settings are
now in a new hypothesis.configuration module.
+ Additional deprecations:
* the average_list_length setting has been deprecated in favour of being
explicit.
* the basic() strategy has been deprecated as it is impossible to support
it under a Conjecture based model, which will hopefully be implemented at
some point in the 2.x series.
* the n_ary_tree strategy (which was never actually part of the public API)
has been deprecated.
* Passing settings or random as keyword arguments to given is deprecated
(use the new functionality instead)
+ Bug fixes:
* No longer emit PendingDeprecationWarning for __iter__ and StopIteration
in streaming() values.
* When running in health check mode with non strict, don’t print quite so
many errors for an exception in reify.
* When an assumption made in a test or a filter is flaky, tests will now
raise Flaky instead of UnsatisfiedAssumption.
- Update to 1.18.1
+ Two behind the scenes changes:
* Hypothesis will no longer write generated code to the file system. This
will improve performance on some systems (e.g. if you’re using
PythonAnywhere which is running your code from NFS) and prevent some
annoying interactions with auto-restarting systems.
* Hypothesis will cache the creation of some strategies. This can
significantly improve performance for code that uses flatmap or composite
and thus has to instantiate strategies a lot.
- Update to 1.18.0
+ Features:
* Tests and find are now explicitly seeded off the global random module.
This means that if you nest one inside the other you will now get a
health check error. It also means that you can control global
randomization by seeding random.
* There is a new random_module() strategy which seeds the global random
module for you and handles things so that you don’t get a health check
warning if you use it inside your tests.
* floats() now accepts two new arguments: allow_nan and allow_infinity.
These default to the old behaviour, but when set to False will do what
the names suggest.
+ Bug fixes:
* Fix a bug where tests that used text() on Python 3.4+ would not actually
be deterministic even when explicitly seeded or using the derandomize
mode, because generation depended on dictionary iteration order which was
affected by hash randomization.
* Fix a bug where with complicated strategies the timing of the initial
health check could affect the seeding of the subsequent test, which would
also render supposedly deterministic tests non-deterministic in some
scenarios.
* In some circumstances flatmap() could get confused by two structurally
similar things it could generate and would produce a flaky test where the
first time it produced an error but the second time it produced the other
value, which was not an error. The same bug was presumably also possible
in composite().
* flatmap() and composite() initial generation should now be moderately
faster. This will be particularly noticeable when you have many values
drawn from the same strategy in a single run, e.g. constructs like
lists(s.flatmap(f)). Shrinking performance may have suffered, but this
didn’t actually produce an interestingly worse result in any of the
standard scenarios tested.
- Update to 1.17.1
* A small bug fix release, which fixes the fact that the ‘note’ function
could not be used on tests which used the @example decorator to provide
explicit examples.
- Update to 1.17.0
+ This is actually the same release as 1.16.1, but 1.16.1 has been pulled
because it contains the following additional change that was not intended
to be in a patch release (it’s perfectly stable, but is a larger change
that should have required a minor version bump):
* Hypothesis will now perform a series of “health checks” as part of
running your tests. These detect and warn about some common error
conditions that people often run into which wouldn’t necessarily have
caued the test to fail but would cause e.g. degraded performance or
confusing results.
- Update to 1.16.1
* A small bugfix release that allows bdists for Hypothesis to be built under
2.7 - the compat3.py file which had Python 3 syntax wasn’t intended to be
loaded under Python 2, but when building a bdist it was. In particular
this would break running setup.py test.
* Wed Dec 09 2015 dmueller@suse.com
- update to 1.16.0:
* Functions from hypothesis.strategies will no longer raise InvalidArgument on bad arguments
* Errors caused by accidentally invoking the legacy API are now much less confusing
* hypothesis.extra.django is 1.9 compatible.
* When tests are run with max_shrinks=0 this will now still rerun the test on failure
* Tue Nov 24 2015 toddrme2178@gmail.com
- Fix license naming.
* Tue Nov 10 2015 tbechtold@suse.com
- Initial packaging (version 1.14.0)
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Fabrice Bellet, Tue Jul 9 11:27:19 2024