This release fixes :func:~hypothesis.strategies.builds so that target
can be used as a keyword argument for passing values to the target. The target
itself can still be specified as a keyword argument, but that behavior is now
deprecated. The target should be provided as the first positional argument.
filefinder2 -> 0.4.1
0.4.1
Fixing PEP link in README. [alexv]
Merge pull request 13 from asmodehn/pyup-update-pytest-
xdist-1.18.1-to-1.18.2. [AlexV]
Update pytest-xdist to 1.18.2
Update pytest-xdist from 1.18.1 to 1.18.2. [pyup-bot]
Restructuring tests. [alexv]
Skipping tests if they are run in unboxed mode (and cannot test any
import properly) [alexv]
Merge pull request 12 from asmodehn/import_23_api. [AlexV]
Import 23 api
Fixing import order. [alexv]
Cleanup and style changes. [alexv]
Removing broken sourcelessfileloader. [alexv]
Small fixes and separate tests with different ways to import with
importlib, to not have one pollute the other if unboxed, given that
one package should use only one way, made for one interpreter version.
[alexv]
ImpFileloader not using broken SourcelessFileLoader for now. [alexv]
Refining activation / deactivation of filefinder2 FileFinder not
raising ImportError on init to match python3 behavior. [alexv]
Implemented importlib API. All tests passing except exec_module on
bytecode loader. [alexv]
Fixing tests by fixing namespace package handling in pathfinder.
[alexv]
WIP refactoring to use filefinder2 as an API for cross py2 py3 custom
importers. [alexv]
Fixing init.py to expose our importer API. [alexv]
Starting to wrap importlib useful api for custom importer... [alexv]
0.3.1
V0.3.1. [alexv]
Preventing multiple activation to pollute sys.path_hooks and
sys.meta_path. [alexv]
Exposing path_hook only if python2. [alexv]
Making ns_hook publish in case hte client wants to do a search on
sys.path_hook. [alexv]
Merge pull request 9 from asmodehn/pyup-pin-pytest-3.1.3. [AlexV]
Pin pytest to latest version 3.1.3
Merge branch 'master' into pyup-pin-pytest-3.1.3. [AlexV]
Merge branch 'master' into pyup-pin-pytest-3.1.3. [AlexV]
Merge pull request 8 from asmodehn/pyup-pin-twine-1.9.1. [AlexV]
Pin twine to latest version 1.9.1
Merge branch 'master' into pyup-pin-twine-1.9.1. [AlexV]
Pin twine to latest version 1.9.1. [pyup-bot]
Merge pull request 10 from asmodehn/pyup-pin-pytest-xdist-1.18.1.
[AlexV]
Pin pytest-xdist to latest version 1.18.1
Pin pytest-xdist to latest version 1.18.1. [pyup-bot]
Merge pull request 7 from asmodehn/pyup-pin-gitchangelog-3.0.3.
[AlexV]
Pin gitchangelog to latest version 3.0.3
Pin gitchangelog to latest version 3.0.3. [pyup-bot]
Pin pytest to latest version 3.1.3. [pyup-bot]
Moving tests outside directory, to keep package code and dependencies
minimal. [alexv]
Exposing PathFinder2 to clients. [alexv]
Extracting PathFinder2 from NamespaceMetaFinder2. [alexv]
Merge pull request 6 from asmodehn/fixing_namespace_repr. [AlexV]
override load_module in namespace loader to fix repr for namespace pa…
Override load_module in namespace loader to fix repr for namespace
package. [alexv]
API compatibility with py3 FileLoader. [alexv]
Fixing logic importing base modules from bytecode or extensions.
[alexv]
Merge pull request 5 from asmodehn/newline_encoding. [AlexV]
Newline encoding
Fixing a few QC issues. [alexv]
Now handling encoding properly in SourceFileLoader. [alexv]
Adding test for source file encoding. [alexv]
Enabling newline encoding detection. [alexv]
Merge pull request 4 from asmodehn/bytecode. [AlexV]
Bytecode
Now compiling to bytecode at the test setup phase. [alexv]
Cleaning loader module. [alexv]
Implemented imp based loader for bytecode on py27. all tests passing.
[alexv]
Added bytecode test. [alexv]
Improved doc. [alexv]
0.2.1
Generating changelog and changing version. [alexv]
Adding gitignore. [alexv]
Added python 3.6 to tests. [alexv]
Exposed loader classes. fixed finder init check. [alexv]
Moving namespace logic in meta_path hook. Splitted loader for
namespace or actual file, to make extending it simpler. [alexv]
Small change to make usage from another importer easier. [alexv]
Adding classifiers. [alexv]
Fixing ReST README. [AlexV]
Fixes for release. [alexv]
V0.1.1. [alexv]
Adding badges. moving to rst README format. [alexv]
Making tox happy for all tested python. [alexv]
Getting all tests to pass for py2. [alexv]
Dropping in first version of filefinder2. [alexv]
Initial commit. [AlexV]
rosimport -> 0.2.1
0.2.1
Now depending on latest filefinder2 release. [alexv]
Letting filefinder2 manage create_module API being available or not.
[alexv]
Removing python version restriction on filefinder since it now manages
API compat. [alexv]
Moving submodules used by tests. [alexv]
Removign submodules that we can get with pip. restructured tests.
[alexv]
Fixing filefinder version. [alexv]
Merge pull request 11 from asmodehn/import_23_api. [AlexV]
Import 23 api
Fixing tests after filefinder2 api change. [alexv]
Small changes to attempt dealing with filefinder providing an importer
API... [alexv]
Now using ROS_PACKAGE_PATH as initial search path if setup in
environment. [alexv]
0.1.1
V0.1.1. [alexv]
Fixing tests after activate/deactivate api change. [alexv]
Refining requirement after filefinder2 release v0.3. [alexv]
Preventing multiple activation to pollute sys.path_hooks and
sys.meta_path. [alexv]
Merge pull request 3 from asmodehn/generate_refactor. [AlexV]
Generate refactor
Change activate to not use paths list. use site.addsiteir instead.
fixing ROS pathfinder to handle case some msg folder is missing. extra
fix since the search path contains sets and not lists. [alexv]
Fixing tests and cleaning up message definitions. [alexv]
All generator tests now passing locally. [alexv]
Adding rospathfinder and refactoring to handle self dependencies
between different subdirectories in same package. [alexv]
Extracted tests again and got all tests to pass for py3. [alexv]
Moving tests outside of pacakge, to make debugging import problems
easier. improved generator and import tests now passing. [alexv]
Adding comment to handle dependency message not found exception (when
it will be available on genmsg). [alexv]
Fixing import srv tests after adding msg dependency. added bwcompat
code for genmsg. [alexv]
Making generator test work by using searchpath from genmsg API.
[alexv]
Adding gitignore. [alexv]
Merge branch 'namespace_meta' [alexv]
Fixing quantified code link and usage example. [alexv]
Merge pull request 1 from asmodehn/namespace_meta. [AlexV]
fixing finder and loader for python3.5 to let default FileFinder do h…
Organizing the public API. [alexv]
Merging identical RosLoader code. [alexv]
Merging identical Rosfinder code. [alexv]
Added dependency on filefinder2. now using develop in tox since genpy
and genmsg need to be used from source. temporarily using unreleased
filefinder2. [alexv]
Fixing finder for py2 by relying on meta_path instead of inheritance.
[alexv]
Adding python 3.6 to test. removing idea files. [alexv]
Adding services test for importlib. [alexv]
Fixing test for srv import. [alexv]
Fixed issue with relative paths in finder. [alexv]
Adding version module. [alexv]
Fixing finder and loader for python3.5 to let default FileFinder do
his thing when there is no ROS directory in sight. [alexv]
Extracting from pyros-msgs. [alexv]
Initial commit. [AlexV]
pytest-xdist -> 1.22.0
1.22.0
================================
Features
Add support for the pytest_runtest_logfinish hook which will be released
in pytest 3.4. (266 <https://github.com/pytest-dev/pytest-xdist/issues/266>_)
1.21.0
================================
Deprecations and Removals
Drop support for EOL Python 2.6. (259 <https://github.com/pytest-dev/pytest-xdist/issues/259>_)
Features
New --dist=loadfile option which load-distributes test to workers grouped
by the file the tests live in. (242 <https://github.com/pytest-dev/pytest-xdist/issues/242>_)
Bug Fixes
Fix accidental mutation of test report during serialization causing longrepr
string-ification to break. (241 <https://github.com/pytest-dev/pytest-xdist/issues/241>_)
1.20.1
================================
Bug Fixes
Fix hang when all worker nodes crash and restart limit is reached (45 <https://github.com/pytest-dev/pytest-xdist/issues/45>_)
Fix issue where the -n option would still run distributed tests when pytest
was run with the --collect-only option (5 <https://github.com/pytest-dev/pytest-xdist/issues/5>_)
1.20.0
================================
Features
xdist now supports tests to log results multiple times, improving
integration with plugins which require it like pytest-rerunfailures <https://github.com/gocept/pytest-rerunfailures> and flaky <https://pypi.python.org/pypi/flaky>. (206 <https://github.com/pytest- dev/pytest-xdist/issues/206>_)
Bug Fixes
Fix issue where tests were being incorrectly identified if a worker crashed
during the teardown stage of the test. (124 <https://github.com/pytest- dev/pytest-xdist/issues/124>_)
1.19.1
================================
Bug Fixes
Fix crash when transferring internal pytest warnings from workers to the
master node. (214 <https://github.com/pytest-dev/pytest- xdist/issues/214>_)
1.19.0
================================
Deprecations and Removals
--boxed functionality has been moved to a separate plugin, pytest-forked <https://github.com/pytest-dev/pytest-forked>. This release now depends on
pytest-forked and provides --boxed as a backward compatibility
option. (1 <https://github.com/pytest-dev/pytest-xdist/issues/1>)
Features
New --dist=loadscope option: sends group of related tests to the same
worker. Tests are grouped by module for test functions and by class for test
methods. See README.rst for more information. (191 <https://github.com /pytest-dev/pytest-xdist/issues/191>_)
Warnings are now properly transferred from workers to the master node. (92 <https://github.com/pytest-dev/pytest-xdist/issues/92>_)
Bug Fixes
Fix serialization of native tracebacks (--tb=native). (196 <https://github.com/pytest-dev/pytest-xdist/issues/196>_)
1.18.2
================================
Bug Fixes
Removal of unnecessary dependency on incorrect version of py. (105 <https://github.com/pytest-dev/pytest-xdist/issues/105>_)
Fix bug in internal event-loop error handler in the master node. This bug
would shadow the original errors making extremely hard/impossible for users
to diagnose the problem properly. (175 <https://github.com/pytest- dev/pytest-xdist/issues/175>_)
1.18.1
================================
Bug Fixes
Fixed serialization of longrepr.sections during error reporting from
workers. (171 <https://github.com/pytest-dev/pytest-xdist/issues/171>_)
Fix ReprLocal not being unserialized breaking --showlocals usages. (176 <https://github.com/pytest-dev/pytest-xdist/issues/176>_)
1.18.0
================================
pytest-xdist now requires pytest>=3.0.0.
Features
Add long option --numprocesses as alternative for -n. (168)
Bug Fixes
Fix serialization and deserialization dropping longrepr details. (133)
1.17.1
================================
Bug Fixes
Hot fix release reverting the change introduced by 124, unfortunately it
broke a number of test suites so we are reversing this change while we
investigate the problem. (157)
Improved Documentation
Introduced towncrier for CHANGELOG management. (154)
Added HOWTORELEASE documentation. (155)
..
You should NOT be adding new change log entries to this file, this
file is managed by towncrier. You may edit previous change logs to
fix problems like typo corrections or such.
To add a new change log entry, please see
https://pip.pypa.io/en/latest/development/adding-a-news-entry
We named the news folder changelog
.. towncrier release notes start
1.17.0
fix 124: xdist would mark test as complete after 'call' step. As a result,
xdist could identify the wrong test as failing when test crashes at teardown.
To address this issue, xdist now marks test as complete at teardown.
1.16.0
pytest-xdist now requires pytest 2.7 or later.
Add worker_id attribute in the TestReport
new hook: pytest_xdist_make_scheduler(config, log), can return custom tests items
distribution logic implementation. You can take a look at built-in LoadScheduling
and EachScheduling implementations. Note that required scheduler class public
API may change in next pytest-xdist versions.
1.15.0
new worker_id fixture, returns the id of the worker in a test or fixture.
Thanks Jared Hellman for the PR.
display progress during collection only when in a terminal, similar to pytest 1397 issue.
Thanks Bruno Oliveira for the PR.
fix internal error message when --maxfail is used (62, 65).
Thanks Collin RM Stocks and Bryan A. Jones for reports and Bruno Oliveira for the PR.
1.14
new hook: pytest_xdist_node_collection_finished(node, ids), called when
a worker has finished collection. Thanks Omer Katz for the request and
Bruno Oliveira for the PR.
fix README display on pypi
fix 22: xdist now works if the internal tmpdir plugin is disabled.
Thanks Bruno Oliveira for the PR.
fix 32: xdist now works if looponfail or boxed are disabled.
Thanks Bruno Oliveira for the PR.
1.13.1
fix a regression -n 0 now disables xdist again
1.13
extended the tox matrix with the supported py.test versions
split up the plugin into 3 plugin's
to prepare the departure of boxed and looponfail.
looponfail will be a part of core
and forked boxed will be replaced
with a more reliable primitive based on xdist
conforming with new pytest-2.8 behavior of returning non-zero when all
tests were skipped or deselected.
new "--max-slave-restart" option that can be used to control maximum
number of times pytest-xdist can restart slaves due to crashes. Thanks to
Anatoly Bubenkov for the report and Bruno Oliveira for the PR.
release as wheel
"-n" option now can be set to "auto" for automatic detection of number
of cpus in the host system. Thanks Suloev Dmitry for the PR.
1.12
fix issue594: properly report errors when the test collection
is random. Thanks Bruno Oliveira.
some internal test suite adaptation (to become forward
compatible with the upcoming pytest-2.8)
1.11
fix pytest/xdist issue485 (also depends on py-1.4.22):
attach stdout/stderr on --boxed processes that die.
fix pytest/xdist issue503: make sure that a node has usually
two items to execute to avoid scoped fixtures to be torn down
pre-maturely (fixture teardown/setup is "nextitem" sensitive).
Thanks to Andreas Pelme for bug analysis and failing test.
restart crashed nodes by internally refactoring setup handling
of nodes. Also includes better code documentation.
Many thanks to Floris Bruynooghe for the complete PR.
1.10
add glob support for rsyncignores, add command line option to pass
additional rsyncignores. Thanks Anatoly Bubenkov.
fix pytest issue382 - produce "pytest_runtest_logstart" event again
in master. Thanks Aron Curzon.
fix pytest issue419 by sending/receiving indices into the test
collection instead of node ids (which are not necessarily unique
for functions parametrized with duplicate values)
send multiple "to test" indices in one network message to a slave
and improve heuristics for sending chunks where the chunksize
depends on the number of remaining tests rather than fixed numbers.
This reduces the number of master -> node messages (but not the
reverse direction)
1.9
changed LICENSE to MIT
fix duplicate reported test ids with --looponfailing
(thanks Jeremy Thurgood)
fix pytest issue41: re-run tests on all file changes, not just
randomly select ones like .py/.c.
fix pytest issue347: slaves running on top of Python3.2
will set PYTHONDONTWRITEYBTECODE to 1 to avoid import concurrency
bugs.
1.8
fix pytest-issue93 - use the refined pytest-2.2.1 runtestprotocol
interface to perform eager teardowns for test items.
1.7
fix incompatibilities with pytest-2.2.0 (allow multiple
pytest_runtest_logreport reports for a test item)
1.6
terser collection reporting
fix issue34 - distributed testing with -p plugin now works correctly
fix race condition in looponfail mode where a concurrent file removal
could cause a crash
1.5
adapt to and require pytest-2.0 changes, rsyncdirs and rsyncignore can now
only be specified in [pytest] sections of ini files, see "py.test -h"
for details.
major internal refactoring to match the pytest-2.0 event refactoring
perform test collection always at slave side instead of at the master
make python2/python3 bridging work, remove usage of pickling
improve initial reporting by using line-rewriting
remove all trailing whitespace from source
1.4
perform distributed testing related reporting in the plugin
rather than having dist-related code in the generic py.test
distribution
depend on execnet-1.0.7 which adds "env1:NAME=value" keys to
gateway specification strings.
show detailed gateway setup and platform information only when
"-v" or "--verbose" is specified.
1.3
fix --looponfailing - it would not actually run against the fully changed
source tree when initial conftest files load application state.
adapt for py-1.3.1's new --maxfailure option
1.2
fix issue79: sessionfinish/teardown hooks are now called systematically
on the slave side
introduce a new data input/output mechanism to allow the master side
to send and receive data from a slave.
fix race condition in underlying pickling/unpickling handling
use and require new register hooks facility of py.test>=1.3.0
require improved execnet>=1.0.6 because of various race conditions
that can arise in xdist testing modes.
fix some python3 related pickling related race conditions
fix PyPI description
1.1
fix an indefinite hang which would wait for events although no events
are pending - this happened if items arrive very quickly while
the "reschedule-event" tried unconditionally avoiding a busy-loop
and not schedule new work.
1.0
moved code out of py-1.1.1 into its own plugin
use a new, faster and more sensible model to do load-balancing
of tests - now no magic "MAXITEMSPERHOST" is needed and load-testing
works effectively even with very few tests.
cleaned up termination handling
make -x cause hard killing of test nodes to decrease wait time
until the traceback shows up on first failure
======================
Releasing pytest-xdist
This document describes the steps to make a new pytest-xdist release.
Version
master should always be green and a potential release candidate. pytest-xdist follows
semantic versioning, so given that the current version is X.Y.Z, to find the next version number
one needs to look at the changelog folder:
If there is any file named *.feature, then we must make a new minor release: next
release will be X.Y+1.0.
Otherwise it is just a bug fix release: X.Y.Z+1.
Steps
To publish a new release X.Y.Z, the steps are as follows:
. Create a new branch named release-X.Y.Z from the latest master.
. Install pytest-xdist and dev requirements in a virtualenv::
$ pip install -e . -r dev-requirements.txt
. Update CHANGELOG.rst file by running::
$ towncrier --version X.Y.Z
It might ask for confirmation to remove news fragments; answer yes.
. Commit and push the branch for review.
. Once PR is green and approved, create and push a tag::
That will build the package and publish it on PyPI automatically.
numpy -> 1.14.0
1.14.0
==========================
Numpy 1.14.0 is the result of seven months of work and contains a large number
of bug fixes and new features, along with several changes with potential
compatibility issues. The major change that users will notice are the
stylistic changes in the way numpy arrays and scalars are printed, a change
that will affect doctests. See below for details on how to preserve the
old style printing when needed.
A major decision affecting future development concerns the schedule for
dropping Python 2.7 support in the runup to 2020. The decision has been made to
support 2.7 for all releases made in 2018, with the last release being
designated a long term release with support for bug fixes extending through
In 2019 support for 2.7 will be dropped in all new releases. More details
can be found in the relevant NEP_.
genfromtxt, loadtxt, fromregex and savetxt can now handle
files with arbitrary Python supported encoding.
Major improvements to printing of NumPy arrays and scalars.
New functions
parametrize: decorator added to numpy.testing
chebinterpolate: Interpolate function at Chebyshev points.
format_float_positional and format_float_scientific : format
floating-point scalars unambiguously with control of rounding and padding.
PyArray_ResolveWritebackIfCopy and PyArray_SetWritebackIfCopyBase,
new C-API functions useful in achieving PyPy compatibity.
Deprecations
Using np.bool_ objects in place of integers is deprecated. Previously
operator.index(np.bool_) was legal and allowed constructs such as
[1, 2, 3][np.True_]. That was misleading, as it behaved differently from
np.array([1, 2, 3])[np.True_].
Truth testing of an empty array is deprecated. To check if an array is not
empty, use array.size > 0.
Calling np.bincount with minlength=None is deprecated.
minlength=0 should be used instead.
Calling np.fromstring with the default value of the sep argument is
deprecated. When that argument is not provided, a broken version of
np.frombuffer is used that silently accepts unicode strings and -- after
encoding them as either utf-8 (python 3) or the default encoding
(python 2) -- treats them as binary data. If reading binary data is
desired, np.frombuffer should be used directly.
The style option of array2string is deprecated in non-legacy printing mode.
PyArray_SetUpdateIfCopyBase has been deprecated. For NumPy versions >= 1.14
use PyArray_SetWritebackIfCopyBase instead, see C API changes below for
more details.
The use of UPDATEIFCOPY arrays is deprecated, see C API changes below
for details. We will not be dropping support for those arrays, but they are
not compatible with PyPy.
Future Changes
np.issubdtype will stop downcasting dtype-like arguments.
It might be expected that issubdtype(np.float32, 'float64') and
issubdtype(np.float32, np.float64) mean the same thing - however, there
was an undocumented special case that translated the former into
issubdtype(np.float32, np.floating), giving the surprising result of True.
This translation now gives a warning that explains what translation is
occurring. In the future, the translation will be disabled, and the first
example will be made equivalent to the second.
np.linalg.lstsq default for rcond will be changed. The rcond
parameter to np.linalg.lstsq will change its default to machine precision
times the largest of the input array dimensions. A FutureWarning is issued
when rcond is not passed explicitly.
a.flat.__array__() will return a writeable copy of a when a is
non-contiguous. Previously it returned an UPDATEIFCOPY array when a was
writeable. Currently it returns a non-writeable copy. See gh-7054 for a
discussion of the issue.
Unstructured void array's .item method will return a bytes object. In the
future, calling .item() on arrays or scalars of np.void datatype will
return a bytes object instead of a buffer or int array, the same as
returned by bytes(void_scalar). This may affect code which assumed the
return value was mutable, which will no longer be the case. A
FutureWarning is now issued when this would occur.
Compatibility notes
The mask of a masked array view is also a view rather than a copy
There was a FutureWarning about this change in NumPy 1.11.x. In short, it is
now the case that, when changing a view of a masked array, changes to the mask
are propagated to the original. That was not previously the case. This change
affects slices in particular. Note that this does not yet work properly if the
mask of the original array is nomask and the mask of the view is changed.
See gh-5580 for an extended discussion. The original behavior of having a copy
of the mask can be obtained by calling the unshare_mask method of the view.
np.ma.masked is no longer writeable
Attempts to mutate the masked constant now error, as the underlying arrays
are marked readonly. In the past, it was possible to get away with::
emulating a function that sometimes returns np.ma.masked
val = random.choice([np.ma.masked, 10])
var_arr = np.asarray(val)
val_arr += 1 now errors, previously changed np.ma.masked.data
np.ma functions producing fill_values have changed
Previously, np.ma.default_fill_value would return a 0d array, but
np.ma.minimum_fill_value and np.ma.maximum_fill_value would return a
tuple of the fields. Instead, all three methods return a structured np.void
object, which is what you would already find in the .fill_value attribute.
Additionally, the dtype guessing now matches that of np.array - so when
passing a python scalar x, maximum_fill_value(x) is always the same as
maximum_fill_value(np.array(x)). Previously x = long(1) on Python 2
violated this assumption.
a.flat.__array__() returns non-writeable arrays when a is non-contiguous
The intent is that the UPDATEIFCOPY array previously returned when a was
non-contiguous will be replaced by a writeable copy in the future. This
temporary measure is aimed to notify folks who expect the underlying array be
modified in this situation that that will no longer be the case. The most
likely places for this to be noticed is when expressions of the form
np.asarray(a.flat) are used, or when a.flat is passed as the out
parameter to a ufunc.
np.tensordot now returns zero array when contracting over 0-length dimension
Previously np.tensordot raised a ValueError when contracting over 0-length
dimension. Now it returns a zero array, which is consistent with the behaviour
of np.dot and np.einsum.
numpy.testing reorganized
This is not expected to cause problems, but possibly something has been left
out. If you experience an unexpected import problem using numpy.testing
let us know.
np.asfarray no longer accepts non-dtypes through the dtype argument
This previously would accept dtype=some_array, with the implied semantics
of dtype=some_array.dtype. This was undocumented, unique across the numpy
functions, and if used would likely correspond to a typo.
1D np.linalg.norm preserves float input types, even for arbitrary orders
Previously, this would promote to float64 when arbitrary orders were
passed, despite not doing so under the simple cases::
This change affects only float32 and float16 arrays.
count_nonzero(arr, axis=()) now counts over no axes, not all axes
Elsewhere, axis==() is always understood as "no axes", but
count_nonzero had a special case to treat this as "all axes". This was
inconsistent and surprising. The correct way to count over all axes has always
been to pass axis == None.
__init__.py files added to test directories
This is for pytest compatibility in the case of duplicate test file names in
the different directories. As a result, run_module_suite no longer works,
i.e., python <path-to-test-file> results in an error.
.astype(bool) on unstructured void arrays now calls bool on each element
On Python 2, void_array.astype(bool) would always return an array of
True, unless the dtype is V0. On Python 3, this operation would usually
crash. Going forwards, astype matches the behavior of bool(np.void),
considering a buffer of all zeros as false, and anything else as true.
Checks for V0 can still be done with arr.dtype.itemsize == 0.
MaskedArray.squeeze never returns np.ma.masked
np.squeeze is documented as returning a view, but the masked variant would
sometimes return masked, which is not a view. This has been fixed, so that
the result is always a view on the original masked array.
This breaks any code that used masked_arr.squeeze() is np.ma.masked, but
fixes code that writes to the result of .squeeze().
Renamed first parameter of can_cast from from to from_
The previous parameter name from is a reserved keyword in Python, which made
it difficult to pass the argument by name. This has been fixed by renaming
the parameter to from_.
isnat raises TypeError when passed wrong type
The ufunc isnat used to raise a ValueError when it was not passed
variables of type datetime or timedelta. This has been changed to
raising a TypeError.
dtype.__getitem__ raises TypeError when passed wrong type
When indexed with a float, the dtype object used to raise ValueError.
User-defined types now need to implement __str__ and __repr__
Previously, user-defined types could fall back to a default implementation of
__str__ and __repr__ implemented in numpy, but this has now been
removed. Now user-defined types will fall back to the python default
object.__str__ and object.__repr__.
Many changes to array printing, disableable with the new "legacy" printing mode
The str and repr of ndarrays and numpy scalars have been changed in
a variety of ways. These changes are likely to break downstream user's
doctests.
These new behaviors can be disabled to mostly reproduce numpy 1.13 behavior by
enabling the new 1.13 "legacy" printing mode. This is enabled by calling
np.set_printoptions(legacy="1.13"), or using the new legacy argument to
np.array2string, as np.array2string(arr, legacy='1.13').
In summary, the major changes are:
For floating-point types:
The repr of float arrays often omits a space previously printed
in the sign position. See the new sign option to np.set_printoptions.
Floating-point arrays and scalars use a new algorithm for decimal
representations, giving the shortest unique representation. This will
usually shorten float16 fractional output, and sometimes float32 and
float128 output. float64 should be unaffected. See the new
floatmode option to np.set_printoptions.
Float arrays printed in scientific notation no longer use fixed-precision,
and now instead show the shortest unique representation.
The str of floating-point scalars is no longer truncated in python2.
For other data types:
Non-finite complex scalars print like nanj instead of nan*j.
NaT values in datetime arrays are now properly aligned.
Arrays and scalars of np.void datatype are now printed using hex
notation.
For line-wrapping:
The "dtype" part of ndarray reprs will now be printed on the next line
if there isn't space on the last line of array output.
The linewidth format option is now always respected.
The repr or str of an array will never exceed this, unless a single
element is too wide.
The last line of an array string will never have more elements than earlier
lines.
An extra space is no longer inserted on the first line if the elements are
too wide.
For summarization (the use of ... to shorten long arrays):
A trailing comma is no longer inserted for str.
Previously, str(np.arange(1001)) gave
'[ 0 1 2 ..., 998 999 1000]', which has an extra comma.
For arrays of 2-D and beyond, when ... is printed on its own line in
order to summarize any but the last axis, newlines are now appended to that
line to match its leading newlines and a trailing space character is
removed.
MaskedArray arrays now separate printed elements with commas, always
print the dtype, and correctly wrap the elements of long arrays to multiple
lines. If there is more than 1 dimension, the array attributes are now
printed in a new "left-justified" printing style.
recarray arrays no longer print a trailing space before their dtype, and
wrap to the right number of columns.
0d arrays no longer have their own idiosyncratic implementations of str
and repr. The style argument to np.array2string is deprecated.
Arrays of bool datatype will omit the datatype in the repr.
User-defined dtypes (subclasses of np.generic) now need to
implement __str__ and __repr__.
You may want to do something like::
FIXME: Set numpy array str/repr to legacy behaviour on numpy > 1.13
Some of these changes are described in more detail below.
C API changes
PyPy compatible alternative to UPDATEIFCOPY arrays
UPDATEIFCOPY arrays are contiguous copies of existing arrays, possibly with
different dimensions, whose contents are copied back to the original array when
their refcount goes to zero and they are deallocated. Because PyPy does not use
refcounts, they do not function correctly with PyPy. NumPy is in the process of
eliminating their use internally and two new C-API functions,
PyArray_SetWritebackIfCopyBase
PyArray_ResolveWritebackIfCopy,
have been added together with a complimentary flag,
NPY_ARRAY_WRITEBACKIFCOPY. Using the new functionality also requires that
some flags be changed when new arrays are created, to wit:
NPY_ARRAY_INOUT_ARRAY should be replaced by NPY_ARRAY_INOUT_ARRAY2 and
NPY_ARRAY_INOUT_FARRAY should be replaced by NPY_ARRAY_INOUT_FARRAY2.
Arrays created with these new flags will then have the WRITEBACKIFCOPY
semantics.
If PyPy compatibility is not a concern, these new functions can be ignored,
although there will be a DeprecationWarning. If you do wish to pursue PyPy
compatibility, more information on these functions and their use may be found
in the c-api documentation and the example in how-to-extend.
genfromtxt, loadtxt, fromregex and savetxt can now handle files
with arbitrary encoding supported by Python via the encoding argument.
For backward compatibility the argument defaults to the special bytes value
which continues to treat text as raw byte values and continues to pass latin1
encoded bytes to custom converters.
Using any other value (including None for system default) will switch the
functions to real text IO so one receives unicode strings instead of bytes in
the resulting arrays.
External nose plugins are usable by numpy.testing.Tester
numpy.testing.Tester is now aware of nose plugins that are outside the
nose built-in ones. This allows using, for example, nose-timer like
so: np.test(extra_argv=['--with-timer', '--timer-top-n', '20']) to
obtain the runtime of the 20 slowest tests. An extra keyword timer was
also added to Tester.test, so np.test(timer=20) will also report the 20
slowest tests.
parametrize decorator added to numpy.testing
A basic parametrize decorator is now available in numpy.testing. It is
intended to allow rewriting yield based tests that have been deprecated in
pytest so as to facilitate the transition to pytest in the future. The nose
testing framework has not been supported for several years and looks like
abandonware.
The new parametrize decorator does not have the full functionality of the
one in pytest. It doesn't work for classes, doesn't support nesting, and does
not substitute variable names. Even so, it should be adequate to rewrite the
NumPy tests.
chebinterpolate function added to numpy.polynomial.chebyshev
The new chebinterpolate function interpolates a given function at the
Chebyshev points of the first kind. A new Chebyshev.interpolate class
method adds support for interpolation over arbitrary intervals using the scaled
and shifted Chebyshev points of the first kind.
Support for reading lzma compressed text files in Python 3
With Python versions containing the lzma module the text IO functions can
now transparently read from files with xz or lzma extension.
sign option added to np.setprintoptions and np.array2string
This option controls printing of the sign of floating-point types, and may be
one of the characters '-', '+' or ' '. With '+' numpy always prints the sign of
positive values, with ' ' it always prints a space (whitespace character) in
the sign position of positive values, and with '-' it will omit the sign
character for positive values. The new default is '-'.
This new default changes the float output relative to numpy 1.13. The old
behavior can be obtained in 1.13 "legacy" printing mode, see compatibility
notes above.
hermitian option added tonp.linalg.matrix_rank
The new hermitian option allows choosing between standard SVD based matrix
rank calculation and the more efficient eigenvalue based method for
symmetric/hermitian matrices.
threshold and edgeitems options added to np.array2string
These options could previously be controlled using np.set_printoptions, but
now can be changed on a per-call basis as arguments to np.array2string.
concatenate and stack gained an out argument
A preallocated buffer of the desired dtype can now be used for the output of
these functions.
Support for PGI flang compiler on Windows
The PGI flang compiler is a Fortran front end for LLVM released by NVIDIA under
the Apache 2 license. It can be invoked by ::
There is little experience with this new compiler, so any feedback from people
using it will be appreciated.
Improvements
Numerator degrees of freedom in random.noncentral_f need only be positive.
Prior to NumPy 1.14.0, the numerator degrees of freedom needed to be > 1, but
the distribution is valid for values > 0, which is the new requirement.
The GIL is released for all np.einsum variations
Some specific loop structures which have an accelerated loop version
did not release the GIL prior to NumPy 1.14.0. This oversight has been
fixed.
The np.einsum function will use BLAS when possible and optimize by default
The np.einsum function will now call np.tensordot when appropriate.
Because np.tensordot uses BLAS when possible, that will speed up execution.
By default, np.einsum will also attempt optimization as the overhead is
small relative to the potential improvement in speed.
f2py now handles arrays of dimension 0
f2py now allows for the allocation of arrays of dimension 0. This allows
for more consistent handling of corner cases downstream.
numpy.distutils supports using MSVC and mingw64-gfortran together
Numpy distutils now supports using Mingw64 gfortran and MSVC compilers
together. This enables the production of Python extension modules on Windows
containing Fortran code while retaining compatibility with the
binaries distributed by Python.org. Not all use cases are supported,
but most common ways to wrap Fortran for Python are functional.
Compilation in this mode is usually enabled automatically, and can be
selected via the --fcompiler and --compiler options to
setup.py. Moreover, linking Fortran codes to static OpenBLAS is
supported; by default a gfortran compatible static archive
openblas.a is looked for.
np.linalg.pinv now works on stacked matrices
Previously it was limited to a single 2d array.
numpy.save aligns data to 64 bytes instead of 16
Saving NumPy arrays in the npy format with numpy.save inserts
padding before the array data to align it at 64 bytes. Previously
this was only 16 bytes (and sometimes less due to a bug in the code
for version 2). Now the alignment is 64 bytes, which matches the
widest SIMD instruction set commonly available, and is also the most
common cache line size. This makes npy files easier to use in
programs which open them with mmap, especially on Linux where an
mmap offset must be a multiple of the page size.
NPZ files now can be written without using temporary files
In Python 3.6+ numpy.savez and numpy.savez_compressed now write
directly to a ZIP file, without creating intermediate temporary files.
Better support for empty structured and string types
Structured types can contain zero fields, and string dtypes can contain zero
characters. Zero-length strings still cannot be created directly, and must be
constructed through structured dtypes::
It was always possible to work with these, but the following operations are
now supported for these arrays:
arr.sort()
arr.view(bytes)
arr.resize(...)
pickle.dumps(arr)
Support for decimal.Decimal in np.lib.financial
Unless otherwise stated all functions within the financial package now
support using the decimal.Decimal built-in type.
Float printing now uses "dragon4" algorithm for shortest decimal representation
The str and repr of floating-point values (16, 32, 64 and 128 bit) are
now printed to give the shortest decimal representation which uniquely
identifies the value from others of the same type. Previously this was only
true for float64 values. The remaining float types will now often be shorter
than in numpy 1.13. Arrays printed in scientific notation now also use the
shortest scientific representation, instead of fixed precision as before.
Additionally, the str of float scalars scalars will no longer be truncated
in python2, unlike python2 floats. np.double scalars now have a str
and repr identical to that of a python3 float.
New functions np.format_float_scientific and np.format_float_positional
are provided to generate these decimal representations.
A new option floatmode has been added to np.set_printoptions and
np.array2string, which gives control over uniqueness and rounding of
printed elements in an array. The new default is floatmode='maxprec' with
precision=8, which will print at most 8 fractional digits, or fewer if an
element can be uniquely represented with fewer. A useful new mode is
floatmode="unique", which will output enough digits to specify the array
elements uniquely.
Numpy complex-floating-scalars with values like inf*j or nan*j now
print as infj and nanj, like the pure-python complex type.
The FloatFormat and LongFloatFormat classes are deprecated and should
both be replaced by FloatingFormat. Similarly ComplexFormat and
LongComplexFormat should be replaced by ComplexFloatingFormat.
void datatype elements are now printed in hex notation
A hex representation compatible with the python bytes type is now printed
for unstructured np.void elements, e.g., V4 datatype. Previously, in
python2 the raw void data of the element was printed to stdout, or in python3
the integer byte values were shown.
printing style for void datatypes is now independently customizable
The printing style of np.void arrays is now independently customizable
using the formatter argument to np.set_printoptions, using the
'void' key, instead of the catch-all numpystr key as before.
Reduced memory usage of np.loadtxt
np.loadtxt now reads files in chunks instead of all at once which decreases
its memory usage significantly for large files.
Changes
Multiple-field indexing/assignment of structured arrays
The indexing and assignment of structured arrays with multiple fields has
changed in a number of ways, as warned about in previous releases.
First, indexing a structured array with multiple fields, e.g.,
arr[['f1', 'f3']], returns a view into the original array instead of a
copy. The returned view will have extra padding bytes corresponding to
intervening fields in the original array, unlike the copy in 1.13, which will
affect code such as arr[['f1', 'f3']].view(newdtype).
Second, assignment between structured arrays will now occur "by position"
instead of "by field name". The Nth field of the destination will be set to the
Nth field of the source regardless of field name, unlike in numpy versions 1.6
to 1.13 in which fields in the destination array were set to the
identically-named field in the source array or to 0 if the source did not have
a field.
Correspondingly, the order of fields in a structured dtypes now matters when
computing dtype equality. For example, with the dtypes ::
the expression x == y will now return False, unlike before.
This makes dictionary based dtype specifications like
dtype({'a': ('i4', 0), 'b': ('f4', 4)}) dangerous in python < 3.6
since dict key order is not preserved in those versions.
Assignment from a structured array to a boolean array now raises a ValueError,
unlike in 1.13, where it always set the destination elements to True.
Assignment from structured array with more than one field to a non-structured
array now raises a ValueError. In 1.13 this copied just the first field of the
source to the destination.
Using field "titles" in multiple-field indexing is now disallowed, as is
repeating a field name in a multiple-field index.
The documentation for structured arrays in the user guide has been
significantly updated to reflect these changes.
Integer and Void scalars are now unaffected by np.set_string_function
Previously, unlike most other numpy scalars, the str and repr of
integer and void scalars could be controlled by np.set_string_function.
This is no longer possible.
0d array printing changed, style arg of array2string deprecated
Previously the str and repr of 0d arrays had idiosyncratic
implementations which returned str(a.item()) and 'array(' + repr(a.item()) + ')' respectively for 0d array a, unlike both numpy
scalars and higher dimension ndarrays.
Now, the str of a 0d array acts like a numpy scalar using str(a[()])
and the repr acts like higher dimension arrays using formatter(a[()]),
where formatter can be specified using np.set_printoptions. The
style argument of np.array2string is deprecated.
This new behavior is disabled in 1.13 legacy printing mode, see compatibility
notes above.
Seeding RandomState using an array requires a 1-d array
RandomState previously would accept empty arrays or arrays with 2 or more
dimensions, which resulted in either a failure to seed (empty arrays) or for
some of the passed values to be ignored when setting the seed.
MaskedArray objects show a more useful repr
The repr of a MaskedArray is now closer to the python code that would
produce it, with arrays now being shown with commas and dtypes. Like the other
formatting changes, this can be disabled with the 1.13 legacy printing mode in
order to help transition doctests.
The repr of np.polynomial classes is more explicit
It now shows the domain and window parameters as keyword arguments to make
them more clear::
This is a bugfix release for some problems found since 1.13.1. The most
important fixes are for CVE-2017-12852 and temporary elision. Users of earlier
versions of 1.13 should upgrade.
The Python versions supported are 2.7 and 3.4 - 3.6. The Python 3.6 wheels
available from PIP are built with Python 3.6.2 and should be compatible with
all previous versions of Python 3.6. It was cythonized with Cython 0.26.1,
which should be free of the bugs found in 0.27 while also being compatible with
Python 3.7-dev. The Windows wheels were built with OpenBlas instead ATLAS,
which should improve the performance of the linear algebra functions.
The NumPy 1.13.3 release is a re-release of 1.13.2, which suffered from a
bug in Cython 0.27.0.
Contributors
A total of 12 people contributed to this release. People with a "+" by their
names contributed a patch for the first time.
Allan Haldane
Brandon Carter
Charles Harris
Eric Wieser
Iryna Shcherbina +
James Bourbeau +
Jonathan Helmus
Julian Taylor
Matti Picus
Michael Lamparski +
Michael Seifert
Ralf Gommers
Pull requests merged
A total of 22 pull requests were merged for this release.
9390 BUG: Return the poly1d coefficients array directly
9555 BUG: Fix regression in 1.13.x in distutils.mingw32ccompiler.
9556 BUG: Fix true_divide when dtype=np.float64 specified.
9557 DOC: Fix some rst markup in numpy/doc/basics.py.
9558 BLD: Remove -xhost flag from IntelFCompiler.
9559 DOC: Removes broken docstring example (source code, png, pdf)...
9580 BUG: Add hypot and cabs functions to WIN32 blacklist.
9732 BUG: Make scalar function elision check if temp is writeable.
9736 BUG: Various fixes to np.gradient
9742 BUG: Fix np.pad for CVE-2017-12852
9744 BUG: Check for exception in sort functions, add tests
9745 DOC: Add whitespace after "versionadded::" directive so it actually...
9746 BUG: Memory leak in np.dot of size 0
9747 BUG: Adjust gfortran version search regex
9757 BUG: Cython 0.27 breaks NumPy on Python 3.
9764 BUG: Ensure _npy_scaled_cexp{,f,l} is defined when needed.
9765 BUG: PyArray_CountNonzero does not check for exceptions
9766 BUG: Fixes histogram monotonicity check for unsigned bin values
9767 BUG: Ensure consistent result dtype of count_nonzero
9771 BUG: MAINT: Fix mtrand for Cython 0.27.
9772 DOC: Create the 1.13.2 release notes.
9794 DOC: Create 1.13.3 release notes.
=========================
1.13.1
==========================
This is a bugfix release for problems found in 1.13.0. The major changes are
fixes for the new memory overlap detection and temporary elision as well as
reversion of the removal of the boolean binary - operator. Users of 1.13.0
should upgrade.
Thr Python versions supported are 2.7 and 3.4 - 3.6. Note that the Python 3.6
wheels available from PIP are built against 3.6.1, hence will not work when
used with 3.6.0 due to Python bug 29943_. NumPy 1.13.2 will be released shortly
after Python 3.6.2 is out to fix that problem. If you are using 3.6.0 the
workaround is to upgrade to 3.6.1 or use an earlier Python version.
A total of 19 pull requests were merged for this release.
9240 DOC: BLD: fix lots of Sphinx warnings/errors.
9255 Revert "DEP: Raise TypeError for subtract(bool, bool)."
9261 BUG: don't elide into readonly and updateifcopy temporaries for...
9262 BUG: fix missing keyword rename for common block in numpy.f2py
9263 BUG: handle resize of 0d array
9267 DOC: update f2py front page and some doc build metadata.
9299 BUG: Fix Intel compilation on Unix.
9317 BUG: fix wrong ndim used in empty where check
9319 BUG: Make extensions compilable with MinGW on Py2.7
9339 BUG: Prevent crash if ufunc doc string is null
9340 BUG: umath: un-break ufunc where= when no out= is given
9371 DOC: Add isnat/positive ufunc to documentation
9372 BUG: Fix error in fromstring function from numpy.core.records...
9373 BUG: ')' is printed at the end pointer of the buffer in numpy.f2py.
9374 DOC: Create NumPy 1.13.1 release notes.
9376 BUG: Prevent hang traversing ufunc userloop linked list
9377 DOC: Use x1 and x2 in the heaviside docstring.
9378 DOC: Add $PARAMS to the isnat docstring
9379 DOC: Update the 1.13.1 release notes
Contributors
A total of 12 people contributed to this release. People with a "+" by their
names contributed a patch for the first time.
Andras Deak +
Bob Eldering +
Charles Harris
Daniel Hrisca +
Eric Wieser
Joshua Leahy +
Julian Taylor
Michael Seifert
Pauli Virtanen
Ralf Gommers
Roland Kaufmann
Warren Weckesser
=========================
1.13.0
==========================
This release supports Python 2.7 and 3.4 - 3.6.
Highlights
Operations like a + b + c will reuse temporaries on some platforms,
resulting in less memory use and faster execution.
Inplace operations check if inputs overlap outputs and create temporaries
to avoid problems.
New __array_ufunc__ attribute provides improved ability for classes to
override default ufunc behavior.
New np.block function for creating blocked arrays.
New functions
New np.positive ufunc.
New np.divmod ufunc provides more efficient divmod.
New np.isnat ufunc tests for NaT special values.
New np.heaviside ufunc computes the Heaviside function.
New np.isin function, improves on in1d.
New np.block function for creating blocked arrays.
New PyArray_MapIterArrayCopyIfOverlap added to NumPy C-API.
See below for details.
Deprecations
Calling np.fix, np.isposinf, and np.isneginf with f(x, y=out)
is deprecated - the argument should be passed as f(x, out=out), which
matches other ufunc-like interfaces.
Use of the C-API NPY_CHAR type number deprecated since version 1.7 will
now raise deprecation warnings at runtime. Extensions built with older f2py
versions need to be recompiled to remove the warning.
np.ma.argsort, np.ma.minimum.reduce, and np.ma.maximum.reduce
should be called with an explicit axis argument when applied to arrays with
more than 2 dimensions, as the default value of this argument (None) is
inconsistent with the rest of numpy (-1, 0, and 0, respectively).
np.ma.MaskedArray.mini is deprecated, as it almost duplicates the
functionality of np.MaskedArray.min. Exactly equivalent behaviour
can be obtained with np.ma.minimum.reduce.
The single-argument form of np.ma.minimum and np.ma.maximum is
deprecated. np.maximum. np.ma.minimum(x) should now be spelt
np.ma.minimum.reduce(x), which is consistent with how this would be done
with np.minimum.
Calling ndarray.conjugate on non-numeric dtypes is deprecated (it
should match the behavior of np.conjugate, which throws an error).
Calling expand_dims when the axis keyword does not satisfy
-a.ndim - 1 <= axis <= a.ndim, where a is the array being reshaped,
is deprecated.
Future Changes
Assignment between structured arrays with different field names will change
in NumPy 1.14. Previously, fields in the dst would be set to the value of the
identically-named field in the src. In numpy 1.14 fields will instead be
assigned 'by position': The n-th field of the dst will be set to the n-th
field of the src array. Note that the FutureWarning raised in NumPy 1.12
incorrectly reported this change as scheduled for NumPy 1.13 rather than
NumPy 1.14.
Build System Changes
numpy.distutils now automatically determines C-file dependencies with
GCC compatible compilers.
pyup-bot
commented
6 years ago
Updates
Here's a list of all the updates bundled in this pull request. I've added some links to make it easier for you to find all the information you need.
Changelogs
hypothesis 3.44.26 -> 3.45.0
filefinder2 -> 0.4.1
rosimport -> 0.2.1
pytest-xdist -> 1.22.0
numpy -> 1.14.0