Scheduled weekly dependency update for week 12

[pyup-bot]

Update biopython from 1.72 to 1.73.

The bot wasn't able to find a changelog for this release. Got an idea?

Links

• PyPI: https://pypi.org/project/biopython
• Changelog: https://pyup.io/changelogs/biopython/
• Homepage: https://biopython.org/

Update click-plugins from 1.0.3 to 1.0.4.

Changelog

1.0.4

------------------

- Preemptive fix for a breaking change in Click v7.  CLI command names generated from functions with underscores will have dashes instead of underscores.  See https://github.com/click-contrib/click-plugins/issues/19.

Links

• PyPI: https://pypi.org/project/click-plugins
• Changelog: https://pyup.io/changelogs/click-plugins/
• Repo: https://github.com/click-contrib/click-plugins

Update click from 6.7 to 7.0.

Changelog

7.0

-----------

Released 2018-09-25

-   Drop support for Python 2.6 and 3.3. (`967`_, `976`_)
-   Wrap ``click.Choice``'s missing message. (`202`_, `1000`_)
-   Add native ZSH autocompletion support. (`323`_, `865`_)
-   Document that ANSI color info isn't parsed from bytearrays in
 Python 2. (`334`_)
-   Document byte-stripping behavior of ``CliRunner``. (`334`_,
 `1010`_)
-   Usage errors now hint at the ``--help`` option. (`393`_, `557`_)
-   Implement streaming pager. (`409`_, `889`_)
-   Extract bar formatting to its own method. (`414`_)
-   Add ``DateTime`` type for converting input in given date time
 formats. (`423`_)
-   ``secho``'s first argument can now be ``None``, like in ``echo``.
 (`424`_)
-   Fixes a ``ZeroDivisionError`` in ``ProgressBar.make_step``, when the
 arg passed to the first call of ``ProgressBar.update`` is 0.
 (`447`_, `1012`_)
-   Show progressbar only if total execution time is visible. (`487`_)
-   Added the ability to hide commands and options from help. (`500`_)
-   Document that options can be ``required=True``. (`514`_, `1022`_)
-   Non-standalone calls to ``Context.exit`` return the exit code,
 rather than calling ``sys.exit``. (`533`_, `667`_, `1098`_)
-   ``click.getchar()`` returns Unicode in Python 3 on Windows,
 consistent with other platforms. (`537`_, `821`_, `822`_,
 `1088`_, `1108`_)
-   Added ``FloatRange`` type. (`538`_, `553`_)
-   Added support for bash completion of ``type=click.Choice`` for
 ``Options`` and ``Arguments``. (`535`_, `681`_)
-   Only allow one positional arg for ``Argument`` parameter
 declaration. (`568`_, `574`_, `1014`_)
-   Add ``case_sensitive=False`` as an option to Choice. (`569`_)
-   ``click.getchar()`` correctly raises ``KeyboardInterrupt`` on "^C"
 and ``EOFError`` on "^D" on Linux. (`583`_, `1115`_)
-   Fix encoding issue with ``click.getchar(echo=True)`` on Linux.
 (`1115`_)
-   ``param_hint`` in errors now derived from param itself. (`598`_,
 `704`_, `709`_)
-   Add a test that ensures that when an argument is formatted into a
 usage error, its metavar is used, not its name. (`612`_)
-   Allow setting ``prog_name`` as extra in ``CliRunner.invoke``.
 (`616`_, `999`_)
-   Help text taken from docstrings truncates at the ``\f`` form feed
 character, useful for hiding Sphinx-style parameter documentation.
 (`629`_, `1091`_)
-   ``launch`` now works properly under Cygwin. (`650`_)
-   Update progress after iteration. (`651`_, `706`_)
-   ``CliRunner.invoke`` now may receive ``args`` as a string
 representing a Unix shell command. (`664`_)
-   Make ``Argument.make_metavar()`` default to type metavar. (`675`_)
-   Add documentation for ``ignore_unknown_options``. (`684`_)
-   Add bright colors support for ``click.style`` and fix the reset
 option for parameters ``fg`` and ``bg``. (`703`_, `809`_)
-   Add ``show_envvar`` for showing environment variables in help.
 (`710`_)
-   Avoid ``BrokenPipeError`` during interpreter shutdown when stdout or
 stderr is a closed pipe. (`712`_, `1106`_)
-   Document customizing option names. (`725`_, `1016`_)
-   Disable ``sys._getframes()`` on Python interpreters that don't
 support it. (`728`_)
-   Fix bug in test runner when calling ``sys.exit`` with ``None``.
 (`739`_)
-   Clarify documentation on command line options. (`741`_, `1003`_)
-   Fix crash on Windows console. (`744`_)
-   Fix bug that caused bash completion to give improper completions on
 chained commands. (`754`_, `774`_)
-   Added support for dynamic bash completion from a user-supplied
 callback. (`755`_)
-   Added support for bash completions containing spaces. (`773`_)
-   Allow autocompletion function to determine whether or not to return
 completions that start with the incomplete argument. (`790`_,
 `806`_)
-   Fix option naming routine to match documentation and be
 deterministic. (`793`_, `794`_)
-   Fix path validation bug. (`795`_, `1020`_)
-   Add test and documentation for ``Option`` naming: functionality.
 (`799`_)
-   Update doc to match arg name for ``path_type``. (`801`_)
-   Raw strings added so correct escaping occurs. (`807`_)
-   Fix 16k character limit of ``click.echo`` on Windows. (`816`_,
 `819`_)
-   Overcome 64k character limit when writing to binary stream on
 Windows 7. (`825`_, `830`_)
-   Add bool conversion for "t" and "f". (`842`_)
-   ``NoSuchOption`` errors take ``ctx`` so that ``--help`` hint gets
 printed in error output. (`860`_)
-   Fixed the behavior of Click error messages with regards to Unicode
 on 2.x and 3.x. Message is now always Unicode and the str and
 Unicode special methods work as you expect on that platform.
 (`862`_)
-   Progress bar now uses stderr by default. (`863`_)
-   Add support for auto-completion documentation. (`866`_, `869`_)
-   Allow ``CliRunner`` to separate stdout and stderr. (`868`_)
-   Fix variable precedence. (`873`_, `874`_)
-   Fix invalid escape sequences. (`877`_)
-   Fix ``ResourceWarning`` that occurs during some tests. (`878`_)
-   When detecting a misconfigured locale, don't fail if the ``locale``
 command fails. (`880`_)
-   Add ``case_sensitive=False`` as an option to ``Choice`` types.
 (`887`_)
-   Force stdout/stderr writable. This works around issues with badly
 patched standard streams like those from Jupyter. (`918`_)
-   Fix completion of subcommand options after last argument (`919`_,
 `930`_)
-   ``_AtomicFile`` now uses the ``realpath`` of the original filename
 so that changing the working directory does not affect it.
 (`920`_)
-   Fix incorrect completions when defaults are present (`925`_,
 `930`_)
-   Add copy option attrs so that custom classes can be re-used.
 (`926`_, `994`_)
-   "x" and "a" file modes now use stdout when file is ``"-"``.
 (`929`_)
-   Fix missing comma in ``__all__`` list. (`935`_)
-   Clarify how parameters are named. (`949`_, `1009`_)
-   Stdout is now automatically set to non blocking. (`954`_)
-   Do not set options twice. (`962`_)
-   Move ``fcntl`` import. (`965`_)
-   Fix Google App Engine ``ImportError``. (`995`_)
-   Better handling of help text for dynamic default option values.
 (`996`_)
-   Fix ``get_winter_size()`` so it correctly returns ``(0,0)``.
 (`997`_)
-   Add test case checking for custom param type. (`1001`_)
-   Allow short width to address cmd formatting. (`1002`_)
-   Add details about Python version support. (`1004`_)
-   Added deprecation flag to commands. (`1005`_)
-   Fixed issues where ``fd`` was undefined. (`1007`_)
-   Fix formatting for short help. (`1008`_)
-   Document how ``auto_envvar_prefix`` works with command groups.
 (`1011`_)
-   Don't add newlines by default for progress bars. (`1013`_)
-   Use Python sorting order for ZSH completions. (`1047`_, `1059`_)
-   Document that parameter names are converted to lowercase by default.
 (`1055`_)
-   Subcommands that are named by the function now automatically have
 the underscore replaced with a dash. If you register a function
 named ``my_command`` it becomes ``my-command`` in the command line
 interface.
-   Hide hidden commands and options from completion. (`1058`_,
 `1061`_)
-   Fix absolute import blocking Click from being vendored into a
 project on Windows. (`1068`_, `1069`_)
-   Fix issue where a lowercase ``auto_envvar_prefix`` would not be
 converted to uppercase. (`1105`_)

.. _202: https://github.com/pallets/click/issues/202
.. _323: https://github.com/pallets/click/issues/323
.. _334: https://github.com/pallets/click/issues/334
.. _393: https://github.com/pallets/click/issues/393
.. _409: https://github.com/pallets/click/issues/409
.. _414: https://github.com/pallets/click/pull/414
.. _423: https://github.com/pallets/click/pull/423
.. _424: https://github.com/pallets/click/pull/424
.. _447: https://github.com/pallets/click/issues/447
.. _487: https://github.com/pallets/click/pull/487
.. _500: https://github.com/pallets/click/pull/500
.. _514: https://github.com/pallets/click/issues/514
.. _533: https://github.com/pallets/click/pull/533
.. _535: https://github.com/pallets/click/issues/535
.. _537: https://github.com/pallets/click/issues/537
.. _538: https://github.com/pallets/click/pull/538
.. _553: https://github.com/pallets/click/pull/553
.. _557: https://github.com/pallets/click/pull/557
.. _568: https://github.com/pallets/click/issues/568
.. _569: https://github.com/pallets/click/issues/569
.. _574: https://github.com/pallets/click/issues/574
.. _583: https://github.com/pallets/click/issues/583
.. _598: https://github.com/pallets/click/issues/598
.. _612: https://github.com/pallets/click/pull/612
.. _616: https://github.com/pallets/click/issues/616
.. _629: https://github.com/pallets/click/pull/629
.. _650: https://github.com/pallets/click/pull/650
.. _651: https://github.com/pallets/click/issues/651
.. _664: https://github.com/pallets/click/pull/664
.. _667: https://github.com/pallets/click/issues/667
.. _675: https://github.com/pallets/click/pull/675
.. _681: https://github.com/pallets/click/pull/681
.. _684: https://github.com/pallets/click/pull/684
.. _703: https://github.com/pallets/click/issues/703
.. _704: https://github.com/pallets/click/issues/704
.. _706: https://github.com/pallets/click/pull/706
.. _709: https://github.com/pallets/click/pull/709
.. _710: https://github.com/pallets/click/pull/710
.. _712: https://github.com/pallets/click/pull/712
.. _719: https://github.com/pallets/click/issues/719
.. _725: https://github.com/pallets/click/issues/725
.. _728: https://github.com/pallets/click/pull/728
.. _739: https://github.com/pallets/click/pull/739
.. _741: https://github.com/pallets/click/issues/741
.. _744: https://github.com/pallets/click/issues/744
.. _754: https://github.com/pallets/click/issues/754
.. _755: https://github.com/pallets/click/pull/755
.. _773: https://github.com/pallets/click/pull/773
.. _774: https://github.com/pallets/click/pull/774
.. _790: https://github.com/pallets/click/issues/790
.. _793: https://github.com/pallets/click/issues/793
.. _794: https://github.com/pallets/click/pull/794
.. _795: https://github.com/pallets/click/issues/795
.. _799: https://github.com/pallets/click/pull/799
.. _801: https://github.com/pallets/click/pull/801
.. _806: https://github.com/pallets/click/pull/806
.. _807: https://github.com/pallets/click/pull/807
.. _809: https://github.com/pallets/click/pull/809
.. _816: https://github.com/pallets/click/pull/816
.. _819: https://github.com/pallets/click/pull/819
.. _821: https://github.com/pallets/click/issues/821
.. _822: https://github.com/pallets/click/issues/822
.. _825: https://github.com/pallets/click/issues/825
.. _830: https://github.com/pallets/click/pull/830
.. _842: https://github.com/pallets/click/pull/842
.. _860: https://github.com/pallets/click/issues/860
.. _862: https://github.com/pallets/click/issues/862
.. _863: https://github.com/pallets/click/pull/863
.. _865: https://github.com/pallets/click/pull/865
.. _866: https://github.com/pallets/click/issues/866
.. _868: https://github.com/pallets/click/pull/868
.. _869: https://github.com/pallets/click/pull/869
.. _873: https://github.com/pallets/click/issues/873
.. _874: https://github.com/pallets/click/pull/874
.. _877: https://github.com/pallets/click/pull/877
.. _878: https://github.com/pallets/click/pull/878
.. _880: https://github.com/pallets/click/pull/880
.. _883: https://github.com/pallets/click/pull/883
.. _887: https://github.com/pallets/click/pull/887
.. _889: https://github.com/pallets/click/pull/889
.. _918: https://github.com/pallets/click/pull/918
.. _919: https://github.com/pallets/click/issues/919
.. _920: https://github.com/pallets/click/pull/920
.. _925: https://github.com/pallets/click/issues/925
.. _926: https://github.com/pallets/click/issues/926
.. _929: https://github.com/pallets/click/pull/929
.. _930: https://github.com/pallets/click/pull/930
.. _935: https://github.com/pallets/click/pull/935
.. _949: https://github.com/pallets/click/issues/949
.. _954: https://github.com/pallets/click/pull/954
.. _962: https://github.com/pallets/click/pull/962
.. _965: https://github.com/pallets/click/pull/965
.. _967: https://github.com/pallets/click/pull/967
.. _976: https://github.com/pallets/click/pull/976
.. _990: https://github.com/pallets/click/pull/990
.. _991: https://github.com/pallets/click/pull/991
.. _993: https://github.com/pallets/click/pull/993
.. _994: https://github.com/pallets/click/pull/994
.. _995: https://github.com/pallets/click/pull/995
.. _996: https://github.com/pallets/click/pull/996
.. _997: https://github.com/pallets/click/pull/997
.. _999: https://github.com/pallets/click/pull/999
.. _1000: https://github.com/pallets/click/pull/1000
.. _1001: https://github.com/pallets/click/pull/1001
.. _1002: https://github.com/pallets/click/pull/1002
.. _1003: https://github.com/pallets/click/pull/1003
.. _1004: https://github.com/pallets/click/pull/1004
.. _1005: https://github.com/pallets/click/pull/1005
.. _1007: https://github.com/pallets/click/pull/1007
.. _1008: https://github.com/pallets/click/pull/1008
.. _1009: https://github.com/pallets/click/pull/1009
.. _1010: https://github.com/pallets/click/pull/1010
.. _1011: https://github.com/pallets/click/pull/1011
.. _1012: https://github.com/pallets/click/pull/1012
.. _1013: https://github.com/pallets/click/pull/1013
.. _1014: https://github.com/pallets/click/pull/1014
.. _1016: https://github.com/pallets/click/pull/1016
.. _1020: https://github.com/pallets/click/pull/1020
.. _1022: https://github.com/pallets/click/pull/1022
.. _1027: https://github.com/pallets/click/pull/1027
.. _1047: https://github.com/pallets/click/pull/1047
.. _1055: https://github.com/pallets/click/pull/1055
.. _1058: https://github.com/pallets/click/pull/1058
.. _1059: https://github.com/pallets/click/pull/1059
.. _1061: https://github.com/pallets/click/pull/1061
.. _1068: https://github.com/pallets/click/issues/1068
.. _1069: https://github.com/pallets/click/pull/1069
.. _1088: https://github.com/pallets/click/issues/1088
.. _1091: https://github.com/pallets/click/pull/1091
.. _1098: https://github.com/pallets/click/pull/1098
.. _1105: https://github.com/pallets/click/pull/1105
.. _1106: https://github.com/pallets/click/pull/1106
.. _1108: https://github.com/pallets/click/pull/1108
.. _1115: https://github.com/pallets/click/pull/1115

Links

• PyPI: https://pypi.org/project/click
• Changelog: https://pyup.io/changelogs/click/
• Homepage: https://palletsprojects.com/p/click/

Update coverage from 4.5.1 to 4.5.3.

The bot wasn't able to find a changelog for this release. Got an idea?

Links

• PyPI: https://pypi.org/project/coverage
• Changelog: https://pyup.io/changelogs/coverage/
• Repo: https://github.com/nedbat/coveragepy

Update matplotlib from 3.0.0 to 3.0.3.

Changelog

Links

• PyPI: https://pypi.org/project/matplotlib
• Changelog: https://pyup.io/changelogs/matplotlib/
• Homepage: http://matplotlib.org

Update numpy from 1.15.2 to 1.16.2.

Changelog

1.16.1

==========================

The NumPy 1.16.1 release fixes bugs reported against the 1.16.0 release, and
also backports several enhancements from master that seem appropriate for a
release series that is the last to support Python 2.7. The wheels on PyPI are
linked with OpenBLAS v0.3.4+,  which should fix the known threading issues
found in previous OpenBLAS versions.

Downstream developers building this release should use Cython >= 0.29.2 and, if
using OpenBLAS, OpenBLAS > v0.3.4.

If you are installing using pip, you may encounter a problem with older
installed versions of NumPy that pip did not delete becoming mixed with the
current version, resulting in an ``ImportError``. That problem is particularly
common on Debian derived distributions due to a modified pip.  The fix is to
make sure all previous NumPy versions installed by pip have been removed. See
`12736 <https://github.com/numpy/numpy/issues/12736>`__ for discussion of the
issue. Note that previously this problem resulted in an ``AttributeError``.


Contributors
============

A total of 16 people contributed to this release.  People with a "+" by their
names contributed a patch for the first time.

* Antoine Pitrou
* Arcesio Castaneda Medina +
* Charles Harris
* Chris Markiewicz +
* Christoph Gohlke
* Christopher J. Markiewicz +
* Daniel Hrisca +
* EelcoPeacs +
* Eric Wieser
* Kevin Sheppard
* Matti Picus
* OBATA Akio +
* Ralf Gommers
* Sebastian Berg
* Stephan Hoyer
* Tyler Reddy


Enhancements
============

* `12767 <https://github.com/numpy/numpy/pull/12767>`__: ENH: add mm->q floordiv
* `12768 <https://github.com/numpy/numpy/pull/12768>`__: ENH: port np.core.overrides to C for speed
* `12769 <https://github.com/numpy/numpy/pull/12769>`__: ENH: Add np.ctypeslib.as_ctypes_type(dtype), improve `np.ctypeslib.as_ctypes`
* `12773 <https://github.com/numpy/numpy/pull/12773>`__: ENH: add "max difference" messages to np.testing.assert_array_equal...
* `12820 <https://github.com/numpy/numpy/pull/12820>`__: ENH: Add mm->qm divmod
* `12890 <https://github.com/numpy/numpy/pull/12890>`__: ENH: add _dtype_ctype to namespace for freeze analysis


Compatibility notes
===================

* The changed error message emited by array comparison testing functions may
affect doctests. See below for detail.

* Casting from double and single denormals to float16 has been corrected.  In
some rare cases, this may result in results being rounded up instead of down,
changing the last bit (ULP) of the result.


New Features
============

divmod operation is now supported for two ``timedelta64`` operands
------------------------------------------------------------------
The divmod operator now handles two ``np.timedelta64`` operands, with
type signature ``mm->qm``.


Improvements
============

Further improvements to ``ctypes`` support in ``np.ctypeslib``
--------------------------------------------------------------
A new ``np.ctypeslib.as_ctypes_type`` function has been added, which can be
used to converts a `dtype` into a best-guess `ctypes` type. Thanks to this
new function, ``np.ctypeslib.as_ctypes`` now supports a much wider range of
array types, including structures, booleans, and integers of non-native
endianness.

Array comparison assertions include maximum differences
-------------------------------------------------------
Error messages from array comparison tests such as
`np.testing.assert_allclose` now include "max absolute difference" and
"max relative difference," in addition to the previous "mismatch" percentage.
This information makes it easier to update absolute and relative error
tolerances.


Changes
=======

``timedelta64 % 0`` behavior adjusted to return ``NaT``
-------------------------------------------------------
The modulus operation with two ``np.timedelta64`` operands now returns
``NaT`` in the case of division by zero, rather than returning zero





==========================

1.16.0

==========================

This NumPy release is the last one to support Python 2.7 and will be maintained
as a long term release with bug fixes until 2020.  Support for Python 3.4 been
dropped, the supported Python versions are 2.7 and 3.5-3.7. The wheels on PyPI
are linked with OpenBLAS v0.3.4+,  which should fix the known threading issues
found in previous OpenBLAS versions.

Downstream developers building this release should use Cython >= 0.29 and, if
using OpenBLAS, OpenBLAS > v0.3.4.

This release has seen a lot of refactoring and features many bug fixes, improved
code organization, and better cross platform compatibility. Not all of these
improvements will be visible to users, but they should help make maintenance
easier going forward.


Highlights
==========

* Experimental (opt-in only) support for overriding numpy functions,
see ``__array_function__`` below.

* The ``matmul`` function is now a ufunc. This provides better
performance and allows overriding with ``__array_ufunc__``.

* Improved support for the ARM and POWER architectures.

* Improved support for AIX and PyPy.

* Improved interop with ctypes.

* Improved support for PEP 3118.



New functions
=============

* New functions added to the `numpy.lib.recfuntions` module to ease the
structured assignment changes:

 * ``assign_fields_by_name``
 * ``structured_to_unstructured``
 * ``unstructured_to_structured``
 * ``apply_along_fields``
 * ``require_fields``

See the user guide at <https://docs.scipy.org/doc/numpy/user/basics.rec.html>
for more info.


New deprecations
================

* The type dictionaries `numpy.core.typeNA` and `numpy.core.sctypeNA` are
deprecated. They were buggy and not documented and will be removed in the
1.18 release. Use`numpy.sctypeDict` instead.

* The `numpy.asscalar` function is deprecated. It is an alias to the more
powerful `numpy.ndarray.item`, not tested, and fails for scalars.

* The `numpy.set_array_ops` and `numpy.get_array_ops` functions are deprecated.
As part of `NEP 15`, they have been deprecated along with the C-API functions
:c:func:`PyArray_SetNumericOps` and :c:func:`PyArray_GetNumericOps`. Users
who wish to override the inner loop functions in built-in ufuncs should use
:c:func:`PyUFunc_ReplaceLoopBySignature`.

* The `numpy.unravel_index` keyword argument ``dims`` is deprecated, use
``shape`` instead.

* The `numpy.histogram` ``normed`` argument is deprecated.  It was deprecated
previously, but no warning was issued.

* The ``positive`` operator (``+``) applied to non-numerical arrays is
deprecated. See below for details.

* Passing an iterator to the stack functions is deprecated


Expired deprecations
====================

* NaT comparisons now return ``False`` without a warning, finishing a
deprecation cycle begun in NumPy 1.11.

* ``np.lib.function_base.unique`` was removed, finishing a deprecation cycle
begun in NumPy 1.4. Use `numpy.unique` instead.

* multi-field indexing now returns views instead of copies, finishing a
deprecation cycle begun in NumPy 1.7. The change was previously attempted in
NumPy 1.14 but reverted until now.

* ``np.PackageLoader`` and ``np.pkgload`` have been removed. These were
deprecated in 1.10, had no tests, and seem to no longer work in 1.15.


Future changes
==============

* NumPy 1.17 will drop support for Python 2.7.


Compatibility notes
===================

f2py script on Windows
----------------------
On Windows, the installed script for running f2py is now an ``.exe`` file
rather than a ``*.py`` file and should be run from the command line as ``f2py``
whenever the ``Scripts`` directory is in the path. Running ``f2py`` as a module
``python -m numpy.f2py [...]`` will work without path modification in any
version of NumPy.

NaT comparisons
---------------
Consistent with the behavior of NaN, all comparisons other than inequality
checks with datetime64 or timedelta64 NaT ("not-a-time") values now always
return ``False``, and inequality checks with NaT now always return ``True``.
This includes comparisons beteween NaT values. For compatibility with the
old behavior, use ``np.isnat`` to explicitly check for NaT or convert
datetime64/timedelta64 arrays with ``.astype(np.int64)`` before making
comparisons.

complex64/128 alignment has changed
-----------------------------------
The memory alignment of complex types is now the same as a C-struct composed of
two floating point values, while before it was equal to the size of the type.
For many users (for instance on x64/unix/gcc) this means that complex64 is now
4-byte aligned instead of 8-byte aligned. An important consequence is that
aligned structured dtypes may now have a different size. For instance,
``np.dtype('c8,u1', align=True)`` used to have an itemsize of 16 (on x64/gcc)
but now it is 12.

More in detail, the complex64 type now has the same alignment as a C-struct
``struct {float r, i;}``, according to the compiler used to compile numpy, and
similarly for the complex128 and complex256 types.

nd_grid __len__ removal
-----------------------
``len(np.mgrid)`` and ``len(np.ogrid)`` are now considered nonsensical
and raise a ``TypeError``.

``np.unravel_index`` now accepts ``shape`` keyword argument
-----------------------------------------------------------
Previously, only the ``dims`` keyword argument was accepted
for specification of the shape of the array to be used
for unraveling. ``dims`` remains supported, but is now deprecated.

multi-field views return a view instead of a copy
-------------------------------------------------
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 often have extra padding bytes corresponding to intervening fields in the
original array, unlike before, which will affect code such as
``arr[['f1', 'f3']].view('float64')``. This change has been planned since numpy
1.7. Operations hitting this path have emitted ``FutureWarnings`` since then.
Additional ``FutureWarnings`` about this change were added in 1.12.

To help users update their code to account for these changes, a number of
functions have been added to the ``numpy.lib.recfunctions`` module which
safely allow such operations. For instance, the code above can be replaced
with ``structured_to_unstructured(arr[['f1', 'f3']], dtype='float64')``.
See the "accessing multiple fields" section of the
`user guide <https://docs.scipy.org/doc/numpy/user/basics.rec.htmlaccessing-multiple-fields>`__.


C API changes
=============

The :c:data:`NPY_API_VERSION` was incremented to 0x0000D, due to the addition
of:

* :c:member:`PyUFuncObject.core_dim_flags`
* :c:member:`PyUFuncObject.core_dim_sizes`
* :c:member:`PyUFuncObject.identity_value`
* :c:function:`PyUFunc_FromFuncAndDataAndSignatureAndIdentity`


New Features
============

Integrated squared error (ISE) estimator added to ``histogram``
---------------------------------------------------------------
This method (``bins='stone'``) for optimizing the bin number is a
generalization of the Scott's rule. The Scott's rule assumes the distribution
is approximately Normal, while the ISE_ is a non-parametric method based on
cross-validation.

.. _ISE: https://en.wikipedia.org/wiki/HistogramMinimizing_cross-validation_estimated_squared_error

``max_rows`` keyword added for ``np.loadtxt``
---------------------------------------------
New keyword ``max_rows`` in `numpy.loadtxt` sets the maximum rows of the
content to be read after ``skiprows``, as in `numpy.genfromtxt`.

modulus operator support added for ``np.timedelta64`` operands
--------------------------------------------------------------
The modulus (remainder) operator is now supported for two operands
of type ``np.timedelta64``. The operands may have different units
and the return value will match the type of the operands.


Improvements
============

no-copy pickling of numpy arrays
--------------------------------
Up to protocol 4, numpy array pickling created 2 spurious copies of the data
being serialized.  With pickle protocol 5, and the ``PickleBuffer`` API, a
large variety of numpy arrays can now be serialized without any copy using
out-of-band buffers, and with one less copy using in-band buffers. This
results, for large arrays, in an up to 66% drop in peak memory usage.

build shell independence
------------------------
NumPy builds should no longer interact with the host machine
shell directly. ``exec_command`` has been replaced with
``subprocess.check_output`` where appropriate.

`np.polynomial.Polynomial` classes render in LaTeX in Jupyter notebooks
-----------------------------------------------------------------------
When used in a front-end that supports it, `Polynomial` instances are now
rendered through LaTeX. The current format is experimental, and is subject to
change.

``randint`` and ``choice`` now work on empty distributions
----------------------------------------------------------
Even when no elements needed to be drawn, ``np.random.randint`` and
``np.random.choice`` raised an error when the arguments described an empty
distribution. This has been fixed so that e.g.
``np.random.choice([], 0) == np.array([], dtype=float64)``.

``linalg.lstsq``, ``linalg.qr``, and ``linalg.svd`` now work with empty arrays
------------------------------------------------------------------------------
Previously, a ``LinAlgError`` would be raised when an empty matrix/empty
matrices (with zero rows and/or columns) is/are passed in. Now outputs of
appropriate shapes are returned.

Chain exceptions to give better error messages for invalid PEP3118 format strings
---------------------------------------------------------------------------------
This should help track down problems.

Einsum optimization path updates and efficiency improvements
------------------------------------------------------------
Einsum was synchronized with the current upstream work.

`numpy.angle` and `numpy.expand_dims` now work on ``ndarray`` subclasses
------------------------------------------------------------------------
In particular, they now work for masked arrays.

``NPY_NO_DEPRECATED_API`` compiler warning suppression
------------------------------------------------------
Setting ``NPY_NO_DEPRECATED_API`` to a value of 0 will suppress the current compiler
warnings when the deprecated numpy API is used.

``np.diff`` Added kwargs prepend and append
-------------------------------------------
New kwargs ``prepend`` and ``append``, allow for values to be inserted on
either end of the differences.  Similar to options for `ediff1d`. Now the
inverse of `cumsum` can be obtained easily via ``prepend=0``.

ARM support updated
-------------------
Support for ARM CPUs has been updated to accommodate 32 and 64 bit targets,
and also big and little endian byte ordering. AARCH32 memory alignment issues
have been addressed. CI testing has been expanded to include AARCH64 targets
via the services of shippable.com.

Appending to build flags
------------------------
`numpy.distutils` has always overridden rather than appended to `LDFLAGS` and
other similar such environment variables for compiling Fortran extensions.
Now, if the `NPY_DISTUTILS_APPEND_FLAGS` environment variable is set to 1, the
behavior will be appending.  This applied to: `LDFLAGS`, `F77FLAGS`,
`F90FLAGS`, `FREEFLAGS`, `FOPT`, `FDEBUG`, and `FFLAGS`.  See gh-11525 for more
details.

Generalized ufunc signatures now allow fixed-size dimensions
------------------------------------------------------------
By using a numerical value in the signature of a generalized ufunc, one can
indicate that the given function requires input or output to have dimensions
with the given size. E.g., the signature of a function that converts a polar
angle to a two-dimensional cartesian unit vector would be ``()->(2)``; that
for one that converts two spherical angles to a three-dimensional unit vector
would be ``(),()->(3)``; and that for the cross product of two
three-dimensional vectors would be ``(3),(3)->(3)``.

Note that to the elementary function these dimensions are not treated any
differently from variable ones indicated with a name starting with a letter;
the loop still is passed the corresponding size, but it can now count on that
size being equal to the fixed one given in the signature.

Generalized ufunc signatures now allow flexible dimensions
----------------------------------------------------------
Some functions, in particular numpy's implementation of ` as ``matmul``,
are very similar to generalized ufuncs in that they operate over core
dimensions, but one could not present them as such because they were able to
deal with inputs in which a dimension is missing. To support this, it is now
allowed to postfix a dimension name with a question mark to indicate that the
dimension does not necessarily have to be present.

With this addition, the signature for ``matmul`` can be expressed as
``(m?,n),(n,p?)->(m?,p?)``.  This indicates that if, e.g., the second operand
has only one dimension, for the purposes of the elementary function it will be
treated as if that input has core shape ``(n, 1)``, and the output has the
corresponding core shape of ``(m, 1)``. The actual output array, however, has
the flexible dimension removed, i.e., it will have shape ``(..., m)``.
Similarly, if both arguments have only a single dimension, the inputs will be
presented as having shapes ``(1, n)`` and ``(n, 1)`` to the elementary
function, and the output as ``(1, 1)``, while the actual output array returned
will have shape ``()``. In this way, the signature allows one to use a
single elementary function for four related but different signatures,
``(m,n),(n,p)->(m,p)``, ``(n),(n,p)->(p)``, ``(m,n),(n)->(m)`` and
``(n),(n)->()``.

``np.clip`` and the ``clip`` method check for memory overlap
------------------------------------------------------------
The ``out`` argument to these functions is now always tested for memory overlap
to avoid corrupted results when memory overlap occurs.

New value ``unscaled`` for option ``cov`` in ``np.polyfit``
-----------------------------------------------------------
A further possible value has been added to the ``cov`` parameter of the
``np.polyfit`` function. With ``cov='unscaled'`` the scaling of the covariance
matrix is disabled completely (similar to setting ``absolute_sigma=True`` in
``scipy.optimize.curve_fit``). This would be useful in occasions, where the
weights are given by 1/sigma with sigma being the (known) standard errors of
(Gaussian distributed) data points, in which case the unscaled matrix is
already a correct estimate for the covariance matrix.

Detailed docstrings for scalar numeric types
--------------------------------------------
The ``help`` function, when applied to numeric types such as `numpy.intc`,
`numpy.int_`, and `numpy.longlong`, now lists all of the aliased names for that
type, distinguishing between platform -dependent and -independent aliases.

``__module__`` attribute now points to public modules
-----------------------------------------------------
The ``__module__`` attribute on most NumPy functions has been updated to refer
to the preferred public module from which to access a function, rather than
the module in which the function happens to be defined. This produces more
informative displays for functions in tools such as IPython, e.g., instead of
``<function 'numpy.core.fromnumeric.sum'>`` you now see
``<function 'numpy.sum'>``.

Large allocations marked as suitable for transparent hugepages
--------------------------------------------------------------
On systems that support transparent hugepages over the madvise system call
numpy now marks that large memory allocations can be backed by hugepages which
reduces page fault overhead and can in some fault heavy cases improve
performance significantly. On Linux the setting for huge pages to be used,
`/sys/kernel/mm/transparent_hugepage/enabled`, must be at least `madvise`.
Systems which already have it set to `always` will not see much difference as
the kernel will automatically use huge pages where appropriate.

Users of very old Linux kernels (~3.x and older) should make sure that
`/sys/kernel/mm/transparent_hugepage/defrag` is not set to `always` to avoid
performance problems due concurrency issues in the memory defragmentation.

Alpine Linux (and other musl c library distros) support
-------------------------------------------------------
We now default to use `fenv.h` for floating point status error reporting.
Previously we had a broken default that sometimes would not report underflow,
overflow, and invalid floating point operations. Now we can support non-glibc
distrubutions like Alpine Linux as long as they ship `fenv.h`.

Speedup ``np.block`` for large arrays
-------------------------------------
Large arrays (greater than ``512 * 512``) now use a blocking algorithm based on
copying the data directly into the appropriate slice of the resulting array.
This results in significant speedups for these large arrays, particularly for
arrays being blocked along more than 2 dimensions.

``arr.ctypes.data_as(...)`` holds a reference to arr
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Previously the caller was responsible for keeping the array alive for the
lifetime of the pointer.

Speedup ``np.take`` for read-only arrays
----------------------------------------
The implementation of ``np.take`` no longer makes an unnecessary copy of the
source array when its ``writeable`` flag is set to ``False``.

Support path-like objects for more functions
--------------------------------------------
The ``np.core.records.fromfile`` function now supports ``pathlib.Path``
and other path-like objects in addition to a file object. Furthermore, the
``np.load`` function now also supports path-like objects when using memory
mapping (``mmap_mode`` keyword argument).

Better behaviour of ufunc identities during reductions
------------------------------------------------------
Universal functions have an ``.identity`` which is used when ``.reduce`` is
called on an empty axis.

As of this release, the logical binary ufuncs, `logical_and`, `logical_or`,
and `logical_xor`, now have ``identity`` s of type `bool`, where previously they
were of type `int`. This restores the 1.14 behavior of getting ``bool`` s when
reducing empty object arrays with these ufuncs, while also keeping the 1.15
behavior of getting ``int`` s when reducing empty object arrays with arithmetic
ufuncs like ``add`` and ``multiply``.

Additionally, `logaddexp` now has an identity of ``-inf``, allowing it to be
called on empty sequences, where previously it could not be.

This is possible thanks to the new
:c:function:`PyUFunc_FromFuncAndDataAndSignatureAndIdentity`, which allows
arbitrary values to be used as identities now.

Improved conversion from ctypes objects
---------------------------------------
Numpy has always supported taking a value or type from ``ctypes`` and
converting it into an array or dtype, but only behaved correctly for simpler
types. As of this release, this caveat is lifted - now:

* The ``_pack_`` attribute of ``ctypes.Structure``, used to emulate C's
``__attribute__((packed))``, is respected.
* Endianness of all ctypes objects is preserved
* ``ctypes.Union`` is supported
* Non-representable constructs raise exceptions, rather than producing
dangerously incorrect results:

* Bitfields are no longer interpreted as sub-arrays
* Pointers are no longer replaced with the type that they point to

A new ``ndpointer.contents`` member
-----------------------------------
This matches the ``.contents`` member of normal ctypes arrays, and can be used
to construct an ``np.array`` around the pointers contents.  This replaces
``np.array(some_nd_pointer)``, which stopped working in 1.15.  As a side effect
of this change, ``ndpointer`` now supports dtypes with overlapping fields and
padding.

``matmul`` is now a ``ufunc``
-----------------------------
`numpy.matmul` is now a ufunc which means that both the function and the
``__matmul__`` operator can now be overridden by ``__array_ufunc__``. Its
implementation has also changed. It uses the same BLAS routines as
`numpy.dot`, ensuring its performance is similar for large matrices.

Start and stop arrays for ``linspace``, ``logspace`` and ``geomspace``
----------------------------------------------------------------------
These functions used to be limited to scalar stop and start values, but can
now take arrays, which will be properly broadcast and result in an output
which has one axis prepended.  This can be used, e.g., to obtain linearly
interpolated points between sets of points.

CI extended with additional services
------------------------------------
We now use additional free CI services, thanks to the companies that provide:

* Codecoverage testing via codecov.io
* Arm testing via shippable.com
* Additional test runs on azure pipelines

These are in addition to our continued use of travis, appveyor (for wheels) and
LGTM


Changes
=======

Comparison ufuncs will now error rather than return NotImplemented
------------------------------------------------------------------
Previously, comparison ufuncs such as ``np.equal`` would return
`NotImplemented` if their arguments had structured dtypes, to help comparison
operators such as ``__eq__`` deal with those.  This is no longer needed, as the
relevant logic has moved to the comparison operators proper (which thus do
continue to return `NotImplemented` as needed). Hence, like all other ufuncs,
the comparison ufuncs will now error on structured dtypes.

Positive will now raise a deprecation warning for non-numerical arrays
----------------------------------------------------------------------
Previously, ``+array`` unconditionally returned a copy. Now, it will
raise a ``DeprecationWarning`` if the array is not numerical (i.e.,
if ``np.positive(array)`` raises a ``TypeError``. For ``ndarray``
subclasses that override the default ``__array_ufunc__`` implementation,
the ``TypeError`` is passed on.

``NDArrayOperatorsMixin`` now implements matrix multiplication
--------------------------------------------------------------
Previously, ``np.lib.mixins.NDArrayOperatorsMixin`` did not implement the
special methods for Python's matrix multiplication operator (`). This has
changed now that ``matmul`` is a ufunc and can be overridden using
``__array_ufunc__``.

The scaling of the covariance matrix in ``np.polyfit`` is different
-------------------------------------------------------------------
So far, ``np.polyfit`` used a non-standard factor in the scaling of the the
covariance matrix. Namely, rather than using the standard ``chisq/(M-N)``, it
scaled it with ``chisq/(M-N-2)`` where M is the number of data points and N is the
number of parameters.  This scaling is inconsistent with other fitting programs
such as e.g. ``scipy.optimize.curve_fit`` and was changed to ``chisq/(M-N)``.

``maximum`` and ``minimum`` no longer emit warnings
---------------------------------------------------
As part of code introduced in 1.10,  ``float32`` and ``float64`` set invalid
float status when a Nan is encountered in `numpy.maximum` and `numpy.minimum`,
when using SSE2 semantics. This caused a `RuntimeWarning` to sometimes be
emitted. In 1.15 we fixed the inconsistencies which caused the warnings to
become more conspicuous. Now no warnings will be emitted.

Umath and multiarray c-extension modules merged into a single module
--------------------------------------------------------------------
The two modules were merged, according to `NEP 15`_. Previously `np.core.umath`
and `np.core.multiarray` were seperate c-extension modules. They are now python
wrappers to the single `np.core/_multiarray_math` c-extension module.

.. _`NEP 15` : http://www.numpy.org/neps/nep-0015-merge-multiarray-umath.html

``getfield`` validity checks extended
-------------------------------------
`numpy.ndarray.getfield` now checks the dtype and offset arguments to prevent
accessing invalid memory locations.

NumPy functions now support overrides with ``__array_function__``
-----------------------------------------------------------------
NumPy has a new experimental mechanism for overriding the implementation of
almost all NumPy functions on non-NumPy arrays by defining an
``__array_function__`` method, as described in `NEP 18`_.

This feature is not yet been enabled by default, but has been released to
facilitate experimentation by potential users. See the NEP for details on
setting the appropriate environment variable. We expect the NumPy 1.17 release
will enable overrides by default, which will also be more performant due to a
new implementation written in C.

.. _`NEP 18` : http://www.numpy.org/neps/nep-0018-array-function-protocol.html

Arrays based off readonly buffers cannot be set ``writeable``
-------------------------------------------------------------
We now disallow setting the ``writeable`` flag True on arrays created
from ``fromstring(readonly-buffer)``.


==========================

1.15.4

==========================

This is a bugfix release for bugs and regressions reported following the 1.15.3
release.  The Python versions supported by this release are 2.7, 3.4-3.7. The
wheels are linked with OpenBLAS v0.3.0, which should fix some of the linalg
problems reported for NumPy 1.14.

Compatibility Note
==================

The NumPy 1.15.x OS X wheels released on PyPI no longer contain 32-bit
binaries.  That will also be the case in future releases. See
`11625 <https://github.com/numpy/numpy/issues/11625>`__ for the related
discussion.  Those needing 32-bit support should look elsewhere or build
from source.

Contributors
============

A total of 4 people contributed to this release.  People with a "+" by their
names contributed a patch for the first time.

* Charles Harris
* Matti Picus
* Sebastian Berg
* bbbbbbbbba +

Pull requests merged
====================

A total of 4 pull requests were merged for this release.

* `12296 <https://github.com/numpy/numpy/pull/12296>`__: BUG: Dealloc cached buffer info
* `12297 <https://github.com/numpy/numpy/pull/12297>`__: BUG: Fix fill value in masked array '==' and '!=' ops.
* `12307 <https://github.com/numpy/numpy/pull/12307>`__: DOC: Correct the default value of `optimize` in `numpy.einsum`
* `12320 <https://github.com/numpy/numpy/pull/12320>`__: REL: Prepare for the NumPy 1.15.4 release


==========================

1.15.3

==========================

This is a bugfix release for bugs and regressions reported following the 1.15.2
release.  The Python versions supported by this release are 2.7, 3.4-3.7. The
wheels are linked with OpenBLAS v0.3.0, which should fix some of the linalg
problems reported for NumPy 1.14.

Compatibility Note
==================

The NumPy 1.15.x OS X wheels released on PyPI no longer contain 32-bit
binaries.  That will also be the case in future releases. See
`11625 <https://github.com/numpy/numpy/issues/11625>`__ for the related
discussion.  Those needing 32-bit support should look elsewhere or build
from source.

Contributors
============

A total of 7 people contributed to this release.  People with a "+" by their
names contributed a patch for the first time.

* Allan Haldane
* Charles Harris
* Jeroen Demeyer
* Kevin Sheppard
* Matthew Bowden +
* Matti Picus
* Tyler Reddy

Pull requests merged
====================

A total of 12 pull requests were merged for this release.

* `12080 <https://github.com/numpy/numpy/pull/12080>`__: MAINT: Blacklist some MSVC complex functions.
* `12083 <https://github.com/numpy/numpy/pull/12083>`__: TST: Add azure CI testing to 1.15.x branch.
* `12084 <https://github.com/numpy/numpy/pull/12084>`__: BUG: test_path() now uses Path.resolve()
* `12085 <https://github.com/numpy/numpy/pull/12085>`__: TST, MAINT: Fix some failing tests on azure-pipelines mac and...
* `12187 <https://github.com/numpy/numpy/pull/12187>`__: BUG: Fix memory leak in mapping.c
* `12188 <https://github.com/numpy/numpy/pull/12188>`__: BUG: Allow boolean subtract in histogram
* `12189 <https://github.com/numpy/numpy/pull/12189>`__: BUG: Fix in-place permutation
* `12190 <https://github.com/numpy/numpy/pull/12190>`__: BUG: limit default for get_num_build_jobs() to 8
* `12191 <https://github.com/numpy/numpy/pull/12191>`__: BUG: OBJECT_to_* should check for errors
* `12192 <https://github.com/numpy/numpy/pull/12192>`__: DOC: Prepare for NumPy 1.15.3 release.
* `12237 <https://github.com/numpy/numpy/pull/12237>`__: BUG: Fix MaskedArray fill_value type conversion.
* `12238 <https://github.com/numpy/numpy/pull/12238>`__: TST: Backport azure-pipeline testing fixes for Mac


=========================

Links

• PyPI: https://pypi.org/project/numpy
• Changelog: https://pyup.io/changelogs/numpy/
• Homepage: https://www.numpy.org

Update pandas from 0.23.4 to 0.24.2.

The bot wasn't able to find a changelog for this release. Got an idea?

Links

• PyPI: https://pypi.org/project/pandas
• Homepage: http://pandas.pydata.org

Update pyfaidx from 0.5.4.2 to 0.5.5.2.

Changelog

0.5.5.1

- Added better exceptions for files that do not contain any valid sequences (144)

0.5.5

- Added proper BGZF support, fixing 131. Note: this fix requires code present in Biopython 1.73, which is not yet released. If you need this functionality in the mean time, install the biopython development version
- Enhancement to `faidx` script: allow -v to be specified alongside -g (142). Thanks daler!

Links

• PyPI: https://pypi.org/project/pyfaidx
• Changelog: https://pyup.io/changelogs/pyfaidx/
• Homepage: http://mattshirley.com
• Docs: https://pythonhosted.org/pyfaidx/

Update pyparsing from 2.2.1 to 2.3.1.

Changelog

2.3.1

-----------------------------
- POSSIBLE API CHANGE: this release fixes a bug when results names were
attached to a MatchFirst or Or object containing an And object.
Previously, a results name on an And object within an enclosing MatchFirst
or Or could return just the first token in the And. Now, all the tokens
matched by the And are correctly returned. This may result in subtle
changes in the tokens returned if you have this condition in your pyparsing
scripts.

- New staticmethod ParseException.explain() to help diagnose parse exceptions
by showing the failing input line and the trace of ParserElements in
the parser leading up to the exception. explain() returns a multiline
string listing each element by name. (This is still an experimental
method, and the method signature and format of the returned string may
evolve over the next few releases.)

Example:
      define a parser to parse an integer followed by an
      alphabetic word
     expr = pp.Word(pp.nums).setName("int")
            + pp.Word(pp.alphas).setName("word")
     try:
          parse a string with a numeric second value instead of alpha
         expr.parseString("123 355")
     except pp.ParseException as pe:
         print_(pp.ParseException.explain(pe))

Prints:
     123 355
         ^
     ParseException: Expected word (at char 4), (line:1, col:5)
     __main__.ExplainExceptionTest
     pyparsing.And - {int word}
     pyparsing.Word - word

explain() will accept any exception type and will list the function
names and parse expressions in the stack trace. This is especially
useful when an exception is raised in a parse action.

Note: explain() is only supported under Python 3.

- Fix bug in dictOf which could match an empty sequence, making it
infinitely loop if wrapped in a OneOrMore.

- Added unicode sets to pyparsing_unicode for Latin-A and Latin-B ranges.

- Added ability to define custom unicode sets as combinations of other sets
using multiple inheritance.

 class Turkish_set(pp.pyparsing_unicode.Latin1, pp.pyparsing_unicode.LatinA):
     pass

 turkish_word = pp.Word(Turkish_set.alphas)

- Updated state machine import examples, with state machine demos for:
. traffic light
. library book checkin/checkout
. document review/approval

In the traffic light example, you can use the custom 'statemachine' keyword
to define the states for a traffic light, and have the state classes
auto-generated for you:

   statemachine TrafficLightState:
       Red -> Green
       Green -> Yellow
       Yellow -> Red

Similar for state machines with named transitions, like the library book
state example:

   statemachine LibraryBookState:
       New -(shelve)-> Available
       Available -(reserve)-> OnHold
       OnHold -(release)-> Available
       Available -(checkout)-> CheckedOut
       CheckedOut -(checkin)-> Available

Once the classes are defined, then additional Python code can reference those
classes to add class attributes, instance methods, etc.

See the examples in examples/statemachine

- Added an example parser for the decaf language. This language is used in
CS compiler classes in many colleges and universities.

- Fixup of docstrings to Sphinx format, inclusion of test files in the source
package, and convert markdown to rst throughout the distribution, great job
by Matěj Cepl!

- Expanded the whitespace characters recognized by the White class to include
all unicode defined spaces. Suggested in Issue 51 by rtkjbillo.

- Added optional postParse argument to ParserElement.runTests() to add a
custom callback to be called for test strings that parse successfully. Useful
for running tests that do additional validation or processing on the parsed
results. See updated chemicalFormulas.py example.

- Removed distutils fallback in setup.py. If installing the package fails,
please update to the latest version of setuptools. Plus overall project code
cleanup (CRLFs, whitespace, imports, etc.), thanks Jon Dufresne!

- Fix bug in CaselessKeyword, to make its behavior consistent with
Keyword(caseless=True). Fixes Issue 65 reported by telesphore.

2.3.0

-----------------------------
- NEW SUPPORT FOR UNICODE CHARACTER RANGES
This release introduces the pyparsing_unicode namespace class, defining
a series of language character sets to simplify the definition of alphas,
nums, alphanums, and printables in the following language sets:
. Arabic
. Chinese
. Cyrillic
. Devanagari
. Greek
. Hebrew
. Japanese (including Kanji, Katakana, and Hirigana subsets)
. Korean
. Latin1 (includes 7 and 8-bit Latin characters)
. Thai
. CJK (combination of Chinese, Japanese, and Korean sets)

For example, your code can define words using:

 korean_word = Word(pyparsing_unicode.Korean.alphas)

See their use in the updated examples greetingInGreek.py and
greetingInKorean.py.

This namespace class also offers access to these sets using their
unicode identifiers.

- POSSIBLE API CHANGE: Fixed bug where a parse action that explicitly
returned the input ParseResults could add another nesting level in
the results if the current expression had a results name.

     vals = pp.OneOrMore(pp.pyparsing_common.integer)("int_values")

     def add_total(tokens):
         tokens['total'] = sum(tokens)
         return tokens   this line can be removed

     vals.addParseAction(add_total)
     print(vals.parseString("244 23 13 2343").dump())

Before the fix, this code would print (note the extra nesting level):

 [244, 23, 13, 2343]
 - int_values: [244, 23, 13, 2343]
   - int_values: [244, 23, 13, 2343]
   - total: 2623
 - total: 2623

With the fix, this code now prints:

 [244, 23, 13, 2343]
 - int_values: [244, 23, 13, 2343]
 - total: 2623

This fix will change the structure of ParseResults returned if a
program defines a parse action that returns the tokens that were
sent in. This is not necessary, and statements like "return tokens"
in the example above can be safely deleted prior to upgrading to
this release, in order to avoid the bug and get the new behavior.

Reported by seron in Issue 22, nice catch!

- POSSIBLE API CHANGE: Fixed a related bug where a results name
erroneously created a second level of hierarchy in the returned
ParseResults. The intent for accumulating results names into ParseResults
is that, in the absence of Group'ing, all names get merged into a
common namespace. This allows us to write:

    key_value_expr = (Word(alphas)("key") + '=' + Word(nums)("value"))
    result = key_value_expr.parseString("a = 100")

and have result structured as {"key": "a", "value": "100"}
instead of [{"key": "a"}, {"value": "100"}].

However, if a named expression is used in a higher-level non-Group
expression that *also* has a name, a false sub-level would be created
in the namespace:

     num = pp.Word(pp.nums)
     num_pair = ("[" + (num("A") + num("B"))("values") + "]")
     U = num_pair.parseString("[ 10 20 ]")
     print(U.dump())

Since there is no grouping, "A", "B", and "values" should all appear
at the same level in the results, as:

     ['[', '10', '20', ']']
     - A: '10'
     - B: '20'
     - values: ['10', '20']

Instead, an extra level of "A" and "B" show up under "values":

     ['[', '10', '20', ']']
     - A: '10'
     - B: '20'
     - values: ['10', '20']
       - A: '10'
       - B: '20'

This bug has been fixed. Now, if this hierarchy is desired, then a
Group should be added:

     num_pair = ("[" + pp.Group(num("A") + num("B"))("values") + "]")

Giving:

     ['[', ['10', '20'], ']']
     - values: ['10', '20']
       - A: '10'
       - B: '20'

But in no case should "A" and "B" appear in multiple levels. This bug-fix
fixes that.

If you have current code which relies on this behavior, then add or remove
Groups as necessary to get your intended results structure.

Reported by Athanasios Anastasiou.

- IndexError's raised in parse actions will get explicitly reraised
as ParseExceptions that wrap the original IndexError. Since
IndexError sometimes occurs as part of pyparsing's normal parsing
logic, IndexErrors that are raised during a parse action may have
gotten silently reinterpreted as parsing errors. To retain the
information from the IndexError, these exceptions will now be
raised as ParseExceptions that reference the original IndexError.
This wrapping will only be visible when run under Python3, since it
emulates "raise ... from ..." syntax.

Addresses Issue 4, reported by guswns0528.

- Added Char class to simplify defining expressions of a single
character. (Char("abc") is equivalent to Word("abc", exact=1))

- Added class PrecededBy to perform lookbehind tests. PrecededBy is
used in the same way as FollowedBy, passing in an expression that
must occur just prior to the current parse location.

For fixed-length expressions like a Literal, Keyword, Char, or a
Word with an `exact` or `maxLen` length given, `PrecededBy(expr)`
is sufficient. For varying length expressions like a Word with no
given maximum length, `PrecededBy` must be constructed with an
integer `retreat` argument, as in
`PrecededBy(Word(alphas, nums), retreat=10)`, to specify the maximum
number of characters pyparsing must look backward to make a match.
pyparsing will check all the values from 1 up to retreat characters
back from the current parse location.

When stepping backwards through the input string, PrecededBy does
*not* skip over whitespace.

PrecededBy can be created with a results name so that, even though
it always returns an empty parse result, the result *can* include
named results.

Idea first suggested in Issue 30 by Freakwill.

- Updated FollowedBy to accept expressions that contain named results,
so that results names defined in the lookahead expression will be
returned, even though FollowedBy always returns an empty list.
Inspired by the same feature implemented in PrecededBy.

2.2.2

-------------------------------
- Fixed bug in SkipTo, if a SkipTo expression that was skipping to
an expression that returned a list (such as an And), and the
SkipTo was saved as a named result, the named result could be
saved as a ParseResults - should always be saved as a string.
Issue 28, reported by seron.

- Added simple_unit_tests.py, as a collection of easy-to-follow unit
tests for various classes and features of the pyparsing library.
Primary intent is more to be instructional than actually rigorous
testing. Complex tests can still be added in the unitTests.py file.

- New features added to the Regex class:
- optional asGroupList parameter, returns all the capture groups as
 a list
- optional asMatch parameter, returns the raw re.match result
- new sub(repl) method, which adds a parse action calling
 re.sub(pattern, repl, parsed_result). Simplifies creating
 Regex expressions to be used with transformString. Like re.sub,
 repl may be an ordinary string (similar to using pyparsing's
 replaceWith), or may contain references to capture groups by group
 number, or may be a callable that takes an re match group and
 returns a string.

 For instance:
     expr = pp.Regex(r"([Hh]\d):\s*(.*)").sub(r"<\1>\2</\1>")
     expr.transformString("h1: This is the title")

 will return
     <h1>This is the title</h1>

- Fixed omission of LICENSE file in source tarball, also added
CODE_OF_CONDUCT.md per GitHub community standards.

Links

• PyPI: https://pypi.org/project/pyparsing
• Changelog: https://pyup.io/changelogs/pyparsing/
• Repo: https://github.com/pyparsing/pyparsing/
• Docs: https://pythonhosted.org/pyparsing/

Update python-dateutil from 2.7.3 to 2.8.0.

Changelog

2.8.0

==========================

Data updates
------------

- Updated tzdata version to to 2018i.


Features
--------

- Added support for ``EXDATE`` parameters when parsing ``rrule`` strings.
Reported by mlorant (gh issue 410), fixed by nicoe (gh pr 859).
- Added support for sub-minute time zone offsets in Python 3.6+.
Fixed by cssherry (gh issue 582, pr 763)
- Switched the ``tzoffset``, ``tzstr`` and ``gettz`` caches over to using weak
references, so that the cache expires when no other references to the
original ``tzinfo`` objects exist. This cache-expiry behavior is not
guaranteed in the public interface and may change in the future. To improve
performance in the case where transient references to the same time zones
are repeatedly created but no strong reference is continuou

[pyup-bot]

Closing this in favor of #29