{"action":"opened","number":357,"pull_request":{"url":"https://api.github.com/repos/UGentBiomath/wwdata/pulls/357","id":210742048,"node_id":"MDExOlB1bGxSZXF1ZXN0MjEwNzQyMDQ4","html_url":"https://github.com/UGentBiomath/wwdata/pull/357","diff_url":"https://github.com/UGentBiomath/wwdata/pull/357.diff","patch_url":"https://github.com/UGentBiomath/wwdata/pull/357.patch","issue_url":"https://api.github.com/repos/UGentBiomath/wwdata/issues/357","number":357,"state":"open","locked":false,"title":"Bug #12345 Scheduled daily dependency update on friday","user":{"login":"pyup-bot","id":16239342,"node_id":"MDQ6VXNlcjE2MjM5MzQy","avatar_url":"https://avatars0.githubusercontent.com/u/16239342?v=4","gravatar_id":"","url":"https://api.github.com/users/pyup-bot","html_url":"https://github.com/pyup-bot","followers_url":"https://api.github.com/users/pyup-bot/followers","following_url":"https://api.github.com/users/pyup-bot/following{/other_user}","gists_url":"https://api.github.com/users/pyup-bot/gists{/gist_id}","starred_url":"https://api.github.com/users/pyup-bot/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/pyup-bot/subscriptions","organizations_url":"https://api.github.com/users/pyup-bot/orgs","repos_url":"https://api.github.com/users/pyup-bot/repos","events_url":"https://api.github.com/users/pyup-bot/events{/privacy}","received_events_url":"https://api.github.com/users/pyup-bot/received_events","type":"User","site_admin":false},"body":"\n\n\n\n\n### Update [pandas](https://pypi.org/project/pandas) from **0.23.0** to **0.23.4**.\n\n\n<details>\n  <summary>Changelog</summary>\n  \n  \n   ### 0.23.4\n   ```\n   ------------------------\n\nThis is a minor bug-fix release in the 0.23.x series and includes some small regression fixes\nand bug fixes. We recommend that all users upgrade to this version.\n\n.. warning::\n\n   Starting January 1, 2019, pandas feature releases will support Python 3 only.\n   See :ref:`install.dropping-27` for more.\n\n.. contents:: What&#39;s new in v0.23.4\n    :local:\n    :backlinks: none\n\n.. _whatsnew_0234.fixed_regressions:\n\nFixed Regressions\n~~~~~~~~~~~~~~~~~\n\n- Python 3.7 with Windows gave all missing values for rolling variance calculations (:issue:`21813`)\n\n.. _whatsnew_0234.bug_fixes:\n\nBug Fixes\n~~~~~~~~~\n\n**Groupby/Resample/Rolling**\n\n- Bug where calling :func:`DataFrameGroupBy.agg` with a list of functions including ``ohlc`` as the non-initial element would raise a ``ValueError`` (:issue:`21716`)\n- Bug in ``roll_quantile`` caused a memory leak when calling ``.rolling(...).quantile(q)`` with ``q`` in (0,1) (:issue:`21965`)\n\n**Missing**\n\n- Bug in :func:`Series.clip` and :func:`DataFrame.clip` cannot accept list-like threshold containing ``NaN`` (:issue:`19992`)\n   ```\n   \n  \n  \n   ### 0.23.3\n   ```\n   ----------------------\n\nThis release fixes a build issue with the sdist for Python 3.7 (:issue:`21785`)\nThere are no other changes.\n\n\n.. _whatsnew_0211:\n   ```\n   \n  \n  \n   ### 0.23.2\n   ```\n   ----------------------\n\nThis is a minor bug-fix release in the 0.23.x series and includes some small regression fixes\nand bug fixes. We recommend that all users upgrade to this version.\n\n.. note::\n\n   Pandas 0.23.2 is first pandas release that&#39;s compatible with\n   Python 3.7 (:issue:`20552`)\n\n.. warning::\n\n   Starting January 1, 2019, pandas feature releases will support Python 3 only.\n   See :ref:`install.dropping-27` for more.\n\n.. contents:: What&#39;s new in v0.23.2\n    :local:\n    :backlinks: none\n\n.. _whatsnew_0232.enhancements:\n\nLogical Reductions over Entire DataFrame\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n\n:meth:`DataFrame.all` and :meth:`DataFrame.any` now accept ``axis=None`` to reduce over all axes to a scalar (:issue:`19976`)\n\n.. ipython:: python\n\n   df = pd.DataFrame({&quot;A&quot;: [1, 2], &quot;B&quot;: [True, False]})\n   df.all(axis=None)\n\n\nThis also provides compatibility with NumPy 1.15, which now dispatches to ``DataFrame.all``.\nWith NumPy 1.15 and pandas 0.23.1 or earlier, :func:`numpy.all` will no longer reduce over every axis:\n\n.. code-block:: python\n\n   &gt;&gt;&gt;  NumPy 1.15, pandas 0.23.1\n   &gt;&gt;&gt; np.any(pd.DataFrame({&quot;A&quot;: [False], &quot;B&quot;: [False]}))\n   A    False\n   B    False\n   dtype: bool\n\nWith pandas 0.23.2, that will correctly return False, as it did with NumPy &lt; 1.15.\n\n.. ipython:: python\n\n   np.any(pd.DataFrame({&quot;A&quot;: [False], &quot;B&quot;: [False]}))\n\n\n.. _whatsnew_0232.fixed_regressions:\n\nFixed Regressions\n~~~~~~~~~~~~~~~~~\n\n- Fixed regression in :meth:`to_csv` when handling file-like object incorrectly (:issue:`21471`)\n- Re-allowed duplicate level names of a ``MultiIndex``. Accessing a level that has a duplicate name by name still raises an error (:issue:`19029`).\n- Bug in both :meth:`DataFrame.first_valid_index` and :meth:`Series.first_valid_index` raised for a row index having duplicate values (:issue:`21441`)\n- Fixed printing of DataFrames with hierarchical columns with long names (:issue:`21180`)\n- Fixed regression in :meth:`~DataFrame.reindex` and :meth:`~DataFrame.groupby`\n  with a MultiIndex or multiple keys that contains categorical datetime-like values (:issue:`21390`).\n- Fixed regression in unary negative operations with object dtype (:issue:`21380`)\n- Bug in :meth:`Timestamp.ceil` and :meth:`Timestamp.floor` when timestamp is a multiple of the rounding frequency (:issue:`21262`)\n- Fixed regression in :func:`to_clipboard` that defaulted to copying dataframes with space delimited instead of tab delimited (:issue:`21104`)\n\n\nBuild Changes\n~~~~~~~~~~~~~\n\n- The source and binary distributions no longer include test data files, resulting in smaller download sizes. Tests relying on these data files will be skipped when using ``pandas.test()``. (:issue:`19320`)\n\n.. _whatsnew_0232.bug_fixes:\n\nBug Fixes\n~~~~~~~~~\n\n**Conversion**\n\n- Bug in constructing :class:`Index` with an iterator or generator (:issue:`21470`)\n- Bug in :meth:`Series.nlargest` for signed and unsigned integer dtypes when the minimum value is present (:issue:`21426`)\n\n**Indexing**\n\n- Bug in :meth:`Index.get_indexer_non_unique` with categorical key (:issue:`21448`)\n- Bug in comparison operations for :class:`MultiIndex` where error was raised on equality / inequality comparison involving a MultiIndex with ``nlevels == 1`` (:issue:`21149`)\n- Bug in :meth:`DataFrame.drop` behaviour is not consistent for unique and non-unique indexes (:issue:`21494`)\n- Bug in :func:`DataFrame.duplicated` with a large number of columns causing a &#39;maximum recursion depth exceeded&#39; (:issue:`21524`).\n\n**I/O**\n\n- Bug in :func:`read_csv` that caused it to incorrectly raise an error when ``nrows=0``, ``low_memory=True``, and ``index_col`` was not ``None`` (:issue:`21141`)\n- Bug in :func:`json_normalize` when formatting the ``record_prefix`` with integer columns (:issue:`21536`)\n\n**Categorical**\n\n- Bug in rendering :class:`Series` with ``Categorical`` dtype in rare conditions under Python 2.7 (:issue:`21002`)\n\n**Timezones**\n\n- Bug in :class:`Timestamp` and :class:`DatetimeIndex` where passing a :class:`Timestamp` localized after a DST transition would return a datetime before the DST transition (:issue:`20854`)\n- Bug in comparing :class:`DataFrame`s with tz-aware :class:`DatetimeIndex` columns with a DST transition that raised a ``KeyError`` (:issue:`19970`)\n\n**Timedelta**\n\n- Bug in :class:`Timedelta` where non-zero timedeltas shorter than 1 microsecond were considered False (:issue:`21484`)\n\n\n.. _whatsnew_0170:\n   ```\n   \n  \n  \n   ### 0.23.1\n   ```\n   -----------------------\n\nThis is a minor bug-fix release in the 0.23.x series and includes some small regression fixes\nand bug fixes. We recommend that all users upgrade to this version.\n\n.. warning::\n\n   Starting January 1, 2019, pandas feature releases will support Python 3 only.\n   See :ref:`install.dropping-27` for more.\n\n.. contents:: What&#39;s new in v0.23.1\n    :local:\n    :backlinks: none\n\n.. _whatsnew_0231.fixed_regressions:\n\nFixed Regressions\n~~~~~~~~~~~~~~~~~\n\n**Comparing Series with datetime.date**\n\nWe&#39;ve reverted a 0.23.0 change to comparing a :class:`Series` holding datetimes and a ``datetime.date`` object (:issue:`21152`).\nIn pandas 0.22 and earlier, comparing a Series holding datetimes and ``datetime.date`` objects would coerce the ``datetime.date`` to a datetime before comapring.\nThis was inconsistent with Python, NumPy, and :class:`DatetimeIndex`, which never consider a datetime and ``datetime.date`` equal.\n\nIn 0.23.0, we unified operations between DatetimeIndex and Series, and in the process changed comparisons between a Series of datetimes and ``datetime.date`` without warning.\n\nWe&#39;ve temporarily restored the 0.22.0 behavior, so datetimes and dates may again compare equal, but restore the 0.23.0 behavior in a future release.\n\nTo summarize, here&#39;s the behavior in 0.22.0, 0.23.0, 0.23.1:\n\n.. code-block:: python\n\n    0.22.0... Silently coerce the datetime.date\n   &gt;&gt;&gt; Series(pd.date_range(&#39;2017&#39;, periods=2)) == datetime.date(2017, 1, 1)\n   0     True\n   1    False\n   dtype: bool\n\n    0.23.0... Do not coerce the datetime.date\n   &gt;&gt;&gt; Series(pd.date_range(&#39;2017&#39;, periods=2)) == datetime.date(2017, 1, 1)\n   0    False\n   1    False\n   dtype: bool\n\n    0.23.1... Coerce the datetime.date with a warning\n   &gt;&gt;&gt; Series(pd.date_range(&#39;2017&#39;, periods=2)) == datetime.date(2017, 1, 1)\n   /bin/python:1: FutureWarning: Comparing Series of datetimes with &#39;datetime.date&#39;.  Currently, the\n   &#39;datetime.date&#39; is coerced to a datetime. In the future pandas will\n   not coerce, and the values not compare equal to the &#39;datetime.date&#39;.\n   To retain the current behavior, convert the &#39;datetime.date&#39; to a\n   datetime with &#39;pd.Timestamp&#39;.\n     !/bin/python3\n   0     True\n   1    False\n   dtype: bool\n\nIn addition, ordering comparisons will raise a ``TypeError`` in the future.\n\n**Other Fixes**\n\n- Reverted the ability of :func:`~DataFrame.to_sql` to perform multivalue\n  inserts as this caused regression in certain cases (:issue:`21103`).\n  In the future this will be made configurable.\n- Fixed regression in the :attr:`DatetimeIndex.date` and :attr:`DatetimeIndex.time`\n  attributes in case of timezone-aware data: :attr:`DatetimeIndex.time` returned\n  a tz-aware time instead of tz-naive (:issue:`21267`) and :attr:`DatetimeIndex.date`\n  returned incorrect date when the input date has a non-UTC timezone (:issue:`21230`).\n- Fixed regression in :meth:`pandas.io.json.json_normalize` when called with ``None`` values\n  in nested levels in JSON, and to not drop keys with value as `None` (:issue:`21158`, :issue:`21356`).\n- Bug in :meth:`~DataFrame.to_csv` causes encoding error when compression and encoding are specified (:issue:`21241`, :issue:`21118`)\n- Bug preventing pandas from being importable with -OO optimization (:issue:`21071`)\n- Bug in :meth:`Categorical.fillna` incorrectly raising a ``TypeError`` when `value` the individual categories are iterable and `value` is an iterable (:issue:`21097`, :issue:`19788`)\n- Fixed regression in constructors coercing NA values like ``None`` to strings when passing ``dtype=str`` (:issue:`21083`)\n- Regression in :func:`pivot_table` where an ordered ``Categorical`` with missing\n  values for the pivot&#39;s ``index`` would give a mis-aligned result (:issue:`21133`)\n- Fixed regression in merging on boolean index/columns (:issue:`21119`).\n\n.. _whatsnew_0231.performance:\n\nPerformance Improvements\n~~~~~~~~~~~~~~~~~~~~~~~~\n\n- Improved performance of :meth:`CategoricalIndex.is_monotonic_increasing`, :meth:`CategoricalIndex.is_monotonic_decreasing` and :meth:`CategoricalIndex.is_monotonic` (:issue:`21025`)\n- Improved performance of :meth:`CategoricalIndex.is_unique` (:issue:`21107`)\n\n\n.. _whatsnew_0231.bug_fixes:\n\nBug Fixes\n~~~~~~~~~\n\n**Groupby/Resample/Rolling**\n\n- Bug in :func:`DataFrame.agg` where applying multiple aggregation functions to a :class:`DataFrame` with duplicated column names would cause a stack overflow (:issue:`21063`)\n- Bug in :func:`pandas.core.groupby.GroupBy.ffill` and :func:`pandas.core.groupby.GroupBy.bfill` where the fill within a grouping would not always be applied as intended due to the implementations&#39; use of a non-stable sort (:issue:`21207`)\n- Bug in :func:`pandas.core.groupby.GroupBy.rank` where results did not scale to 100% when specifying ``method=&#39;dense&#39;`` and ``pct=True``\n- Bug in :func:`pandas.DataFrame.rolling` and :func:`pandas.Series.rolling` which incorrectly accepted a 0 window size rather than raising (:issue:`21286`)\n\n**Data-type specific**\n\n- Bug in :meth:`Series.str.replace()` where the method throws `TypeError` on Python 3.5.2 (:issue:`21078`)\n- Bug in :class:`Timedelta` where passing a float with a unit would prematurely round the float precision (:issue:`14156`)\n- Bug in :func:`pandas.testing.assert_index_equal` which raised ``AssertionError`` incorrectly, when comparing two :class:`CategoricalIndex` objects with param ``check_categorical=False`` (:issue:`19776`)\n\n**Sparse**\n\n- Bug in :attr:`SparseArray.shape` which previously only returned the shape :attr:`SparseArray.sp_values` (:issue:`21126`)\n\n**Indexing**\n\n- Bug in :meth:`Series.reset_index` where appropriate error was not raised with an invalid level name (:issue:`20925`)\n- Bug in :func:`interval_range` when ``start``/``periods`` or ``end``/``periods`` are specified with float ``start`` or ``end`` (:issue:`21161`)\n- Bug in :meth:`MultiIndex.set_names` where error raised for a ``MultiIndex`` with ``nlevels == 1`` (:issue:`21149`)\n- Bug in :class:`IntervalIndex` constructors where creating an ``IntervalIndex`` from categorical data was not fully supported (:issue:`21243`, :issue:`21253`)\n- Bug in :meth:`MultiIndex.sort_index` which was not guaranteed to sort correctly with ``level=1``; this was also causing data misalignment in particular :meth:`DataFrame.stack` operations (:issue:`20994`, :issue:`20945`, :issue:`21052`)\n\n**Plotting**\n\n- New keywords (sharex, sharey) to turn on/off sharing of x/y-axis by subplots generated with pandas.DataFrame().groupby().boxplot() (:issue:`20968`)\n\n**I/O**\n\n- Bug in IO methods specifying ``compression=&#39;zip&#39;`` which produced uncompressed zip archives (:issue:`17778`, :issue:`21144`)\n- Bug in :meth:`DataFrame.to_stata` which prevented exporting DataFrames to buffers and most file-like objects (:issue:`21041`)\n- Bug in :meth:`read_stata` and :class:`StataReader` which did not correctly decode utf-8 strings on Python 3 from Stata 14 files (dta version 118) (:issue:`21244`)\n- Bug in IO JSON :func:`read_json` reading empty JSON schema with ``orient=&#39;table&#39;`` back to :class:`DataFrame` caused an error (:issue:`21287`)\n\n**Reshaping**\n\n- Bug in :func:`concat` where error was raised in concatenating :class:`Series` with numpy scalar and tuple names (:issue:`21015`)\n- Bug in :func:`concat` warning message providing the wrong guidance for future behavior (:issue:`21101`)\n\n**Other**\n\n- Tab completion on :class:`Index` in IPython no longer outputs deprecation warnings (:issue:`21125`)\n- Bug preventing pandas being used on Windows without C++ redistributable installed (:issue:`21106`)\n\n\n\n.. _whatsnew_050:\n   ```\n   \n  \n</details>\n\n\n \n\n<details>\n  <summary>Links</summary>\n  \n  - PyPI: https://pypi.org/project/pandas\n  - Changelog: https://pyup.io/changelogs/pandas/\n  - Homepage: http://pandas.pydata.org\n</details>\n\n\n\n\n\n### Update [numpy](https://pypi.org/project/numpy) from **1.14.4** to **1.15.1**.\n\n\n<details>\n  <summary>Changelog</summary>\n  \n  \n   ### 1.15.0\n   ```\n   ==========================\n\nNumPy 1.15.0 is a release with an unusual number of cleanups, many deprecations\nof old functions, and improvements to many existing functions. Please read the\ndetailed descriptions below to see if you are affected.\n\nFor testing, we have switched to pytest as a replacement for the no longer\nmaintained nose framework. The old nose based interface remains for downstream\nprojects who may still be using it.\n\nThe Python versions supported by this release are 2.7, 3.4-3.7. The wheels are\nlinked with OpenBLAS v0.3.0, which should fix some of the linalg problems\nreported for NumPy 1.14.\n\n\nHighlights\n==========\n\n* NumPy has switched to pytest for testing.\n* A new  `numpy.printoptions` context manager.\n* Many improvements to the histogram functions.\n* Support for unicode field names in python 2.7.\n* Improved support for PyPy.\n* Fixes and improvements to `numpy.einsum`.\n\n\nNew functions\n=============\n\n* `numpy.gcd` and `numpy.lcm`, to compute the greatest common divisor and least\n  common multiple.\n\n* `numpy.ma.stack`, the `numpy.stack` array-joining function generalized to\n  masked arrays.\n\n* `numpy.quantile` function, an interface to ``percentile`` without factors of\n  100\n\n* `numpy.nanquantile` function, an interface to ``nanpercentile`` without\n  factors of 100\n\n* `numpy.printoptions`, a context manager that sets print options temporarily\n  for the scope of the ``with`` block::\n\n    &gt;&gt;&gt; with np.printoptions(precision=2):\n    ...     print(np.array([2.0]) / 3)\n    [0.67]\n\n* `numpy.histogram_bin_edges`, a function to get the edges of the bins used by a\n  histogram without needing to calculate the histogram.\n\n* C functions `npy_get_floatstatus_barrier` and `npy_clear_floatstatus_barrier`\n  have been added to deal with compiler optimization changing the order of\n  operations.  See below for details.\n\n\nDeprecations\n============\n\n* Aliases of builtin `pickle` functions are deprecated, in favor of their\n  unaliased ``pickle.&lt;func&gt;`` names:\n\n  * `numpy.loads`\n  * `numpy.core.numeric.load`\n  * `numpy.core.numeric.loads`\n  * `numpy.ma.loads`, `numpy.ma.dumps`\n  * `numpy.ma.load`, `numpy.ma.dump` - these functions already failed on\n    python 3 when called with a string.\n\n* Multidimensional indexing with anything but a tuple is deprecated. This means\n  that the index list in ``ind = [slice(None), 0]; arr[ind]`` should be changed\n  to a tuple, e.g., ``ind = [slice(None), 0]; arr[tuple(ind)]`` or\n  ``arr[(slice(None), 0)]``. That change is necessary to avoid ambiguity in\n  expressions such as ``arr[[[0, 1], [0, 1]]]``, currently interpreted as\n  ``arr[array([0, 1]), array([0, 1])]``, that will be interpreted\n  as ``arr[array([[0, 1], [0, 1]])]`` in the future.\n\n* Imports from the following sub-modules are deprecated, they will be removed\n  at some future date.\n\n  * `numpy.testing.utils`\n  * `numpy.testing.decorators`\n  * `numpy.testing.nosetester`\n  * `numpy.testing.noseclasses`\n  * `numpy.core.umath_tests`\n\n* Giving a generator to `numpy.sum` is now deprecated. This was undocumented\n  behavior, but worked. Previously, it would calculate the sum of the generator\n  expression.  In the future, it might return a different result. Use\n  ``np.sum(np.from_iter(generator))`` or the built-in Python ``sum`` instead.\n\n* Users of the C-API should call ``PyArrayResolveWriteBackIfCopy`` or\n  ``PyArray_DiscardWritbackIfCopy`` on any array with the ``WRITEBACKIFCOPY``\n  flag set, before deallocating the array. A deprecation warning will be\n  emitted if those calls are not used when needed.\n\n* Users of ``nditer`` should use the nditer object as a context manager\n  anytime one of the iterator operands is writeable, so that numpy can\n  manage writeback semantics, or should call ``it.close()``. A\n  `RuntimeWarning` may be emitted otherwise in these cases.\n\n* The ``normed`` argument of ``np.histogram``, deprecated long ago in 1.6.0,\n  now emits a ``DeprecationWarning``.\n\n\nFuture Changes\n==============\n\n* NumPy 1.16 will drop support for Python 3.4.\n* NumPy 1.17 will drop support for Python 2.7.\n\n\nCompatibility notes\n===================\n\nCompiled testing modules renamed and made private\n-------------------------------------------------\nThe following compiled modules have been renamed and made private:\n\n* ``umath_tests`` -&gt; ``_umath_tests``\n* ``test_rational`` -&gt; ``_rational_tests``\n* ``multiarray_tests`` -&gt; ``_multiarray_tests``\n* ``struct_ufunc_test`` -&gt; ``_struct_ufunc_tests``\n* ``operand_flag_tests`` -&gt; ``_operand_flag_tests``\n\nThe ``umath_tests`` module is still available for backwards compatibility, but\nwill be removed in the future.\n\nThe ``NpzFile`` returned by ``np.savez`` is now a ``collections.abc.Mapping``\n-----------------------------------------------------------------------------\nThis means it behaves like a readonly dictionary, and has a new ``.values()``\nmethod and ``len()`` implementation.\n\nFor python 3, this means that ``.iteritems()``, ``.iterkeys()`` have been\ndeprecated, and ``.keys()`` and ``.items()`` now return views and not lists.\nThis is consistent with how the builtin ``dict`` type changed between python 2\nand python 3.\n\nUnder certain conditions, ``nditer`` must be used in a context manager\n----------------------------------------------------------------------\nWhen using an `numpy.nditer` with the ``&quot;writeonly&quot;`` or ``&quot;readwrite&quot;`` flags, there\nare some circumstances where nditer doesn&#39;t actually give you a view of the\nwritable array. Instead, it gives you a copy, and if you make changes to the\ncopy, nditer later writes those changes back into your actual array. Currently,\nthis writeback occurs when the array objects are garbage collected, which makes\nthis API error-prone on CPython and entirely broken on PyPy. Therefore,\n``nditer`` should now be used as a context manager whenever it is used\nwith writeable arrays, e.g., ``with np.nditer(...) as it: ...``. You may also\nexplicitly call ``it.close()`` for cases where a context manager is unusable,\nfor instance in generator expressions.\n\nNumpy has switched to using pytest instead of nose for testing\n--------------------------------------------------------------\nThe last nose release was 1.3.7 in June, 2015, and development of that tool has\nended, consequently NumPy has now switched to using pytest. The old decorators\nand nose tools that were previously used by some downstream projects remain\navailable, but will not be maintained. The standard testing utilities,\n``assert_almost_equal`` and such, are not be affected by this change except for\nthe nose specific functions ``import_nose`` and ``raises``. Those functions are\nnot used in numpy, but are kept for downstream compatibility.\n\nNumpy no longer monkey-patches ``ctypes`` with ``__array_interface__``\n----------------------------------------------------------------------\nPreviously numpy added ``__array_interface__`` attributes to all the integer\ntypes from ``ctypes``.\n\n``np.ma.notmasked_contiguous`` and ``np.ma.flatnotmasked_contiguous`` always return lists\n-----------------------------------------------------------------------------------------\nThis is the documented behavior, but previously the result could be any of\nslice, None, or list.\n\nAll downstream users seem to check for the ``None`` result from\n``flatnotmasked_contiguous`` and replace it with ``[]``.  Those callers will\ncontinue to work as before.\n\n``np.squeeze`` restores old behavior of objects that cannot handle an ``axis`` argument\n---------------------------------------------------------------------------------------\nPrior to version ``1.7.0``, `numpy.squeeze` did not have an ``axis`` argument and\nall empty axes were removed by default. The incorporation of an ``axis``\nargument made it possible to selectively squeeze single or multiple empty axes,\nbut the old API expectation was not respected because axes could still be\nselectively removed (silent success) from an object expecting all empty axes to\nbe removed. That silent, selective removal of empty axes for objects expecting\nthe old behavior has been fixed and the old behavior restored.\n\nunstructured void array&#39;s ``.item`` method now returns a bytes object\n---------------------------------------------------------------------\n``.item`` now returns a ``bytes`` object instead of a buffer or byte array.\nThis may affect code which assumed the return value was mutable, which is no\nlonger the case.\n\n``copy.copy`` and ``copy.deepcopy`` no longer turn ``masked`` into an array\n---------------------------------------------------------------------------\nSince ``np.ma.masked`` is a readonly scalar, copying should be a no-op. These\nfunctions now behave consistently with ``np.copy()``.\n\nMultifield Indexing of Structured Arrays will still return a copy\n-----------------------------------------------------------------\nThe change that multi-field indexing of structured arrays returns a view\ninstead of a copy is pushed back to 1.16. A new method\n``numpy.lib.recfunctions.repack_fields`` has been introduced to help mitigate\nthe effects of this change, which can be used to write code compatible with\nboth numpy 1.15 and 1.16. For more information on how to update code to account\nfor this future change see the &quot;accessing multiple fields&quot; section of the\n`user guide &lt;https://docs.scipy.org/doc/numpy/user/basics.rec.html&gt;`__.\n\n\nC API changes\n=============\n\nNew functions ``npy_get_floatstatus_barrier`` and ``npy_clear_floatstatus_barrier``\n-----------------------------------------------------------------------------------\nFunctions ``npy_get_floatstatus_barrier`` and ``npy_clear_floatstatus_barrier``\nhave been added and should be used in place of the ``npy_get_floatstatus``and\n``npy_clear_status`` functions. Optimizing compilers like GCC 8.1 and Clang\nwere rearranging the order of operations when the previous functions were used\nin the ufunc SIMD functions, resulting in the floatstatus flags being checked\nbefore the operation whose status we wanted to check was run.  See `10339\n&lt;https://github.com/numpy/numpy/issues/10370&gt;`__.\n\nChanges to ``PyArray_GetDTypeTransferFunction``\n-----------------------------------------------\n``PyArray_GetDTypeTransferFunction`` now defaults to using user-defined\n``copyswapn`` / ``copyswap`` for user-defined dtypes. If this causes a\nsignificant performance hit, consider implementing ``copyswapn`` to reflect the\nimplementation of ``PyArray_GetStridedCopyFn``.  See `10898\n&lt;https://github.com/numpy/numpy/pull/10898&gt;`__.\n\n\nNew Features\n============\n\n``np.gcd`` and ``np.lcm`` ufuncs added for integer and objects types\n--------------------------------------------------------------------\nThese compute the greatest common divisor, and lowest common multiple,\nrespectively. These work on all the numpy integer types, as well as the\nbuiltin arbitrary-precision ``Decimal`` and ``long`` types.\n\nSupport for cross-platform builds for iOS\n-----------------------------------------\nThe build system has been modified to add support for the\n``_PYTHON_HOST_PLATFORM`` environment variable, used by ``distutils`` when\ncompiling on one platform for another platform. This makes it possible to\ncompile NumPy for iOS targets.\n\nThis only enables you to compile NumPy for one specific platform at a time.\nCreating a full iOS-compatible NumPy package requires building for the 5\narchitectures supported by iOS (i386, x86_64, armv7, armv7s and arm64), and\ncombining these 5 compiled builds products into a single &quot;fat&quot; binary.\n\n``return_indices`` keyword added for ``np.intersect1d``\n-------------------------------------------------------\nNew keyword ``return_indices`` returns the indices of the two input arrays\nthat correspond to the common elements.\n\n``np.quantile`` and ``np.nanquantile``\n--------------------------------------\nLike ``np.percentile`` and ``np.nanpercentile``, but takes quantiles in [0, 1]\nrather than percentiles in [0, 100]. ``np.percentile`` is now a thin wrapper\naround ``np.quantile`` with the extra step of dividing by 100.\n\n\nBuild system\n------------\nAdded experimental support for the 64-bit RISC-V architecture.\n\n\nImprovements\n============\n\n``np.einsum`` updates\n---------------------\nSyncs einsum path optimization tech between `numpy` and `opt_einsum`. In\nparticular, the `greedy` path has received many enhancements by jcmgray. A\nfull list of issues fixed are:\n\n* Arbitrary memory can be passed into the `greedy` path. Fixes gh-11210.\n* The greedy path has been updated to contain more dynamic programming ideas\n  preventing a large number of duplicate (and expensive) calls that figure out\n  the actual pair contraction that takes place. Now takes a few seconds on\n  several hundred input tensors. Useful for matrix product state theories.\n* Reworks the broadcasting dot error catching found in gh-11218 gh-10352 to be\n  a bit earlier in the process.\n* Enhances the `can_dot` functionality that previous missed an edge case (part\n  of gh-11308).\n\n``np.ufunc.reduce`` and related functions now accept an initial value\n---------------------------------------------------------------------\n``np.ufunc.reduce``, ``np.sum``, ``np.prod``, ``np.min`` and ``np.max`` all\nnow accept an ``initial`` keyword argument that specifies the value to start\nthe reduction with.\n\n``np.flip`` can operate over multiple axes\n------------------------------------------\n``np.flip`` now accepts None, or tuples of int, in its ``axis`` argument. If\naxis is None, it will flip over all the axes.\n\n``histogram`` and ``histogramdd`` functions have moved to ``np.lib.histograms``\n-------------------------------------------------------------------------------\nThese were originally found in ``np.lib.function_base``. They are still\navailable under their un-scoped ``np.histogram(dd)`` names, and\nto maintain compatibility, aliased at ``np.lib.function_base.histogram(dd)``.\n\nCode that does ``from np.lib.function_base import *`` will need to be updated\nwith the new location, and should consider not using ``import *`` in future.\n\n``histogram`` will accept NaN values when explicit bins are given\n-----------------------------------------------------------------\nPreviously it would fail when trying to compute a finite range for the data.\nSince the range is ignored anyway when the bins are given explicitly, this error\nwas needless.\n\nNote that calling ``histogram`` on NaN values continues to raise the\n``RuntimeWarning`` s typical of working with nan values, which can be silenced\nas usual with ``errstate``.\n\n``histogram`` works on datetime types, when explicit bin edges are given\n------------------------------------------------------------------------\nDates, times, and timedeltas can now be histogrammed. The bin edges must be\npassed explicitly, and are not yet computed automatically.\n\n``histogram`` &quot;auto&quot; estimator handles limited variance better\n--------------------------------------------------------------\nNo longer does an IQR of 0 result in ``n_bins=1``, rather the number of bins\nchosen is related to the data size in this situation.\n\nThe edges retuned by `histogram`` and ``histogramdd`` now match the data float type\n-----------------------------------------------------------------------------------\nWhen passed ``np.float16``, ``np.float32``, or ``np.longdouble`` data, the\nreturned edges are now of the same dtype. Previously, ``histogram`` would only\nreturn the same type if explicit bins were given, and ``histogram`` would\nproduce ``float64`` bins no matter what the inputs.\n\n``histogramdd`` allows explicit ranges to be given in a subset of axes\n----------------------------------------------------------------------\nThe ``range`` argument of `numpy.histogramdd` can now contain ``None`` values to\nindicate that the range for the corresponding axis should be computed from the\ndata. Previously, this could not be specified on a per-axis basis.\n\nThe normed arguments of ``histogramdd`` and ``histogram2d`` have been renamed\n-----------------------------------------------------------------------------\nThese arguments are now called ``density``, which is consistent with\n``histogram``. The old argument continues to work, but the new name should be\npreferred.\n\n``np.r_`` works with 0d arrays, and ``np.ma.mr_`` works with ``np.ma.masked``\n-----------------------------------------------------------------------------\n0d arrays passed to the `r_` and `mr_` concatenation helpers are now treated as\nthough they are arrays of length 1. Previously, passing these was an error.\nAs a result, `numpy.ma.mr_` now works correctly on the ``masked`` constant.\n\n``np.ptp`` accepts a ``keepdims`` argument, and extended axis tuples\n--------------------------------------------------------------------\n``np.ptp`` (peak-to-peak) can now work over multiple axes, just like ``np.max``\nand ``np.min``.\n\n``MaskedArray.astype`` now is identical to ``ndarray.astype``\n-------------------------------------------------------------\nThis means it takes all the same arguments, making more code written for\nndarray work for masked array too.\n\nEnable AVX2/AVX512 at compile time\n----------------------------------\nChange to simd.inc.src to allow use of AVX2 or AVX512 at compile time. Previously\ncompilation for avx2 (or 512) with -march=native would still use the SSE\ncode for the simd functions even when the rest of the code got AVX2.\n\n``nan_to_num`` always returns scalars when receiving scalar or 0d inputs\n------------------------------------------------------------------------\nPreviously an array was returned for integer scalar inputs, which is\ninconsistent with the behavior for float inputs, and that of ufuncs in general.\nFor all types of scalar or 0d input, the result is now a scalar.\n\n``np.flatnonzero`` works on numpy-convertible types\n---------------------------------------------------\n``np.flatnonzero`` now uses ``np.ravel(a)`` instead of ``a.ravel()``, so it\nworks for lists, tuples, etc.\n\n``np.interp`` returns numpy scalars rather than builtin scalars\n---------------------------------------------------------------\nPreviously ``np.interp(0.5, [0, 1], [10, 20])`` would return a ``float``, but\nnow it returns a ``np.float64`` object, which more closely matches the behavior\nof other functions.\n\nAdditionally, the special case of ``np.interp(object_array_0d, ...)`` is no\nlonger supported, as ``np.interp(object_array_nd)`` was never supported anyway.\n\nAs a result of this change, the ``period`` argument can now be used on 0d\narrays.\n\nAllow dtype field names to be unicode in Python 2\n-------------------------------------------------\nPreviously ``np.dtype([(u&#39;name&#39;, float)])`` would raise a ``TypeError`` in\nPython 2, as only bytestrings were allowed in field names. Now any unicode\nstring field names will be encoded with the ``ascii`` codec, raising a\n``UnicodeEncodeError`` upon failure.\n\nThis change makes it easier to write Python 2/3 compatible code using\n``from __future__ import unicode_literals``, which previously would cause\nstring literal field names to raise a TypeError in Python 2.\n\nComparison ufuncs accept ``dtype=object``, overriding the default ``bool``\n--------------------------------------------------------------------------\nThis allows object arrays of symbolic types, which override ``==`` and other\noperators to return expressions, to be compared elementwise with\n``np.equal(a, b, dtype=object)``.\n\n``sort`` functions accept ``kind=&#39;stable&#39;``\n-------------------------------------------\nUp until now, to perform a stable sort on the data, the user must do:\n\n    &gt;&gt;&gt; np.sort([5, 2, 6, 2, 1], kind=&#39;mergesort&#39;)\n    [1, 2, 2, 5, 6]\n\nbecause merge sort is the only stable sorting algorithm available in\nNumPy. However, having kind=&#39;mergesort&#39; does not make it explicit that\nthe user wants to perform a stable sort thus harming the readability.\n\nThis change allows the user to specify kind=&#39;stable&#39; thus clarifying\nthe intent.\n\nDo not make temporary copies for in-place accumulation\n------------------------------------------------------\nWhen ufuncs perform accumulation they no longer make temporary copies because\nof the overlap between input an output, that is, the next element accumulated\nis added before the accumulated result is stored in its place, hence the\noverlap is safe. Avoiding the copy results in faster execution.\n\n``linalg.matrix_power`` can now handle stacks of matrices\n---------------------------------------------------------\nLike other functions in ``linalg``, ``matrix_power`` can now deal with arrays\nof dimension larger than 2, which are treated as stacks of matrices. As part\nof the change, to further improve consistency, the name of the first argument\nhas been changed to ``a`` (from ``M``), and the exceptions for non-square\nmatrices have been changed to ``LinAlgError`` (from ``ValueError``).\n\nIncreased performance in ``random.permutation`` for multidimensional arrays\n---------------------------------------------------------------------------\n``permutation`` uses the fast path in ``random.shuffle`` for all input\narray dimensions.  Previously the fast path was only used for 1-d arrays.\n\nGeneralized ufuncs now accept ``axes``, ``axis`` and ``keepdims`` arguments\n---------------------------------------------------------------------------\nOne can control over which axes a generalized ufunc operates by passing in an\n``axes`` argument, a list of tuples with indices of particular axes.  For\ninstance, for a signature of ``(i,j),(j,k)-&gt;(i,k)`` appropriate for matrix\nmultiplication, the base elements are two-dimensional matrices and these are\ntaken to be stored in the two last axes of each argument.  The corresponding\naxes keyword would be ``[(-2, -1), (-2, -1), (-2, -1)]``. If one wanted to\nuse leading dimensions instead, one would pass in ``[(0, 1), (0, 1), (0, 1)]``.\n\nFor simplicity, for generalized ufuncs that operate on 1-dimensional arrays\n(vectors), a single integer is accepted instead of a single-element tuple, and\nfor generalized ufuncs for which all outputs are scalars, the (empty) output\ntuples can be omitted.  Hence, for a signature of ``(i),(i)-&gt;()`` appropriate\nfor an inner product, one could pass in ``axes=[0, 0]`` to indicate that the\nvectors are stored in the first dimensions of the two inputs arguments.\n\nAs a short-cut for generalized ufuncs that are similar to reductions, i.e.,\nthat act on a single, shared core dimension such as the inner product example\nabove, one can pass an ``axis`` argument. This is equivalent to passing in\n``axes`` with identical entries for all arguments with that core dimension\n(e.g., for the example above, ``axes=[(axis,), (axis,)]``).\n\nFurthermore, like for reductions, for generalized ufuncs that have inputs that\nall have the same number of core dimensions and outputs with no core dimension,\none can pass in ``keepdims`` to leave a dimension with size 1 in the outputs,\nthus allowing proper broadcasting against the original inputs. The location of\nthe extra dimension can be controlled with ``axes``. For instance, for the\ninner-product example, ``keepdims=True, axes=[-2, -2, -2]`` would act on the\ninner-product example, ``keepdims=True, axis=-2`` would act on the\none-but-last dimension of the input arguments, and leave a size 1 dimension in\nthat place in the output.\n\nfloat128 values now print correctly on ppc systems\n--------------------------------------------------\nPreviously printing float128 values was buggy on ppc, since the special\ndouble-double floating-point-format on these systems was not accounted for.\nfloat128s now print with correct rounding and uniqueness.\n\nWarning to ppc users: You should upgrade glibc if it is version &lt;=2.23,\nespecially if using float128. On ppc, glibc&#39;s malloc in these version often\nmisaligns allocated memory which can crash numpy when using float128 values.\n\nNew ``np.take_along_axis`` and ``np.put_along_axis`` functions\n--------------------------------------------------------------\nWhen used on multidimensional arrays, ``argsort``, ``argmin``, ``argmax``, and\n``argpartition`` return arrays that are difficult to use as indices.\n``take_along_axis`` provides an easy way to use these indices to lookup values\nwithin an array, so that::\n\n    np.take_along_axis(a, np.argsort(a, axis=axis), axis=axis)\n\nis the same as::\n\n    np.sort(a, axis=axis)\n\n``np.put_along_axis`` acts as the dual operation for writing to these indices\nwithin an array.\n\n\n\n=========================\n   ```\n   \n  \n  \n   ### 1.14.5\n   ```\n   ==========================\n\nThis is a bugfix release for bugs reported following the 1.14.4 release. The\nmost significant fixes are:\n\n* fixes for compilation errors on alpine and NetBSD\n\nThe Python versions supported in this release are 2.7 and 3.4 - 3.6. The Python\n3.6 wheels available from PIP are built with Python 3.6.2 and should be\ncompatible with all previous versions of Python 3.6. The source releases were\ncythonized with Cython 0.28.2 and should work for the upcoming Python 3.7.\n\nContributors\n============\n\nA total of 1 person contributed to this release.  People with a &quot;+&quot; by their\nnames contributed a patch for the first time.\n\n* Charles Harris\n\nPull requests merged\n====================\n\nA total of 2 pull requests were merged for this release.\n\n* `11274 &lt;https://github.com/numpy/numpy/pull/11274&gt;`__: BUG: Correct use of NPY_UNUSED.\n* `11294 &lt;https://github.com/numpy/numpy/pull/11294&gt;`__: BUG: Remove extra trailing parentheses.\n\n\n\n=========================\n   ```\n   \n  \n</details>\n\n\n \n\n<details>\n  <summary>Links</summary>\n  \n  - PyPI: https://pypi.org/project/numpy\n  - Changelog: https://pyup.io/changelogs/numpy/\n  - Homepage: http://www.numpy.org\n</details>\n\n\n\n\n\n### Update [matplotlib](https://pypi.org/project/matplotlib) from **2.2.2** to **2.2.3**.\n\n\n<details>\n  <summary>Changelog</summary>\n  \n  \n  \n</details>\n\n\n \n\n<details>\n  <summary>Links</summary>\n  \n  - PyPI: https://pypi.org/project/matplotlib\n  - Changelog: https://pyup.io/changelogs/matplotlib/\n  - Homepage: http://matplotlib.org\n</details>\n\n\n\n\n\n### Update [pip](https://pypi.org/project/pip) from **10.0.1** to **18.0**.\n\n\n<details>\n  <summary>Changelog</summary>\n  \n  \n   ### 18.0\n   ```\n   =================\n\nProcess\n-------\n\n- Switch to a Calendar based versioning scheme.\n- Formally document our deprecation process as a minimum of 6 months of deprecation\n  warnings.\n- Adopt and document NEWS fragment writing style.\n- Switch to releasing a new, non bug fix version of pip every 3 months.\n\nDeprecations and Removals\n-------------------------\n\n- Remove the legacy format from pip list. (3651, 3654)\n- Dropped support for Python 3.3. (3796)\n- Remove support for cleaning up egg fragment postfixes. (4174)\n- Remove the shim for the old get-pip.py location. (5520)\n\n  For the past 2 years, it&#39;s only been redirecting users to use the newer\n  https://bootstrap.pypa.io/get-pip.py location.\n\nFeatures\n--------\n\n- Introduce a new --prefer-binary flag, to prefer older wheels over newer source packages. (3785)\n- Improve autocompletion function on file name completion after options\n  which have ``&lt;file&gt;``, ``&lt;dir&gt;`` or ``&lt;path&gt;`` as metavar. (4842, 5125)\n- Add support for installing PEP 518 build dependencies from source. (5229)\n- Improve status message when upgrade is skipped due to only-if-needed strategy. (5319)\n\nBug Fixes\n---------\n\n- Update pip&#39;s self-check logic to not use a virtualenv specific file and honor cache-dir. (3905)\n- Remove compiled pyo files for wheel packages. (4471)\n- Speed up printing of newly installed package versions. (5127)\n- Restrict install time dependency warnings to directly-dependant packages. (5196, 5457)\n\n  Warning about the entire package set has resulted in users getting confused as\n  to why pip is printing these warnings.\n- Improve handling of PEP 518 build requirements: support environment markers and extras. (5230, 5265)\n- Remove username/password from log message when using index with basic auth. (5249)\n- Remove trailing os.sep from PATH directories to avoid false negatives. (5293)\n- Fix &quot;pip wheel pip&quot; being blocked by the &quot;don&#39;t use pip to modify itself&quot; check. (5311, 5312)\n- Disable pip&#39;s version check (and upgrade message) when installed by a different package manager. (5346)\n\n  This works better with Linux distributions where pip&#39;s upgrade message may\n  result in users running pip in a manner that modifies files that should be\n  managed by the OS&#39;s package manager.\n- Check for file existence and unlink first when clobbering existing files during a wheel install. (5366)\n- Improve error message to be more specific when no files are found as listed in as listed in PKG-INFO. (5381)\n- Always read ``pyproject.toml`` as UTF-8. This fixes Unicode handling on Windows and Python 2. (5482)\n- Fix a crash that occurs when PATH not set, while generating script location warning. (5558)\n- Disallow packages with ``pyproject.toml`` files that have an empty build-system table. (5627)\n\nVendored Libraries\n------------------\n\n- Update CacheControl to 0.12.5.\n- Update certifi to 2018.4.16.\n- Update distro to 1.3.0.\n- Update idna to 2.7.\n- Update ipaddress to 1.0.22.\n- Update pkg_resources to 39.2.0 (via setuptools).\n- Update progress to 1.4.\n- Update pytoml to 0.1.16.\n- Update requests to 2.19.1.\n- Update urllib3 to 1.23.\n\nImproved Documentation\n----------------------\n\n- Document how to use pip with a proxy server. (512, 5574)\n- Document that the output of pip show is in RFC-compliant mail header format. (5261)\n   ```\n   \n  \n</details>\n\n\n \n\n<details>\n  <summary>Links</summary>\n  \n  - PyPI: https://pypi.org/project/pip\n  - Changelog: https://pyup.io/changelogs/pip/\n  - Homepage: https://pip.pypa.io/\n</details>\n\n\n\n\n\n### Update [tox](https://pypi.org/project/tox) from **3.0.0** to **3.2.1**.\n\n\n<details>\n  <summary>Changelog</summary>\n  \n  \n   ### 3.2.0\n   ```\n   ------------------\n\nFeatures\n^^^^^^^^\n\n- Switch pip invocations to use the module ``-m pip`` instead of direct invocation. This could help\n  avoid some of the shebang limitations.  - by :user:`gaborbernat` (`935 &lt;https://github.com/tox-dev/tox/issues/935&gt;`_)\n- Ability to specify package requirements for the tox run via the ``tox.ini`` (``tox`` section under key ``requires`` - PEP-508 style): can be used to specify both plugin requirements or build dependencies. - by :user:`gaborbernat` (`783 &lt;https://github.com/tox-dev/tox/issues/783&gt;`_)\n- Allow to run multiple tox instances in parallel by providing the\n  ``--parallel--safe-build`` flag. - by :user:`gaborbernat` (`849 &lt;https://github.com/tox-dev/tox/issues/849&gt;`_)\n   ```\n   \n  \n  \n   ### 3.1.3\n   ```\n   ------------------\n\nBugfixes\n^^^^^^^^\n\n- A caching issue that caused the ``develop-inst-nodeps`` action, which\n  reinstalls the package under test, to always run has been resolved. The\n  ``develop-inst-noop`` action, which, as the name suggests, is a no-op, will now\n  run unless there are changes to ``setup.py`` or ``setup.cfg`` files that have\n  not been reflected - by stephenfin (`909 &lt;https://github.com/tox-dev/tox/issues/909&gt;`_)\n\n\nFeatures\n^^^^^^^^\n\n- Python version testenvs are now automatically detected instead of comparing\n  against a hard-coded list of supported versions.  This enables ``py38`` and\n  eventually ``py39`` / ``py40`` / etc. to work without requiring an upgrade to\n  ``tox``.  As such, the following public constants are now deprecated\n  (and scheduled for removal in ``tox`` 4.0: ``CPYTHON_VERSION_TUPLES``,\n  ``PYPY_VERSION_TUPLES``, ``OTHER_PYTHON_INTERPRETERS``, and ``DEFAULT_FACTORS`` -\n  by :user:`asottile` (`914 &lt;https://github.com/tox-dev/tox/issues/914&gt;`_)\n\n\nDocumentation\n^^^^^^^^^^^^^\n\n- Add a system overview section on the index page that explains briefly how tox works -\n  by :user:`gaborbernat`. (`867 &lt;https://github.com/tox-dev/tox/issues/867&gt;`_)\n   ```\n   \n  \n  \n   ### 3.1.2\n   ```\n   ------------------\n\nBugfixes\n^^^^^^^^\n\n- Revert &quot;Fix bug with incorrectly defactorized dependencies (`772 &lt;https://github.com/tox-dev/tox/issues/772&gt;`_)&quot; due to a regression (`(799) &lt;https://github.com/tox-dev/tox/issues/899&gt;`_) - by :user:`obestwalter`\n   ```\n   \n  \n  \n   ### 3.1.1\n   ```\n   ------------------\n\nBugfixes\n^^^^^^^^\n\n- PyPi documentation for ``3.1.0`` is broken. Added test to check for this, and\n  fix it by :user:`gaborbernat`. (`879\n  &lt;https://github.com/tox-dev/tox/issues/879&gt;`_)\n   ```\n   \n  \n  \n   ### 3.1.0\n   ```\n   ------------------\n\nBugfixes\n^^^^^^^^\n\n- Add ``ignore_basepython_conflict``, which determines whether conflicting\n  ``basepython`` settings for environments containing default factors, such as\n  ``py27`` or ``django18-py35``, should be ignored or result in warnings. This\n  was a common source of misconfiguration and is rarely, if ever, desirable from\n  a user perspective - by :user:`stephenfin` (`477 &lt;https://github.com/tox-dev/tox/issues/477&gt;`_)\n- Fix bug with incorrectly defactorized dependencies (deps passed to pip were not de-factorized) - by :user:`bartsanchez` (`706 &lt;https://github.com/tox-dev/tox/issues/706&gt;`_)\n\n\nFeatures\n^^^^^^^^\n\n- Add support for multiple PyPy versions using default factors. This allows you\n  to use, for example, ``pypy27`` knowing that the correct intepreter will be\n  used by default - by :user:`stephenfin` (`19 &lt;https://github.com/tox-dev/tox/issues/19&gt;`_)\n- Add support to explicitly invoke interpreter directives for environments with\n  long path lengths. In the event that ``tox`` cannot invoke scripts with a\n  system-limited shebang (e.x. a Linux host running a Jenkins Pipeline), a user\n  can set the environment variable ``TOX_LIMITED_SHEBANG`` to workaround the\n  system&#39;s limitation (e.x. ``export TOX_LIMITED_SHEBANG=1``) - by :user:`jdknight` (`794 &lt;https://github.com/tox-dev/tox/issues/794&gt;`_)\n- introduce a constants module to be used internally and as experimental API - by :user:`obestwalter` (`798 &lt;https://github.com/tox-dev/tox/issues/798&gt;`_)\n- Make ``py2`` and ``py3`` aliases also resolve via ``py`` on windows by :user:`asottile`. This enables the following things:\n  ``tox -e py2`` and ``tox -e py3`` work on windows (they already work on posix); and setting ``basepython=python2`` or ``basepython=python3`` now works on windows. (`856 &lt;https://github.com/tox-dev/tox/issues/856&gt;`_)\n- Replace the internal version parsing logic from the not well tested `PEP-386 &lt;https://www.python.org/dev/peps/pep-0386/&gt;`_ parser for the more general `PEP-440 &lt;https://www.python.org/dev/peps/pep-0440/&gt;`_. `packaging &gt;= 17.1 &lt;https://pypi.org/project/packaging/&gt;`_ is now an install dependency by :user:`gaborbernat`. (`860 &lt;https://github.com/tox-dev/tox/issues/860&gt;`_)\n\n\nDocumentation\n^^^^^^^^^^^^^\n\n- extend the plugin documentation and make lot of small fixes and improvements - by :user:`obestwalter` (`797 &lt;https://github.com/tox-dev/tox/issues/797&gt;`_)\n- tidy up tests - remove unused fixtures, update old cinstructs, etc. - by :user:`obestwalter` (`799 &lt;https://github.com/tox-dev/tox/issues/799&gt;`_)\n- Various improvements to documentation: open browser once documentation generation is done, show Github/Travis info on documentation page, remove duplicate header for changelog, generate unreleased news as DRAFT on top of changelog, make the changelog page more compact and readable (width up to 1280px) by :user:`gaborbernat` (`859 &lt;https://github.com/tox-dev/tox/issues/859&gt;`_)\n\n\nMiscellaneous\n^^^^^^^^^^^^^\n\n- filter out unwanted files in package - by :user:`obestwalter` (`754 &lt;https://github.com/tox-dev/tox/issues/754&gt;`_)\n- make the already existing implicit API explicit - by :user:`obestwalter` (`800 &lt;https://github.com/tox-dev/tox/issues/800&gt;`_)\n- improve tox quickstart and corresponding tests - by :user:`obestwalter` (`801 &lt;https://github.com/tox-dev/tox/issues/801&gt;`_)\n- tweak codecov settings via .codecov.yml - by :user:`obestwalter` (`802 &lt;https://github.com/tox-dev/tox/issues/802&gt;`_)\n   ```\n   \n  \n</details>\n\n\n \n\n<details>\n  <summary>Links</summary>\n  \n  - PyPI: https://pypi.org/project/tox\n  - Changelog: https://pyup.io/changelogs/tox/\n  - Docs: https://tox.readthedocs.org/\n</details>\n\n\n\n\n\n### Update [Sphinx](https://pypi.org/project/Sphinx) from **1.7.5** to **1.7.7**.\n\n\n<details>\n  <summary>Changelog</summary>\n  \n  \n   ### 1.7.7\n   ```\n   =====================================\n\nBugs fixed\n----------\n\n* 5198: document not in toctree warning when including files only for parallel\n  builds\n* LaTeX: reduce &quot;Token not allowed in a PDF string&quot; hyperref warnings in latex\n  console output (refs: 5236)\n* LaTeX: suppress &quot;remreset Warning: The remreset package is obsolete&quot; in latex\n  console output with recent LaTeX (refs: 5237)\n* 5234: PDF output: usage of PAPER environment variable is broken since Sphinx\n  1.5\n* LaTeX: fix the :confval:`latex_engine` documentation regarding Latin Modern\n  font with XeLaTeX/LuaLateX (refs: 5251)\n* 5280: autodoc: Fix wrong type annotations for complex typing\n* autodoc: Optional types are wrongly rendered\n* 5291: autodoc crashed by ForwardRef types\n* 5211: autodoc: No docs generated for functools.partial functions\n* 5306: autodoc: ``getargspec()`` raises NameError for invalid typehints\n* 5298: imgmath: math_number_all causes equations to have two numbers in html\n* 5294: sphinx-quickstart blank prompts in PowerShell\n   ```\n   \n  \n  \n   ### 1.7.6\n   ```\n   =====================================\n\nBugs fixed\n----------\n\n* 5037: LaTeX ``\\sphinxupquote{}`` breaks in Russian\n* sphinx.testing uses deprecated pytest API; ``Node.get_marker(name)``\n* 5016: crashed when recommonmark.AutoStrictify is enabled\n* 5022: latex: crashed with docutils package provided by Debian/Ubuntu\n* 5009: latex: a label for table is vanished if table does not have a caption\n* 5048: crashed with numbered toctree\n* 2410: C, render empty argument lists for macros.\n* C++, fix lookup of full template specializations with no template arguments.\n* 4667: C++, fix assertion on missing references in global scope when using\n  intersphinx. Thanks to Alan M. Carroll.\n* 5019: autodoc: crashed by Form Feed Character\n* 5032: autodoc: loses the first staticmethod parameter for old styled classes\n* 5036: quickstart: Typing Ctrl-U clears the whole of line\n* 5066: html: &quot;relations&quot; sidebar is not shown by default\n* 5091: latex: curly braces in index entries are not handled correctly\n* 5070: epub: Wrong internal href fragment links\n* 5104: apidoc: Interface of ``sphinx.apidoc:main()`` has changed\n* 4272: PDF builds of French projects have issues with XeTeX\n* 5076: napoleon raises RuntimeError with python 3.7\n* 5125: sphinx-build: Interface of ``sphinx:main()`` has changed\n* sphinx-build: ``sphinx.cmd.build.main()`` refers ``sys.argv`` instead of given\n  argument\n* 5146: autosummary: warning is emitted when the first line of docstring ends\n  with literal notation\n* autosummary: warnings of autosummary indicates wrong location (refs: 5146)\n* 5143: autodoc: crashed on inspecting dict like object which does not support\n  sorting\n* 5139: autodoc: Enum argument missing if it shares value with another\n* 4946: py domain: rtype field could not handle &quot;None&quot; as a type\n* 5176: LaTeX: indexing of terms containing `, ``!``, or ``&quot;`` fails\n* 5161: html: crashes if copying static files are failed\n* 5167: autodoc: Fix formatting type annotations for tuples with more than two\n  arguments\n* 3329: i18n: crashed by auto-symbol footnote references\n* 5158: autosummary: module summary has been broken when it starts with heading\n   ```\n   \n  \n</details>\n\n\n \n\n<details>\n  <summary>Links</summary>\n  \n  - PyPI: https://pypi.org/project/sphinx\n  - Changelog: https://pyup.io/changelogs/sphinx/\n  - Homepage: http://sphinx-doc.org/\n</details>\n\n\n\n\n\n### Update [cryptography](https://pypi.org/project/cryptography) from **2.2.2** to **2.3.1**.\n\n\n<details>\n  <summary>Changelog</summary>\n  \n  \n   ### 2.3\n   ```\n   ~~~~~~~~~~~~~~~~\n\n* **SECURITY ISSUE:**\n  :meth:`~cryptography.hazmat.primitives.ciphers.AEADDecryptionContext.finalize_with_tag`\n  allowed tag truncation by default which can allow tag forgery in some cases.\n  The method now enforces the ``min_tag_length`` provided to the\n  :class:`~cryptography.hazmat.primitives.ciphers.modes.GCM` constructor.\n  *CVE-2018-10903*\n* Added support for Python 3.7.\n* Added :meth:`~cryptography.fernet.Fernet.extract_timestamp` to get the\n  authenticated timestamp of a :doc:`Fernet &lt;/fernet&gt;` token.\n* Support for Python 2.7.x without ``hmac.compare_digest`` has been deprecated.\n  We will require Python 2.7.7 or higher (or 2.7.6 on Ubuntu) in the next\n  ``cryptography`` release.\n* Fixed multiple issues preventing ``cryptography`` from compiling against\n  LibreSSL 2.7.x.\n* Added\n  :class:`~cryptography.x509.CertificateRevocationList.get_revoked_certificate_by_serial_number`\n  for quick serial number searches in CRLs.\n* The :class:`~cryptography.x509.RelativeDistinguishedName` class now\n  preserves the order of attributes. 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