Scheduled monthly dependency update for August

[pyup-bot]

Update coverage from 5.1 to 5.2.1.

Changelog

5.2.1

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

- The dark mode HTML report still used light colors for the context listing,
making them unreadable (`issue 1009`_).  This is now fixed.

- The time stamp on the HTML report now includes the time zone. Thanks, Xie
Yanbo (`pull request 960`_).

.. _pull request 960: https://github.com/nedbat/coveragepy/pull/960
.. _issue 1009: https://github.com/nedbat/coveragepy/issues/1009


.. _changes_52:

5.2

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

- The HTML report has been redesigned by Vince Salvino.  There is now a dark
mode, the code text is larger, and system sans serif fonts are used, in
addition to other small changes (`issue 858`_ and `pull request 931`_).

- The ``coverage report`` and ``coverage html`` commands now accept a
``--precision`` option to control the number of decimal points displayed.
Thanks, Teake Nutma (`pull request 982`_).

- The ``coverage report`` and ``coverage html`` commands now accept a
``--no-skip-covered`` option to negate ``--skip-covered``.  Thanks, Anthony
Sottile (`issue 779`_ and `pull request 932`_).

- The ``--skip-empty`` option is now available for the XML report, closing
`issue 976`_.

- The ``coverage report`` command now accepts a ``--sort`` option to specify
how to sort the results.  Thanks, Jerin Peter George (`pull request 1005`_).

- If coverage fails due to the coverage total not reaching the ``--fail-under``
value, it will now print a message making the condition clear.  Thanks,
Naveen Yadav (`pull request 977`_).

- TOML configuration files with non-ASCII characters would cause errors on
Windows (`issue 990`_).  This is now fixed.

- The output of ``--debug=trace`` now includes information about how the
``--source`` option is being interpreted, and the module names being
considered.

.. _pull request 931: https://github.com/nedbat/coveragepy/pull/931
.. _pull request 932: https://github.com/nedbat/coveragepy/pull/932
.. _pull request 977: https://github.com/nedbat/coveragepy/pull/977
.. _pull request 982: https://github.com/nedbat/coveragepy/pull/982
.. _pull request 1005: https://github.com/nedbat/coveragepy/pull/1005
.. _issue 779: https://github.com/nedbat/coveragepy/issues/779
.. _issue 858: https://github.com/nedbat/coveragepy/issues/858
.. _issue 976: https://github.com/nedbat/coveragepy/issues/976
.. _issue 990: https://github.com/nedbat/coveragepy/issues/990


.. _changes_51:

Links

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

Update hypothesis from 5.16.0 to 5.23.8.

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

Links

• PyPI: https://pypi.org/project/hypothesis
• Repo: https://github.com/HypothesisWorks/hypothesis/tree/master/hypothesis-python

Update joblib from 0.15.1 to 0.16.0.

Changelog

0.16.0

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

- Fix a problem in the constructors of of Parallel backends classes that
inherit from the `AutoBatchingMixin` that prevented the dask backend to
properly batch short tasks.
https://github.com/joblib/joblib/pull/1062

- Fix a problem in the way the joblib dask backend batches calls that would
badly interact with the dask callable pickling cache and lead to wrong
results or errors.
https://github.com/joblib/joblib/pull/1055

- Prevent a dask.distributed bug from surfacing in joblib's dask backend
during nested Parallel calls (due to joblib's auto-scattering feature)
https://github.com/joblib/joblib/pull/1061

- Workaround for a race condition after Parallel calls with the dask backend
that would cause low level warnings from asyncio coroutines:
https://github.com/joblib/joblib/pull/1078

Links

• PyPI: https://pypi.org/project/joblib
• Changelog: https://pyup.io/changelogs/joblib/
• Docs: https://joblib.readthedocs.io

Update matplotlib from 3.2.1 to 3.3.0.

Changelog

3.3.0

Highlights of this release include:

- Provisional API for composing semantic axes layouts from text or nested lists
- New Axes.sharex, Axes.sharey methods
- Turbo colormap
- colors.BoundaryNorm supports extend keyword argument
- Text color for legend labels
- Pcolor and Pcolormesh now accept shading='nearest' and 'auto'
- Allow tick formatters to be set with str or function inputs
- New Axes.axline method
- Dates use a modern epoch
- Improved font weight detection
- Axes3D no longer distorts the 3D plot to match the 2D aspect ratio
- More consistent toolbar behavior across backends
- Toolbar icons are now styled for dark themes
- Cursor text now uses a number of significant digits matching pointing precision
- Functions to compute a Path's size
- savefig() gained a backend keyword argument
- Saving SVG now supports adding metadata
- Saving PDF metadata via PGF now consistent with PDF backend
- NbAgg and WebAgg no longer use jQuery & jQuery UI

For the full details please see the [What's New](https://matplotlib.org/3.3.0/users/whats_new.html) and [API changes](https://matplotlib.org/3.3.0/api/api_changes.html) in the documentation.

3.2.2

This is the second bugfix release of the 3.2.x series.

This release contains several critical bug-fixes:

- support fractional HiDPI scaling with Qt backends
- support new Python and fix syntax errors in legacy Python
- support new Qt 5 and fix support for Qt 4
- fix animation writer fallback
- fix figure resizing
- fix handling of large arcs
- fix issues with tight layout
- fix saving figures after closing windows or under certain size conditions
- fix scatter when specifying a single color
- fix several memory leaks
- fix unexpected autoscaling behavior
- fix various issues with usetex
- various minor bug and documentation fixes

Links

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

Update multiprocess from 0.70.9 to 0.70.10.

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

Links

• PyPI: https://pypi.org/project/multiprocess
• Changelog: https://pyup.io/changelogs/multiprocess/
• Repo: https://github.com/uqfoundation/multiprocess/releases/download/multiprocess-0.70.10/multiprocess-0.70.10.tar.gz
• Homepage: https://pypi.org/project/multiprocess

Update mypy from 0.770 to 0.782.

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

Links

• PyPI: https://pypi.org/project/mypy
• Homepage: http://www.mypy-lang.org/

Update numpy from 1.18.4 to 1.19.1.

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

Links

• PyPI: https://pypi.org/project/numpy
• Homepage: https://www.numpy.org

Update pandas from 1.0.4 to 1.1.0.

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

Links

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

Update pre-commit from 2.4.0 to 2.6.0.

Changelog

2.6.0

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

Fixes
- Fix node hooks when `NPM_CONFIG_USERCONFIG` is set
 - 1521 PR by asottile.
 - 1516 issue by rkm.

Features
- Skip `rbenv` / `ruby-download` if system ruby is available
 - 1509 PR by asottile.
- Partial support for ruby on windows (if system ruby is installed)
 - 1509 PR by asottile.
 - 201 issue by asottile.

2.5.1

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

Fixes
- Prevent infinite recursion of post-checkout on clone
 - 1497 PR by asottile.
 - 1496 issue by admorgan.

2.5.0

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

Features
- Expose a `PRE_COMMIT=1` environment variable when running hooks
 - 1467 PR by tech-chad.
 - 1426 issue by lorenzwalthert.

Fixes
- Fix `UnicodeDecodeError` on windows when using the `py` launcher to detect
executables with non-ascii characters in the path
 - 1474 PR by asottile.
 - 1472 issue by DrFobos.
- Fix `DeprecationWarning` on python3.9 for `random.shuffle` method
 - 1480 PR by asottile.
 - 1479 issue by isidentical.
- Normalize slashes earlier such that global `files` / `exclude` use forward
slashes on windows as well.
 - 1494 PR by asottile.
 - 1476 issue by harrybiddle.

Links

• PyPI: https://pypi.org/project/pre-commit
• Changelog: https://pyup.io/changelogs/pre-commit/
• Repo: https://github.com/pre-commit/pre-commit

Update pytest from 5.4.2 to 6.0.1.

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

Links

• PyPI: https://pypi.org/project/pytest
• Homepage: https://docs.pytest.org/en/latest/

Update pytest-cov from 2.9.0 to 2.10.0.

Changelog

2.10.0

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

* Improved the ``--no-cov`` warning. Now it's only shown if ``--no-cov`` is present before ``--cov``.
* Removed legacy pytest support. Changed ``setup.py`` so that ``pytest>=4.6`` is required.

Links

• PyPI: https://pypi.org/project/pytest-cov
• Changelog: https://pyup.io/changelogs/pytest-cov/
• Repo: https://github.com/pytest-dev/pytest-cov

Update scipy from 1.4.1 to 1.5.2.

Changelog

1.5.1

compared to `1.5.0`. In particular, an issue where DLL loading
can fail for SciPy wheels on Windows with Python `3.6` has been
fixed.

Authors
=======

* Peter Bell
* Loïc Estève
* Philipp Thölke +
* Tyler Reddy
* Paul van Mulbregt
* Pauli Virtanen
* Warren Weckesser

A total of 7 people contributed to this release.
People with a "+" by their names contributed a patch for the first time.
This list of names is automatically generated, and may not be fully complete.

1.5.0

many new features, numerous bug-fixes, improved test coverage and better
documentation. There have been a number of deprecations and API changes
in this release, which are documented below. All users are encouraged to
upgrade to this release, as there are a large number of bug-fixes and
optimizations. Before upgrading, we recommend that users check that
their own code does not use deprecated SciPy functionality (to do so,
run your code with ``python -Wd`` and check for ``DeprecationWarning`` s).
Our development attention will now shift to bug-fix releases on the
1.5.x branch, and on adding new features on the master branch.

This release requires Python `3.6+` and NumPy `1.14.5` or greater.

For running on PyPy, PyPy3 `6.0+` and NumPy `1.15.0` are required.

Highlights of this release
----------------------------

- wrappers for more than a dozen new ``LAPACK`` routines are now available
in `scipy.linalg.lapack`
- Improved support for leveraging 64-bit integer size from linear algebra
backends
- addition of the probability distribution for two-sided one-sample 
Kolmogorov-Smirnov tests


New features
=========

`scipy.cluster` improvements
--------------------------------
Initialization of `scipy.cluster.vq.kmeans2` using ``minit="++"`` had a 
quadratic complexity in the number of samples. It has been improved, resulting 
in a much faster initialization with quasi-linear complexity.

`scipy.cluster.hierarchy.dendrogram` now respects the ``matplotlib`` color
palette

`scipy.fft` improvements
------------------------------
A new keyword-only argument ``plan`` is added to all FFT functions in this 
module. It is reserved for passing in a precomputed plan from libraries 
providing a FFT backend (such as ``PyFFTW`` and ``mkl-fft``), and it is 
currently not used in SciPy.

`scipy.integrate` improvements
----------------------------------


`scipy.interpolate` improvements
-------------------------------------

`scipy.io` improvements
---------------------------
`scipy.io.wavfile` error messages are more explicit about what's wrong, and 
extraneous bytes at the ends of files are ignored instead of raising an error 
when the data has successfully been read.

`scipy.io.loadmat` gained a ``simplify_cells`` parameter, which if set to 
``True`` simplifies the structure of the return value if the ``.mat`` file 
contains cell arrays.

``pathlib.Path`` objects are now supported in `scipy.io` Matrix Market I/O
functions

`scipy.linalg` improvements
-------------------------------
`scipy.linalg.eigh` has been improved. Now various ``LAPACK`` drivers can be 
selected at will and also subsets of eigenvalues can be requested via 
``subset_by_value`` keyword. Another keyword ``subset_by_index`` is introduced.
Keywords ``turbo`` and ``eigvals`` are deprecated.

Similarly, standard and generalized Hermitian eigenvalue ``LAPACK`` routines 
``?<sy/he>evx`` are added and existing ones now have full ``_lwork``
counterparts.

Wrappers for the following ``LAPACK`` routines have been added to 
`scipy.linalg.lapack`:

- ``?getc2``: computes the LU factorization of a general matrix with complete 
 pivoting
- ``?gesc2``: solves a linear system given an LU factorization from ``?getc2``
- ``?gejsv``: computes the singular value decomposition of a general matrix 
 with higher accuracy calculation of tiny singular values and their 
 corresponding singular vectors
- ``?geqrfp``: computes the QR factorization of a general matrix with 
 non-negative elements on the diagonal of R
- ``?gtsvx``: solves a linear system with general tridiagonal matrix
- ``?gttrf``: computes the LU factorization of a tridiagonal matrix
- ``?gttrs``: solves a linear system given an LU factorization from ``?gttrf``
- ``?ptsvx``: solves a linear system with symmetric positive definite 
 tridiagonal matrix
- ``?pttrf``: computes the LU factorization of a symmetric positive definite 
 tridiagonal matrix
- ``?pttrs``: solves a linear system given an LU factorization from ``?pttrf``
- ``?pteqr``: computes the eigenvectors and eigenvalues of a positive definite 
 tridiagonal matrix
- ``?tbtrs``: solves a linear system with a triangular banded matrix
- ``?csd``: computes the Cosine Sine decomposition of an orthogonal/unitary 
 matrix

Generalized QR factorization routines (``?geqrf``) now have full ``_lwork`` 
counterparts.

`scipy.linalg.cossin` Cosine Sine decomposition of unitary matrices has been 
added.

The function `scipy.linalg.khatri_rao`, which computes the Khatri-Rao product,
was added.

The new function `scipy.linalg.convolution_matrix` constructs the Toeplitz 
matrix representing one-dimensional convolution.

`scipy.ndimage` improvements
----------------------------------


`scipy.optimize` improvements
----------------------------------
The finite difference numerical differentiation used in various ``minimize``
methods that use gradients has several new features:

-  2-point, 3-point, or complex step finite differences can be used. Previously 
only a 2-step finite difference was available.
-  There is now the possibility to use a relative step size, previously only an
absolute step size was available.
-  If the ``minimize`` method uses bounds the numerical differentiation strictly 
obeys those limits.
-  The numerical differentiation machinery now makes use of a simple cache, 
which in some cases can reduce the number of function evaluations.
-  ``minimize``'s ``method= 'powell'`` now supports simple bound constraints

There have been several improvements to `scipy.optimize.linprog`:

-  The ``linprog`` benchmark suite has been expanded considerably.
-  ``linprog``'s dense pivot-based redundancy removal routine and sparse 
presolve are faster
-  When ``scikit-sparse`` is available, solving sparse problems with 
``method='interior-point'`` is faster

The caching of values when optimizing a function returning both value and 
gradient together has been improved, avoiding repeated function evaluations 
when using a ``HessianApproximation`` such as ``BFGS``.

``differential_evolution`` can now use the modern ``np.random.Generator`` as 
well as the legacy ``np.random.RandomState`` as a seed.

`scipy.signal` improvements
-------------------------------
A new optional argument ``include_nyquist`` is added to ``freqz`` functions in 
this module. It is used for including the last frequency (Nyquist frequency).

`scipy.signal.find_peaks_cwt` now accepts a ``window_size`` parameter for the 
size of the window used to calculate the noise floor.

`scipy.sparse` improvements
--------------------------------
Outer indexing is now faster when using a 2d column vector to select column 
indices.

`scipy.sparse.lil.tocsr` is faster

Fixed/improved comparisons between pydata sparse arrays and sparse matrices

BSR format sparse multiplication performance has been improved.

`scipy.sparse.linalg.LinearOperator` has gained the new ``ndim`` class
attribute

`scipy.spatial` improvements
--------------------------------
`scipy.spatial.geometric_slerp` has been added to enable geometric 
spherical linear interpolation on an n-sphere

`scipy.spatial.SphericalVoronoi` now supports calculation of region areas in 2D 
and 3D cases

The tree building algorithm used by ``cKDTree`` has improved from quadratic
worst case time complexity to loglinear. Benchmarks are also now available for
building and querying of balanced/unbalanced kd-trees.

`scipy.special` improvements
---------------------------------
The following functions now have Cython interfaces in `cython_special`:

-  `scipy.special.erfinv`
-  `scipy.special.erfcinv`
-  `scipy.special.spherical_jn`
-  `scipy.special.spherical_yn`
-  `scipy.special.spherical_in`
-  `scipy.special.spherical_kn`

`scipy.special.log_softmax` has been added to calculate the logarithm of softmax 
function. It provides better accuracy than ``log(scipy.special.softmax(x))`` for 
inputs that make softmax saturate.

`scipy.stats` improvements
-------------------------------
The function for generating random samples in `scipy.stats.dlaplace` has been 
improved. The new function is approximately twice as fast with a memory
footprint reduction between 25 % and 60 % (see gh-11069).

`scipy.stats` functions that accept a seed for reproducible calculations using 
random number generation (e.g. random variates from distributions) can now use 
the modern ``np.random.Generator`` as well as the legacy 
``np.random.RandomState`` as a seed.

The ``axis`` parameter was added to `scipy.stats.rankdata`. This allows slices 
of an array along the given axis to be ranked independently.

The ``axis`` parameter was added to `scipy.stats.f_oneway`, allowing it to
compute multiple one-way ANOVA tests for data stored in n-dimensional
arrays.  The performance of ``f_oneway`` was also improved for some cases.

The PDF and CDF methods for ``stats.geninvgauss`` are now significantly faster 
as  the numerical integration to calculate the CDF uses a Cython based 
``LowLevelCallable``.

Moments of the normal distribution (`scipy.stats.norm`) are now calculated using 
analytical formulas instead of numerical integration for greater speed and 
accuracy

Moments and entropy trapezoidal distribution (`scipy.stats.trapz`) are now 
calculated using analytical formulas instead of numerical integration for 
greater speed and accuracy

Methods of the truncated normal distribution (`scipy.stats.truncnorm`), 
especially ``_rvs``, are significantly faster after a complete rewrite.

The `fit` method of the Laplace distribution,  `scipy.stats.laplace`, now uses 
the analytical formulas for the maximum likelihood estimates of the parameters.

Generation of random variates is now thread safe for all SciPy distributions. 
3rd-party distributions may need to modify the signature of the ``_rvs()`` 
method to conform to ``_rvs(self, ..., size=None, random_state=None)``. (A 
one-time VisibleDeprecationWarning is emitted when using non-conformant 
distributions.)

The Kolmogorov-Smirnov two-sided test statistic distribution 
(`scipy.stats.kstwo`) was added. Calculates the distribution of the K-S 
two-sided statistic ``D_n`` for a sample of size n, using a mixture of exact 
and asymptotic algorithms.

The new function ``median_abs_deviation`` replaces the deprecated 
``median_absolute_deviation``.

The ``wilcoxon`` function now computes the p-value for Wilcoxon's signed rank 
test using the exact distribution for inputs up to length 25.  The function has 
a new ``mode`` parameter to specify how the p-value is to be computed.  The 
default is ``"auto"``, which uses the exact distribution for inputs up to length 
25 and the normal approximation for larger inputs.

Added a new Cython-based implementation to evaluate guassian kernel estimates,
which should improve the performance of ``gaussian_kde``

The ``winsorize`` function now has a ``nan_policy`` argument for refined
handling of ``nan`` input values.

The ``binned_statistic_dd`` function with ``statistic="std"`` performance was
improved by ~4x.

``scipy.stats.kstest(rvs, cdf,...)`` now handles both one-sample and 
two-sample testing. The one-sample variation uses `scipy.stats.ksone` 
(or `scipy.stats.kstwo` with back off to `scipy.stats.kstwobign`) to calculate 
the p-value. The two-sample variation, invoked if ``cdf`` is array_like, uses 
an algorithm described by Hodges to compute the probability directly, only 
backing off to `scipy.stats.kstwo` in case of overflow. The result in both 
cases is more accurate p-values, especially for two-sample testing with 
smaller (or quite different) sizes.

`scipy.stats.maxwell` performance improvements include a 20 % speed up for
`fit()`` and 5 % for ``pdf()``

`scipy.stats.shapiro` and `scipy.stats.jarque_bera` now return a named tuple 
for greater consistency with other ``stats`` functions

Deprecated features
=============

`scipy` deprecations
----------------------

`scipy.special` changes
--------------------------
The ``bdtr``, ``bdtrc``, and ``bdtri`` functions are deprecating non-negative 
non-integral ``n`` arguments.

`scipy.stats` changes
-----------------------
The function ``median_absolute_deviation`` is deprecated. Use 
``median_abs_deviation`` instead.

The use of the string ``"raw"`` with the ``scale`` parameter of ``iqr`` is 
deprecated. Use ``scale=1`` instead.

Backwards incompatible changes
======================

`scipy.interpolate` changes
-------------------------------

`scipy.linalg` changes
------------------------
The output signatures of ``?syevr``, ``?heevr`` have been changed from 
``w, v, info`` to ``w, v, m, isuppz, info``

The order of output arguments ``w``, ``v`` of ``<sy/he>{gv, gvd, gvx}`` is 
swapped.

`scipy.signal` changes
-------------------------
The output length of `scipy.signal.upfirdn` has been corrected, resulting 
outputs may now be shorter for some combinations of up/down ratios and input 
signal and filter lengths.

`scipy.signal.resample` now supports a ``domain`` keyword argument for
specification of time or frequency domain input.

`scipy.stats` changes
------------------------


Other changes
==========
Improved support for leveraging 64-bit integer size from linear algebra backends
in several parts of the SciPy codebase.

Shims designed to ensure the compatibility of SciPy with Python 2.7 have now 
been removed.

Many warnings due to unused imports and unused assignments have been addressed.

Many usage examples were added to function docstrings, and many input 
validations and intuitive exception messages have been added throughout the
codebase.

Early stage adoption of type annotations in a few parts of the codebase


Authors
=======

* endolith
* Hameer Abbasi
* ADmitri +
* Wesley Alves +
* Berkay Antmen +
* Sylwester Arabas +
* Arne Küderle +
* Christoph Baumgarten
* Peter Bell
* Felix Berkenkamp
* Jordão Bragantini +
* Clemens Brunner +
* Evgeni Burovski
* Matthias Bussonnier +
* CJ Carey
* Derrick Chambers +
* Leander Claes +
* Christian Clauss
* Luigi F. Cruz +
* dankleeman
* Andras Deak
* Milad Sadeghi DM +
* jeremie du boisberranger +
* Stefan Endres
* Malte Esders +
* Leo Fang +
* felixhekhorn +
* Isuru Fernando
* Andrew Fowlie
* Lakshay Garg +
* Gaurav Gijare +
* Ralf Gommers
* Emmanuelle Gouillart +
* Kevin Green +
* Martin Grignard +
* Maja Gwozdz
* gyu-don +
* Matt Haberland
* hakeemo +
* Charles Harris
* Alex Henrie
* Santi Hernandez +
* William Hickman +
* Till Hoffmann +
* Joseph T. Iosue +
* Anany Shrey Jain
* Jakob Jakobson
* Charles Jekel +
* Julien Jerphanion +
* Jiacheng-Liu +
* Christoph Kecht +
* Paul Kienzle +
* Reidar Kind +
* Dmitry E. Kislov +
* Konrad +
* Konrad0
* Takuya KOUMURA +
* Krzysztof Pióro
* Peter Mahler Larsen
* Eric Larson
* Antony Lee
* Gregory Lee +
* Gregory R. Lee
* Chelsea Liu
* Cong Ma +
* Kevin Mader +
* Maja Gwóźdź +
* Alex Marvin +
* Matthias Kümmerer
* Nikolay Mayorov
* Mazay0 +
* G. D. McBain
* Nicholas McKibben +
* Sabrina J. Mielke +
* Sebastian J. Mielke +
* Miloš Komar�ević +
* Shubham Mishra +
* Santiago M. Mola +
* Grzegorz Mrukwa +
* Peyton Murray
* Andrew Nelson
* Nico Schlömer
* nwjenkins +
* odidev +
* Sambit Panda
* Vikas Pandey +
* Rick Paris +
* Harshal Prakash Patankar +
* Balint Pato +
* Matti Picus
* Ilhan Polat
* poom +
* Siddhesh Poyarekar
* Vladyslav Rachek +
* Bharat Raghunathan
* Manu Rajput +
* Tyler Reddy
* Andrew Reed +
* Lucas Roberts
* Ariel Rokem
* Heshy Roskes
* Matt Ruffalo
* Atsushi Sakai +
* Benjamin Santos +
* Christoph Schock +
* Lisa Schwetlick +
* Chris Simpson +
* Leo Singer
* Kai Striega
* Søren Fuglede Jørgensen
* Kale-ab Tessera +
* Seth Troisi +
* Robert Uhl +
* Paul van Mulbregt
* Vasiliy +
* Isaac Virshup +
* Pauli Virtanen
* Shakthi Visagan +
* Jan Vleeshouwers +
* Sam Wallan +
* Lijun Wang +
* Warren Weckesser
* Richard Weiss +
* wenhui-prudencemed +
* Eric Wieser
* Josh Wilson
* James Wright +
* Ruslan Yevdokymov +
* Ziyao Zhang +

A total of 129 people contributed to this release.
People with a "+" by their names contributed a patch for the first time.
This list of names is automatically generated, and may not be fully complete.

Links

• PyPI: https://pypi.org/project/scipy
• Changelog: https://pyup.io/changelogs/scipy/
• Repo: https://github.com/scipy/scipy/releases
• Homepage: https://www.scipy.org

Update tqdm from 4.46.0 to 4.48.0.

Changelog

4.47.0

- add `contrib.discord` (similar to `contrib.telegram`) (976)
- add `contrib.bells` to auto-enable all extras
- add `contrib.utils_worker` for common slow tasks (e.g. web I/O)
+ fix lazy large memory usage & discard unsent messages (unprocessed tasks)
- fix slow notebook imports (955 <- 709)
- fix `gui` `TypeError` on unknown `len()` (971)
- misc documentation/error message updates
+ more succinct ImportError on missing `ipywidgets` (872)
+ fix broken/deprecated link (981)
+ add inline usage for `contrib.discord` and `contrib.telegram`
- misc framework updates
+ add official `py3.8` support (986)
+ fix `snap` builds

![contrib.discord](https://user-images.githubusercontent.com/10780059/82755091-62374c80-9dc9-11ea-88bb-fd8cafe854ff.png)

![contrib.telegram](https://github.com/ermakovpetr/tg_tqdm/blob/master/tg_tqdm_how_it_work.gif?raw=true)

4.46.1

- fix missing `sys.setcheckinterval` in py3.9 (978)
- fix `keras.TqdmCallback` compatibility with `tensorflow==2.2.0` (979)
- update documentation
+ correct `contrib.concurrent` correct `max_workers` (977)
+ drop prominent mention of `xrange` (965)
- minor linting

Links

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

[pyup-bot]

Closing this in favor of #161